Publications

Collalti A., Tjoelker M.G., Hoch G., Mäkelä A., Guidolotti G., Heskel M., Petit G., Ryan M.G., Battipaglia G., Matteucci G., Prentice I.C.

2019

Plant respiration: Controlled by photosynthesis or biomass?

Abstract:

Two simplifying hypotheses have been proposed for whole-plant respiration. One links respiration to photosynthesis; the other to biomass. Using a first-principles carbon balance model with a prescribed live woody biomass turnover, we show that if turnover is fast, the accumulation of respiring biomass is low and respiration depends primarily on photosynthesis; while if turnover is slow, the accumulation of respiring biomass is high and respiration depends primarily on biomass. But the first scenario is inconsistent with evidence for substantial carryover of fixed carbon between years, while the second implies far too great an increase in respiration during stand development – leading to depleted carbohydrate reserves and an unrealistically high mortality risk. These two mutually incompatible hypotheses are thus both incorrect. Respiration is not linearly related either to photosynthesis or to biomass, but rather it is more strongly controlled by recent photosynthates (and reserve availability) than by total biomass.

Global Change Biology

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Merganičová K., Merganič J., Lehtonen A., Vacchiano G., Ostrogović Sever M.Z., Augustynczik A.L.D., Grote R., Kyselová I., Mäkelä A., Yousefpour R., Krejza J., Collalti A., Reyer C.P.O.

2019

Forest carbon allocation modelling under climate change

Abstract:

Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared to our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that although the number of carbon allocation studies over the last 10 years has substantially increased, some background processes are still insufficiently understood, and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are: (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilisation of non-structural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration, and improved resource uptake in order to better account for changing environmental conditions.

Tree Physiology

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Collalti A. and Prentice I.C.

2019

Is NPP proportional to GPP? Waring's hypothesis twenty years on

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Tree Physiology

Abstract:

Gross primary production (GPP) is partitioned to autotrophic respiration (Ra) and net primary production (NPP), the latter being used to build plant tissues and synthesize non-structural and secondary compounds. Waring et al. (1998) suggested that a NPP:GPP ratio of 0.47 ± 0.04 (s.d.) is universal across biomes, tree species and stand ages. Representing NPP in models as a fixed fraction of GPP, they argued, would be both simpler and more accurate than trying to simulate Ra mechanistically. This paper reviews progress in understanding the NPP:GPP ratio in forests during the 20 years since Waring et al.. Research has confirmed the existence of pervasive acclimation mechanisms that tend to stabilize the NPP:GPP ratio, and indicates that Ra should not be modelled independently of GPP. Nonetheless, studies indicate that the value of this ratio is influenced by environmental factors, stand age and management. The average NPP:GPP ratio in over 200 studies, representing different biomes, species and forest stand ages, was found to be 0.46, consistent with the central value that Waring et al. proposed but with a much larger standard deviation (± 0.12) and a total range (0.22 to 0.79) that is too large to be disregarded.

Collalti A., Thornton P.E., Cescatti A., Rita A., Borghetti M., Nolé A., Trotta C., Ciais P., Matteucci G.

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2019

The sensitivity of the forest carbon budget shifts across processes along with stand development and climate change

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Ecological Applications

Abstract:

The future trajectory of atmospheric CO2 concentration depends on the development of the terrestrial carbon sink, which in turn is influenced by forest dynamics under changing environmental conditions. An in-depth understanding of model sensitivities and uncertainties in non steady-state conditions is necessary for reliable and robust projections of forest development and under scenarios of global warming and CO2-enrichment. Here, we systematically assessed if a bio-geochemical process-based model (3D-CMCC-CNR), which embeds similarities with many other vegetation models, applied in simulating net primary productivity (NPP) and standing woody biomass (SWB), maintained a consistent sensitivity to its 55 input parameters through time, during forest-ageing and -structuring as well as under climate-change scenarios. Overall, the model applied at three contrasting European forests showed low sensitivity to the majority of its parameters. Interestingly, model sensitivity to parameters varied through the course of >100 years of simulations. In particular, the model showed a large responsiveness to the allometric parameters used for initialize forest carbon- and nitrogen-pools early in forest simulation (i.e. for NPP up to ~37%, 256 gC m-2 yr-1 and for SWB up to ~90%, 65 tC ha-1, when compared to standard simulation), with this sensitivity decreasing sharply during forest development. At medium- to longer-time scales, and under climate-change scenarios, the model became increasingly more sensitive to additional and/or different parameters controlling biomass accumulation and autotrophic respiration (i.e. for NPP up to ~30%, 167 gC m-2 yr-1 and for SWB up to ~24%, 64 tC ha-1, when compared to standard simulation). Interestingly, model outputs were shown to be more sensitive to parameters and processes controlling stand development rather than to climate-change (i.e. warming and changes in atmospheric CO2 concentration) itself although model sensitivities were generally higher under climate-change scenarios . Our results suggest the need for sensitivity and uncertainty analyses that cover multiple temporal scales along forest developmental stages to better assess the potential of future forests to act as a global terrestrial carbon sink.

