Tools and Resources
ForestGALES is a computer-based decision support system and hybrid-mechanistic model that assesses the risk of wind damage to forests in Britain and in several other countries, allowing to compare the impacts of different silvicultural practices. The three current versions of ForestGALES operate at different spatial scales: at the stand level (ForestGALES Desktop 2.5 and ForestGALES 3.0/fgr), at site level (ForestGALES Online 2.5), and for individual trees within a stand (ForestGALES 3.0/fgr). Regardless of the version used, because of the effects of topographic complexity and of the inherently stochastic nature of windstorms on the risk of wind damage, for practical applications ForestGALES is recommended for use at forest scales, rather than for individual stands.
ForestGALES operates within a standard risk framework whereby risk is defined as the interplay between the vulnerability of a system and the hazard it is exposed to. Risk is therefore calculated in two stages. Firstly, the vulnerability of trees to wind damage is computed as the critical wind speed at which trees will be damaged, either by uprooting or stem breakage. Secondly, the localised wind climate is derived to represent the wind hazard. Multiple ways exist to characterise wind climates. Traditionally and most commonly, this is done with a Weibull distribution of mean wind speeds in a specific location. In British forestry, the DAMS windiness score was developed to provide an accessible interpretation of the Weibull distribution of wind speeds. Risk is then defined as the probability of exceeding the calculated critical wind speeds given the localised wind climate. The return periods of damaging storms based on stand location can then be calculated from this probability.
ForestGALES calculates the vulnerability to wind damage using information from the trees:
and then the site:
The probability of damaging winds occurring at the site is then calculated using information on the wind climate. Throughout Britain, this is classified in the DAMS scoring system, a modelled windiness score calculated from tatter flag observations, elevation, aspect, topographical exposure, valley shape and direction.
DAMS values can be:
ForestGALES Desktop 2.5 and ForestGALES Online 2.5 already feature the DAMS dataset. ForestGALES 3.0/fgr requires downloading DAMS scores in raster format (as GeoTIFF). These are freely available in two coordinate reference systems (CRS): one compatible with Ordnance Survey data (DAMS in EPSG: 27700), and also in a CRS compatible with Google Maps, OpenStreetMap, etc. (DAMS in EPSG: 3857).
Outside of Britain, the wind hazard can be modelled with the scale and shape parameters of the Weibull distribution of mean hourly wind speeds. These can be calculated from wind data obtained from local meteorological stations, or from accessible sources such as the Global Wind Atlas. Weibull parameters can be supplied directly to ForestGALES 3.0/fgr, and to ForestGALES Desktop 2.5 when used in Research Mode.
The critical wind speeds of damage (for stem breakage and uprooting) calculated for the stand or for individual trees within the stand are calculated in ForestGALES to model the vulnerability of the system to wind damage. The risk of wind damage is then calculated as the probability of exceeding these critical wind speeds given the mean wind climate at the stand’s location. However, it is well known that wind damage is caused by wind gusts that represent the extreme winds rather than the mean. The relationship between the force exerted on trees by the mean wind and that delivered by wind gusts, and the multiple factors influencing this relationship, have been extensively studied in the research fields of tree stability and of wind impacts across different landscapes. The state-of-the-art scientific understanding of these phenomena is incorporated in ForestGALES to convert the effects of mean winds on trees to those of damaging gusts.
While ForestGALES Online 2.5 only allows simple, static wind risk calculations at one point in time, in ForestGALES Desktop 2.5 and in ForestGALES 3.0/fgr wind risk can be calculated over time and for different silvicultural scenarios. This information can be used to assist stand management decisions, for example felling age, silvicultural practice and cultivation.
The three current versions of ForestGALES yield comparable results. The three versions are aimed at different user categories.
ForestGALES Online 2.5 is freely available as software that you operate through your web browser. The web-based version calculates the probability of wind damage for a single stand, but is only available for areas in Britain, and has limited capabilities compared to the other versions. It features the same parameters and equations used in ForestGALES Desktop 2.5.
