Parametrización de modelos de procesos para predecir de crecimiento y productividad en plantaciones de Gmelina arborea en escenarios de cambio climático

The development of forest plantations tolerant to stress conditions is key to guaranteeing the sustainability of crops in the face of future climate change (CC) scenarios, especially the tropical region that is emerging as highly vulnerable to droughts and extreme climate events. Therefore, it is key to develop adaptation strategies such as the selection of tolerant species/clones, optimization of silvicultural management, and synchronization of cultivation with the current and future availability of resources of the locality. At this point, it is essential to have tools to project the growth and productivity of the crop in different scenarios to reduce the risk of loss of crop area and uncompetitive production levels. In this context, adjusting process models has shown to be a precise and versatile option to initiate adaptation to CC, especially in regions or localities where there is no previous establishment experience and there is uncertainty about the tolerance of the species/ clones to use. Therefore, the study aims to incorporate the use of physiological process models as a tool to predict the growth and productivity of Gmelina arborea forest plantations in potential climate change scenarios. The study considers the collection of morphological, physiological, and hydraulic data from commercial Gmelina arborea materials in Costa Rica, from which to define discriminative traits between materials on pathways to create a first categorization criterion of phenotypic plasticity. It then incorporates these traits together with soil and climate data in the calibration of the models: 3-PG (Physiological principles that predict growth) and APSIM Next Generation (Agricultural production systems simulator), to subsequently validate and use the model under different CC scenarios (Focused on reducing water availability), and evaluate the response in yield and growth (example: volume, accumulation, and biomass partitioning), in order to generate a categorization of degrees of plasticity of commercial materials, discriminating materials potentially susceptible and tolerant to CC. Along with this, it is intended that calibrated models are approved and standardized for public use, both national and international, which is why it considers a link with the CSIRO APSIM NG development team (Australia) for the generation of repositories according to the use of R and C# language; Finally, calibrated models are intended to develop technology transfer workshops for companies, nongovernmental organizations, state institutions, and independent consultants associated with national forest management, with the aim of being a tool to evaluate the current state of plantations and potential scenarios in order to improve decision-making decisions and actions to guarantee the sustainability of forest resource in the country.

Incorporar el uso de modelos de procesos fisiológicos como herramienta para predicción de crecimiento y productividad den plantaciones forestales de Gmelina arborea bajo potenciales escenarios de cambio climático.

Gestión del cultivo de árboles para la restauración, conservación y producción de madera y servicios ecosistémicos.