CHAPTER 11

APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES

11.1 INTRODUCTION 11.2 CLIMATE AND WEATHER ANALYSIS FOR FORESTRY AND NON-FOREST Every stage in the development, growth and TREE OPERATIONS harvesting of forest and also non-forest trees is in a large measure controlled by weather and 11.2.1 Tree response to meteorological climate. The establishment of a new forest, elements whether by seeding and planting or by natural means, depends on the proper sequence of 11.2.1.1 Temperature weather events as they interact with soil condi- tions, on the one hand, and the plant material Together with light, water and nutrients, tempera- (seed, young seedlings), on the other. As the ture is a key environmental factor controlling young forest grows, the incidence of plant plant function. Temperature is a measure of the diseases, the development of insects and other concentration of heat energy within a medium, pests, and the occurrence of destructive forest such as air, water or soil. It thus affects physical fires all depend on weather and climate. Added characteristics of these media, including atmos- to this is the fact that when the trees are finally pheric humidity, the viscosity of liquid water (as harvested, rain and/or snow may affect the effi- well as freezing and thawing) in soils, and molecu- ciency – or indeed even the possibility – of lar and turbulent exchanges of heat, water vapour cutting and removing the crop trees. Non-forest and CO2 (from the scales of individual leaves up to trees typically receive more attention and there- entire regions). Changes in environmental temper- fore the knowledge of weather may have even ature manifest themselves primarily through more impact on crop operations. Real-time changes in air temperature, driven by seasonal and weather data may be input to expert systems, diurnal variations in incident solar radiation, management models or simple applications to coupled with downwelling long-wave radiation support the decisions of the forester or grower. from the atmosphere and clouds, which drive Climate data are widely used to assess probabil- surface heating of vegetation and soils. Some of ity and risk of extreme events and to compute the heat arriving at the surface is transmitted statistics of the relevant weather events. downwards into the soil, contributing to soil warming. Heat loss occurs through convective While in some situations foresters and growers exchange of sensible and latent heat, coupled with may utilize data from their National long-wave reradiation from all natural surfaces. Meteorological Services, in others they may have The temperatures of plant tissues and organs are to rely on their own observations and knowledge thus intimately coupled to changes in environ- of weather and climate. In many cases, weather mental temperature, both reacting to changes and data collected for agricultural purposes may be contributing to them. For more detailed explana- used by the forester or grower; in other situa- tions of these processes, see standard texts such as tions, specialized observations are necessary. Monteith and Unsworth (1990), Jones (1992) and Specialized observations are usually needed for Campbell and Norman (1998). pest management, local frost forecasts and fire danger rating systems. In the following sections, Temperature is the major environmental factor most of the issues mentioned that are relevant affecting the activity of enzymes (such as ribulose to forestry and non-forest trees are discussed in diphosphate carboxylase, which is responsible for some detail. Climate variability and change are CO2 fixation). It therefore strongly influences the also very important for forestry and non-forest rates of all biochemical reactions that occur in plant tree sustainability. In some regions, some crops cells, including those involved in the complex may have too much damage too often, or may pathways of cellular respiration (both for mainte- become unavailable under climate change condi- nance and for growth) in the mitochondria, and tions. Information on these and other topics in photosynthesis and photorespiration in chloro- forest meteorology is contained in a number of plasts. These processes are directly linked to stomatal WMO publications (WMO, 1978a, 1988, 1994a, functioning and root activity and hence to controls 2000). of the movement of water and photosynthate 11–2 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES through and within the plant. Temperature also importance to forest and non-forest trees will be strongly influences rates of cell division (both discussed in 11.2.1.5. mitotic at apical and cambial meristems and meiotic in the formation of pollen and ovules) (see Salisbury Global radiation is composed of direct and diffuse and Ross (1992) for more detailed explanations). radiation, and has wavelengths between 0.3 µm Some of these effects contribute to “macroscale” and 3.0 µm. It is determined by the amount of radi- phenological responses, such as the timing of ation that reaches the top of the atmosphere, which cambial activity (namely, the onset of growth), leaf depends on latitude and day of the year, cloudiness, emergence, flowering, seed production and disper- cloud type and atmospheric turbidity. Estimates of sal. Many of these have been shown to require global radiation and thus of visible radiation are species-specific critical “heat sums”, generally possible using appropriate models (Linacre, 1992). computed as integrals of daily mean temperatures above a threshold value from the beginning of the The region of the solar spectrum that is more impor- growing season. These processes then influence tant to photosynthesis is the visible band, also competition among and within species, survival known as photosynthetically active radiation (PAR), and growth. which consists of wavelengths between approxi- mately 0.4 µm and 0.7 µm. The photons in the Extreme temperatures (see also 11.2.3.2) can cause visible light are all absorbed by the photosynthetic denaturing of enzymes and hence contribute to system, but photons in the yellow and green bands cellular and tissue damage and in some cases mortal- have lower absorptivities. ity of the entire plant. The definition of an extreme temperature in this context is difficult because most Solar spectrum varies with solar altitude, atmos- plant species are able to tolerate a range of tempera- pheric turbidity and cloudiness. The fraction of tures, which tends to vary with latitude and visible radiation in direct radiation, in terms of elevation. Most vascular plants will die when energy, for a solar altitude between 30° and 50° is exposed to temperatures above 45°C, though some about to 0.5 for clean air and 0.4 for very turbid air. can survive appreciably higher temperatures. Many The fraction of visible radiation in global radiation tree seeds can tolerate substantially higher tempera- is close to 0.5 under clear sky conditions. This ratio tures for brief periods, notably those of fire-adapted increases with cloudiness, especially in the tropics, species that produce serotinous structures. Extreme where it may reach 0.63 under very cloudy skies low temperatures pose other risks. In regions with (Monteith and Unsworth, 1990). strong seasonal variations in temperature, native species will typically exhibit some form of seasonal The fraction of the global radiation that reaches the acclimation, to avoid tissue damage due to cellular canopy level is reflected by the canopy and soil and freezing during winter. In cold climates, many is often termed albedo. Typical values for forests species can avoid freezing down to –40°C by super- and orchards range from 12 to 18 per cent (Monteith cooling internal water. In extremely cold regions, and Unsworth, 1990). Another fraction of the radi- such as the boreal zone, native tree species are able ation is absorbed by the canopy elements, and the to withstand much lower temperatures due to remaining fraction is transmitted through the mechanisms of extracellular frost tolerance (FAO, canopy and absorbed by the soil and transformed 2005). into heat. Often it is useful to consider another frac- tion, f, which is the fraction intercepted by the canopy (f = 1 – fraction transmitted). All these frac- 11.2.1.2 Radiation tions may be computed using simple models that Solar radiation has great importance in the are presented in most textbooks of environmental establishment and growth of forest and non-forest physics (for example, Monteith and Unsworth, trees. Radiation is captured by canopies and its 1990; Campbell and Norman, 1998). energy is used to convert carbon dioxide into sugar- like structures in a process called photosynthesis. Once global radiation (or visible radiation) is Radiation may also induce movement or govern known, the computation of the radiation capture some formative processes. Photosynthesis requires by trees may be achieved using models of different higher radiation intensity than photo-stimulus complexity (Ross, 1981; Monteith and Unsworth, processes, but both are of major importance for 1990; Campbell and Norman, 1998). The most plant growth and development. Formative processes complex models of light interception in forests are often determined by the relative lengths of light account for the distribution of phytoelements in and dark periods to which plants are exposed, a the canopy and their optical properties. Orchard phenomenon known as photoperiodism, whose interception of radiation, due to the regular CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–3 distribution of the trees and similar size and form, low radiation requirements. Knowledge of the allows some simplifications to be introduced, relative light requirement in forest tree species is namely the definition of envelopes of known important in forest management. For example, geometry where phytoelements are distributed and shade-tolerant species need shade in order to radiation extinction takes place (Charles Edwards thrive, while species with high radiation and Thorpe, 1976; Norman and Welles, 1983; Oker requirements need high levels of radiation, Blom et al., 1991; Mariscal et al., 2000, 2004). Many because these plants frequently grow in full operational models, however, use simpler sunlight in their original habitat. The light regime approaches that lack the generality of more in forests may be controlled by selective cutting sophisticated models, but are easier to understand, in order to increase the penetration of light and construct, parameterize and use (see 11.4.1 and facilitate reproduction. 