The web-based version of ForestGALES is free. If you encounter any problems during registration or whilst logging in, please email us at: forestgales.support@forestresearch.gov.uk
ForestGALES Desktop 2.5 allows users to carry out comprehensive wind risk assessments for a variety of settings and scenarios. Calculations can be performed for individual stands or for multiple stands in batch mode, at one point in time or for wind risk projections over time. Users can manually provide the inputs to the model, or rely on the included growth model data based on Forest Research’s Forest Yield model. When using Forest Yield model outputs, wind risk calculations can be performed over time, for instance to assess how risk is likely to change over a rotation. ForestGALES Desktop 2.5 is the upgrade to ForestGALES 2.1. The main changes are:
Users’ experience indicated that ForestGALES 2.1 tended to predict more damage than was observed. A comparison with actual storm damage, and ongoing research into the science of wind risk in forests, has supported this. As a result, in ForestGALES Desktop 2.5 the estimated critical wind speeds for damage are higher, and stands are now predicted to be less at risk of damage.
In ForestGALES Desktop 2.5, the effects of cultivation and drainage on anchorage have been combined and replaced by rooting depth. A Soil and Rooting Helper is provided to help users decide on the correct combination of soil and rooting for a given site.
The calculations of crown size within ForestGALES have been revised and are now based on a much larger data set than before. For most species this makes little difference. Crown size calculations are substantially improved for western hemlock, Douglas-fir and lodgepole pine.
ForestGALES Desktop 2.5 has a Research mode which has added features that make ForestGALES more flexible for research users. Species-specific external parameter files make it easier to alter parameters such as crown relationships or anchorage coefficients. New species can also be added. Weibull parameters describing the wind regime can be entered directly rather than being calculated from DAMS. A wide range of outputs is now optionally saved to a file.
ForestGALES Desktop 2.5 is available for download.
ForestGALES 3.0/fgr is the latest version of the ForestGALES wind risk model, available for use by forestry and land-use change scientists and specialists, ecologists, economists, and meteorologists, in a format that is flexible and fully customisable. ForestGALES 3.0/fgr is designed to meet users’ needs for application in any forested landscape, and to encourage national and international collaboration on forest wind risk research.
Since the release of ForestGALES Desktop 2.5, the tree stability team at Forest Research have used the R programming language for all further model development. The ForestGALES R package `fgr` is the product of the latest research and development.
The R programming language is widely used in the forestry and land-use change research sectors in Britain and throughout the world. Many models and utilities are available as R packages, thus providing the opportunity for relatively straightforward integration between tools within a common platform. R packages can also be used as a plugin within the free and open source QGIS GIS software, as done with fgr in the FOSPREF-Wind project. This is possible thanks to QGIS ability to integrate R procedures and functions easily and intuitively. The wind risk team at Forest Research have started creating QGIS procedure to integrate ForestGALES 3.0/fgr functionalities into a QGIS workflow. The first procedure is available upon request. As more procedures are developed, these will be added to the ForestGALES 3.0/fgr package and shared with new and existing users.
ForestGALES 3.0/fgr features a series of modifications and improvements from ForestGALES Desktop 2.5, representing the cutting edge of forest wind risk modelling. Two sets of changes have been introduced:
These changes are described in more detail:
ForestGALES 3.0/fgr represents an improvement on the traditional stand-level approach used in previous ForestGALES releases. Several scientific advances have been incorporated into the calculations of critical wind speed in uniform stands:
The traditional roughness method of ForestGALES calculates vulnerability and risk of the average tree in a stand. Based on the innovative work published in Hale et al. (2012) and Hale et al. (2015), ForestGALES 3.0/fgr allows the calculation of individual-tree vulnerability, and the associated risk of wind damage, in complex stands of mixed-species and irregular structure. The effect of complex stand dynamics on wind risk can be accounted for with the TMC method if tree-level competition indices are available. While still in a developmental stage, several tests have shown that results are consistent with observed damage.