Collalti A., Trotta C., Keenan T.F., Ibrom A., Bond-Lamberty B., Grote R., Vicca S., Reyer C.P.O., Migliavacca M., Veroustraete F., Anav A., Campioli M.,  Scoccimarro E., Šigut L., Grieco E., Cescatti A., Matteucci G.

2018

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Thinning can reduce losses in carbon use efficiency and carbon stocks in managed forests under warmer climate

Journal of Advances in Modelling Earth System

Abstract:

Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here, we assess the potential impact of thinning on projected carbon‐cycle dynamics and implications for forest CUE and its components (i.e. gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process‐based forest‐ecosystem‐model forced by climate outputs of five Earth System Models under four Representative‐ climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO2 concentration and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations, lead the forests to grow faster mature earlier but also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody‐pools and reduce physiological‐climate‐induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest‐based mitigation strategies and should be carefully considered within a portfolio of mitigation options.

Marconi S., Chiti T., Nolè A., Valentini R. and Collalti A.

2017

The Role of Respiration in Estimation of Net Carbon Cycle: Coupling Soil Carbon Dynamics and Canopy Turnover in a Novel Version of 3D-CMCC Forest Ecosystem Model

​​Forests

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Abstract:

Understanding the dynamics of Organic Carbon mineralization is fundamental in forecasting biosphere to atmosphere Net Carbon Ecosystem Exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid Process Based Model 3D-CMCC FEM where also heterotrophic respiration (R h ) is explicitly simulated. The aim was to quantify NEE as a forward problem, by subtracting Ecosystem Respiration (R eco ) to Gross Primary Productivity (GPP). To do so, we developed a simplification of the Soil Carbon dynamics routine proposed in DNDC [1]. The method calculates decomposition as a function of soil moisture, temperature, state of the organic compartments, and relative abundance of microbial pools. Given the pulse dynamics of soil respiration, we introduced modifications in some of the principal constitutive relations involved in phenology and littering sub-routines. We quantified the model structure related uncertainty in NEE, by running our training simulations over 1000 random parameter-sets extracted from parameters distributions expected from literature. 3D-CMCC-PSM predictability was tested on independent time series for 6 Fluxnet sites. The model resulted in daily and monthly estimations highly consistent with the observed time series. It showed lower predictability in Mediterranean ecosystems, suggesting that it may need further improvements in addressing evapotranspiration and water dynamics.

Collalti A., Biondo C., Buttafuoco G., Maesano M., Caloiero T., Lucà F., Pellicone G., Ricca N., Salvati R., Veltri A., Scarascia Mugnozza G., Matteucci G.

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2017

Simulation, calibration and validation protocols for the model 3D-CMCC-CNR-FEM: a case study in the Bonis’ watershed (Calabria, Italy)

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Forest@

doi: 10.3832/efor2368-014

Abstract:

At present, the climate changes issue is perhaps the greatest threat that is affecting people and the environment. Forest ecosystems have a key role in the mitigation of climate change. In this context, the prediction of the evolution and growth dynamics of the forests including carbon and water fluxes, and in relation to forest management has become a primary objective. The present study aims at defining a protocol for data collection and the workflow for using the 3D-CMCC-CNR-FEM model in a small mountain watershed in the Calabria region. Within this work we synergistically integrate data coming from different methods (e.g., LiDAR, eddy covariance and sample area) to predict forest dynamics (growth, carbon and water fluxes). Carbon and water fluxes will be simulated considering also the effects of forest management.

Collalti A., Marconi S., Ibrom A., Trotta C., Anav A., D’Andrea E., Matteucci G., Montagnani L., Gielen B., Mammarella I., Grunwald T., Knohl A., Berninger F., Zhao Y., Valentini R., Santini M.

