Using the process-based stand model ANAFORE including Bayesian optimisation to predict wood quality and quantity and their uncertainty in Slovenian beech

Physiologically-based (or process-based) models are commonly applied to describe plant responses mechanistically in dependence on environmental conditions. They are increasingly evaluated with eddy-covariance measurements that integrate carbon and water exchange of an area of several hectares (called the fetch). However, almost all models applied to date in such exercises have considered only the dominant tree species and neglected other species that contributed to the measured gas exchange rates-either in separate patches or in mixture. This decreases the transferability of the model from one site to another because the contributions from other species might be different. It is therefore a major challenge in modeling today to separate the measured gas exchanges by sources.In this study, a detailed physiologically-based biosphere model is applied that allows distinguishing between tree species in mixed forests, considering them as «vegetation cohorts» that interact with each other. The sensitivity of the model to different assumptions about how different tree species contribute to an integrated measurement of standscale gas exchange is investigated. The model exercise is carried out for a forest site in Finland with dominant Scots pine but presence of significant amounts of Norway spruce and birch. The results demonstrate that forest structure affects simulated gas exchange rates indicating a possible importance of considering differences in physiological properties at the species level. It is argued that the variation of stand structure within the range of eddy-covariance measurements should be better accounted for in models and that inventory measurements need to consider this variation.Key words: forest structure; understorey; physiologically-oriented model; eddy-flux measurements; sensitivity analysis. ResumenRetos para la evaluación de modelos basados en procesos de intercambio de gases en rodales con diversas especies Los modelos con base fisiológica (o basados en procesos) se aplican habitualmente para describir las respuestas de la planta mecanísticamente dependiendo de las condiciones ambientales. Son evaluados cada vez más frecuentemente con mediciones de eddy-covariance que integran el intercambio de carbono y el agua de una superficie de varias hectáreas. Sin embargo, casi todos los modelos aplicados hasta la fecha han considerado sólo las especies arbóreas dominantes y se han descuidado otras especies que contribuyen a las tasas de intercambio gaseosos medidas-ya sea en zonas separadas o en mezcla. Esto disminuye la posibilidad de transferir el modelo de un sitio a otro debido a que las contribuciones de otras especies pueden ser diferentes. Por tanto, es un reto importante en la modelización separar el intercambio gaseoso medido por fuente emisora.En este estudio, se aplica un modelo detallado con base fisiológica de la biosfera que permite distinguir entre las especies de árboles en bosques mixtos, considerándolas como «cohortes de vegetación» que interaccionan unos con otros. Se estudia l...

Section: Discussionmentioning

confidence: 99%

Challenges for evaluating process-based models of gas exchange

Grote

Korhonen²,

Mammarella³

2011

“…The results are empirically enabled mechanistic models with more predictive power, turning them from an interesting research instrument into a management application tool (Deckmyn et al, 2009). …”

Section: Hybrid Simulationmentioning

confidence: 99%

Simulation tools for decision support to adaptive forest management in Europe

Muys

Hynynen²,

Palahí

et al. 2010

In forest management there is a tendency towards measuring more cost-effective and simulating more. In this context the development of reliable, user friendly forest simulators has become economically relevant. The objective of this perspective paper is to highlight the recent trends in forest simulation and to identify the remaining challenges to make forest simulation a reliable tool for forest policy and management.Experiences with forest simulators for various purposes in different geographical contexts illustrate how the important challenges of forest decision support can be addressed through flexible customization for different end-user categories, offering spatially explicit approaches at the landscape scale, and integrating empirical and mechanistic models in hybrid and bayesian simulation approaches.Recent development trends in forest simulation for decision support are mainly related to the ever increasing calculation speed and capacity of computers, facilitating the development of robust tools with comfortable user interface and realistic functions and options. Another trend is the combination of simulation tools with optimization and choice algorithms fading away the difference between simulators and decision support systems.The remaining challenges are basically in the high expectations of stakeholders concerning the ability of simulators to predict a range of outcomes in terms of ecosystem services and sustainability indicators, as well as the quality of their outcome in terms of output credibility to stakeholders. Need for accepted and realistic model validation and verification methods preferably using empirical data is crucial in this matter.Key words: multi-objective forest planning; forest model; simulator; decision support system; climate change. ResumenHerramientas de simulación para el apoyo de toma de decisiones en la gestión forestal adaptativa en Europa En la planificación de la gestión forestal existe la tendencia a medir menos y similar más. En este contexto, el desarrollo de simuladores forestales es económicamente relevante para el gestor. El objetivo de este artículo es el de discutir y enfatizar tendencias en el ámbito de la simulación forestal e identificar retos importantes para que la simulación forestal sea una herramienta fiable en el proceso decisorio de la planificación forestal y en el de desarrollo de *