The ForestGALES 3.0/fgr package is built in a modular way, so that not only wrapper functions for the two methods (‘roughness’ and ‘TMC’) are available for standard use, but all the individual functions are also available for advanced users. The simulations are fully customisable: all species parameters can be changed (including mechanical properties of wood, wood density, tree anchorage coefficients, etc.), parameter sets for new species can be added and stored, and the values of physical constants (e.g. air density, snow density amongst many others) can be changed and stored for future use.
Model outputs can be produced in a compact form that is suitable for most standard use and contains calculated vulnerabilities and risks of uprooting and stem breakage, or in an extended format reporting the outputs of all advanced calculations. Example datasets are provided to help users familiarise with the functionalities of ForestGALES 3.0/fgr. All functions and datasets are documented. Working in batch mode in ForestGALES 3.0/fgr is easy, since the package takes advantage of all standard R practices for vectorised functions.
The ForestGALES 3.0/fgr manual is a PDF document that details and explains the functionalities of the package and provides extensive background to the numerous aspects of wind damage risk research that went into the creation of the package. Worked examples based on the provided datasets are included in the manual to provide further assistance, together with an extensive bibliography.
For technical support and enquiries relating to ForestGALES 3.0/fgr, please contact Forest Research at: forestgales.support@forestresearch.gov.uk
Throughout its development, ForestGALES was designed in consultation with representatives of both private and state forestry organisations and is designed to be easy to use and includes extensive online help.
ForestGALES 3.0/fgr has been successfully applied to studies of wind damage to forest stands and individual trees alongside infrastructure, and to inform forest management decisions in the UK and several other European countries. ForestGALES 3.0/fgr is used in the management and planning of public forests in Scotland and Wales (ForestGALES Desktop 2.5 and Online 2.5 are used in England).
ForestGALES can be installed on your computer (ForestGALES Desktop 2.5), run directly from the internet (ForestGALES Online 2.5), or installed as an R package for use within the R and/or QGIS platforms (ForestGALES 3.0/fgr).
To download ForestGALES Desktop 2.5 you need an access code. New users of ForestGALES will need to purchase an access code which costs £50 + VAT.
To purchase an access code, contact:
Forestry Commission Publications (CST)
Chetham House, Bird Hall Lane, Cheadle Heath, Cheshire, SK3 0Z3.
0161 495 4845
forestry@theapsgroup.com
Current users of ForestGALES Desktop 2.5 will be sent an access code. If you have not received your code, please contact ForestGALES support: forestgales.support@forestresearch.gov.uk
Download ForestGALES now with your access code
By downloading ForestGALES Desktop 2.5, you agree to the terms of our licence agreement.
ForestGALES is also available as software that you operate through your web browser. The ForestGALES Online 2.5 web-based version calculates the probability of wind damage for a single stand.
The web-based version of ForestGALES is free
If you encounter any problems during registration or whilst logging in, please email us at: forestgales.support@forestresearch.gov.uk
The R library for ForestGALES 3.0/fgr can only be downloaded from Forest Research website.
This online form will capture your contact details. Terms and conditions must be accepted.
Once the form is complete, an email with four attachments will be sent to the email provided in the form. All personal data are treated in compliance with GDPR regulations.
Once the form has been submitted, you will receive an email with four attachments:
If you encounter any problems with the online form, please email us at: forestgales.support@forestresearch.gov.uk
If you encounter any problems, and for any general ForestGALES enquiries, please email us at: forestgales.support@forestresearch.gov.uk
When calculating risk at the stand level (e.g., with ForestGALES Desktop 2.5, Online 2.5, and ForestGALES 3.0/fgr in stand-level mode) the stands are assumed to consist of identical trees. It is suggested that in mixtures the risk of wind damage to each component is calculated separately, using the top height and mean diameter of the component, and the average spacing based on the whole crop (i.e. all components of the mixture). The risk to the stand as a whole can be considered to be the highest risk for any component, since if one species is damaged then the resulting gaps will increase the risk of damage to the remaining trees.
