Funding for this research was provided by the National Science Foundation (DEB-1457675). We thank the many participants in the Ice Storm Experiment (ISE) who helped with the ice application and associated field and laboratory work, especially Geoff Schwaner, Gabe Winant, and Brendan Leonardi. This manuscript is a contribution of the Hubbard Brook Ecosystem Study. Hubbard Brook is part of the Long-Term Ecological Research (LTER) network, which is supported by the National Science Foundation (DEB-1633026). The Hubbard Brook Experimental Forest is operated and maintained by the USDA Forest Service, Northern Research Station, Madison, WI.&#160;Video and images are by Jim Surette and Joe Klementovich, courtesy of the Hubbard Brook Research Foundation.

1. Develop the experimental design
<ol>
	<li>Determine the intensity and frequency of icing based on realistic values.</li>
	<li>Determine the size and shape of the plots.
	<ol>
		<li>If the goal is to evaluate tree responses, select a plot size that is large enough to include multiple trees and most of their root systems, which varies depending on factors such as tree species and age.</li>
		<li>For safety purposes, design the plots so that the entire plot area can be sprayed from outside the boundary.</li>
		<li>Space plots far enough apart (e.g., 10 m) so that a treatment in one plot does not affect another.</li>
		<li>Establish a buffer zone (e.g., 5 m) around plots to reduce edge effects and ensure a more even distribution of the ice coverage.</li>
		<li>Establish subplots within the larger plots for specific sampling needs.</li>
	</ol>
	</li>
	<li>Decide on the number of replicate plots.</li>
</ol>
2. Select and establish a study location
<ol>
	<li>Select a homogeneous forest stand with similar features, such as tree species composition, soils, lithology, and hydrology.</li>
	<li>Select a location for the application in an area where there is access to a water source during winter.</li>
	<li>Ensure that the supply of water is adequate for the ice application based on the pump rate and other factors such as the diameter of the hose, length of hose, nozzle used, and water pressure.</li>
	<li>Mark the boundary of the plots, buffer zone, and subplots.</li>
	<li>Conduct a complete forest inventory with descriptions of tree health conditions including assessments of dead, dying and damaged trees. Additionally, record any potential stressors (e.g., evidence of insect damage or disease) to help interpret the response to the ice treatment.</li>
	<li>If using UTVs to spray water, create passable trails along the sides of the plots while being careful to minimize disturbance.</li>
	<li>Once the plots are established, randomly assign a treatment to each plot and type of sampling that will be conducted in each subplot (e.g., coarse woody debris, fine litter, soil samples).</li>
</ol>
3. Timing of the application
<ol>
	<li>Select an appropriate window of time to perform the spraying.</li>
	<li>Perform the experiment when the weather conditions are conducive (e.g., when air temperature is less than -4 &#176;C and wind speed is less than 5 m/s).</li>
	<li>If spraying at night, deploy high powered lights around the edge of plots and run them on generators if electricity is not available.</li>
</ol>
4. Set up the water supply
<ol>
	<li>Set up a supply pump at the water source and connect a suction hose.</li>
	<li>Connect a strainer to the end of the suction hose to keep debris out of the lines.</li>
	<li>Break through any surface ice and fully submerge the strainer. The minimum depth of the water supply should be about 20 cm.</li>
	<li>Place a booster pump in the bed of a UTV to improve water pressure. In some cases, a booster pump may not be necessary, especially for low-stature vegetation.</li>
	<li>Run a firefighting hose from the supply pump to the booster pump.</li>
	<li>Use a fire-fighting monitor to enable safe, manual control over the high-pressure hose. The monitor can be free standing or mounted on the back of a UTV.</li>
	<li>Avoid situations that may interrupt the flow of water such as kinks in the hose, water drawdown at the supply source, and running out of gasoline for the pumps.</li>
</ol>
5. Creating the ice
<ol>
