Lab

Forest Modelling Lab.


About the lab

The Forest Modelling Laboratory is a research laboratory of the Institute for Agricultural and Forestry Systems in the Mediterranean at the National Research Council of Italy (ISAFOM-CNR) that specifically studies and analyzes the quantitative and qualitative representation of the interactions underlying the productivity, resistance and resilience to perturbations of forest ecosystems and their responses to forcing ecological and climate; develops, parameterises, validates and uses process simulation models, regressive models, dynamics models, both to deepen the understanding of the processes understanding of the processes underlying the functioning of the forest ecosystems, which to evaluate their response to the climate and climate change scenarios.
https://www.forest-modelling-lab.com

Featured research (166)

Forest ecosystems account for about one-third of the Earth's land area, and monitoring their structure and dynamics is essential for understanding the land's carbon cycle and its role in the greenhouse gas balance. In this framework, process-based forest models (PBFMs) allow studying, monitoring and predicting forest growth and dynamics, capturing spatial and temporal patterns of carbon fluxes and stocks. The 'Three Dimensional-Coupled Model Carbon Cycle-Forest Ecosystem Module' (3D-CMCC-FEM) is a well-known eco-physiological, biogeochemical, biophysical process-based model, able to simulate energy, carbon, water and nitrogen fluxes and their allocation in homogeneous and heterogenous forest ecosystem. The model is specifically designed to represent forest stands, from simple ones to those with complex structures, involving several cohorts competing for light and other resources in a prognostic way. Currently, the model is implemented in C-language, which can be challenging for the broad public to use, and thus limiting its applications. In this paper, we present the open-source R package 'R3DFEM' which introduces efficient methods for: i) generating and handling input data needed for the model initialization; ii) running model simulations with different set up and exploring input; and iii) plotting output data. The functions in the R-package are designed to be user-friendly and intended for all R users with little to advanced coding skills, who aim to perform simulations using the 3D-CMCC-FEM. Here we present the package and its functionalities using some real case studies and model applications.
The consequences of climate change continue to threaten European forests, particularly for species located at the edges of their latitudinal and altitudinal ranges. While extensively studied in Central Europe, European beech forests require further investigation to understand how climate change will affect these ecosystems in Mediterranean areas. Proposed silvicultural options increasingly aim at sustainable management to reduce biotic and abiotic stresses and enhance these forest ecosystems' resistance and resilience mechanisms. Process-based models (PBMs) can help us to simulate such phenomena and capture early stress signals while considering the effect of different management approaches. In this study, we focus on estimating sensitivity of two state-of-the-art PBMs forest models by simulating carbon and water fluxes at the stand level to assess productivity changes and feedback resulting from different climatic forcings. Utilizing 3D-CMCC-FEM and MEDFATE models, we simulated and analyzed carbon (C) and water (H20) fluxes in diverse forest plots under managed vs. unmanaged scenarios and under current climate and different climatic forcings (RCP4.5 and RCP8.5), in two sites, on the Italian peninsula, Cansiglio in the north and Mongiana in the south. To ensure confidence in the models' results, we first evaluated their performance in simulating C and H2O flux in three additional beech forests along a latitudinal gradient spanning from Denmark to central Italy. The results from both models for C and H2O flux assessment showed generally good model accuracy. At the Cansiglio site in northern Italy, both models simulated a general increase in C and H2O fluxes under the RCP8.5 climate scenario compared to the current climate. Still, no benefit in managed plots compared to unmanaged ones, as the site does not have water availability limitations, and thus, competition for water is low. At the Mongiana site in southern Italy, both models simulate a decrease in C and H2O fluxes and sensitivity to the different climatic forcings compared to the current climate, with an increase in C and H2O fluxes considering specific management regimes compared to unmanaged scenarios. Conversely, in both models, under unmanaged scenarios, plots are simulated to experience first signals of mortality prematurely due to water stress (MEDFATE) and carbon starvation (3D-CMCC-FEM) scenarios. In conclusion, while management interventions may be considered a viable solution for the conservation of beech forests under future climate conditions at moister sites like Cansiglio, in drier sites like Mongiana may not lie in management interventions alone but rather in the establishment of synergistic mechanisms with other species.