“…Our objective is to demonstrate how this basic approach can be connected with either empirical or process-based growth models at different levels of detail, and how these models can be applied to variable forest management questions. TreeBLOSSIM (Grace et al, 1998;Grace et al, 1999;Grace et al, 2006) represents a fairly empirical, management-oriented approach while ANAFORE (Deckmyn et al, 2008(Deckmyn et al, , 2009) is a physiologically-based model primarily developed as a research tool. PipeQual (Mäkelä and Mäkinen, 2003;Kantola et al, 2007) is intermediate between these two, deriving growth from the carbon balance but using empirical growth-quality relationships for stem structure.…”

Section: Case Studiesmentioning

confidence: 99%

“…The uncertainty can be reduced using Bayesian techniques that allow for model calibration with limited data. A Bayesian routine was included in the ANAFORE model (Deckmyn et al, 2009), and model parameters were calibrated against forest inventory data collected in 1991 at 5 homogeneous, even-aged pedunculate oak stands (Quercus robur L.) in Belgium, on diverse soils (Muys 1993) ( Table 3). The calibrated model was further validated against data from an experimental oak stand at Brasschaat (51°18' N and 4°31' E) ( Table 4).…”

Section: Anaforementioning

confidence: 99%

See 1 more Smart Citation

Simulating wood quality in forest management models

Mäkelä

Grace²,

Deckmyn³

et al. 2010

The raw material properties of wood develop as the tree grows, laying down wood cells with specific properties, and forming the stem structure that is the basis of timber quality. This development is influenced by genetic and environmental factors and forest management practices. It is desirable in growth and yield models intended for the economic assessment of management practices to include some indication of wood quality and how it is affected by genetics, environmental factors and silvicultural measures.In forestry, understanding the development and variation of wood quality is important for different management and planning problems which can be broadly classif ied under (1) management for harvest operations, and (2) long-term silvicultural planning. This paper reviews approaches and models that allow us to study these two problems in quantitative terms. We start the review by discussing the concept of «wood quality model», then classify the approaches on the basis of their complexity, underlying principle and intended application. We illustrate three advanced dynamic quality models and their applications with example case studies. These include empirical, hybrid, and mechanistic models applied to predictions of both sawn timber and fibre properties. Finally, we consider the current challenges for wood quality modelling in connection with forest management.Key words: wood quality; mixed models; empirical models; hybrids models. ResumenSimulación de la calidad de madera en los modelos de gestión forestal Las propiedades de la madera se desarrollan cuando crece el arbol, estableciendose las células de la madera con propiedades específicas, y formandose la estructura del tronco que es central para la calidad de la madera. Esta desarrollo se ve influido por factores genéticos y ambientales y por las prácticas de gestión forestal. Es deseable incluir en los modelos de crecimiento y producción destinados a la evaluación económica de las prácticas de gestión una indicación de la calidad de la madera y cómo se ve afectada por factores genéticos y ambientales y por las medidas silvícolas.En el sector forestal, la comprensión del desarrollo y la variación de la calidad de la madera es importante en distintos programas de gestión y planificación que se pueden clasificar en (1) la gestión de las operaciones de cosecha, y (2) la planificación silvícola a largo plazo. Este artículo discute los principales enfoques y modelos que nos permiten estudiar estos dos problemas en términos cuantitativos. Comenzamos la revisión discutiendo el concepto de «mo-delo de calidad de madera», y luego clasificamos los enfoques sobre la base de su complejidad, el principio subyacente y el uso previsto. Mostramos tres modelos dinámicos avanzados de calidad y sus aplicaciones con estudios de casos. Estos incluyen modelos empíricos, híbridos y mecánicistas aplicadaos a las predicciones tanto de la madera aserrada como a las propiedades de la fibra. Por último, consideramos los retos actuales para el modelado de la calidad de la madera...