	<li>Create ice by spraying water vertically through gaps in the canopy. Make sure the water extends above the height of the canopy so that it is deposited vertically and freezes on contact with sub-freezing surfaces. Avoid stripping branches and bark from trees as water is sprayed upwards.</li>
	<li>Evenly distribute spray over the forest canopy by slowly driving the UTV back-and-forth along the edge of the application area. If free-standing monitors are used, move these manually to ensure that the coverage is even.</li>
	<li>Keep track of the timing of the application to help determine factors such as the weather conditions during application and the volume of water sprayed.</li>
</ol>
6. Measure ice accretion
<ol>
	<li>Make ground-based caliper measurements of radial ice thickness on lower-level branches or twigs near the edge of the application area to monitor ice accretion during application and determine when the target thickness has been attained.</li>
	<li>Obtain more accurate estimates of ice accretion with passive ice collectors after the application (Figure 1).
	<ol>
		<li>Before the application, construct passive ice collectors with two dowels oriented on three cardinal axes30 to create collectors with six component arms.</li>
		<li>Cut 2.54 cm dowels at a length of 30 cm.</li>
		<li>Join the dowels with a 6-way steel connector.</li>
		<li>Use an arborist throw weight to string parachute cord over sturdy branches that can withstand the ice load.</li>
		<li>Attach the passive ice collectors to the cord and raise them up into the canopy.</li>
		<li>Once the application is completed, lower the collectors to the ground, being careful not to lose any ice from the collector.</li>
		<li>Make vertical and horizontal measurements of ice thickness with calipers at multiple locations on the collector (e.g., three vertical and three horizontal measurements at three locations along each arm) before and immediately after ice application.</li>
		<li>Calculate ice thickness on each collector as the difference between the measurements before and after the application.</li>
		<li>To determine ice thickness with the water volume method, use a reciprocating saw to cut each dowel.</li>
		<li>Bring the dowels to a heated building, place them in buckets, and let the ice melt off at room temperature.</li>
		<li>Measure the volume of meltwater with a graduated cylinder.</li>
		<li>Calculate ice thickness based on the water volume and density of ice31.</li>
	</ol>
	</li>
</ol>
7. Safety considerations
<ol>
	<li>Stay well outside of the ice treatment area during spraying because ice loads can cause branches and limbs to break and fall.</li>
	<li>Wear hard hats or helmets to provide protection while the ice is being applied and during any sampling that occurs in the treated area after the application.</li>
	<li>Use a monitor to stabilize the hose during spraying.</li>
	<li>Dress appropriately for hazardous conditions and sub-freezing weather. Wear bright, visible clothing. Be prepared to spend long periods in wet, cold conditions by wearing rain gear and layers of warm clothes. Bring multiple changes of clothes, especially for personnel who are designated to spray.</li>
	<li>If working in a remote location, set up a temporary warming tent equipped with a portable heater.</li>
	<li>Allow personnel to have adequate time for breaks, changing out of wet clothes, and addressing problems that arise with equipment, etc.</li>
	<li>Use radios to communicate among personnel during the experiment. Maintain contact with personnel at a base station.</li>
	<li>Develop a safety plan in case of medical emergencies. Have medical personnel (e.g., Emergency Medical Technicians) and emergency equipment and supplies on site during the experiment.</li>
</ol>

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The authors have nothing to disclose. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government, and shall not be used for advertising or product endorsement purposes.

It is critical to perform experimental simulations of ice storms under appropriate weather conditions to ensure their success. In a previous study30, we found that the optimal conditions for spraying are when air temperatures are below -4 &#176;C and wind speeds are less than 5 m/s. Natural ice storms most commonly occur when air temperatures are slightly less than freezing (-1 to 0 &#176;C), and although the ideal temperatures for ice storm simulations are colder, they are still within the temper...