11.4.2). Radiation affects the growth and production of Monteith (1977) observed that, for a number of trees and radiation also has a deleterious effect on crops including fruit trees, when biomass accumu- many microorganisms that are plant pathogens. lation was plotted as a function of intercepted Fire danger indices often incorporate net radiation radiation, an almost straight line would result. since radiation energy dries the fuel, which Therefore, he suggested that biomass accumulation increases the probability of ignition and the accel- could be modelled as eration of the rate of spread and intensity of a fire (see 11.5). B e f S ∑= ∑ t (11.1) 11.2.1.3 Humidity and precipitation where ∑ B is the accumulated biomass, ∑ St is the sum of daily total solar radiation, e is the radiation Rain is the most common form of precipitation in use efficiency for the crop and f is the fraction of forests, but other forms of precipitation, such as incident radiation intercepted by the canopy. snow, fog and hail, can also be significant. Indeed, extra inputs of moisture stripped from fog by trees In the absence of stress, e is often conservative, typi- (especially conifers) may be considerable –1 cally ranging between 1.0 and 1.5 g MJ for C3 (Bruijnzeel, 2001). Rain, snow and fog also supply species in temperate environments, 1.5 to 1.7 g MJ–1 a certain quantity of nutrient elements to forests –1 for tropical C3 species and up to 2.5 g MJ for tropi- and act as a means of transporting nutrients cal C4 cereals under favourable conditions. Oil trapped on foliage to soil. Generally, the quantity palm, rubber, cocoa and coconut achieve a maxi- of phosphorous transported by precipitation is mum of 0.9 g MJ–1 (Squire, 1990). Gower et al. small, but inputs of potassium, calcium and (1999) report radiation use efficiencies of forests in nitrogen may not be insignificant compared to boreal, temperate and tropical environments. nutrient cycling by forest stands (Miller, 1983). Precipitation may also carry significant amounts Lopez (1989) gives an example of a simple light of atmospheric pollutants, with potentially distribution profile in a forest consisting of four destructive effects on commercial forestry (such as layers. In the first layer the canopy receives all the acid rain). Atmospheric humidity is also an incident radiation, of which 60 to 90 per cent is important factor in the hydrology of forests and absorbed. The absorbed fraction depends on many growth of trees. As with precipitation, the amount factors, including leaf development. In the second and distribution of atmospheric water vapour layer, the canopy receives approximately 25 per content is variable over space and through time. cent of incident light in the forest. The third layer This variability is normally related to meteorological consists of trees of smaller height. The intensity of conditions, season of year and topography, and in the light decreases to 3 per cent of incident light. some local circumstances it may even be related to In this layer, strong competition for light occurs. the presence and structure of forests. Not only is The fourth layer is next to the forest floor. The atmospheric moisture a basic element in intensity of light is often less than 1 per cent and hydrological processes and the biosphere, but it owing to this limited illumination, there are few also has other roles that affect forests. Moisture in leaves and flowers and many sprouts. the air helps moderate temperature extremes because it absorbs or reflects about half of the The radiation requirement of species varies incoming short-wave radiation during the day and widely. Some typical forest trees, such as birch, helps trap outgoing long-wave radiation during larch and pine, have high requirements, while the night and day. Atmospheric moisture also beech and spruce are examples of forest trees with influences transpiration rates from leaf stomata, 11–4 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES thereby affecting soil water storage and hence, the development in a forest ecosystem. Changes to water status of trees. coniferous upland forest plantations begin with transformation of land as a result of rough grazing, 11.2.1.3.1 Humidity followed by drainage, planting and subsequent forest development, and then canopy closure and Atmospheric humidity can be generally described clear-felling. These variations in forest stands as the content of water vapour in the atmosphere at produce significant changes in the water and a given pressure and temperature, and can be nutrient status of growing trees, the hydrological expressed, for example, as relative or absolute balance and hydrochemical function of the humidity. As air becomes warmer, the capacity of catchment. Several useful long-term case studies the atmosphere to hold water vapour increases and from both a hydrological and biological/ecological vice versa, as air cools the capacity of air to hold perspective have been established. These include water vapour decreases and cloud droplets may Coalburn (for example, Robinson et al., 1998) and grow and coalesce to fall as rain. Atmospheric Plynlimon (for example, Neal, 1997) in the United humidity is critical to determining the adaptation Kingdom and the Hubbard Brook experimental and productivity of trees in water-limited areas catchment (for example, Likens and Bormann, through application of the water use efficiency ratio 1995) in the United States. (WUE), which describes the ratio of carbon assimi- lation to transpiration. Humidity levels and relative The operations of non-forestry agriculture, such as evapotranspiration affect the water and nutrient tree nurseries and orchards, in many respects are status of developing trees. Stomatal conductance of similar to the production of any other agricultural water vapour, especially in C3 plants, which include crop. Many of the principles applicable to inten- virtually all woody plants, decreases as the vapour sively cultivated garden crops also apply to pressure deficit close to leaf surfaces increases and, production of non-forest trees. Forecasts and infor- hence, humidity also decreases. Experimental stud- mation on precipitation amounts, intensity and ies indicate that WUE per unit of biomass may duration allow management of water resources increase substantially with changes in atmospheric under circumstances in which nurseries require irri- CO2 concentrations and temperature, implying a gation or drainage installation for optimum reduction in transpiration (Morison, 1987). development of seedlings or fruit. For example, Therefore, it is important either under present water stress on trees will affect both the growth and climate conditions or future global climate change quality of the final product during drought periods, in determining the WUE of the forest stand in the and waterlogged ground is potentially destructive field based on stomatal response to air humidity to sensitive tree species. and CO2 concentrations, for detection of changes in forests’ water use per unit of land. Changes in climate may significantly affect the development and management of forests by altering The influence of atmospheric humidity, expressed tree physiology and tree development. Current as relative humidity (being the ratio of the mass of weather indicators based on the Intergovernmental water vapour in a given volume of air to the mass of Panel on Climate Change (IPCC) Third Assessment saturation water vapour in the same volume, Report (IPCC, 2001a) for changes in twentieth- expressed as a percentage), on fuel moisture content century climate suggest that increases in of trees under dry conditions is an important factor precipitation of between 5 and 10 per cent in the in determining such things as the rate of spread of northern hemisphere will be very likely, although forest fires (Byram, 1957). The effect of relative some regions will experience decreases in humidity includes the fuel combustion rate, rate of precipitation (for instance, parts of the spread of the flame front, smoke production and Mediterranean). An increase in heavy precipitation the rise of smoke plumes in the atmosphere, and events is also expected to be likely at mid- and high the increase or decrease in probability of ignition northern latitudes. Biological consequences from spotting and hence, the acceleration of rate of reported by IPCC (IPCC, 2001b) that affect forestry spread and intensity of a fire. include: observed lengthening of the growing season in the northern hemisphere by 1–4 days per decade during the last 40 years; the poleward shift 11.2.1.3.2 Precipitation of plant ranges and also plant ranges extending to Forestry–precipitation interactions change higher elevations; and the observation in the throughout the course of a forest plantation’s life northern hemisphere of earlier plant flowering. cycle, and this is especially true of the partitioning Therefore, changes in precipitation coupled with of available precipitation through stages of canopy temperature changes may have important CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–5 implications for forest management in the and energy in series with the stomatal and meso- commercial sector, such as the species and phyll terms. It follows that wind has relatively little provenance of trees used in forestry and