When detailed data on the characteristics of individual trees within a stand, and their coordinates, are known, the TMC method of ForestGALES 3.0/fgr can be used to calculate wind risk to individual trees in mixed stands. The spatial distribution of risk within a forested landscape can then be plotted at the tree level on a map in a GIS environment.
The mechanisms by which trees are damaged by the wind are similar throughout the world. However the relationships between diameter and crown size, the resistance of trees to overturning and the wind climate will differ from country to country.
The original release of ForestGALES was designed for British conditions, but as the model developed it has been successfully adapted for use in New Zealand, south-west France, Denmark, Canada (Quebec and British Columbia), Japan, Italy, Norway, Germany, Latvia, Vietnam, and Indonesia. ForestGALES Desktop 2.5 includes a research mode that allows input parameters and wind climate to be easily modified for other countries, and ForestGALES 3.0/fgr features full customisation and model parametrisation capabilities that make it the ideal tool for wind risk assessments to forests in any part of the world.
In stand-level mode, ForestGALES calculates the probability of average trees being damaged within a stand. Damage to the average tree will, by implication, mean that the stand as a whole will be substantially damaged.
When used at the level of individual trees within a stand, ForestGALES 3.0/fgr calculates the vulnerability and associated risk to individual trees, allowing for wind risk assessments in complex stands of mixed species composition and heterogeneous structures.
ForestGALES estimates the chance (or probability) of windthrow or stem breakage, rather than stating a precise height at which damage will occur as in the WHC. Probabilistic predictions are more realistic than precise heights since the occurrence of damaging winds varies from year to year, which has a powerful influence on the occurrence and spread of damage. The risk of damage is dependent on the windiness of the site. In the WHC the measure of windiness is much coarser than is used in ForestGALES. This allows ForestGALES to discriminate several levels of risk for trees in similar WHC classes. A study of actual storm damage indicated that stands can be grown for longer than if they were managed using the WHC.
For technical support and enquiries relating to ForestGALES, please contact Forest Research at the following address or email forestgales.support@forestresearch.gov.uk
Forest Research, Northern Research Station, Roslin, Midlothian, EH25 9SY
Interview: how ForestGALES is the essential tool for wind risk – Forest Research
How ForestGALES is Changing Forest Management in Wales
Achim, A. and Nicoll, B.C. (2009). Modelling the anchorage of shallow-rooted trees. Forestry 82: 273–284.
Albrecht, A., Hanewinkel, M., Bauhus, J. and Kohnle, U. (2012). How does silviculture affect storm damage in forests of south-western Germany? Results from empirical modeling based on longterm observations. European Journal of Forest Research 131: 229–247.
Anon (2006). Forest mensuration: a handbook for practitioners. Forestry Commission
Belcher, S.E., Harman, I.N. and Finnigan, J.J. (2012). The Wind in the Willows: Flows in Forest Canopies in Complex Terrain. Annual Review of Fluid Mechanics 44: 479–504
Björheden, R. (2007). Possible effects of the Hurricane Gudrun on the regional Swedish forest energy supply. Biomass and Bioenergy 31: 617–622.
Blennow, K. and Olofsson, E. (2008). The probability of wind damage in forestry under a changed wind climate. Climatic Change 87: 347–360.
Blennow, K., Andersson, M., Bergh, J., Sallnäs, O. and Olofsson, E. (2010). Potential climate change impacts on the probability of wind damage in a south Swedish forest. Climatic Change 99:261–278.
Blennow, K., Persson, J., Wallin, A., Vareman, N. and Persson, E. (2014). Understanding risk in forest ecosystem services: implications for effective risk management, communication and planning. Forestry 87: 219–228.
Cook, N.J. (1985). The designer’s guide to wind loading of building structures. Part 1: Background, damage survey, wind data and structural classification. Butterworths, London pp 371.
Coutts, M.P. (1986). Components of tree stability in Sitka spruce on peaty gley soil. Forestry 59: 173-197.
