Search

International audience; Abstract. The mechanistic model GO+ describes the functioning and growth of managed forests based upon biophysical and biogeochemical processes. The biophysical and biogeochemical processes included are modelled using standard formulations of radiative transfer, convective heat exchange, evapotranspiration, photosynthesis, respiration, plant phenology, growth and mortality, biomass nutrient content, and soil carbon dynamics. The forest ecosystem is modelled as three layers, namely the tree overstorey, understorey and soil. The vegetation layers include stems, branches and foliage and are partitioned dynamically between sunlit and shaded fractions. The soil carbon submodel is an adaption of the Roth-C model to simulate the impact of forest operations. The model runs at an hourly time step. It represents a forest stand covering typically 1 ha and can be straightforwardly upscaled across gridded data at regional, country or continental levels. GO+ accounts for both the immediate and long-term impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes exhaustive and versatile descriptions of management operations (soil preparation, regeneration, vegetation control, selective thinning, clear-cutting, coppicing, etc.), thus permitting the effects of a wide variety of forest management strategies to be estimated: from close to nature to intensive. This paper examines the sensitivity of the model to its main parameters and estimates how errors in parameter values are propagated into the predicted values of its main output variables.The sensitivity analysis demonstrates an interaction between the sensitivity of variables, with the climate and soil hydraulic properties being dominant under dry conditions but the leaf biochemical properties being most influential with wet soil. The sensitivity profile of the model changes from short to long timescales due to the cumulative effects of the fluxes of carbon, energy and water on the stand growth and canopy structure. Apart from a few specific cases, the model simulations are close to the values of the observations of atmospheric exchanges, tree growth, and soil carbon and water stock changes monitored over Douglas fir, European beech and pine forests of different ages. We also illustrate the capacity of the GO+ model to simulate the provision of key ecosystem services, such as the long-term storage of carbon in biomass and soil under various management and climate scenarios.

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand-level, as well as remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction, and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a SQLite relational database or ASCII flat file version (at https://doi.org/10.5880/PIK.2019.008). The data policies of the individual, contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R-package (https://github.com/COST-FP1304-PROFOUND/ProfoundData), which provides basic functions to explore, plot, and extract the data for model set-up, calibration and evaluation.

Eight years of monitoring ecophysiology and ecosystem services (ES) in a large coffee farm of Costa Rica yields a range of practical applications for the farmer and stakeholders, thanks to numerous scientific actors and disciplines contributing to our collaborative observatory (Coffee-Flux). • A lot of ecosystem services depend on the soil properties, such as runoff/infiltration, water and nutrient storage capacity. It is essential to relate hydrological and soil conservation services to the soil type, since this might have even more importance than the crop itself for ES. Regarding the use of fertilizer, we show that some soils may have a large storage capacity, allowing producing coffee at normal yields with just a reduced, or even a minimum amount of fertilizers, for instance when the economic conditions are unfavorable. Also, due to the soil variability within the farm, it is possible to adjust fertilization to micro-local conditions and reduce the total expenses and risks of leaching of N to the environment. VNIRS and MIR are promising broadband tools for screening the variability in soils. Adjusting N fertilizer to the optimum will also considerably reduce the N2O emissions and improve the GHG balance of the farm. • Pesticides-fongicides: we show that an adequate amount of shade trees allows reducing the severity of the whole complex of leaf diseases. This also should reduce expenses and impacts on the ecosystem. • Roots: a simple survey of basal area at collar allows estimating the belowground biomass and the average age of a plantation, to judge of its market value and to decide when to replace it. • Also starch plays a key role in the trophic equilibrium between the perennial parts of the coffee plant (aerial stump, belowground stump, coarse roots) and its ephemeral parts (resprout, leaves, fruits, fine roots). Coffee plants accumulate starch in the stumps by the end of the life of their resprout, as a strategy for survival. Breeding plants with less starch build-up capacity would probably allow increasing the fraction of productive years during the lifespan of the resprouts. • Coffee farms are probably much closer to C neutrality than currently admitted using the C-Neutrality protocol. We stress the prevailing role of coffee plants + litter + soil in the ecosystem C balance. If those are excluded from the calculations as done so far, coffee farms are GHG sources, by definition. We argue that either full assessments (as proposed here, at the ecosystem level, including trees, coffee, litter, soil and roots) or consensus on “sequestration factors” (the counterpart of emission factors) would allow performing a more realistic assessment of the GHG balance. • Finally, we bring new data confirming that shade trees offer numerous ecosystem services, when adequately managed for the local context. As compared to full sun conditions, they may (i) reduce laminar erosion by a factor of ca. 2, (ii) increase the atmospheric N2 fixation and the % of N recycled into the system, thus reducing the fertilizer requirements, (iii) reduce the severity of the leaf disease complex, (iv) increase C sequestration, (v) improve the microclimate, and (vi) be a large part of the solution to face climate changes. All this is possibly without negative effects on profitability or yield, if managed properly. In our particular case-study, we encount.