the non- impact on heat and mass exchanges of small leaves forest tree sector. (which always have a thin boundary layer), and the greatest effects will be for large leaves at low wind 11.2.1.4 Wind speed (for instance, Grace, 1977). Increases in wind speed may increase or decrease transpiration rates Over the last 50 years or so, much work has been at both the leaf and canopy scales, depending on devoted to understanding the effects of wind on the relative changes in the leaf–air differentials of trees in forests and, to a lesser extent, in non-forest temperature and humidity (for instance, Chang, situations. Interesting examples may be found in 1974; Monteith and Unsworth, 1990; see also Ruck et al. (2003). Another good up-to-date source discussion of the Penman–Monteith equation in is Coutts and Grace (2005), a collection of research 11.4.1.2). Wind-tunnel studies by Aubrun et al. papers covering the physics of airflows over forested (2005) have demonstrated the important role of terrain, the mechanical and physiological effects of wind in canopy–atmosphere exchanges of biogenic wind on trees, and the nature and extent, and trace gases (volatile organic compounds). management implications, of damage caused by storms. A collection of papers in Part II of Hutchison In addition, mechanical stresses on leaves, flowers and Hicks (1985), though somewhat dated, provides and stems cause bending and leaf-fluttering, and a good basis for current research on the aerodynam- may lead to tissue damage (hence stimulating ics of forest canopies. Although new computational growth of callus and “reaction wood”, such as stem fluid dynamics approaches are available (for exam- buttresses). Mechanical stresses also contribute to ple, Wang and Tackle, 1997; Wilson and Flesch, the shedding of dead material (for example, Staelens 1999), Wisse and Stigter (2007) note a lack of knowl- et al., 2003) and the dispersal of pollen and seeds edge in developing regions of the aerodynamic (for example, Greene and Johnson, 1989) and of properties of local biological shelter (see also Stigter pests and pathogens. Strong winds, possibly in et al., 2005). The unfortunate reality is that data on combination with snow and ice accumulation, wind effects in hot climates are generally sparse often cause physical breakage of tree stems and (Wisse and Stigter, 2007; but see Biona et al., branches, while frequent winds in a prevailing 2001). direction (such as in some coastal regions, or on hill slopes) can cause stunted or deformed growth (Chang, 1974; Pereira et al., 2002). 11.2.1.4.1 Role of wind in forested ecosystems Wind couples vegetation to the atmosphere, mixing Cordero (1999), for example, studied wind effects air from above the turbulent boundary layer with on development of potted Cecropia schreberiana that close to the leaves and stems. In the process, it saplings at high elevations in Puerto Rico. He transfers momentum energy into the canopy, while found numerous morphological and physiological reducing concentration gradients of atmospheric adaptations to cope with higher wind loading, constituents, including oxygen and CO2, water including: increased root/shoot ratio, leaf abrasion vapour and heat, between vegetation surfaces and and epinasty, and reduced leaf area and height the atmosphere. These functions are crucial to the (namely, lower stem height to diameter ratio, maintenance of plant growth and survival. It has particularly in windward trees). Wind decreased been said that without turbulence, life on Earth photosynthesis and respiration per unit leaf area would be impossible, because all organisms would (but not per unit mass), resulting from a higher suffocate in their own CO2. light compensation point and lower quantum yields, as well as reduced nitrogen use efficiency The effects of wind on trees can be grouped as (in spite of higher leaf N). Wind-exposed stems ecophysiological (for example, supply and removal were of lower density and more flexible, with of CO2 and oxygen for photosynthesis and respira- higher water contents. Puigdefabregas et al. (1999) tion; losses of water vapour in transpiration) and noted banding structures in primeval Nothofagus physical (for example, exchanges of kinetic, sensi- betuloides forest on Tierra del Fuego (perpendicular ble and latent heat energy). The average thickness to the prevailing wind direction). Trees on exposed of the laminar boundary layers surrounding leaves windward edges of these bands were typically and other objects increases with their size, but is decadent and dying, with basal area and mean tree inversely related to wind speed (for instance, size reduced by up to 50 per cent (compared with Campbell and Norman, 1998). The laminar bound- sheltered locations), while seedlings were found ary layer presents a resistance to exchanges of mass mainly at the leeward edges. The banding patterns 11–6 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES evidently result as trees become more vulnerable 11.2.1.4.2 Wind profiles in forest canopies to wind damage with age and lose protection from older windward trees. The wind speed (u) observed above a plant canopy is a function of synoptic processes moderated by In many regions, wind is a natural disturbance local topography and the proximity to coasts (of agent contributing to changes in structure of oceans or large lakes). Under thermally neutral natural and managed forests (for example, Dyer atmospheric conditions, mean velocity increases and Baird, 1997; Grove et al., 2000; Peterson, 2000; logarithmically with height for several metres above Proctor et al., 2001; Scheller and Mladenoff, 2005; the surface (bare soil or vegetation), following the Nagel and Diaci, 2006). Some studies, however, wind profile equation (for example, Monteith and indicate that the impacts of storm damage on Unsworth, 1990): natural vegetation succession are often benign (for u∗ z − d example, Castelli et al., 1999; Cooper-Ellis et al., u() z = ln [m s–1] with k z 1999; Peterson, 2000). In Melbourne, Australia, o Harper et al. (2005) found that high wind exposure in remnant Eucalyptus forests increases the (11.2) z≥ z0 + d likelihood of hollows occurring in live trees, providing critical habitat for small mammals and where birds, notably in suburban locations. –1 u* = friction velocity (m s ) Wind is also a major factor influencing the estab- z = height of wind measurement (m) lishment and spread of forest fires (for example, d = zero plane displacement height (m) Taylor et al., 2004; Wisse and Stigter, 2007; see also k = von Karman constant (0.41) (dimensionless) 11.5). Areas previously burned by severe fires can z0 = roughness length (for momentum) (m). also suffer accelerated wind erosion, resulting in soil loss and air quality problems (for example, In Figure 11.1, the horizontal axis expresses wind Whicker et al., 2006). speed relative to that at the top of the canopy

1.6 1 Douglas-fir forest 2 Dense conifer with understorey 1.4 3 Moderately dense conifer without understorey 4 Dense hardwood jungle with understorey z/h 1.2 5 Isolated conifer stand 1.0 3 0.8

d+ z 0 0.6 2 4 h 0.4 d

0.2 1 5 0 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

Figure 11.1. Characteristic wind speed profiles above and within different forest canopies, adapted from diagrams in Fritschen (1985), Lopez (1989) and Monteith and Unsworth (1990) CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–7

(z = h), that is, where uz/uh is 1.0. At z > h, wind between canopy light interception measured using speed follows the logarithmic profile, but below hemispherical photography and wind speed within this height, the actual wind speed is determined the canopy relative to that measured above. by canopy structure, including the presence or absence of understorey vegetation. The thick Aerodynamic roughness is key to the sheltering dashed line indicates the extrapolation of the effects provided by tree cover and can be an theoretical logarithmic profile to z = d + z0, where important feedback on local climate. Work by u → 0. The thinner curved lines are based on obser- Branford et al. (2004) shows that cloud and aerosol vations summarized by Fritschen (1985) as deposition are strongly influenced by roughness at indicated in the legend. The height of d + z0 is forest edges. Studies by Chase et al. (1996) and assumed to be 0.7 h, which is typical of many Pielke (2001) suggest that land conversions (notably forests, such as the Douglas-fir forest indicated by large-scale deforestation) affect roughness as well as curve 1. Data sources for the canopy profiles are: albedo, leading in some regions to detectable (1) Fritschen et al. (1973); (2) Gisborne (1941); (3) changes in precipitation patterns. Fons (1940); (4) Latimer (1950); and (5) Reifsnyder (1955). 11.2.1.4.3 Sheltering mechanisms

The zero plane displacement parameter (d) is the Clearly trees provide shelter, meaning that average height at which momentum is considered to be wind velocities below the zero plane are typically completely absorbed by the individual elements of much lower than those in the free airstream above the plant stand. The ratio d/h generally decreases (Figure 11.1). Sheltering stems from the absorption with stand density. The roughness parameter (z0) is a of wind momentum energy by the stand, which complex function of stand density, uniformity of involves a complex combination of factors. tree heights and leaf area index, but defined in such a way that the logarithmic profile indicates u = 0 at Flesch and Wilson (1999a, 1999b; Wilson and d + z0 (for example, Monteith and Unsworth, 1990). Flesch, 1999) investigated the processes contrib- Values for d/h and z0/h for various canopies of Pinus uting to shelter of remnant spruce in experimental species are presented by Lopez (1989): d/h ranges cutover strips adjacent to natural aspen–spruce between 0.67 and 0.92, such values being typical for boreal forest in northern Alberta, Canada. They many closed forests; z0/h ranges between 0.02 and compared mean wind speeds and turbulent 0.92 (the latter representing a smooth bare surface). kinetic energy (TKE) affecting “tree sway” along