Coutts, M. P. and Grace, J. (Eds). (1994). Wind and wind-related damage to trees. Cambridge University Press.
Costa, M., Gardiner, B., Locatelli, T., Marchi, L., Marchi, N. and Lingua, E., 2023. Evaluating wind damage vulnerability in the Alps: A new wind risk model parametrisation. Agricultural and Forest Meteorology, 341, p.109660.
de Langre, E. (2008). Effects of wind on plants. Annual Review of Fluid Mechanics 40: 141–68
Dhote, J-F. (2005). Implication of forest diversity in resistance to strong winds. In: M. Scherer-Lorenzen, C. Korner, and E-D. Schulze (eds.) Forest Diversity and Function: Temperate and Boreal systems. Springer. Pp. 291–307.
Dobbertin, M. (2002). Influence of stand structure and site factors on wind damage comparing the storms Vivian and Lothar. Forest, Snow and Landscape Research 77:187–205
Drouineau S., Laroussinie O., Birot Y., Terrasson D., Formery T. and Roman-Amat B. (2001). Joint evaluation of storms, forests vulnerability and their restoration. EFI Discussion Paper 9. European Forest Institute. 39 p.
Edwards, P.N. and Christie, J.M. (1981). Yield models for Forest Management. Forestry Commission Booklet 48. Forestry Commission, Farnham.
Fraser, A. I. and Gardiner, J. B. H. (1967). Rooting and stability in Sitka spruce. Forestry Commission Bulletin. 40, HMSO, London.
Gardiner, B.A., Stacey, G.R., Belcher, R.E. and Wood, C.J. (1997). Field and wind-tunnel assessments of the implications of respacing and thinning on tree stability. Forestry 70: 233-252.
Gardiner, B., Peltola, H. and Kellomäki, S. (2000). Comparison of two models for predicting the critical wind speeds required to damage coniferous trees. Ecological Modelling 129: 1–23.
Gardiner, B.A. and Quine, C.P. (2000). Management of forests to reduce the risk of abiotic damage – a review with particular reference to the effects of strong winds. Forest Ecology and Management 135: 261–277.
Gardiner, B.A., Marshall, B., Achim, A., Belcher, R. and Wood, C. (2005). The stability of different silvicultural systems: a wind tunnel investigation. Forestry 78: 471–484.
Gardiner, B., Byrne, K., Hale, S., Kamimura, K., Mitchell, S.J., Peltola, H., Ruel, J-C. (2008). A review of mechanistic modelling of wind damage risk to forests. Forestry 81: 447-463.
Gardiner, B., Schuck, A., Schelhaas, M-J., Orazio, C., Blennow, K. and Nicoll, B. (eds). (2013). Living with Storm Damage to Forests: What Science Can Tell Us 3. European Forest Institute.
Gardiner, B., Lorenz, R., Hanewinkel, M., Schmitz, B., Bott, F., Szymczak, S., Frick, A. and Ulbrich, U., 2024. Predicting the risk of tree fall onto railway lines. Forest Ecology and Management, 553, p.121614.
Hale, S.E., Gardiner, B.A., Wellpott, A., Nicoll, B.C. and Achim, A. (2012). Wind loading of trees: influence of tree size and competition. European Journal of Forest Research 131: 203-217.
Hale, S.E., Gardiner B., Peace, A., Nicoll, B., Taylor, P. and Pizzirani, S., 2015. Comparison and validation of three versions of a forest wind risk model. Environmental Modelling and Software 68, 27-41.
Hanewinkel, M., Hummel, S. and Albrecht, A. (2011). Assessing natural hazards in forestry for risk management: a review. European Journal of Forest Research 130: 329–351.
Jactel, H., Nicoll, B.C., Branco, M., Gonzalez-Olabarria, J.R., Grodzki, W., Långström, B., Moreira, F., Netherer, S., Orazio, C., Piou, D., Santos, H., Schelhaas, M.J., Tojic, K. and Vodde, F. (2009). The influences of forest stand management on biotic and abiotic risks of damage. Annals of Forest Science 66:71.