Ice storms are an important natural disturbance that can have both short- and long-term impacts on the environment and society. Intense ice storms are problematic because they damage trees and crops, disrupt utilities, and impair roads and other infrastructure1,2. The hazardous conditions that ice storms create can cause accidents resulting in injuries and fatalities2. Ice storms are costly; financial losses average $313 million per year in the United States (US)3, with some individual storms exceeding $1 billion4. In forest ecosystems, ice storms can have negative consequences including reduced growth and tree mortality5,6,7, increased risk of fire, and proliferation of pests and pathogens8,9,10. They can also have positive effects on forests, such as enhanced growth of surviving trees5 and increased biodiversity11. Improving our ability to predict impacts from ice storms will enable us to better prepare for and respond to these events.
Ice storms occur when a layer of moist air, that is above freezing, overrides a layer of subfreezing air closer to the ground. Rain falling from the warmer layer of air supercools as it passes through the cold layer, forming glaze ice when deposited on sub-freezing surfaces. In the US, this thermal stratification can result from synoptic weather patterns that are characteristic of specific regions12,13. Freezing rain is most commonly caused by Arctic fronts that move southeastward across the US ahead of strong anticyclones13. In some regions, topography contributes to the atmospheric conditions necessary for ice storms through cold air damming, a meteorological phenomenon that occurs when warm air from an incoming storm overrides cold air that becomes entrenched alongside a mountain range14,15.
In the US, ice storms are most common in the &#8220;ice belt&#8221; that extends from Maine to western Texas16,17. Ice storms also occur in a relatively small region of the Pacific Northwest, especially around the Columbia River Basin of Washington and Oregon. Much of the US experiences at least some freezing rain, with the greatest amounts in the Northeast where the most ice prone areas have a median of seven or more freezing rain days (days during which at least one hourly observation of freezing rain occurred) annually16. Many of these storms are relatively minor, although more intense ice storms do occur, albeit with much longer recurrence intervals. For example, in New England, the range in radial ice thickness is 19 to 32 mm for storms with a 50-year recurrence interval18. Empirical evidence indicates that ice storms are becoming more frequent at northern latitudes and less frequent to the south19,20,21. This trend is expected to continue based on computer simulations using future climate change projections22,23. However, the lack of data and physical understanding make it more difficult to detect and project trends in ice storms than other types of extreme events24.
Since major ice storms are relatively rare, they are challenging to study. It is difficult to predict when and where they will occur, and it is generally impractical to &#8220;chase&#8221; storms for research purposes. Consequently, most ice storm studies have been unplanned post hoc assessments occurring in the wake of major storms. This research approach is not ideal because of the inability to collect baseline data before a storm. Additionally, it can be difficult to find unaffected areas for comparison with damaged areas when ice storms cover a large geographic extent. Rather than waiting for natural storms to occur, experimental approaches may offer advantages because they enable close control over the timing and intensity of icing events and allow for appropriate reference conditions to clearly evaluate effects.
Experimental approaches also pose challenges, especially in forested ecosystems. The height and width of trees and the canopy makes them difficult to experimentally manipulate, as compared to lower-stature grasslands or shrublands. Additionally, disturbance from ice storms is diffuse, both vertically through the forest canopy and across the landscape, which is difficult to simulate. We know of only one other study that attempted to simulate ice storm impacts in a forest ecosystem25. In this case, a rifle was used to remove up to 52% of the crown in a loblolly pine stand in Oklahoma. Although this method produced results that are characteristic of ice storms, it is not effective at removing larger branches and does not cause the trees to bend over, which is common with natural ice storms. While no other experimental methods have been used to study ice storms specifically, there are some parallels between our approach and other types of forest disturbance manipulations. For example, gap dynamics have been studied by felling individual trees26, forest pest invasions by girdling trees27, and hurricanes by pruning28 or pulling down whole trees with a winch and cable29. Of these approaches, pruning most closely imitates ice storm impacts but is labor intensive and costly. The other approaches cause mortality of whole trees, rather than the partial breakage of limbs and branches that is typical of natural ice storms.
The protocol described in this paper is useful for closely mimicking natural ice storms and involves spraying water over the forest canopy during sub-freezing conditions to simulate glaze ice events. The method offers advantages over other means because the damage can be distributed relatively evenly throughout forests over a large area with less effort than pruning or downing whole trees. Additionally, the amount of ice accretion can be regulated through the volume of water applied and by selecting a time to spray when weather conditions are conducive for optimal ice formation. This novel and relatively inexpensive experimental approach enables control over the intensity and frequency of icing, which is essential for identifying critical ecological thresholds in forest ecosystems.