The friction velocity, u*, is related to the frictional transects perpendicular to the edge of the unhar- force due to air flow over the surface of the canopy, vested forest. At half canopy height (that is, of as affected by roughness and air stability, the latter the unharvested trees, 0.5 h), the best shelter being a function of vertical temperature gradients. was provided nearest the windward edge, with 80 per cent reduction in average TKE and 90 per In general, daytime surface heating creates unstable cent reduction in average velocity (u). Wind conditions and hence upward movement of warmer speeds increased gently with downwind distance, air; conversely, night-time cooling creates a layer of but TKE increased rapidly, attaining near- colder, stable air closest to the surface. This daily constancy at about 3 h, with a value slightly cycle then contributes to variations of wind speed greater than that of unimpeded air flow. In a and turbulence within the canopy, as well as to second study, Flesch and Wilson (1999b) found diurnal changes in the height of the planetary that the interaction of tree movement and local boundary layer (for example, Oke, 1987). turbulence caused “resonant sway” 10–35 per cent greater than the displacement due to instan- Thermal stability effects are generally unimportant taneous wind force alone. Tree sway was well in forest canopies at moderate to high wind speeds, correlated with the standard deviation of the although Onyewotu et al. (2004) found that wind force, σu|u|. It was found that the wind instability reduces the protection from hot air velocity in the open needed to cause uprooting provided by shelterbelts. At low wind speeds, and varied from 30 m s–1 at the upwind edge in a particularly in more open canopies where significant narrow (1.7 h wide) cutover to only 13 m s–1 near surface heating can occur, vertical convection the downwind forest edge in a wider (6.1 h) area. contributes to turbulence, which interacts with air The best shelter was obtained within 3 h of the movement above the canopy to produce complex upwind protective forest, leading to a recom- effects on mass and energy exchanges with the mendation that cutover areas be less than three atmosphere. Interestingly, some recent research by tree heights wide to provide useful shelter at Zhu et al. (2003) has revealed a strong correlation heights below 0.5 h. 11–8 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Also in Alberta, Rudnicki et al. (2001, 2003) observed observations and experimental variation of the over 60 tree collisions per minute in a lodgepole photoperiod, it is hypothesized that seasonal pine stand, at a mean wind speed of 4.5 m s–1 (with development and endo-dormancy of vegetative gusts to 10 m s–1), noting that the “collision over- buds in stem succulents are controlled by the lap” amounted to about 25 per cent of stand area. photoperiod. These collisions inhibit lateral shoot growth and hence influence crown asymmetry and “shyness” Photoperiodic control of growth and development (the tendency to avoid crown interlocking), and of cool and temperate forest tree species may limit contribute to the formation of canopy gaps. It was their north–south movement. There is little or no also established that slender trees have proportion- evidence of photoperiodic control of flowering ately greater sway distances, causing greater collision among those species, however (Fowells and Means, overlaps, an effect exacerbated by thinning. James 1990). et al. (2006), investigating safety of urban trees in Australia, measured dynamic wind loads on a range Dormancy of fruit trees and vines is sometimes of species (with different crown shapes and branch- initiated by decreasing photoperiod (Gur, 1985; ing habits), including Eucalyptus grandis and E. Wake and Fennell, 2000). The photoperiodic teretecornus, a palm (Washingtonia robusta), a slender response of deciduous fruit trees of the Rosaceae Italian cypress (Cupressus sempervirens) and hoop family varies even within the same species (Gur, pine (Araucaria cunninghamii). Using a model devel- 1985). For example, apples and pears are insensitive oped from their observations, they concluded that to photoperiod (Heide and Prestrud, 2005). branch mass generally damps excessive stem sway, and hence increases mechanical stability of indi- 11.2.2 Pests and diseases in relation to vidual trees. weather This section considers disease agents, pest insects 11.2.1.5 Photoperiod and weeds. These factors can directly threaten a tree’s Photoperiod is for most forest tree species from the structural integrity, water and food (photosynthate) cool and temperate regions a key factor affecting transport systems, above- and below-ground growth, the induction of dormancy, the abscission of leaves food production and storage (for instance, seeds) and the cessation of cambial activity (Koski and and wood and fibre quality. Variation in moisture, Selkäinaho, 1982; Koski and Sievänen, 1985). A temperature, radiation and wind, on both short number of angiosperms and gymnosperms cease (weather) and long (climate) timescales often have growth when exposed to short photoperiods, and critical influences on the tree damage and mortality long days extend the growing period. Under these caused by pests and diseases. Weather affects the conditions, for example, the shoots of some species build-up of many pests and disease agents by deter- of Pinus, red maple (Acer rubrum), birch (Betula) and mining the rates at which their populations grow elm (Ulmus) grow continuously. Even though long and spread (Harrington et al., 2001), and it provides photoperiods are maintained continuously, some opportunity for many pests and diseases when it species of Pinus and Quercus, however, stop growing stresses susceptible host trees (for example, during and form terminal buds, which produce leaves after drought). a period of inactivity (Downs and Borthwick, 1956; Borthwick, 1957). Campbell and Sugano (1975) and Disease agents can be infectious (for example, fungi, Nizinski and Saugier (1988) confirmed that longer bacteria, viruses, nematodes and parasitic plants) or photoperiods accelerate development of Pseudotsuga non-infectious (for example, pollution). Section and Quercus, respectively. 11.2.3 covers the direct effects of extreme weather that can also produce disease (for example, endur- Rivera and Borchert (2001), based on indirect ing moisture deficits are key contributing causes of evidence, attributed the induction of flowering of diebacks and declines). Disease symptoms almost deciduous trees, in a semi-deciduous tropical always involve necrosis (dead tree tissue), or growth forest, to the rapid decline in photoperiod of that is either excessive (hypertrophy, for instance, 30 min or less. Borchert and Rivera (2001) observed galls) or inadequate (atrophy, for instance, chloro- that bud break of vegetative buds of tropical stem- sis). Sometimes a disease agent associates with an succulent trees was not induced before the spring pest insect and together this association is much equinox, despite their high water status. Highly more successful at attacking trees than either would synchronous bud break regularly occurred soon be on its own (for example, Wikler et al., 2003). after the spring equinox, often weeks before the Bark beetles and the plant pathogenic fungi they first rainfalls of the wet season. Based on these carry are an example (Wermelinger, 2004). CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–9

Pest insects can harm trees directly by consuming trees, increasing their risk of mortality (for exam- their foliage, roots, seeds or cambial material, and ple, from starvation or predation). In addition, indirectly by transporting disease organisms prolonged episodes of high humidity and wet (Speight and Wainhouse, 1989). Besides the variety weather are ideal for the increase and spread of of fungal species transported to susceptible host populations of some natural enemies of insect pests, trees by bark beetles, some bacterial and most viral such as insect pathogenic fungi, for example diseases are also spread by insects. Weather affects (Tainter and Baker, 1996). In winter, heavy rain can the mortality, dispersal and activity of insects and is flood soils, drowning the overwintering stages of thus often a critical influence on their populations’ vulnerable species (for example, larch sawfly). On rates of change. Because of their large spatial extent, the other hand, snow can insulate overwintering weather systems can provide simultaneous “shocks” stages from extreme cold and break conifer branches, to the cycles of widely separated populations of an providing potential breeding sites for bark beetles. insect pest, thus synchronizing these cycles in space Rain is a hazard during many pest control opera- and creating regional outbreaks. tions because it can wash sprayed materials off target vegetation too soon for them to be effective. Weeds come in various forms depending on the This can lead to exposure of non-target organisms, context (Anderson, 1983). In tree nurseries and seed and sometimes (for instance, with herbicides) injury orchards, weeds are typically forbs and grasses. For to the crop trees. On the other hand, high humidity site preparation or rehabilitation, or tree release often facilitates the absorption of herbicides by from competition, many weeds are herbs, shrubs or weeds. weed trees. Weeds are most prevalent as fast grow- ing invaders of recently disturbed sites on which 11.2.2.2 Temperature the trees of the regenerating coniferous forest are less than 10 cm diameter breast height (DBH). Weed Most fungi can survive but cannot grow when species use at least three reproductive strategies to temperatures fall below freezing. Like higher plants colonize these sites quickly (Stewart, 1987): produc- and animals, they grow best at 20°C–30°C. ing large quantities of seed that are easily dispersed Nematodes increase their population growth by by wind or animals; producing durable seeds that completing their generations more quickly as soil remain viable for long periods in the soil or surface temperatures rise (to an optimum of 25°C–30°C for litter; and spreading vegetatively (for instance, from many species). Sufficient snow depth can provide sprouts, suckers or tubers). enough insulation to allow certain diseases to thrive underneath, however, such as snow moulds, for example, (Senn, 1999; Karlman, 2001). 