International audience; In Gironde (SW of France), 98% of drinking water comes from the North Aquitaine multilayered aquifer system. It constitutes an important strategic water resource considering the great quality of this water and its natural protection against anthropic pollutions. Nevertheless, some of these aquifers are overexploited. In order to manage these resources, a regional planning of groundwater was approved in 2003. It plans the realization of new facilities to improve the spatial distribution of pumping areas in order to minimize groundwater mining impacts on specific sites.Thus, a new well field is planned in the Medoc region at 35 km west of Bordeaux. It will be composed of 14 wells and will produce 10 million cubic meters by year extract from Oligocene aquifer (150 m below ground surface). In this region, most of the surface is occupied by the Landes forest, which corresponds to a monoculture of maritime pines (Pinus pinaster). Soils are mainly composed of sand in which a phreatic aquifer (Plio-Quaternary) is in development.In order to evaluate the impact of the future well field on the Oligocene aquifer and the multilayered aquifer system, a hydrodynamic model (PHONEME) was specially built for this with MARHTE (Thiéry, 2014). It incorporates 8 aquifers and 7 aquitards, covering a total surface of 4,430 km².Simulations done with the groundwater model show a maximum impact of 30 m on the Oligocene and an impact between 0 and 35 cm on the phreatic aquifer.Results from the hydrodynamic model were used to evaluate impact on forest production using the INRA forest growth model GO+ (Lousteau et al., 2012). This multi-model approach was done in order to gives some answers on the impacts on the growth of trees with the implementation of a well field and to bring solutions to limit use conflicts.

National audience; Forests are one of the most vulnerable ecosystem under the coming climate changeand a growing concern arise about their capacity to maintain ecosystem services suchas production of timber, fiber and energy, climate and hydrological regulations, or soil and biodiversity protection. Climate effects are significant not only at a short timescale, but also on the temporal horizon of a forest life cycle, e.g. through continuous shifts in atmospheric CO2 concentration, air temperature and precipitation regimes induced by the enhanced greenhouse effect. This will affect not only the functioning of forests in situ but also the range and geographical distribution of forest trees pecies and therefore the spatial distribution of ecosystem services and production across countries and continents. The long term sustainable management of European forests must account for thesedynamic changes and the interactions between climate and forests. Observations of forest functioning growth and distribution for the last decades provide a rich information about forest response to climatic shifts and extreme events and the way management interplays with these impacts. We present in this communication how two modeling approaches for predicting the future of managed forest at country scale might optimize past observations to streng then their likelihood and reduce uncertainty of their projections. In situ observation networks such as flux tower networks (FLUXNET, ICOS), ICP forest network and National Forest Inventories are the main data sources used. The climate niche modeling predicts the potential distribution of forest species in the geographic domain using past observations of climate and water balance and presence/absence of tree species. Results show an expected poleward shift of forest biomes or species due to global warming and water balance changes that may reach several 10s to 100s of km during the 21st century. Similarly, a process based modelcan be calibrated and evaluated using past observations to predict forest functioning as forced by climate scenarios. The energy balance and the carbon and water cycles in the soil-plant-atmosphere system are modeled at an hourly scale and integrated over an annual basis. As one of the main disturbance in the temperate forests,management is integrated through practices such as ploughing, thinning or clearcutting. Long time series of flux measurements in monospecific forest stands are used tocalibrate the model while adjusting parameters. In a second step, models have been run in various ecological conditions and we have compared the outputs to long time series of observed data from forest inventories or monitoring networks to model predictions. Last, we use climate projections derived from RCP scenarios until 2100 at8x8 km grid to force the models. This work is conducted across the French metropolitan area for 3 of the main European forest species: Maritime Pine, common Beech and Douglas-fir. Our results provide an evaluation of the ecosystem services (carbon sequestration, wood supply, water regulation) taking into account climate change. Based on these results we will discuss about the way to manage/optimize these French forests in the future. To enhance cooperation between researchers and stakeholders, a panel of managers and decision makers has been involved to implement various forest management scenarios in the model.

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO$_{2}$, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a “SQLite” relational database or “ASCII” flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.