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simulating impacts of ice storms on forest ecosystems

Ice storms can have profound and lasting effects on the structure and function of forest ecosystems in regions that experience freezing conditions. Current models suggest that the frequency and intensity of ice storms could increase over the coming decades in response to changes in climate, heightening interest in understanding their impacts. Because of the stochastic nature of ice storms and difficulties in predicting when and where they will occur, most past investigations of the ecological effects of ice storms have been based on case studies following major storms. Since intense ice storms are exceedingly rare events it is impractical to study them by waiting for their natural occurrence. Here we present a novel alternative experimental approach, involving the simulation of glaze ice events on forest plots under field conditions. With this method, water is pumped from a stream or lake and sprayed above the forest canopy when air temperatures are below freezing. The water rains down and freezes upon contact with cold surfaces. As the ice accumulates on trees, the boles and branches bend and break; damage that can be quantified through comparisons with untreated reference stands. The experimental approach described is advantageous because it enables control over the timing and amount of ice applied. Creating ice storms of different frequency and intensity makes it possible to identify critical ecological thresholds necessary for predicting and preparing for ice storm impacts.

An ice storm simulation was performed in a 70&#8210;100 year-old northern hardwood forest at the Hubbard Brook Experimental Forest in central New Hampshire (43&#176; 56&#8242; N, 71&#176; 45&#8242; W). The stand height is approximately 20 m and the dominant tree species in the area of the ice application are American beech (Fagus grandifolia), sugar maple (Acer saccharum), red maple (Acer rubrum) and yellow birch (Betula alleghaniensis). Ten 20 m x 30 m plots were established and rando...

Watch this Scientific Journal Video about Simulating Impacts of Ice Storms on Forest Ecosystems at JoVE.com

Simulating Impacts of Ice Storms on Forest Ecosystems

Ice storms are important weather events that are challenging to study because of difficulties in predicting their occurrence. Here, we describe a novel method for simulating ice storms that involves spraying water over a forest canopy during sub-freezing conditions.

Ice storms can have profound and lasting effects on the structure and function of forest ecosystems in regions that experience freezing conditions. ...

simulating-impacts-of-ice-storms-on-forest-ecosystems

Research

JoVE Journal

Environment

6.9K Views.  U.S. Forest Service, Durham, NH. IJsstormen zijn een uitdaging om te bestuderen omdat het moeilijk is om te voorspellen wanneer en waar ze zullen plaatsvinden. Dit protocol schetst een nieuwe methode voor het simuleren van natuurijs stormen. De beschreven experimentele aanpak biedt het voordeel van controle over de timing en hoeveelheid toegepast ijs, waardoor het mogelijk is om ijsstormen van verschillende frequentie en intensiteit te creëren.We hebben deze methode getest in een bosecosysteem, maar het kan ook op ve...