11.2.2.1 Moisture (humidity, dew, rain, snow, sleet) Temperature is the most critical weather variable All fungi need water to grow, but the amount for insect pests (Ayres and Lombardero, 2000). It needed varies widely among species. To avoid dessi- controls all facets of their development and activ- cation, bacteria must associate with host plants or ity. Where summers are short or temperatures tissues during dry periods. relatively low all year, many species cannot complete their development without special adaptations Wind-splashed raindrops are important in spread- (Logan et al., 2003). For instance, the green spruce ing fungal infective stages and the bacteria that aphid can live through the harsh winters of conti- cause forest diseases among plants (Tainter and nental Europe only as an egg, but in Britain’s milder Baker, 1996). Often weeds grow fastest in condi- climate, the insect has abandoned the egg stage. On tions of low moisture stress (Radosevich and the other hand, during exceptionally warm Osteryoung, 1987). summers, insect pests can sometimes produce an extra brood of young or even complete additional Salt compounds are often applied to icy roads full generations (Harrington et al., 2001). during winter in North America. The salt spray generated by passing traffic is particularly injurious Temperature variability is also important for insect to conifers. The surge from tropical storms and survival. For instance, during British winters, which hurricanes can flood large areas with salt water. are mostly mild, the green spruce aphid acclimates Much of this salt is eventually absorbed by roots, to the mild conditions. But this leaves the species causing salt burn, which can lead to mortality. vulnerable to occasional bouts of cold, which can cause much mortality. Many defoliating insects (for During storms, heavy wind and rain can wash small example, spruce budworm) specialize in attacking insects (for example, scales, adelgids and aphids) off particularly nutritious stages of their host tree’s 11–10 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES foliage (Volney and Fleming, 2007). To do this, humidity). Wind and moisture levels are both insect feeding stages must appear when the host important considerations in using prescribed burn- tree’s foliage is in the correct stage. The development ing (11.2.6) for weed control (Walstad et al., 1987). of both the insect and its host tree’s foliage depends Third, windthrown trees are often rapidly invaded on temperature, though usually not in exactly the by stain and decay fungi and secondary insects same way, so unusual temperature patterns in time (for example, ambrosia beetles) that reduce wood can disrupt this synchrony and leave the insects to and fibre quality. starve or consume low-quality foliage (Volney and Fleming, 2000). 11.2.2.5 Selected simulation models There are a huge number of purely research models 11.2.2.3 Radiation (light, day length, on this topic, but they are not discussed here cloudiness, lightning) because this chapter is not directed at researchers. Fungi do not need light to grow, but many need at Instead, the paragraphs below focus on manage- least a little to complete their life cycle. Sudden ment models that may be useful to the forester, exposure of shade-tolerant tree species to full forest manager and non-forest tree growers. Rather sunlight (for instance by thinning or intermediate than a comprehensive coverage of the underlying harvest), especially on poor sites, can cause green research, the references are meant to provide this foliage to fade (chlorosis). Opening a closed canopy audience with initial access to using these models. can also stimulate shade-intolerant weeds (for Even so, because of space limitations, it is possible example, many shrubs), resulting in reduced growth to describe only a few of the many management of the remaining overstorey and site preparation models in existence. difficulties after the final harvest. Sun and wind can make foliage surfaces very dry for the insect pests The Gypsy Moth Decision Support System, GypsES, that feed there. Some (for example, leaf miners, (Gottschalk et al., 1996) is a tool for organizing and sawflies, gall formers) go inside the tree’s tissues for evaluating information to be used in gypsy moth the most vulnerable parts of their life cycle. Drought control, suppression, prevention or eradication often stresses trees, which are then less capable of efforts in North America. It is built around a visual defending themselves (for example, against bark display of information through the Geographic beetles). A lightning strike can leave a tree suscepti- Resources Analysis Support System Geographical ble to insects and infectious disease. For instance, Information System (GRASS GIS) and several simu- lightning strikes are thought to have initiated many lation models. small, localized southern pine beetle infestations. Cloudiness can reduce the advantage that many Models integrated into GypsES include a stand- weeds have in growth rate compared with the forest damage model and a gypsy moth phenology model. trees on the site. In addition, concentrations of The stand-damage model (Colbert and Sheehan, herbicide sprays tend to be higher in leaves when 1995) simulates tree diameter and height growth, light is reduced (Walstad et al., 1987). and tree mortality for each year of a simulation. Users supply information on defoliation history and describe defoliation scenarios for each species 11.2.2.4 Wind each year as a percentage for the overstorey and for Wind plays three key roles in the context of pests the understorey. Each year, the model calculates the and diseases. First, it is critical as a longer-distance diameter growth of trees as a function of relative dispersal agent. Many, if not most, important stocking, shading, heat and defoliation. Weather weeds, insects and infectious disease agents rely at drives photosynthesis and tree growth. A cumulative least partially on wind for transport into favoura- heat unit measure, degree-days above a single ble environments. Wind also disperses pollution threshold (4.4°C), is used for all tree species as a from urban centres to downwind forest areas. In primary driver of diameter growth. Default constant addition, by dispersing aggregation and mating weather data can be overridden by entering weather pheromones, wind provides a medium for chemi- variation for each year simulated. The gypsy moth cal communication of many important insect phenology model, GMPHEN (Sheehan, 1992), pests (for instance, the mountain pine beetle). predicts the timing for gypsy moth and host Wind also causes spray drift, an important envi- development. This model simulates gypsy moth ronmental and efficacy consideration during pest egg hatch, larval and pupal development, and control operations (Stewart, 1987). Second, budbreak and leaf expansion for six eastern through interactions with temperature, wind has hardwoods. GMPHEN reports the percentage of important effects on moisture (such as dew and gypsy moths in each life stage, mean life stage, CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–11 mean per cent leaf expansion, and for each host temperature information and uses these forecasts species, per cent budbreak and leaf expansion. The within temperature-driven simulation models to model uses daily maximum and minimum forecast insect development over the season. BioSIM temperatures to calculate heat accumulation is embedded in a number of modelling systems for measured in degree-days. Built-in 30-year averages managing forest insects, including spruce budworm, can be used for gross estimates of timing of egg gypsy moth and mountain pine beetle. hatch and larval development, or users can input the actual temperature data up to the current date The Weed Invasion Susceptibility Predictor, or WISP and then run the model to simulate into the (Gillham et al., 2004), was developed to forecast the future. potential risk of invasion by individual weed species in rangelands. This risk is estimated by comparing CLIMEX is a dynamic simulation model that enables the growth requirements of each weed species with researchers to estimate the potential geographical respect to nine site characteristics obtained from distribution of a species, plant (for instance weeds) geographic data layers: distance from water and or cold-blooded animal (for instance insects), by disturbance sources, elevation, annual precipita- using climatic parameters inferred from an observed tion, soil texture and pH, aspect, slope and land distribution (Sutherst and Maywald, 1985). Using cover. WISP has some applicability to certain climate information and knowledge about the biol- orchards and forest plantations. ogy and distribution of a particular species in its original habitat, CLIMEX enables an assessment of Landscape Vulnerability to Forest Insect and the risks posed by the introduction of that species Pathogens is a system developed by Hessburg et al. in a new habitat and can be used to forecast loca- (1999) for assessing landscape vulnerability to tions to which the species could spread (Sutherst et defoliator, bark beetle, dwarf mistletoe, root al., 2000). CLIMEX can also be used to identify disease, blister rust and stem decay in the