•Mechanical stability is a major functional requirement of land plants.•Wind loading on plants varies temporally on time scales from years to seconds.•Plants change at scales from the cell to the ...whole plant to acclimate to the wind.•The process of wind damage is very similar in all plants.•Wind damage can have major economic and ecological impacts.
Land plants have adapted to survive under a range of wind climates and this involve changes in chemical composition, physical structure and morphology at all scales from the cell to the whole plant. Under strong winds plants can re-orientate themselves, reconfigure their canopies, or shed needles, leaves and branches in order to reduce the drag. If the wind is too strong the plants oscillate until the roots or stem fail. The mechanisms of root and stem failure are very similar in different plants although the exact details of the failure may be different. Cereals and other herbaceous crops can often recover after wind damage and even woody plants can partially recovery if there is sufficient access to water and nutrients. Wind damage can have major economic impacts on crops, forests and urban trees. This can be reduced by management that is sensitive to the local site and climatic conditions and accounts for the ability of plants to acclimate to their local wind climate. Wind is also a major disturbance in many plant ecosystems and can play a crucial role in plant regeneration and the change of successional stage.
When forest stands are thinned, the retained trees are exposed to increased light and greater mechanical strain from the wind. The consequent greater availability of photosynthate and localised ...mechanical strain in stems and roots are both known to increase cambial growth in conifers, but their relative importance has not previously been quantified. Light availability and wind movement were manipulated in a 10-year-old stand of Sitka spruce trees on an exposed upland site. Treatments were “Control”—no change in spacing or wind loading; “Thinned”—light availability and wind loading increased by removing neighbouring trees; “Thinned and guyed”—light increased and wind loading reduced by removing neighbouring trees and guying stems with wires. Twelve trees per treatment were maintained and monitored for four years before harvesting and removal of cross-sectional stem samples from four heights for measurement of radial growth response. Root systems were excavated from each treatment for observations of associated root growth responses. The “Thinned” treatment and “Thinned and guyed” treatment showed no significant stem growth response in the first year after treatment, but very large increases in the second and subsequent years. There were much larger growth responses in the “Thinned” treatment than in the “Thinned and guyed” treatment, especially in the lower stem. Similar growth responses were observed in the structural roots, close to the stem base. These increases in stem and root growth in response to wind movement corresponded with a reduction of branch growth. Such changes in allocation have implications for the hydraulic and biomechanical requirements of trees, and should be incorporated into tree growth and stability models.
•Machine learning techniques were accurate in predicting wind damage to trees.•Random forests proved the most accurate and discriminating methodology.•Models were sensitive to removal of site and ...stand but not tree characteristics.•All models were able to accurately replicate a mechanistic wind risk model.•Machine learning techniques could help the management of wind damage to forests.
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at risk of damage in storms. Models based on these techniques were developed individually for both a small forest area containing a set of 29 permanent sample plots that were damaged in Storm Martin in December 1999, and from a much larger set of 235 forest inventory plots damaged in Storm Klaus in January 2009. Both data sets are within the Landes de Gascogne Forest in Nouvelle-Aquitaine, France. The models were tested both against the data from which they were developed, and against the data set from the other storm. For comparison with an earlier study using the same data, logistic regression models were also developed. In addition, the ability of machine learning techniques to substitute for a mechanistic wind damage risk model by training them with previous mechanistic model predictions was tested.
All models were accurate at identifying whether trees would be damaged or not damaged but the random forests models were more accurate, had higher discriminatory power, and were almost totally unaffected by the removal of any individual input variable. However, if all information relating to a stand was removed the random forests model lost accuracy and discriminatory power. The other models were similarly affected by the removal of all site information but none of the models were affected by removal of all tree information, suggesting that damage in the Landes de Gascogne Forest occurs at stand scale and is not controlled by individual tree characteristics. The models developed with the large comprehensive database were also accurate in identifying damaged trees when applied to the small forest data damaged in the earlier storm. However, none of the models developed with the smaller forest data set could successfully discriminate between damaged and undamaged trees when applied across the whole landscape. All models were very successful in replicating the predictions of the mechanistic wind risk model and using them as a substitute for the mechanistic model predictions of critical wind speed did not affect the damage model results.