Video: Simulating Impacts of Ice Storms on Forest Ecosystems

The Use of High-resolution Infrared Thermography (HRIT) for the Study of Ice Nucleation and Ice Propagation in Plants

Freezing events that occur when plants are actively growing can be a lethal event, particularly if the plant has no freezing tolerance. Such frost events often have devastating effects on agricultural production and can also play an important role in shaping community structure in natural populations of plants, especially in alpine, sub-arctic, and arctic ecosystems. Therefore, a better understanding of the freezing process in plants can play an important role in the development of methods of frost protection and understanding mechanisms of freeze avoidance. Here, we describe a protocol to visualize the freezing process in plants using high-resolution infrared thermography (HRIT). The use of this technology allows one to determine the primary sites of ice formation in plants, how ice propagates, and the presence of ice barriers. Furthermore, it allows one to examine the role of extrinsic and intrinsic nucleators in determining the temperature at which plants freeze and evaluate the ability of various compounds to either affect the freezing process or increase freezing tolerance. The use of HRIT allows one to visualize the many adaptations that have evolved in plants, which directly or indirectly impact the freezing process and ultimately enables plants to survive frost events.

The Use of High-resolution Infrared Thermography HRIT for the Study of Ice Nucleation and Ice Propagation in Plants

Here we present a protocol that allows one to visualize sites of ice formation and avenues of ice propagation in plants utilizing high resolution infrared thermography (HRIT).

Freezing events that occur when plants are actively growing can be a lethal event, particularly if the plant has no freezing tolerance. Such frost events ...

Evaluating Dryocosmus Kuriphilus-induced Damage on Castanea Sativa

Dryocosmus kuriphilus Yasumatsu has become a major pest for Castaneasativa since its arrival in Europe. Its galling activity results in the formation of different gall types and prevents the development of normal shoots. Repeated and uncontrolled attacks cause, besides the production of galls and the attendant gall-related reduction in leaf area, progressive corruption of the branch architecture, including the death of branch parts, and an increase in dormant bud activation. Thus far, there have been few attempts to quantify branch architecture damage. Further, the different methods for assessing infestation degree (MAID) that have been developed focus only on the galls' presence and abundance.
Using the leaf area to sapwood area relationship as a green biomass indicator, we developed in a previous study a damage composite index (DCI) that takes into account the most important branch architectural features, allowing for realistic damage assessment during the entire epidemic process. 
The aim of this study is to present this novel method and highlight differences in the damage description with respect to other broadly used indices. Results show how the DCI depicts branch damage better, especially during the epidemic peak, compared to MAID, which tend to underestimate it. We conclude by suggesting how to properly evaluate the overall impact of the pest by means of our composite damage index, the infestation degree using classic methods, and crown transparency evaluations.

Evaluating Dryocosmus Kuriphilus-induced Damage on Castanea Sativa

It is common practice to assess the damage caused by Dryocosmus kuriphilus by considering the abundance of galls alone rather than by also taking related branch corruption into consideration. We propose a composite damage index that takes into account the most important branch features, thus enabling more realistic damage assessment.

Dryocosmus kuriphilus Yasumatsu has become a major pest for Castaneasativa since its arrival in Europe. Its galling activity results in the formation of ...

Laboratory and Field Protocol for Estimating Sheet Erosion Rates from Dendrogeomorphology

Sheet erosion is among the crucial drivers of soil degradation. Erosion is controlled by environmental factors and human activities, which often lead to severe environmental impacts. The understanding of sheet erosion is, consequently, a worldwide issue with implications for both environment and economies. However, the knowledge on how erosion evolves in space and time is still limited, as well as its effects on the environment. Below, we explain a new dendrogeomorphological protocol for deriving eroded soil thickness (Ex) by acquiring accurate microtopographic data using both terrestrial laser scanning (TLS) and microtopographic profile gauges. Additionally, standard dendrogeomorphic procedures, dependent on anatomical variations in root rings, are utilized to establish the timing of exposure. Both TLS and microtopographic profile gauges are used to obtain ground surface pro&#64257;les, from which Ex is estimated after the threshold distance (TD) is determined, i.e., the distance between the root and the sediment knickpoint, which allows de&#64257;ning the lowering of the ground surface caused by sheet erosion. For each profile, we measured the height between the topside of the root and a virtual plane tangential to the ground surface. In this way, we intended to avoid small-scale impacts of soil deformation, which may be due to pressures exerted by the root system, or by the arrangement of exposed roots. This may provoke small amounts of soil sedimentation or erosion depending on how they physically affect the surface runoff. We demonstrate that an adequate microtopographic characterization of exposed roots and their associated ground surface is very valuable to obtain accurate erosion rates. This finding could be utilized to develop the best management practices designed to eventually halt or perhaps, at least, lessen soil erosion, so that more sustainable management policies can be put into practice.