2016

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Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for 10 European forest sites

Geoscientific Model Development

Abstract:

This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem Model (FEM) in simulating gross primary productivity (GPP), against eddy covariance GPP data for 10 FLUXNET forest sites across Europe. A new carbon allocation module, coupled with new both phenological and autotrophic respiration schemes, was implemented in this new daily version. Model ability in reproducing timing and magnitude of daily and monthly GPP fluctuations is validated at intra-annual and inter-annual scale, including extreme anomalous seasons. With the purpose to test the 3D-CMCC FEM applicability over Europe without a site-related calibration, the model has been deliberately parametrized with a single set of species-specific parametrizations for each forest ecosystem. The model consistently reproduces both in timing and in magnitude daily and monthly GPP variability across all sites, with the exception of the two Mediterranean sites. We find that 3D-CMCC FEM tends to better simulate the timing of inter-annual anomalies than their magnitude within measurements’ uncertainty. In six of eight sites where data are available, the model well reproduces the 2003 summer drought event. Finally, for three sites we evaluate whether a more accurate representation of forest structural characteristics (i.e. cohorts, forest layers) and species composition can improve model results. In two of the three sites results reveal that model slightly increases its performances although, statistically speaking, not in a relevant way.

Collalti A., Perugini L., Chiti T., Nolè A., Matteucci G., Valentini R.

2014

A process-based model to simulate growth in forests with complex structure: evaluation and use of 3D-CMCC Forest Ecosystem Model in a deciduous forest in Central Italy

Ecological Modeling

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Abstract:

Forest ecosystems are characterized by high spatial heterogeneity, often related to complex composition and vertical structure which is a challenge in many process-based models. The need to expand process-based models (PBMs) to take in account such structural complexity led to development and testing of a new approach into Forest Ecosystem Models (FEMs), named 3D-CMCC-FEM, able to investigate carbon and water fluxes, including biomass pools and their partitioning, for complex multi- layer forests. 3D-CMCC FEM integrates several characteristics of the functional–structural tree models and the robustness of the light use efficiency (LUE) approach to investigate forest growth patterns and yield processes. The modelling approach was tested by simulating the effects of competition for light and water, growth and yield of a two-layered deciduous forest dominated by Turkey Oak in central Italy for a period of eight years. The model outputs were validated against a series of independently measured data for the major biomass pools, the inter-annual stem increments and above-ground net primary productivity of the overstorey and understorey, respectively. The comparison of Leaf Area Index, Gross Primary Production, and evapotranspiration produced by the model against MODIS data showed agreement in results. In addition, the multi-layered model approach was evaluated against a series of simplified versions to determine whether the enhanced complexity of the model positively contributed to its predictive ability. The proposed model reduced the error in the estimates of forest productivity (e.g. NPP) and dynamics (e.g. growth, mortality) and indicates the importance of considering, as far as possible, the structural complexity in PBMs.

Pellicone G., Collalti A., Matteucci G., Scarascia Mugnozza G.

2018

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Climate change mitigation by forests: a case study on the role of management on carbon dynamics of a pine forest in South Italy

University of Tuscia Ph.D. Thesis

Abstract:

In the last decades, the problem of global changes has been of major importance, in particular the increase in CO 2 concentration in the atmosphere with the consequent rise in the average temperature of the planet. In this context forests and their rational/optimal management is very important to contribute to the mitigation of the effects of climate change. Studying in deep how forest management modifies the processes that control carbon dynamics during stand development and in response to climate change, is therefore key to improve our understanding of land-based climate mitigation. For these reasons, modelling tools are increasingly used by both forest ecologists, who face the challenge of transferring knowledge to stakeholders and the general community, and forest managers, who benefit from the development of scenario-based supports for decision-making. In particular, the objective of this study is to analyse the impact of the current and alternative forestry practices on carbon fluxes in a pine forest in South Italy under scenarios of climate change. This was done by simulating three different forest planning scenarios using the 3D-CMCC-CNR-FEM model, and evaluated over time with respect to carbon fluxes variables. The first part of thesis has focused its attention on analysis of dendrometric characteristics of the forest, sensitivity analysis and Bayesian calibration of the model. This has allowed to estimate the uncertainty of the model output in comparison with the measured data and its analysis, in response of the model outputs. The second part is focused, firstly, on analysing the different behaviour of the forest under management (reference management: rotation: 90 yrs; interval: 15 yrs; intensity: 25%), in comparison with the “not managed” forest in terms of temporal variation of Gross Primary Production (GPP), Autotrophic Respiration (RA), woody C-stock and Net Primary Production (NPP) under different climate scenarios. In this respect, results show that a progressive reduction in forest cover through thinning confers beneficial effects on the growth and development of the remaining plants. If management, on the one hand, due to a reduction in leaf area, determines a decrease in photosynthesis as a whole, on the other hand it creates better light conditions that contribute to increase and make the photosynthetic process of the remaining plants more efficient and consequently contribute to the enhanced NPP of forest ecosystems. Secondly, the analysis focused its attention on the woody C-stock and NPP dynamics by comparing different forest management options. The purpose is to analyse in detail how the variation of several management factors (rotation, interval, intensity), affect the forest development under different climatic scenarios. From the analysis it emerged that the factor that determines a greater weight on the productivity of the forest is the choice of rotation. In particular, it has been observed that an increase in rotation length has beneficial effects not only on the carbon stock but also on carbon sequestration. This would suggest the hypothesis that in conditions of climate change, in Mediterranean climate and for conifer forest, careful forest management characterized by rotations, intervals and intensities well calibrated on specific biotic and abiotic conditions may guarantee a carbon assimilation comparable in an undisturbed forest maximizing the total carbon stock at the same time. This confirms the importance of sustainable forest management, which not only provides for the optimal maximization of timber production, but also has the potential to guarantee the performance of various ecosystem services that are important for the community.

