Windthrow Dynamics in Boreal Ontario: A Simulation of the Vulnerability of Several Stand Types across a Range of Wind Speeds

Anyomi, Kenneth A.; Mitchell, Stephen J.; Perera, Ajith H.; Ruel, Jean‐Claude

doi:10.3390/f8070233

Cited by 24 publications

(19 citation statements)

References 49 publications

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“…Sustainable forest management should focus on spatially re-engineering a forest landscape for the production of ecological, economic, and socio-cultural values [87]. Currently, we can observe a shift in the focus of forest management in many European countries, from resource-based to holistic management planning, which takes into account a wide range of risks in order to achieve multifunctional forests [88].…”

Section: Discussionmentioning

confidence: 99%

Application of GIS to Empirical Windthrow Risk Model in Mountain Forested Landscapes

Krejčí

Kolejka

Voženílek

et al. 2018

Forests

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Abstract:Norway spruce dominates mountain forests in Europe. Natural variations in the mountainous coniferous forests are strongly influenced by all the main components of forest and landscape dynamics: species diversity, the structure of forest stands, nutrient cycling, carbon storage, and other ecosystem services. This paper deals with an empirical windthrow risk model based on the integration of logistic regression into GIS to assess forest vulnerability to wind-disturbance in the mountain spruce forests of Šumava National Park (Czech Republic). It is an area where forest management has been the focus of international discussions by conservationists, forest managers, and stakeholders. The authors developed the empirical windthrow risk model, which involves designing an optimized data structure containing dependent and independent variables entering logistic regression. The results from the model, visualized in the form of map outputs, outline the probability of risk to forest stands from wind in the examined territory of the national park. Such an application of the empirical windthrow risk model could be used as a decision support tool for the mountain spruce forests in a study area. Future development of these models could be useful for other protected European mountain forests dominated by Norway spruce.

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Section: Discussionmentioning

confidence: 99%

Application of GIS to Empirical Windthrow Risk Model in Mountain Forested Landscapes

Krejčí

Kolejka

Voženílek

et al. 2018

Forests

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“…Increasing abiotic and biotic damage risks to forests should be considered in adapting forest management strategies to properly accommodate/counteract projected climate change Seidl et al 2011;Hanewinkel et al 2013;Subramanian et al 2016;Reyer et al 2017). For example, growing forests with more climate change adapted tree species (genotypes), and their mixtures, could help to reduce the possible negative effects of climate change on forests (Neuner et al 2015;Metz et al 2016;Anyomi et al 2017;Jactel et al 2017). The wind damage risk to forests could also be lessened by avoiding the creation of large height differences among adjacent older stands and using shorter rotation lengths (Zeng et al 2007;Heinonen et al 2009;Jactel et al 2009;Zubizarreta-Gerendiain et al 2012).…”

Section: Evaluation Of Main Findingsmentioning

confidence: 99%

Effects of using certain tree species in forest regeneration on regional wind damage risks in Finnish boreal forests under different CMIP5 projections

et al. 2020

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We studied how the use of certain tree species in forest regeneration affected the regional wind damage risks to Finnish boreal forests under the current climate and recent-generation global climate model (GCM) predictions (i.e., 10 GCMs of CMIP5, with wide variations in temperature and precipitation), using the representative concentration pathways RCP4.5 and RCP8.5 over the period 2010-2099. The study employed forest ecosystem and mechanistic wind damage risk model simulations on upland national forest inventory plots throughout Finland. The amount of wind damage was estimated based on the predicted critical wind speeds for uprooting trees and their probabilities. In a baseline management regime, forest regeneration was performed by planting the same tree species that was dominant before the final cut. In other management regimes, either Scots pine, Norway spruce or silver birch was planted on medium-fertility sites. Other management actions were performed as for a baseline management. The calculated amount of wind damage was greatest in southern and central Finland under CNRM-CM5 RCP8.5, and the smallest under HadGEM2-ES RCP8.5. The most severe climate projections (HadGEM2-ES RCP8.5 and GFDL-CM3 RCP8.5) affected the wind damage risk even more than did the tree species preferences in forest regeneration. The situation was the opposite for the less severe climate projections (e.g., MPI-ESM-MR RCP4.5 and MPI-ESM-MR RCP8.5). The calculated amount of wind damage was clearly greater in the south than in the north, due to differences in forest structure. The volume of growing stock is much higher in the south for the more vulnerable Norway spruce (and birch) than in the north, which is opposite for the less vulnerable Scots pine. The increasing risk of wind damage should be taken into account in forest management because it could amplify, or even cancel out, any expected increases in forest productivity due to climate change.