Characterizing erosion from dendrogeomorphology has usually focused on accurately finding the starting time of root exposure, by examining macroscopic or cell level changes caused by exposure. Here, we offer a detailed description of different novel techniques to obtain more precise erosion rates from highly accurate microtopographic data.

Sheet erosion is among the crucial drivers of soil degradation. Erosion is controlled by environmental factors and human activities, which often lead to ...

A Method for Quantifying Foliage-Dwelling Arthropods

Terrestrial arthropods play an important role in our environment. Quantifying arthropods in a way that allows for a precise index or estimates of density requires a method with high detection probability and a known sampling area. While most described methods provide a qualitative or semi-quantitative estimate adequate for describing species presence, richness, and diversity, few provide an adequately consistent detection probability and known or consistent sampling areas to provide an index or estimate with adequate precision to detect differences in abundance across environmental, spatial, or temporal variables. We describe how to quantify leaf-dwelling arthropods by sealing the leaves and end of branches in a bag, clipping and freezing the bagged material, and rinsing the previously frozen material in water to separate arthropods from the substrate and quantify them. As we demonstrate, this method can be used at a landscape scale to quantify leaf-dwelling arthropods with adequate precision to test for and describe how spatial, temporal, environmental, and ecological variables influence arthropod richness and abundance. This method allowed us to detect differences in density, richness, and diversity of leaf-dwelling arthropods among 5 genera of trees commonly found in southeastern deciduous forests.

We describe how to quantify leaf dwelling arthropods by sealing the leaves and end of branches in a bag, clipping and freezing the bagged material, and rinsing the previously frozen material in water to separate arthropods from the substrate for quantification.

Terrestrial arthropods play an important role in our environment. Quantifying arthropods in a way that allows for a precise index or estimates of density ...

Laser-Induced Fluorescence Emission (L.I.F.E.) as Novel Non-Invasive Tool for In-Situ Measurements of Biomarkers in Cryospheric Habitats

Global warming affects microbial communities in a variety of ecosystems, especially cryospheric habitats. However, little is known about microbial-mediated carbon fluxes in extreme environments. Hence, the methodology of sample acquisition described in the very few studies available implies two major problems: A) high resolution data require a large number of samples, which is difficult to obtain in remote areas; B) unavoidable sample manipulation such as cutting, sawing, and melting of ice cores that leads to a misunderstanding of in situ conditions. In this study, a prototype device that requires neither sample preparation nor sample destruction is presented. The device can be used for in situ measurements with a high spectral and spatial resolution in terrestrial and ice ecosystems and is based on the Laser-Induced Fluorescence Emission (L.I.F.E.) technique. Photoautotrophic supraglacial communities can be identified by the detection of L.I.F.E. signatures in photopigments. The L.I.F.E. instrument calibration for the porphyrin derivates chlorophylla (chla) (405 nm laser excitation) and B-phycoerythrin (B-PE) (532 nm laser excitation) is demonstrated. For the validation of this methodology, L.I.F.E. data were ratified by a conventional method for chla quantification that involved pigment extraction and subsequent absorption spectroscopy. The prototype applicability in the field was proven in extreme polar environments. Further testing on terrestrial habitats took place during Mars analog simulations in the Moroccan dessert and on an Austrian rock glacier. The L.I.F.E. instrument enables high resolution scans of large areas with acceptable operation logistics and contributes to a better understanding of the ecological potential of supraglacial communities in the context of global change.