Marconi S., Chiti T., Collalti A., Valentini R.

2014

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Assessing NEE and Carbon Dynamics among 5 European Forest types: Development and Validation of a new Phenology and Soil Carbon routines within the process oriented 3D-CMCC-Forest-Ecosystem Model

University of Tuscia Master Thesis

doi: 10.13140/2.1.5065.1848

Abstract:

The two main processes involved in forest ecosystems carbon balance are photosynthesis (GPP) and respiration. Ecosystem respiration (Reco) is determined by heterotrophic and autotrophic respiration, the former driven by microbial decomposition of soil organic matter (SOM), the latter by growth and maintenance of plant tissues. By differencing photosynthesis and respiration we have an estimate of the global carbon budget of a forest ecosystem, namely the Net Ecosystem Exchange (NEE). In this purpose, the aim of this work was to implement the 3D-CMCC-Forest Ecosystem Model (6.1.) to better estimate GPP and assess the C cycle in European  forests. We included a new soil Carbon dynamics routine and several modifications in phenology, respiration and littering. Bud burst phenology has been improved with a new “Nonstructural Carbon injection function” representing the quantity of Carbon daily destined to new leaves and fine roots development. Fall phenology has been improved with a novel semi empirical logistic function to simulate leaf falling. Evergreen leaves turnover has been completely redesigned following an intra-crown competition logic. Soil carbon dynamics through the Residues, Microbial and Humus pools have been developed following a zero order kinetics equation, representing microbial decomposition activity. Autotrophic respiration has been implemented with a soil water potential factor to represent stomata closure when drought occurs. A new canopy vertical structure initialization rationale has been developed using the Perfect Plasticity Approximation algorithm; unfortunately it could be tested only on sites where dendrometric data were available. 3D-CMCC-FEM 6.1.v was validated against 6 EddyCovariance CarboEurope towers, representing 5 of the most diffuse forest ecosystems in Europe. The sites have been chosen to represent a climatic and longitudinal transect trough the European continent, so that the model could be tested on different critical boundary conditions. The GPP, Reco and NEE fluxes were validated for about 10 years at each site. To evaluate the model efficiency we tested daily and monthly correlation, Nash-Sutcliffe Model Efficiency, Goodness of Fit to a mono parametric linear regression.The model’s plasticity and ability in representing observed anomalies was determined by analyzing inter annual, month and seasonal variability following published methods. We then statistically inferred the relationships between expected and observed frequency distributions of the anomalies. The results were quite encouraging; GPP r 2 was averagely 0.74 (daily) and 0.89 (monthly), the RMSE of about 1gC m-2 d-1 , the NSE greater than 0.7. Anomalies results were very good too; the NRMSE was averagely of 1.2 gC m -2 d -1 and their distribution were always significantly consistent with the observed ones. Reco r2 was averagely 0.59 (daily) and 0.69 (monthly), the RMSE of about 0.83 gC m-2 d-1 , the NSE greater than 0.54 (daily) and .75 (monthly). Anomalies results were very good too; the NRMSE was averagely of 1.2 gC m-2 d-1 , their sign was captured for about 70% of the times and their distribution were always significantly consistent with the observed ones. The propagation of uncertainties resulted in NEE r2 averagely of 0.56 (daily) and 0.89 (monthly) (0.66 and 0.82 excluding the Mediterranean forest), the RMSE of about 1.5 gC m -2 d -1 , the NSE greater than 0.51 excluding the negative value of the Q. ilex stand. Anomalies results were acceptable and in line with the other PBMs in literature. Even though the NRMSE was averagely of 1.3 gC m -2 d -1 the frequency distribution of the anomalies distribution coincided with the observed ones just for half the sites. The model showed interesting improvements from the 5.1. version (in prep.), even more from the published 4.0 version. The model showed its weakness in representing the Mediterranean Forests, probably because of the over simplistic way to represent soil water dynamics and stresses. The use of the water potential RA liming factor apparently confirmed this hypothesis, since Reco was significantly improved and gave even better results than GPP after its implementation. In conclusion this work positively achieved its objectives. The model now reliably estimate all the components of the C cycle for the main European forest ecosystems. The new functions resulted in better GPP and RA estimation, finally allowed the model to simulate RH, Reco and NEE, and introduced new ideas to the forest modeling international panorama. The 6.1. version thus has wider perspectives and applicability and may be taken into account for several different applications; from predicting the net C cycle on regional scale, to assistingfuture forest management on finer scales up to 1 hectare.