Kennedy, F. (2002). The identification of soils for forest management. Forestry Commission Field Guide
Lavers, G.M., (1969). The strength properties of timbers, For. Prod. Res. Lab. Bull. 50 (2nd edition), HMSO, London.
Levy, P.E., Hale, S.E. and Nicoll, B.C. (2004). Biomass expansion factors and root:shoot ratios for coniferous tree species in Great Britain. Forestry 77: 421-430.
Lindroth, A., Lagergren, F., Grelle, A., Klemedtsson, L., Langvall, O., Weslien, P. and Tuulik, J. (2009). Storms can cause Europe-wide reduction in forest carbon sink. Global Change Biology 15: 346–355.
Locatelli, T., Gardiner, B., Tarantola, S., Nicoll, B., Bonnefond, J.M., Garrigou, D., Kamimura, K. and Patenaude, G., 2016. Modelling wind risk to Eucalyptus globulus (Labill.) stands. Forest Ecology and Management, 365, pp.159-173.
Locatelli, T., Tarantola, S., Gardiner, B. and Patenaude, G., 2017. Variance-based sensitivity analysis of a wind risk model-Model behaviour and lessons for forest modelling. Environmental Modelling & Software, 87, pp.84-109.
Mason, W. L. and Quine, C. P. (1995). Silvicultural possibilities for increasing structural diversity in British spruce forests: the case of Kielder forest. Forest Ecology and Management 79:13–28.
Mason, W.L. (2002). Are irregular stands more windfirm? Forestry 75: 347–355.
Mayhead, G.J. (1973). Some drag coefficients for British forest tree derived from wind tunnel studies. Agricultural Meteorology 12: 123-130.
Miller, K. F. (1985). Windthrow Hazard Classification. Forestry Commission Leaflet 85, HMSO, London.
Neild, S.A. and Wood, C.J. (1999). Estimating stem and root-anchorage flexibility in trees. Tree Physiology 19: 141-151.
Nicoll, B.C. and Ray, D. (1996). Adaptive growth of tree root systems in response to wind action and site conditions. Tree Physiology 16: 891-898.
Nicoll, B.C., Gardiner, B.A., Rayner, B. and Peace, A.J. (2006). Anchorage of coniferous trees in relation to species, soil type and rooting depth. Canadian Journal of Forest Research 36: 1871-1883.
Nicoll, B.C., Gardiner, B.A. and Peace, A.J. (2008). Improvements in anchorage provided by the acclimation of forest trees to wind stress. Forestry 81: 389-398.
Peltola, H., Gardiner, B.A., Kellomäki, S., Kolström, T., Lässig, R., Moore, J. and Quine, C.P. and Ruel, J-C (Eds). (2000). Wind and other Abiotic Risks to Forests. Forest Ecology and Management, Special Issue.
Petty, J.A. and Swain, C. (1985). Factors influencing stem breakage of conifers in high winds. Forestry 58: 75-84.
Pukkala, T. and Kangas, J. (1996). A method for integrating risk and attitudes towards risk in forest planning. Forest Science 42:198–205.
Quine, C.P. (2000). Estimation of mean wind climate and probability of strong winds for wind risk assessment. Forestry 73: 247-258.
Quine, C.P. and Miller, K.F. (1991). Windthrow – a factor influencing the choice of silvicultural systems. In: Silvicultural Systems, Ed: P. Gordon, ICF, Edinburgh, pp 71-81.
Quine, C.P. and Gardiner, B.A. (1992). Incorporating the threat of windthrow into forest design plans. Research Information Note 220. Forestry Commission Research Division, Farnham.
Quine, C.P. and White, I.M.S. (1993). Revised windiness scores for the Windthrow Hazard Classification. Forestry Commission Research Information Note 230, FC, Edinburgh.
Quine, C.P., Coutts, M., Gardiner, B. and Pyatt, G. (1995). Forest and Wind: Management to Minimise Damage. Forestry Commission Bulletin 114, HMSO, London.