Overall the results suggest that random forests provide a significant advantage over other statistical modelling techniques and the random forest models were found to be more robust in their predictions if all input variables were not available. In addition, the ability to replace the mechanistic wind damage model suggests that random forests could provide a powerful tool for damage risk assessment over large regions and provide rapid assessment of the impact of different management strategies or be used in the development of optimised forest management with multiple objectives and constraints including the risk of wind damage.
Over the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ...ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long‐term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of >170,000 records of ground‐based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m3 of disturbed timber volume per year over the 70‐year study period. This value is likely a conservative estimate due to under‐reporting, especially of small‐scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m3/year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long‐term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes.
Shifts in forest disturbance regimes may compromise the continuous provisioning of ecosystem services to society. Although forests in Europe are central to many policies, empirical data for understanding disturbance dynamics are lacking. We present a unique database of >170,000 ground‐based natural disturbance records in European forests from 1950 to 2019. Disturbances significantly increase over the study period, damaging on average 43.8 million m3 of timber volume per year. This is likely a conservative estimate due to under‐reporting. We estimated the magnitude of unreported damages to be between 8.6 and 18.3 million m3/year.
In the future with climate change, we expect more forest and tree damage due to the increasing strength and changing trajectories of tropical cyclones (TCs). However, to date, we have limited ...information to estimate likely damage levels, and nobody has ever measured exactly how forest trees behave mechanically during a TC. In 2018, a category-5 TC destroyed trees in our ongoing research plots, in which we were measuring tree movement and wind speed in two different tree spacing plots. We found damaged trees in only the wider spaced plot. Here, we present how trees dynamically respond to strong winds during a TC. Sustained strong winds obviously trigger the damage to trees and forests but inter-tree spacing is also a key factor because the level of support from neighboring trees modifies the effective "stiffness" against the wind both at the single tree and whole forest stand level.
Modelling Canopy Flows over Complex Terrain Grant, Eleanor R.; Ross, Andrew N.; Gardiner, Barry A.
Boundary-layer meteorology,
12/2016, Letnik:
161, Številka:
3
Journal Article
Recenzirano
Recent studies of flow over forested hills have been motivated by a number of important applications including understanding CO
2
and other gaseous fluxes over forests in complex terrain, predicting ...wind damage to trees, and modelling wind energy potential at forested sites. Current modelling studies have focussed almost exclusively on highly idealized, and usually fully forested, hills. Here, we present model results for a site on the Isle of Arran, Scotland with complex terrain and heterogeneous forest canopy. The model uses an explicit representation of the canopy and a 1.5-order turbulence closure for flow within and above the canopy. The validity of the closure scheme is assessed using turbulence data from a field experiment before comparing predictions of the full model with field observations. For near-neutral stability, the results compare well with the observations, showing that such a relatively simple canopy model can accurately reproduce the flow patterns observed over complex terrain and realistic, variable forest cover, while at the same time remaining computationally feasible for real case studies. The model allows closer examination of the flow separation observed over complex forested terrain. Comparisons with model simulations using a roughness length parametrization show significant differences, particularly with respect to flow separation, highlighting the need to explicitly model the forest canopy if detailed predictions of near-surface flow around forests are required.
This paper presents a review of our current understanding of the process of wind damage to trees and forests, with a particular, but not exclusive focus, on planted and managed forests. It makes a ...direct comparison with the state of knowledge just over 50 years ago when systematic research on wind damage to forests was beginning and discusses how our knowledge has changed over that period. The paper starts with a discussion of the types of severe winds that cause damage and then explores the effect of a number of factors on the risk of wind damage. These include species differences, the influence of different tree characteristics, and the effect of tree competition, tree spacing, gaps and edges in the forest, and soil and site preparation. There is then a section dealing with wind damage at a variety of spatial and temporal scales and the processes occurring at these different scales. The penultimate part of the paper describes the actual physical mechanisms of stem damage and uprooting, how this understanding can be used to develop wind damage risk models, and then how the different parts of the overall wind damage problem can be brought together to form a holistic view. Finally, there is a brief review of the advance in our understanding over the last few decades, the continued areas of uncertainty or that require further work, and recommendations of subjects and topics that could be a focus for future research.