Collalti A., Valentini R.

2011

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Sviluppo di un modello dinamico ecologico-forestale per foreste a struttura complessa

University of Tuscia PhD Thesis

Abstract:

Forests are important both for socio-economic and for environmental aspects. Forests changes affect a delicate balance that involves not only vegetation components but also bio-geochemical cycles and global climate and they play an important role in biodiversity conservation. Hence the knowledge of the amount of Carbon sequestered for carbon cycle by forests, represents precious information for their sustainable management in the framework of climate changes. The aim of the present work is the development of a forest dynamic model, generic, hybrid on ecosystem spatial scale able to obtain useful predictive information for the knowledge of the process at the base of forest dynamic and forest management using ecophysiological parameters easy to be assessed and to be measured. The 3D-CMCC Forest Model is based on light use efficiency (LUE) approach at the canopy level. It's well documented that the mutual interaction of forest growth and light conditions cause vertical and horizontal differentiation in the natural forest mosaic. Only eco-physiological parameters which can be either directly measured or estimates with reasonable certainty, are used. The model has been created considering a tridimensional cell structure with different vertical layers depending on the forest type that has to be simulated. The 3D-CMCC Forest Model is able to work on multi-layer and multi-species forests type from one hectare cell resolution and at monthly time-step for the typical Italian forest species. The multi-layer version is the result of the implementation and development of Lambert-Beer law for the estimation of intercepted, absorbed and transmitted light through different storeys of the forest in a new logic structure. It is possible estimates, for each storey, a PAR value (Photosynthetic Active Radiation) through Leaf Area Index (LAI), Light Extinction Coefficient and cell Canopy Cover using a “Big Leaf” approach and the evapotraspiration rate, itself closely linked to the light intercepted, for each layer and the evaporation from soil. Hence, the presence of a cohort in a storey determines the amount of light received for the photosynthetic processes. The population density (numbers of trees per cell) represents a good competition index for determining the tree crown structure and tree crown dimension within a forest population. The model assesses the structure of the tree crown both vertically and horizontally on the base of the population density and it upscale the result to the whole stand. The canopy depth and the percentage of horizontal coverage determines moreover a crowding competition index that lead to a specific biomass partitioning-allocation ratio among the different tree components (foliage, roots, stem and fruits) and especially for the stem affecting Height-Diameter (at breast height) ratio hence modeling the forest dynamic. In this model, Height-Diameter ratio is used as an alternative competition index in determining the vigour and the strength of competition on free growth status of trees. The forest dominant vegetative cover affects moreover the presence of a dominated layer, it influences its yield and its carbon stocking capacity and thereby the forest ecosystem CO2 carbon balance. Using this model it is possible to simulate the impact of climate change on forests as a result of productivity decrement or in some cases increment as well as the feedback of one or more dominated layers in terms of CO2 uptake in a forest stand and the effects of forest management activities for the next years. The model has been applied in an explanatory investigation to compute the medium-term (10 years) development of a multi-layer, multi-age and multi-species turkey oak forest (Q. cerris L.). The results obtained agree with measured data.

3D-CMCC-Forest Ecosystem Model

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