Introduction to the theme - Christine Deleuze (ONF) takes the floor©ONF
How to better understand the forest carbon cycle - Eric Dufrêne (CNRS) takes the floor©ONF
In a context of climate change, the stakes are double for our forests: they must adapt to rapidly changing environmental conditions while they also play a role in attenuating climatic upheavals through their ability capture and store atmospheric carbon, most notably in wood.
We use models to mobilize our existing knowledge in order to simulate natural phenomena and to try to respond to questions about how forests will evolve in the future.
Basically, we can separate forest growth models into two main categories:
- models based on dendrometry, which extrapolate growth from observed local growing conditions assuming a "stable" future climate;
- models of bio-physical processes, which offer short-term extrapolations of how trees will respond to climate changes.
Recently, attempts have been made to combine these two types of models.
The global model called ORCHIDEE is based on broad functional types while the CANTANEA model explicitly takes into account forest species. In France, each of these models have been combined with forest stand structure models. These hybrid models include long-term stand structure dynamics and therefore allow us to extend the predictive capacity of process-based models to the whole forest cycle.
The hybrid model CASTANEA-SSM also makes it possible to evaluate the combined effects of climate changes and silvicultural regime on stand production and survival depending on the dominant tree species.
In both types of models, to calibrate the equations and test the accuracy of their predictions, on-site observations and measurements are required. Dendrometric models use a restricted number of equations and parameters but process-based models and hybrids require large numbers of equations and parameters in order to represent the wide variety of processes simulated.
The CASTANEA model was developed in the mid-1990s drawing on knowledge in plant organ ecophysiology and forest canopy bio-climatology. CASTANEA was first designed as a Soil-Vegetation-Atmosphere (SVAT) model to predict water vapour and CO2 fluxes between forest ecosystems and the atmosphere on an hourly basis throughout the year. The goal was to simulate the effects of an increase in atmospheric CO2 on forest ecosystems through experiments with open-top chambers in controlled environments (European ECOCRAFT Project). Within a decade, however, advances in flux measurements through eddy covariance in forest canopies made it possible to calibrate and test CASTANEA under real conditions in forest stands (the European CarboFlux and later Carbo-Europe projects).
Thus, after an important series of studies in the Hesse beech forest, CASTANEA was adapted and tested for several other tree species thanks to data from the European (for Holm oak, sessile oak, Scots pine, spruce, maritime pine) and American (for Douglas fir) flux tower networks. The main objective was to reproduce daily, seasonal and inter-annual variations in water vapour and CO2 fluxes.
Meanwhile, work began elsewhere to improve our knowledge of carbon reserves in order to simulate growth in the main components of the tree, in particular the trunk. The CASTANEA (SVAT) flux model was adopted as a carbon balance model and used to simulate growth for several species (sessile oak, beech, Holm oak, spruce).
Simulating carbon allocation to the different plant compartments is much more dependent on species than it is for gaseous fluxes. Simulating fluxes requires specific parametrisation but the rules (or processes translated into equations) are often rather "generic". Simulating carbon allocation not only requires specific parametrisation but, in addition, the rules can vary considerably from one species to another. It is also difficult to simulate net carbon absorption or release for a given forest rotation since tree age and size have considerable effects on parametrisation and sometimes on allocation rules.
To respond to the challenge set by this variability, different sets of data must be integrated from monitoring networks at the landscape scale (for example, the Fontainebleau forest), the country scale (France) and the European scale. Typically, the number of plots or sites in a monitoring network is inversely proportionate to the number of variables measured. On the other hand, there is no relation between the spatial scale of the network and the number of plots or variables concerned.
RENECOFOR data, either alone or in combination with data from other networks, have made it possible to parametrise the bud burst model, to parametrise and develop the leaf-yellowing model, to test the schema for carbon allocation connected with the management model (ceci n'est pas clair pour moi et je n'ai trouvé aucune reference internet pour m'aider - au secours!) , and finally, to develop and test a model for fruiting (in progress).
Are forest soils a carbon sink? - Mathieu Jonard (Catholic University of Louvain) takes the floor©ONF
Soils play an important role in climate regulation. They store considerable amounts of carbon in the form of organic matter, which, if increased by only 4/1000 a year, could possible stop the increase in atmospheric CO2 concentrations. Inversely, decreasing organic matter in the soil could accelerate climate change.
Many countries, including France, have shown their commitment to reducing greenhouse gas (GHG) emissions by signing the Kyoto protocol, and more recently the 2015 Paris Agreement, in the framework of international negotiations on climate change. To prove that they are honouring their commitments, signatory countries must track their emissions. For the 2008-2012 period, France committed to reducing its GHG emissions by 5% compared to 1990 levels and chose to incorporate forestry in their calculations, based on the assumption (unproven to date) that forest soils were either neutral or positive carbon sinks.
In this light, results from the first repeated soil samples taken at a 15-year interval on the 102 RENECOFOR plots were analysed. The objective of the study, supported by the Ministry in charge of Agriculture, aimed to detect and quantify the changes that had taken place in the organic carbon stocks found in the forest soils and litter. Two approaches were used to try to understand the causes of the observed changes: a statistical procedure to select explanatory factors, and an estimated carbon status report based on incoming and outgoing fluxes.
Soil data were collected during two sampling campaigns, one between 1993 and 1995, and the second between 2007 and 2012. On each plot, five square sub-plots were set up (one in the centre and four near the edges of the plot). Each sub-plot was further divided using an overlay grid to determine 16 nodes, five of which were chosen for sampling to guarantee good spatial distribution. For each soil layer, a composite sample was created by combining the soil in that layer from the five sub-plot samples. This sampling design made it possible to quantify intra-plot variability and to reveal possible changes over time at the plot scale. Depending on the sampling campaign and the plot, soil samples contained four to six layers. Up to three layers were described for forest floor litter; then the underlying mineral soil was sampled in successive pre-determined layers: 0-10cm, 10-20cm, and 20-40cm.