Wood mechanical properties, such as modulus of elasticity (MOE) and modulus of rupture (MOR), are important determinants of solid lumber performance and value. These properties vary systematically at ...different scales owing to multiple, potentially confounding, factors. Therefore, a statistical modeling approach may be an effective way to predict the impact of silvicultural practices on mechanical properties. The aim of this study was to develop models for predicting MOE and MOR in Scots pine (Pinus sylvestris L.), as functions of cambial age, height in the stem, wood density, and microfibril angle (MFA). Thirty-six trees were sampled from four mature Scots pine plantations in Scotland, UK. Longitudinal MOE and MOR were determined in static bending on 513 small (300 × 20 × 20 mm) defect-free samples. Nonlinear mixed-effects models based on an exponential function of cambial age were developed to predict the within-stem patterns of variation. The best model for MOR included cambial age, height in the stem, and sample density as explanatory variables, whereas the best MOE model also included a density/MFA term in the predictors. In growth simulations over a range of typical scenarios, the largest effect of silvicultural interventions was on the proportion of juvenile wood in the stem, but these had a negligible impact on mean tree MOE and MOR. The models will be incorporated into a growth, yield, and wood quality simulation system.
Ceccherini et al.1 quantify change using map pixel counts, rather than using a statistically rigorous sampling approach that is more appropriate for the estimation of area change7. ...although ...Ceccherini et al.1 considered false positives (incorrect detection of forest loss) in their sample analyses, they did not consider false negatives (undetected forest loss). ...analyses, which address both omission and commission errors, offer accurate and unbiased results of forest change. ...sample reference data tailored to the specific purpose of a given study can be used to discriminate proportions of loss due to natural disturbances within the overall forest loss rates12. ...we are confident that natural disturbances were not correctly excluded. ...information and knowledge are crucial to develop science-based, climate-smart forestry strategies18 to ensure that European forests continue to be an important carbon sink and a key ecosystem service provider in relation to the protection of biodiversity and the development of the bioeconomy. https://doi.org/10.1038/s41586-021-03292-x Received: 3 July 2020 Accepted: 26 January 2021 Published online: 28 April 2021 Check for updates Acknowledgements We thank G. Ceccherini and co-authors for immediately making available all original material, processing codes and results of their study upon request.
Abstract
Widely distributed in Quebec, balsam fir (Abies balsamea (L.) Mill.) is highly vulnerable to wind damage. Recently, there has been a trend in forest management to increase the use of partial ...cuttings in naturally regenerating stands, leaving the remnant trees at increased risk of wind damage. In order to limit wind damage after partial cuttings, it is therefore important to find silvicultural practices that minimize the risk of wind damage in these fir stands. Our main objective was to find balsam fir-specific values of parameters to integrate into the wind risk model ForestGALES, in order to simulate the impact of different types of commercial thinning on wind damage risk, and to determine which practice potentially minimizes the risk in a naturally regenerated stand. An anemometer placed at canopy height and strain gauges attached to the trunks of balsam firs allowed us to measure the wind-induced bending moments experienced by a sample of balsam fir trees. This enabled the calculation of the turning moment coefficients specific to each of the trees in order to compare them with the ForestGALES model predictions and to adapt the model for balsam fir stands. The model was tested first with only tree diameter and height as input variables to calculate the turning moment coefficient, then with the addition of a competition index, and finally with the addition of crown dimensions. Wind climate parameters for prediction of the probability of damage were calculated using the Wind Atlas Analysis and Application Program airflow model. The model with the highest accuracy was then used to simulate two types of thinning and determine the impact on wind damage risk for each tree in the stand. According to the model’s predictions, thinning from below has a reduced risk of wind damage compared with thinning from above.
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