Quine, C.P. and Bell, P.D. (1998). Monitoring of windthrow occurrence and progression in spruce forests in Britain. Forestry 71: 87–97.
Quine, C.P. and Gardiner, B.A. (2007). Understanding how the interaction of wind and trees results in windthrow, stem breakage and canopy gap formation. In Johnson, E. and Miyanishi, K. (Eds) Plant disturbance ecology: the process and the response. Academic Press. 698p. Burlington, MA, USA.
Raupach, M.R. (1994). Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index. Boundary-Layer Meteorology 71: 211-216.
Raupach, M.R., Finnigan, J.J., and Brunet, Y. (1996). Coherent eddies and turbulence in vegetation canopies: the mixing layer analogy. Boundary-Layer Meteorology 78: 351–382.
Ray, D., White, I.M.S. and Pyatt, D.G. (1992). The effect of ditches, slope and peat thickness on the water regime of a forested gley soil. Soil Use and Management 8: 105-111.
Ray, D. and Nicoll, B.C. (1998). The effect of soil water-table depth on root-plate development and stability of Sitka spruce. Forestry 71: 169-182.
Rudnicki, M., Mitchell, S.J. and Novak, M.D. (2004). Wind tunnel measurements of crown streamlining and drag relationships for three conifer species. Canadian Journal of Forest Research 34: 666-676.
Ruel, J.-C., Achim, A., Espinoza, R.H., Cloutier, A. and Brossier, B. (2010). Wood Degradation after Windthrow in a Northern Environment. Forest Products Journal 60: 200-206.
Savill, P.S. (1983). Silviculture in windy climates. Forestry Abstracts 44: 473-488.
Schelhaas, M.J., Nabuurs, G-J. and Schuck, A. (2003). Natural disturbances in the European forests in the 19th and 20th centuries. Global Change Biology 9: 1620–1633.
Schelhaas, M.-J., Hengeveld, G., Moriondo, M., Reinds, G.J., Kundzewicz, Z.W., Maat, H.t., and Bindi, M. (2010). Assessing risk and adaptation options to fires and windstorms in European forestry. Mitigation and Adaptation Strategies for Global Change 15: 681–701.
Seidl, R. and Blennow, K. (2012). Pervasive growth reduction in Norway spruce forests following wind disturbance. PLoS ONE 7:1–8. http://dx.plos.org/10.1371/journal.pone.0033301.
Somerville, A. (1980). Wind stability: forest layout and silviculture. New Zealand Journal of Forestry Science 10: 476-501.
Suárez, J.C., Gardiner, B.A. and Quine, C.P. (1999). A comparison of three methods for predicting wind speeds in complex forest terrain. Meteorological Applications 6: 1-14.
Telewski, F.W. and Beals, W.J. (1995). Wind induced physiological and developmental responses in trees. In: Wind and wind related damage to trees. (Ed) Coutts and Grace. Cambridge University Press, 485 pp
Thom, A.S. (1971). Momentum absorption by vegetation. Quarterly Journal of the Royal Meteorological Society 97: 414-428.
Troen, I. and Petersen, E.L. (1989). European Wind Atlas. Risø National Laboratory, Denmark.
Usbeck, T., Wohlgemuth, T., Dobbertin, M., Pfister, C., Bürgi, A. and Rebetez, M. (2010). Increasing storm damage to forests in Switzerland from 1858 to 2007. Agricultural and Forest Meteorology 150: 47–55.
Valinger, E. and Fridman, J. (2011). Factors affecting the probability of windthrow at stand level as a result of Gudrun winter storm in southern Sweden. Forest Ecology and Management 262:398–403.
Vollsinger, S., Mitchell, S.J., Byrne, K.E., Novak, M.D. and Rudnicki, M. (2005). Wind tunnel measurements of crown streamlining and drag relationships for several hardwood species. Canadian Journal of Forest Research 35: 1238-1249.