Laboratory analysis methods were the same for both sampling campaigns. Organic carbon content was determined by dry combustion (after removing carbonates) for the litter layers and the first mineral layer (0-10 cm), and by the Anne method for the other mineral layers (10-20 cm and 20-40 cm). Total carbon content for the litter layers was calculated by multiplying the mass of each layer by its organic carbon content, then by adding the results for all the layers. For the mineral layers, organic carbon content was calculated according to the apparent density of the soil layer while the percentage of coarse elements was accounted for.
Since the time between the two sampling campaigns varied from one plot to another, statistical analyses were carried out on the differences in carbon stocks between the two campaigns proportionate to the time elapsed. Annual variations in carbon stocks were significant only for the litter layers, the 0-10 cm soil layer and total stocks (see Table below). The variations were positive, thus indicating that carbon sequestration took place, reaching 0.35 tC per ha per year, which, in terms of soil carbon sequestration, equates to around 4/1000. Assuming that forest soils throughout France have gone through comparable changes, this results in a carbon sink equal to approximately 5% of the GHG emissions due to the use of fossil fuels in France.
To identify the factors explaining the variability in carbon sequestration rates among the plots in the network, a selection methodology was applied to a series of 34 potential explanatory variables; two factors were highlighted: stand age and stand structure.
Soil carbon sequestration rates slow down as the stand ages and are higher in irregular than in regular (even-aged) stands. However, these two factors combined explain only 14% of the variability. This small proportion is due to high within-plot variations in soil carbon sequestration. In addition, stand age effect could have been confounded by a possible species effect or an effect due to how long the plot had been forested: in the data set, softwood stands were on average younger and, in terms of historic land use, appeared later than hardwood stands. These results do suggest, however, that forest management practices may have an effect on soil carbon sequestration.
To assess which processes might underlie forest soil carbon sequestration, a carbon balance of incoming and outgoing carbon was built for a virtual plot representative of the whole network. The balance was estimated for above-ground (litter) and below-ground (mineral layers) soil components and assumed that there was initially an equilibrium between carbon intake and release. The results indicate that the carbon sequestration rate found for the litter layers could be due to slowed decomposition resulting from a deterioration in the quality of the organic matter (increase in the carbon/nitrogen ratio).
For the mineral layers, the rate of sequestration estimated in the balance was much lower than actual observed levels, thus indicating that there was probably no state of equilibrium at the time of the first sampling campaign and that litter was building up faster than it could decompose. One wonders, for example, if a reforestation campaign similar to the one that began at the turn of the 19th century were to be undertaken today, whether stocks of organic material in the mineral soil would increase with the change-over from previous agricultural use.
Following this study, many questions remain. Will forest soils continue to store carbon over the long term? How stable is the newly stocked carbon? What are the processes underlying forest soil carbon sequestration?
Understanding the dynamics of soil organic matter - Delphine Derrien (INRA) takes the floor©ONF
The international initiative "4/1000" hopes to increase by 0.4% each year the global amount of carbon stored in the first 30 centimetres of the soil. Theoretically, this would slow down, or even stop, the current rise in CO2 levels in the atmosphere. What is more, increasing carbon (C) stocks in the soil would improve soil quality and reduce erosion. Of course, soils would be richer in organic material, and in nutrients, yields would improve, and our ability to feed the planet would be strengthened. For the moment, 82 countries are willing to commit to applying this initiative through different international programmes.
Adding plant material would appear to be the most obvious way to increase soil carbon. However, adding organic material to the soil could in fact increase carbon release... That is why it is important to understand the fine-tuned mechanisms that control soil carbon storage: Where does soil carbon come from? What forms does it take? How long will it remain stored in the soil?
In this talk, we will take a look at the studies and reflections going on within the CarboSMS group (Soil Carbon, Stabilisation Mechanisms - https://carbosms.wordpress.com/). The group has 120 members from the French-speaking scientific community who are working on soils and their capacity to store carbon.
We will first look at recent advances in our knowledge of carbon stabilisation mechanisms in the soil. Two major types of mechanisms influence stabilisation / destabilisation of organic C in soils: those related to living organisms and biodiversity (plants, fauna, micro-organisms), and abiotic mechanisms (location in the physical soil structure and interactions among the different mineral particles).
Next, we will talk about how silvicultural practices affect carbon stocks in the soil. By acting on both the biotic and abiotic mechanisms, the choice of species and planting density, harvesting and extraction intensity, soil amendments, fertilisation or working the soil determine not only the amount of organic matter brought to the soil over time and in space, but also influence the sensitivity of the soil organic matter to mineralization. We will illustrate the complexity of the interactions between these mechanisms and their effect over time on carbon stocks through meta-analyses and long-term field studies.
Finally, we will show how taking these mechanisms into account in global models of carbon dynamics or when determining indicators for carbon storage stability can improve our predictions of trends in soil organic carbon storage. However, these new models or indicators, which include the fine mechanisms of carbon storage, must first go through a validation process before they can be applied at a larger territorial scale. Here, networks of monitoring sites like RENECOFOR are especially precious. Indeed, detecting changes in carbon stocks necessitates repeated analyses over extended periods of time. Furthermore, determining whether a model or indicator is robust enough to be generalised requires comparing predictions and estimates to actual recorded data from a variety of pedological and climatic contexts.