Columbia possible collection and release sites for biological River basin. Factors affecting patch vulnerability control agents. in this system include site quality, host abundance, canopy layers, host age or size, patch vigour, patch CLIMEX has a built-in database of records from (stand) density, connectivity of host patches, topo- about 2 400 meteorological stations worldwide. It graphic setting and visible evidence of logging. needs monthly long-term average maximum and This approach to assessing landscape vulnerability minimum temperatures, rainfall and relative could potentially be adapted in other landscape or humidity. It allows the user to edit lists of stations watershed analyses to evaluate or monitor change into subsets, and add new data for specific locations in the magnitude and spatial pattern of vegetation of interest (Sutherst et al., 1999). CLIMEX uses vulnerability to insects and pathogens, and in minimal datasets and simple functions to describe planning to compare potential futures associated the species’ response to temperature and moisture with alternative vegetation management (Maywald and Sutherst, 1989). For each species of scenarios. interest, the year is split into a favourable and an unfavourable season. A growth index describes the Site quality was used as a vulnerability factor potential for population growth during the favour- because hosts on poorer sites are often more vulner- able season, and four stress indices (cold, hot, wet able to a particular pathogen or insect than those and dry) describe the probability of the population on more productive sites. By frequently distinguish- surviving through the unfavourable season. ing cool-moist sites from warm-dry sites, the Combined, the growth and stress indices provide integrated effects of climate are implicitly included an overall indication of the favourableness of the in site quality. For instance, cool-moist sites are location or year for the species of interest. Results modelled as being generally more vulnerable than can be presented as tables, graphs or maps. warm-dry sites to root disease and the stem decay known as rust-red stringy rot. BioSIM (Régnière et al., 1995) is a software tool for use in forecasting events in the seasonal biology of The situation is modelled as more complex for insect pests. Forecasts are made by simulation rusts, mistletoes and insects. In the model, vulner- models provided by the system and are based on ability to white pine blister rust is often different regional air temperature and precipitation on cool-moist and warm-dry sites, but the host interpolated from nearby weather stations, adjusted species determines on which type of sites the for elevation and location differentials with regional greater vulnerability exists. Douglas-fir and west- gradients. BioSIM produces geographically specific ern dwarf mistletoes are modelled as greater temperature forecasts using historical and real-time hazards on warm-dry sites than on cool-moist 11–12 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES sites. The opposite holds for western larch mistle- Solar irradiance is a key variable. For example, toe. Areas most vulnerable to insect defoliation beetles observed developing in a sun-exposed tree are characterized in the model by low annual situated at the forest edge at an elevation of precipitation, droughty growing season condi- 1 000 m were able to complete two generations tions, cold winters and cool spring and fall successfully, with offspring emerging up until temperature regimes. The areas least vulnerable August. Nearby in a shaded tree, offspring reached to insect defoliation are characterized by higher only the larval stage of the second generation annual precipitation, mild winter temperatures within the same period. and warmer spring and fall temperature regimes. Bark beetle outbreaks are associated in the model Many universities with agricultural programmes with large winds, fire, extended drought periods maintain Websites with integrated pest manage- or defoliation events. In endemic populations, ment (IPM) information, including a large number each bark beetle species attacks low-vigour, of integrated tools and models that have been diseased, weakened or injured trees and recent developed to assist non-forest-tree growers with windthrown or collapsed trees. In outbreaks, IPM activities (for example, http://ipm.ucdavis.edu; vigorous hosts are mass-attacked and killed, occa- http://fruit.wsu.edu/; http://pnwpest.org/). sionally across large areas. In pine-dominated patches, stressed trees are commonly associated Within the scope of the modelling, GIS is used for with high‑density growing conditions, droughty data processing and visualization. The output is growing seasons or protracted droughts. In succes- meant to aid in monitoring, retrospective analysis sionally advanced patches comprised of and prognosis of brood development at any site. shade-tolerant species, an abundance of beetle- vulnerable stressed trees can be maintained in the 11.2.3 Weather hazards to forest and model by root pathogens, dwarf mistletoes, non-forest trees drought and overstocking. 11.2.3.1 Snow and ice The Phenology and populatIoN SIMulator, or INSIM (Mols and Diederik, 1996), is a simulation environ- Snowfall and heavy ice storms damage trees prin- ment for developing pest-forecasting models of the cipally by causing branches to break or bend from phenology and population development of an the extra weight of snow/ice on the tree structure. insect species. INSIM is menu-driven and generates Trees bent more than 60 per cent generally do not age-structured models to calculate the number and recover sufficiently to be retained as crop trees, development of insects. A simple phenological or but they often remain alive for many years population model needs information on the life (Brewer and Linnartz, 1973). Furthermore, with cycle, development rate and standard deviation of the extra weight of snow or ice, high winds may each insect stage, sex ratio, life expectancy of the also cause significant windthrow in stands of adult and age-dependent reproduction. The required trees. For tree nurseries, broken or bent branches weather inputs are the minimum and maximum may result in misshapen trees as they develop. daily temperature. The output of the chosen varia- Freezing and thawing processes may also fracture bles (relative or absolute numbers of each stage and trees (bark splitting) and damage roots through temperature sums) can be presented graphically or soil heaving, which pushes shallow roots to the numerically. User-supplied programming in soil surface, exposing them to cold and QuickBASIC allows the simulation of predator–prey desiccation. interactions. While trees may survive this process, they are The Monitoring and Risk Assessment of the Spruce potentially more prone to infection and disease Bark Beetle methodology was developed by Netherer afterwards. Indirect forest stand damage may occur et al. (2003), who used a modelling approach to from soil acidification following spring snowmelt. describe the development of the spruce bark beetle, In upland forest plantations, especially on acidic Ips typographus. This approach combines topocli- bedrock or where a prolonged and heavy winter matic aspects of the terrain with the insect’s snowfall has occurred, spring snowmelt from the ecophysiological characteristics. By correlating air snowpack will release 50–80 per cent of ions in the temperature and solar irradiation measured at a initial 30 per cent of meltwater (Johannessen and reference station, along with topographic data and Henriksen, 1978). If winter snowpacks are acidified, microclimatic conditions of terrain plots, topocli- soils can become flooded with protons, causing an matic models of a given research area are acid pulse into soil, which may not only damage established. roots, but may also release toxic amounts of CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–13 aluminium and manganese for uptake by root inversions develop. Under these circumstances, systems, resulting in permanent damage to frost hazard may be a significant recurring problem commercial forestry. that requires particular attention from forest managers. 11.2.3.2 Temperature extremes In mountainous terrain, when synoptic conditions Compared with neighbouring treeless areas, forests are favourable, forestry can be subject to distinctive reduce diurnal amplitude of air temperature winds blowing down the lee slopes of mountain through modification, by tree canopy, of the ranges – called fall winds – of which the foehn, amount and penetration of solar radiation to the chinook and bora winds are the most well known. ground (Ní Dhubháin and Gardiner, 2004). This These winds have a considerable effect on tempera- effect usually helps buffer trees from extreme tures. In simple terms, the foehn wind is defined temperatures. Such regulation of air temperature with reference to a downslope wind that causes by forests is reduced considerably, however, when temperatures to rise (and relative humidity to fall) the canopy is opened either through clear-felling on the lee side of a mountain, whereas the corre- or leaf fall of deciduous trees, or from planting of sponding bora causes temperatures to fall. The young seedling trees. Windy nights also reduce seasonal but rapid changes in temperature associ- this effect by air mixing, and specific geographical ated with these winds can have considerable locations (such as latitude or mountainous/hilly desiccating effects on vegetation and soil moisture. terrain) and seasonal factors will inevitably expose In the case of the chinook wind, desiccation can forests to temperature extremes. Extreme tempera- extend approximately 50 km from the foothills of ture conditions are of concern to forest managers the Rocky Mountains (Riehl, 1971). and silviculture, as for example, spring or autumn frosts may be sufficient to cause significant