François De Coligny

Capsis: an open software framework and community for forest growth modelling

ContextForest scientists build models to simulate stand growth and forests dynamics. Dedicated computer tools are often developed to implement these models in order to run silvicultural scenarios and explore simulation results.AimsOur objective was to encourage software reuse and simplify model implementation.MethodsThe scheme was to develop a framework and methodology allowing to simplify the implementation, integration, simulation and comparison of forest models by providing a set of common and standard tools.ResultsCapsis provides an open and modular software architecture based on various components, allowing to run forest growth simulations and display the results. The benefits of this framework are shown with the Samsara2 model, an individual-based and spatialised tree model. Capsis has been used successfully in many similar projects. In addition, the Capsis methodology defines how developers, modellers and end-users may interact.ConclusionThe Capsis framework facilitates collaborative and shared software development. Moreover, it is a powerful way to support scientific animation in the frame of forest science.

Reconstructing harvesting diameter distribution from aggregate data

Abstract• ContextDistribution of removed trees among species and diameter classes is usually used to characterize selection harvesting. This information is, however, rarely available when analysing past time series. The challenge is then to determine the minimal level of information required to characterize harvests.• AimsWe tested in this work whether an algorithm based on the total number of trees and volume to be removed enabled the reconstruction of harvesting diameter distributions, when combined with stand diameter distribution before harvest.• MethodsWe tested the algorithm against empirical data in the case of selection system, comparing distributions by χ² tests, and extended its evaluation to more diversified theoretical situations.• ResultsObserved harvesting distributions were well-reconstructed in most empirical cases, with better results when considering mean simulated distributions. The algorithm was also effective for other thinning and harvesting strategies: low thinning, thinning of dominants, and mechanical thinning, whatever the structure of the stand before being cut.• ConclusionTotal number of trees and volume harvested appeared thus sufficient to reconstruct DBH distribution of removed trees in diverse situations, provided that the distribution before harvest was known. This algorithm, therefore, enables the simulation of complex harvesting operations with minimal information.

A Forest Growth Simulator Based on Functional-Structural Modelling of Individual Trees

The objective of this paper is to study forest growth simulation based on functional-structural modelling and its potentials for forestry applications. The GreenLab model is used for this purpose owing to its computational performances, its calibration capacity on real plants and its extension to the stand level, by taking into account the competition between neighbouring plants and the interactions with the environment. We first propose a software design: - to manage the composition of forest scenes, - to simulate their growth based on parallel computing of individual trees with the GreenLab model, - to get the realistic and real-time 3D rendering of the simulation results. We then detail a test case to illustrate the potentialities of this new tool. Mono-specific stands of poplars and pines are simulated. We analyze the computation performances and illustrate the simulation results with 3D outputs. A very classical application in forest management, stand thinning, is also tested. Our tool provides new insights thanks to the detailed architectures of trees resulting from the functional-structural model.

Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach

Summary 1.Calibration of local, regional or global allometric equations to estimate biomass at the tree level constitutes a significant burden on projects aiming at reducing Carbon emissions from forest degradation and deforestation. The objective of this contribution is to assess the precision and accuracy of Terrestrial Laser Scanning (TLS) for estimating volumes and aboveground biomass (AGB) of the woody parts of tropical trees, and for the calibration of allometric models. 2.We used a destructive dataset of 61 trees, with diameters and AGB of up to 186.6 cm and 60 Mg respectively, which were scanned, felled and weighed in the semi-deciduous forests of eastern Cameroon. We present an operational approach based on available software allowing to retrieve TLS volume with low bias and high accuracy for large tropical trees. Edition of the obtained models proved necessary, mainly to account for the complexity of buttressed parts of tree trunks, which were separately modelled through a meshing approach, and to bring a few corrections in the topology and geometry of branches, thanks to the AMAPStudio-Scan software. 3.Over the entire dataset, TLS derived volumes proved highly reliable for branches larger than 5 cm in diameter. The volumes of the remaining woody parts estimated for stumps, stems and crowns as well as for the whole tree proved very accurate (RMSE below 2.81% and R² above of 0.98) and unbiased. Once converted to AGB using mean local specific wood density values, TLS estimates allowed calibrating a biomass allometric model with coefficients statistically undistinguishable from those of a model based on destructive data. Un-edited Quantitative Structure Model (QSM) however lead to systematic overestimations of woody volumes and subsequently to significantly different allometric parameters. 4.We can therefore conclude that the non-destructive TLS approach can now be used as an operational alternative to traditional destructive sampling to build the allometric equations, although attention must be paid to the quality of QSM model adjustments to avoid systematic bias. This article is protected by copyright. All rights reserved.

Modeling thinning effects on fire behavior with STANDFIRE

Key messageWe describe a modeling system that enables detailed, 3D fire simulations in forest fuels. Using data from three sites, we analyze thinning fuel treatments on fire behavior and fire effects and compare outputs with a more commonly used model.ContextThinning is considered useful in altering fire behavior, reducing fire severity, and restoring resilient ecosystems. Yet, few tools currently exist that enable detailed analysis of such efforts.AimsThe study aims to describe and demonstrate a new modeling system. A second goal is to put its capabilities in context of previous work through comparisons with established models.MethodsThe modeling system, built in Python and Java, uses data from a widely used forest model to develop spatially explicit fuel inputs to two 3D physics-based fire models. Using forest data from three sites in Montana, USA, we explore effects of thinning on fire behavior and fire effects and compare model outputs.ResultsThe study demonstrates new capabilities in assessing fire behavior and fire effects changes from thinning. While both models showed some increases in fire behavior relating to higher winds within the stand following thinning, results were quite different in terms of tree mortality. These different outcomes illustrate the need for continuing refinement of decision support tools for forest management.ConclusionThis system enables researchers and managers to use measured forest fuel data in dynamic, 3D fire simulations, improving capabilities for quantitative assessment of fuel treatments, and facilitating further refinement in physics-based fire modeling.

Correction to: “Modeling thinning effects on fire behavior with STANDFIRE”

The original article shows unit errors in Table 2: The torching index (TI) and crowning index (CI).