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“…A sigmoid damage function is used to simulate the rate of storm damage to a forest. A similar approach has been applied and tested by Anyomi et al (2017) for estimating storm damage as a function of the daily maximum wind speed. This relationship is formalized as…”

Section: Storm Damagementioning

confidence: 99%

“…The wind-throw module calculates the critical wind speed based on the principles applied in ForestGALES (Gardiner et al, 2000) and storm damage based on the approach developed and tested by Anyomi et al (2017). Figure 1 summarizes the major components of storm damage calculations in ORCHIDEE-CAN.…”

Section: Orchidee-can (Revision 4262)mentioning

confidence: 99%

Simulating damage for wind storms in the land surface model ORCHIDEE-CAN (revision 4262)

Chen

Gardiner²,

Pasztor

et al. 2018

Geosci. Model Dev.

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Abstract. Earth system models (ESMs) are currently the most advanced tools with which to study the interactions among humans, ecosystem productivity, and the climate. The inclusion of storm damage in ESMs has long been hampered by their big-leaf approach, which ignores the canopy structure information that is required for process-based windthrow modelling. Recently the big-leaf assumptions in the large-scale land surface model ORCHIDEE-CAN were replaced by a three-dimensional description of the canopy structure. This opened the way to the integration of the processes from the small-scale wind damage risk model Forest-GALES into ORCHIDEE-CAN. The integration of Forest-GALES into ORCHIDEE-CAN required, however, developing numerically efficient solutions to deal with (1) landscape heterogeneity, i.e. account for newly established forest edges for the parameterization of gusts; (2) downscaling spatially and temporally aggregated wind fields to obtain more realistic wind speeds that would represents gusts; and (3) downscaling storm damage within the 2500 km 2 pixels of ORCHIDEE-CAN. This new version of ORCHIDEE-CAN was parameterized over Sweden. Subsequently, the performance of the model was tested against data for historical storms in southern Sweden between 1951 and 2010 and south-western France in 2009. In years without big storms, here defined as a storm damaging less than 15 × 10 6 m 3 of wood in Sweden, the model error is 1.62 × 10 6 m 3 , which is about 100 % of the observed damage. For years with big storms, such as Gudrun in 2005, the model error increased to 5.05 × 10 6 m 3 , which is between 10 and 50 % of the observed damage. When the same model parameters were used over France, the model reproduced a decrease in leaf area index and an increase in albedo, in accordance with SPOT-VGT and MODIS records following the passing of Cyclone Klaus in 2009. The current version of ORCHIDEE-CAN (revision 4262) is therefore expected to have the capability to capture the dynamics of forest structure due to storm disturbance on both regional and global scales, although the empirical parameters calculating gustiness from the gridded wind fields and storm damage from critical wind speeds may benefit from regional fitting.

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Windthrow Dynamics in Boreal Ontario: A Simulation of the Vulnerability of Several Stand Types across a Range of Wind Speeds

Cited by 24 publications

References 49 publications

Application of GIS to Empirical Windthrow Risk Model in Mountain Forested Landscapes

Application of GIS to Empirical Windthrow Risk Model in Mountain Forested Landscapes

Effects of using certain tree species in forest regeneration on regional wind damage risks in Finnish boreal forests under different CMIP5 projections

Simulating damage for wind storms in the land surface model ORCHIDEE-CAN (revision 4262)

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