damage 11.2.3.3 Windthrow to young plantations. Significant effort has been invested in trying to While extreme high temperatures can, under certain understand causes of wind damage, particularly in circumstances, help generate dry conditions for Northern Europe, where storm damage (uprooting forest fire ignition (such as drought conditions), the and stem breakage) is frequent. There appears to particular weather parameters that appear to have have been limited success in applying the knowl- the greatest influence on the degree of fire risk are edge gained to reduce impacts. precipitation and relative humidity. It is common practice now for forest services to report indices Windthrow refers to stem breakage or tree uproot- relating fire danger to weather conditions (see ing caused by wind. Windthrow involves complex 11.5.6). Prolonged high temperatures in conjunc- interactions among tree and stand characteristics, tion with reduced precipitation will also lead to site conditions, topography and storm conditions water and nutrient stress on trees by reducing water (wind speed, duration and gustiness) (Mayer, 1989). availability and causing desiccation of the tree Regional wind climates also vary greatly; coastal structure. regions, those in storm tracks, either for the passage of major depressions or subject to thunderstorms By contrast, extreme low temperatures can lead to and tornados, and mountainous regions are often frost, which can damage trees, especially young subject to damaging wind speeds. Locally, topo- trees and saplings or new growth. Two different graphic conditions can funnel winds, creating high types of frost may form depending upon the wind speeds on upper mountain slopes and saddles, meteorological conditions: advective frost and in converging valleys, and adjacent to landform radiation frost. Advective frosts are associated with discontinuities, including forest edges. Most cold air currents and may cause damage, especially windthrow is caused by turbulent gusts that are to young saplings or new growth (Day and Peace, much stronger than the mean wind speed. 1946). At most locations, however, radiation frosts are more common and occur on calm-clear nights. Soil conditions are important for tree anchorage, Heat is lost from soil and vegetation rapidly by both in terms of root strength and the mass of soil radiation, which escapes through the atmosphere, adhering to the root plate. Shallow, impervious, thus cooling the soil surface. Radiation frosts can anaerobic, stony or infertile soils can restrict root be damaging to plantations during spring and development, increasing windthrow susceptibility. autumn (Ní Dhubháin and Gardiner, 2004). Also, wetter soils provide less shear strength than Furthermore, in undulating terrain, cooled air can drier soils, so storm precipitation and wind are a pool as a result of poor air drainage, and temperature factor. 11–14 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Wind firmness generally decreases with tree height rainstorms, substantial spring snowmelt, or both. and root or stem decay, and increases with stem taper While no clear pattern of changes in flooding has and root development. Trees in exposed places physi- emerged as a result of forestry (for example, ologically adapt to wind, developing shorter, thicker, Robinson, 1998), rainfall runoff is modified to an more tapered stems. Greatest windthrow often occurs extent through higher infiltration and forest when trees growing in sheltered locations are suddenly interception losses. Flood events, depending upon exposed to wind. Tree species also vary in windthrow the magnitude, can produce destructive effects on susceptibility depending on size, crown structure, tree stands, as flood currents may be sufficient to rooting habit and foliar characteristics (for example, topple trees. In addition, flood currents, waves and deciduous as compared to evergreen). suspended particulate matter may cause significant quantities of soil around the base of trees to be Stand characteristics affect windthrow by influenc- washed away. Such secondary impacts from flood ing the degree to which wind penetrates the canopy, scouring include exposed root systems, which can the mutual support of bending stems, the height and lead not only to tree stress, but can also make trees roughness of the canopy (which generates turbu- more vulnerable to windthrow. By contrast, flood lence) and species composition. Dense, uniform sedimentation from deposited silt or sand may seal stands, while composed of trees with little stem taper or smother tree roots and limit oxygen supply to and limited root development, provide considerable root systems. Further secondary impacts from wind protection through mutual stem support and flooding may include a period of waterlogging aerodynamically smooth canopies. Windthrow (although this may occur without a flood event). In susceptibility is also affected by the proximity, size, waterlogged ground, oxygen deficiency to root shape and structural characteristics of adjoining systems from poor soil aeration is likely the most stands and by landscape heterogeneity. important environmental factor that triggers growth inhibition and injury in flooded trees (Smith In some regions, windthrow hazard classifications et al., 2001). Waterlogged soil will also alter soil pH, have been used to assess windthrow potential and rates of organic decomposition and supply of guide forest management. The United Kingdom clas- nutrients, which can damage root systems and sification combines site windiness (wind zone, affect tree development. elevation, topographic exposure and aspect) and tree anchorage (soil type) to define hazard class, and 11.2.3.5 Other biophysical controls affecting relates this to tree height (Quine and White, 1993). forest growth Mathematical risk assessment models for windthrow, based on bending and resistive moments, have also The constraints on forest and non-forest tree growth been developed (Gardiner et al., 2000) and applied and productivity imposed by dominant meteoro- (for example, Achim et al. 2005). Pellikka and logical factors have been discussed above. There are Järvenpää (2003) and Zhu et al. (2006) found vary- numerous other biophysically regulated environ- ing sensitivities among species to snow and wind mental factors that directly or indirectly affect a damage in Finland and north-eastern China, respec- forest’s status and they are briefly highlighted in tively. Zeng et al. (2004), working in Finland, this section. They include forest fires, air pollution combined a mechanistic wind damage model and and soil effects. an airflow model with forest databases containing information at the tree, stand and regional levels. 11.2.3.5.1 Forest fires They found that newly exposed edges were particu- larly vulnerable to increased wind if the stand was Forest fire can be a dominant factor that has a detri- harvested at minimum allowable rotation age or mental or rejuvenating effect on the forest status in basal area. The risk of damage was actually most northern boreal and tropical forests, in varying increased for older stands, however, because these degrees. Pyne et al. (1996) define fires as those tended to be exposed when younger stands were ignited by natural causes, such as lightning, or harvested. Finally, handbooks for mitigating unintentionally by human actions. On the other windthrow damage have been published by several hand, prescribed burning refers to those fires that jurisdictions (for example, Stathers et al., 1994; are intentionally created to burn a particular forest Navratil, 1995; Quine et al., 1995). area in order to achieve predetermined objectives (Weber and Taylor, 1992), which will be discussed in detail in 11.2.6. Studies reveal that both frequency 11.2.3.4 Flooding of fires and the total area burned in the boreal forest The frequency of floods is related, but not identical have increased over the last 20 to 40 years. In 1994, to, the frequency and return period of major Canada lost 4 million hectares of forests due to fires. CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–15

Average annual property losses in Canada from will enhance evaporation of the moisture on forest fires between 1990 and 2000 are estimated to materials such as dead wood, fallen needles, leaves have exceeded $7 million, while fire protection and litter (Mitchell, 1990). Tree mortality or dead costs averaged over $400 million per year (Canadian tops resulting from insect attack determine the Forest Service, 2001). Several reviews highlight availability of fuels on the soil surface (such as dead specific mechanisms and effects mediated by fires wood and vegetation on the ground) and ladder affecting forestry (for example, Viereck, 1973; fuels (vertically distributed dead wood). These Heinselman, 1981; Weber and Taylor, 1992; Pyne factors play a large role in determining the risk of et al., 1996). fire ignition, behaviour and intensity. The monitoring and management of forest fires by Ecological and environmental effects of forest fires micrometeorologists warrant the adoption of are highly variable, difficult to predict and influ- powerful remote-sensing techniques. Advantages enced by fire behaviour, vegetation type, topography, including large synoptic coverage, medium to high climate, pre- and post-burn weather and other temporal and spatial resolution, monitoring of factors (Weber and Taylor, 1992; McCullogh, 1998). inaccessible burning areas and low costs enable Fires can be classified by their behaviour and inten- remote-sensing to be effectively used for the precise sity. Surface fires burn through material like litter, mapping of forest fire boundaries and for shrubs, dead wood and the like on the soil surface. understanding the fire regimes and post-fire plant Crown fires are invariably ignited by surface fires regeneration ratios (Díaz-Delgado et al., 2002). and burn through the crowns of standing trees. Ground