Laser-Induced Fluorescence Emission L.I.F.E. as Novel Non-Invasive Tool for In-Situ Measurements of Biomarkers in Cryospheric Habitats

Carbon fluxes in the cryosphere are hardly assessed yet but are crucial regarding climate change. Here we show a novel prototype device that captures the phototrophic potential in supraglacial environments based on laser-induced fluorescence emission (L.I.F.E.) technology offering high spectral and spatial resolution data under in situ conditions.

Global warming affects microbial communities in a variety of ecosystems, especially cryospheric habitats. However, little is known about ...

Using Tree-Rings to Reconstruct Fire History Information from Forested Areas

Annual tree-ring patterns are a source of ecological and environmental information including the history of fires in forested areas. Tree-ring based fire histories include three fundamental phases: field collection, laboratory methods (preparation and dating), and data analysis. Here we provide step-by-step instructions and issues to consider, including the process for selecting the study area, sampling sites, plus how and which fire-scarred trees to sample. In addition, we describe fire-scar sample preparation and dating which are done in the laboratory. Finally, we describe basic analysis and relevant results, including examples from studies that have reconstructed fire history patterns. These studies allow us to understand the historical fire frequency, changes in those frequencies related to anthropogenic factors, and analyzes of how climate influences fire occurrence over time. The description of these methods and techniques should provide a greater understanding of fire history studies that will benefit researchers, educators, technicians, and students interested in this field. These detailed methods will allow new researchers to this field, a resource to start their own work and achieve greater success. This resource will provide a greater integration of tree-ring aspects within other studies and lead to a better understanding of natural processes with forested ecosystems.

This work explains the most appropriate techniques and methods for conducting a fire history study from beginning site selection to final analysis of fire-climate relationship.

Annual tree-ring patterns are a source of ecological and environmental information including the history of fires in forested areas. Tree-ring based fire ...

How to Extract Climate Variability from Tree-Rings

Tree rings have been used to reconstruct climatological variables in many locations around the world. Moreover, tree-rings can provide valuable insights into climatic variability of the last few centuries and, in some areas, several millennia. Despite the important development, that dendrochronology has had in recent decades to study the dendroclimatic potential of a large number of species present in different ecosystems, much remains to be done and explored. In addition to this, in the last few years more people (students, teachers and researchers) around the world are interested in implementing this science to extend the timeline of climate information backwards and understand how climate has changed on scales of decades, centuries or millennia. Therefore, the objective of this work is to describe the general aspects and basic steps needed to conduct a tree-ring climate reconstruction, from site selection and field sampling to laboratory methods and data analysis. In this method's video and manuscript, the general basis in tree-ring climatic reconstructions is explained so newcomers and students can use it as an available guide into this field of research.

Tree-ring climate reconstructions can be helpful to better understand past climate variability beyond instrumental records. This protocol shows how to reconstruct past climate using tree rings and meteorological instrumental records.

Tree rings have been used to reconstruct climatological variables in many locations around the world. Moreover, tree-rings can provide valuable insights ...

Simulating Temperature in a Soil Incubation Experiment

The study of warming impact on soils requires a realistic and accurate representation of temperature. In laboratory incubation studies, a widely adopted method has been to render constant temperatures in multiple chambers, and via comparisons of soil responses between low- and high-temperature chambers, to derive the warming impact on soil changes. However, this commonly used method failed to imitate both the magnitude and amplitude of actual temperatures as observed in field conditions, thus potentially undermining the validity of such studies. With sophisticated environmental chambers becoming increasingly available, it is imperative to examine alternative methods of temperature control for soil incubation research. This protocol will introduce a state-of-the-art environmental chamber and demonstrate both conventional and new methods of temperature control to improve the experimental design of soil incubation. The protocol mainly comprises four steps: temperature monitoring and programming, soil collection, laboratory incubation, and warming effect comparison. One example will be presented to demonstrate different methods of temperature control and the resultant contrasting warming scenarios; that is, a constant temperature design referred to as stepwise warming (SW) and simulated in situ temperature design as gradual warming (GW), as well as their effects on soil respiration, microbial biomass, and extracellular enzyme activities. In addition, we present a strategy to diversify temperature change scenarios to meet specific climate change research needs (e.g., extreme heat). The temperature control protocol and the recommended well-tailored and diversified temperature change scenarios will assist researchers in establishing reliable and realistic soil incubation experiments in the laboratory.