The impacts of climate uncertainty pose important questions regarding the capability of forest ecosystems to buffer current and future climate-induced global changes while still delivering ecosystem services as society demands and future policy requirements advocate (e.g., the European Green Deal). Medium- to long-term forest dynamics (growth, competition, mortality), forest structure, and biodiversity may be profoundly altered by climatic-induced extremes in the future. Disturbances (e.g., wildfires, droughts, windthrows, bark-beetle outbreaks) risk increasing the susceptibility of forests, thus enhancing tree mortality despite afforestation/reforestation efforts to offset CO2 emissions. In addition, the role of forest management practices (i.e., adaptive forest management) may buffer and/or dampen forest response to extreme events; however, multiple and diversified choices should be tested. In such uncertain scenarios, the role of simulation models and decision support systems is much advocated by the scientific community and policymakers to be able to assess and potentially quantify the behavior and responses of forest ecosystems under varying environmental conditions. In this Special Issue, we encourage and welcome studies introducing new methods, novel applications, and innovative designs to i) model the impacts of climate change on medium- to long-term forest dynamics; ii) assess the impacts of climate change on the delivery of crucial ecosystem services in all forest ecosystems; and iii) analyze, assess, and quantify the impact of climate-induced disturbances on forest carbon cycle, water dynamics, and on the overall forest productivity, in both data-driven and dynamic vegetation models.
Tropical deforestation in the African continent plays a key role in the global carbon cycle and bears significant implications in terms of climate change and sustainable development. Especially in Sub-Saharan Africa, where more than two-thirds of the population rely on forest and woodland resources for their livelihoods, deforestation and land use changes for crop production lead to a substantial loss of ecosystem-level carbon stock. Unfortunately, the impacts of deforestation and land use change can be more critical than in any other region, but these are poorly quantified. We analyse changes in the main carbon pools (above-and below-ground, soil and litter, respectively) after deforestation and land use/land cover change, for the Jomoro District (Ghana), by assessing the initial reference level of carbon stock for primary forest and the subsequent stock changes and dynamics as a consequence of conversion to the secondary forest and to five different tree plantations (rubber, coconut, cocoa, oil palm, and mixed plantations) on a total of 72 plots. Results indicate overall a statistically significant carbon loss across all the land uses/covers and for all the carbon pools compared to the primary forest with the total carbon stock loss ranging between 35% and 85% but with no statistically significant differences observed in the comparison between primary forest and mixed plantations and secondary forest. Results also suggest that above-ground carbon and soil organic carbon are the primary pools contributing to the total carbon stocks but with opposite trends of carbon loss and accumulation. Strategies for sustainable development, policies to reduce emissions from deforestation and forest degradation, carbon stock enhancement (REDD+), and planning for sustainable land use management should carefully consider the type of conversion and carbon stock dynamics behind land use change for a win-win strategy while preserving carbon stocks potential in tropical ecosystems.

Lab head

Alessio Collalti
Department
  • Institute for Agricultural and Forestry Systems in the Mediterranean
About Alessio Collalti
  • Alessio Collalti has a Master Science Degree in Natural Sciences and a Ph.D. in Forest Ecology. His background concerns Forest Ecology, Carbon, Water and Nitrogen Cycle, Forest and Vegetation Modelling, particularly with regard to vegetation numerical modelling and response under natural and anthropogenic stress, including climate change impacts and forest management scenarios He is the Forest Modelling Lab. head and a senior researcher at CNR.

Members (6)

Elia Vangi
  • Italian National Research Council
Daniela Dalmonech
  • Italian National Research Council
Elisa Grieco
  • Italian National Research Council
Mauro Morichetti
  • Italian National Research Council
Paulina Puchi
  • Italian National Research Council
Vincenzo Saponaro
  • Tuscia University

Alumni (4)

Gaetano Pellicone
  • Italian National Research Council
Sergio Marconi
  • University of Florida
Giulia Mengoli
  • Imperial College London
Corrado Biondo
  • Centro Euro-Mediterraneo sui Cambiamenti Climatici