Laboratory soil warming experiments usually employ two or more constant temperatures in multiple chambers. By presenting a sophisticated environmental chamber, we provide an accurate temperature control method to imitate the magnitude and amplitude of in situ soil temperature and improve the experimental design of soil incubation studies.

The study of warming impact on soils requires a realistic and accurate representation of temperature. In laboratory incubation studies, a widely adopted ...

Determination of the Friction Coefficients of Icy Pavements Under Different Amounts of Snowfall

Ice on road surfaces can lead to a significant decrease in the friction coefficient, thus endangering driving safety. However, there are still no studies that provide exact friction coefficient values for pavements covered in ice, which is detrimental to both road design and the selection of winter road maintenance measures. Therefore, this article presents an experimental method to determine the friction coefficient of icy road surfaces in the winter. A British portable tester (BPT), also known as a pendulum friction coefficient meter, was employed for the experiment. The experiment was divided into the following five steps: the preparation of the equipment, the calculation and analysis of the snowfall, equipment calibration, friction coefficient determination, and data analysis. The accuracy of the final experiment is directly affected by the equipment accuracy, which is described in detail. Moreover, this article suggests a method for calculating the ice thickness for corresponding amounts of snowfall. The results illustrate that even patchy ice formed by very light snowfall may lead to a significant decrease in the friction coefficient of the pavement, thus endangering driving safety. Additionally, the friction coefficient is at its peak when the ice thickness reaches 5 mm, meaning protection measures should be taken to avoid the formation of such ice.

Here, we present a method for determining the friction coefficient of pavements with different ice thicknesses indoors. The complete procedure includes the preparation of the equipment, the calculation and analysis of the snowfall, equipment calibration, friction coefficient determination, and data analysis.

Ice on road surfaces can lead to a significant decrease in the friction coefficient, thus endangering driving safety. However, there are still no studies ...

Engineering

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Here, we developed an individual-tree model of 5-year basal area increments based on a dataset including 21898 Picea asperata trees from 779 sample plots located in Xinjiang Province, northwest China. To prevent high correlations among observations from the same sampling unit, we developed the model using a linear mixed-effects approach with random plot effect to account for stochastic variability. Various tree- and stand-level variables, such as indices for tree size, competition, and site condition, were included as fixed effects to explain the residual variability. In addition, heteroscedasticity and autocorrelation were described by introducing variance functions and autocorrelation structures. The optimal linear mixed-effects model was determined by several fit statistics: Akaike&#8217;s information criterion, Bayesian information criterion, logarithm likelihood, and a likelihood ratio test. The results indicated that significant variables of individual-tree basal area increment were the inverse transformation of diameter at breast height, the basal area of trees larger than the subject tree, the number of trees per hectare, and elevation. Furthermore, errors in variance structure were most successfully modeled by the exponential function, and the autocorrelation was significantly corrected by first-order autoregressive structure (AR(1)). The performance of the linear mixed-effects model was significantly improved relative to the model using ordinary least squares regression.

Mixed-effects models are flexible and useful tools for analyzing data with a hierarchical stochastic structure in forestry and could also be used to significantly improve the performance of forest growth models. Here, a protocol is presented that synthesizes information relating to linear mixed-effects models.

Here, we developed an individual-tree model of 5-year basal area increments based on a dataset including 21898 Picea asperata trees from 779 sample plots ...

Simulating Impacts of Ice Storms on Forest Ecosystems

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