fires burn in subsurface organic fuels such 11.2.3.5.2 Air pollution as duff layers under Arctic tundra or taiga or in organic soils of swamps and bogs (McCullogh, Asher (1956) observed unexplained foliar symp- 1998). Forest fuels directly influence fire intensity toms on ponderosa pine, which was then described (for instance, production of heat per unit area) as “x-disease”. The field experiment discussed by through fuel accumulation (or fuel load), distribu- Miller et al. (1963) and the ozone fumigation exper- tion and moisture content characteristics. Fuel iments of Richards et al. (1968) confirmed that includes wood such as dead trees, logs and slashes ozone was the cause of the chlorotic mottle and (tree tops, branches and other logging debris). Fine early abscission of affected needles and demon- fuels include dead needles, leaves and litter. In areas strated the relationship between urban smog with a high accumulation of fuels, fires may burn containing high levels of ozone and the disease. hotter, move more slowly and have more profound ecological effects than in areas with low fuel Air pollutants could be speculated to have an impor- accumulation. tant role in declining tree health and forest status. In a study conducted in Europe by Muller-Edzardz Distribution and extent of fuels, wind, aspect (direc- et al. (1997), one quarter of the coniferous trees tion of slope orientation), topography and other assessed were damaged (20 per cent defoliation) factors interact and affect fire intensity and behav- and damage was worst in central Europe where the iour, typically creating different types of post-fire probability of air pollution is the highest, although conditions. Though studies to understand the post- crown condition has improved in regions of eastern fire vegetation growth have been attempted, very Europe where atmospheric SO2 concentrations have little has been done to understand the canopy been reduced significantly. Severe deterioration in temperatures and vegetation stress after the occur- the crown condition of broadleaved trees has also rence of fires. Interactions of fire and insects can been observed. Skarby et al. (1998) speculate that delay or redirect forest succession and can have ozone might play an important role in the deterio- significant consequences for forest productivity and rating foliar status of trees in Europe. A feature of biological diversity. Fires can affect insects by kill- atmospheric ozone is that as soon as it is deposited ing them directly or by altering soil properties, on a surface, it disappears, causing the oxidation of overstorey or understorey vegetation, tree density other chemical compounds. or other aspects of their habitat (Mitchell, 1990; McCullough, 1998). Other studies include physiological responses (Grulke, 1999), deposition of multiple pollutants to Pest outbreaks can also dramatically affect the forest canopies (Bytnerowicz et al., 1999), nitrogen likelihood and severity of forest fires. This could be saturation, stream water nitrate export trends (Fenn explained by the formation of dead wood, litter and and Poth, 1999) and biochemical changes (Tausz et debris as a result of plant damage caused by al., 2000). Most of this work was summarized in the enhanced pest infestation in forests. Solar radiation report Oxidant Air Pollution Impacts in the Montane 11–16 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Forests of Southern California: A Case Study of the San strong need to raise tree seedlings in nurseries Bernardino Mountains (Miller and McBride, 1999). because: (a) newly raised seedlings from direct Work since then has begun to examine the effects sowing of most tree species fail to establish or with- of multiple pollutants on carbon allocation and stand field competition (winds, sun scorching, sequestration (Arbaugh et al., 1999; Grulke et al., insect pests, soil conditions, diseases, fire, and so 1998). These studies indicate that ozone and nitro- on); (b) seedlings of introduced species are not gen may cause a shift in pine tree foliar biomass adapted to new sites and must first be raised in allocation towards that of deciduous trees (Grulke nurseries; and (c) economic losses may occur if and Balduman, 1999) and acceleration of litter there is failure of forest establishment by direct accumulation (Arbaugh et al., 1999; Takemoto et sowing in the field. al., 2001). At present nurseries are easy to establish because of the availability of technological aids; they are 11.2.3.5.3 Soil effects widely distributed because of the ever-increasing Landslides and soil erosion are serious challenges demand for tree seedlings for urban uses (private for forest management in areas with steep slopes, and public) and for special types of plantations (for unstable soils and high rainfall. A landslide is the example, for planting on road and canal sites, for movement of a mass of rock, debris or earth down sand dune fixation). Traditionally, forest nurseries a slope (Cruden et al., 1991). Landslides are a funda- were divided into temporary, permanent and exten- mental concern for forest development planning sion or educational nurseries (FAO, 1955, 1959; and operations in mountainous terrain (Wise et al., Evans, 1982). Temporary nurseries with a lifespan 2004). This is primarily a function of topography, of less than five years were established for specific soil type and soil water content. Landslides may be planting programmes in the field and did not need viewed as a biophysical phenomenon because of sophisticated installations; permanent nurseries the strong coupling induced by soil hydrology and concentrate efforts (capital, labour and technolo- soil physical properties mediated through changes gies) in one area for bulk production of seedlings in precipitation patterns. Most of the time, however, and efficient management. landslides adversely affect social, environmental and economic values in mountainous forestry or 11.2.4.2 Location, design and equipment agroforestry systems and therefore can be a limiting factor. This concern relates mainly to the potential Many points have to be considered when planning effect of landslides on elements such as forest to establish a nursery (FAO, 1955, 1959; Evans, resources (for instance, water quality), infrastruc- 1982; Landis et al., 1999). The nursery must be ture (for instance, buildings and transportation and placed in an accessible location, preferably in or utility corridors) and people (Wise et al., 2004). near the plantation area. The ground must be flat Forest development involving forest roads and with a gentle slope of about 3° to guarantee free trails, as well as the harvesting of hillslope areas, drainage, both vertically into the ground and on can significantly contribute to the occurrence of the surface. In hilly or hummocky areas, the land landslides. Soil erosion in humid regions, especially should be freed from stones and levelled off by in tropical pristine ecosystems or agroecosystems, constructing terraces. The area must be oriented in could affect forest growth and tree health. It could an east–west direction to allow exposure to maxi- remove the surface soil, leaving surface roots mum radiation; mid-sections of slopes are the most exposed, which decreases the tree anchorage and suitable for nurseries in hilly areas, while summits increases the susceptibility of trees to windthrow and deep valleys are to be avoided for fear of strong and other types of natural hazards. desiccating winds and permanent shading, respec- tively (Evans, 1982). Areas prone to frost are also to 11.2.4 Tree nursery location and be excluded. Where naked-rooted seedlings (coni- operation fers mostly) are raised, the soil must be fertile and free of weeds, pests and diseases; fertilizers and products to kill these agents may be used. 11.2.4.1 Introduction A forest nursery is an area of earth or plot designed The shape of the nursery should be quadrilateral, and prepared to raise and produce various kinds of preferably rectangular or square. It should be tree seedlings using many methods, with a view to spacious, particularly if it is a permanent one, to readying them for planting out in the field. The accommodate many installations, such as seedbeds, goal is to produce the largest possible number of stores, offices, irrigation devices and systems, good-quality seedlings in a limited area. There is a reserve yards and space for the manoeuvring and CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–17 stationing of vehicles and equipment. Thorough be detrimental to seedlings. At present, however, protection of a nursery enclosure may be provided there are appropriate technological means to by an appropriate fencing system (barbed wire, destroy such damaging agents. wood or thorn, a live hedge, and so forth). Nursery beds may be rectangular, with an east–west 11.2.4.3 Operations and management orientation, between 1.2 m and 1.5 m wide, and of any convenient length (for example, 5 m); they One of the basic tasks in nursery management is to should be separated by pathways to permit easy deal with seed stocks, including their procurement, movement of personnel and equipment. In dry handling, treatment, viability testing and storage. areas, the beds are covered by wire or wooden Many seeds need treatment (by soaking in cold and thatching works to provide partial shading to hot water, acid corrosion, mechanical scratching) seedlings in order to mitigate excessive heating to break seed coat dormancy, or some may need to and drying conditions. be stored for a period until complete maturation. Thus, there ought to be adequate installations to Many types of containers of different materials accommodate seed-handling activities. (such as ceramic, earth, wood, plastic, tin, card- board) and of various sizes and shapes are commonly Bare-rooted seedlings are raised in beds filled with used in nurseries to contain seedlings (Landis et al., soil, or in adjacent yards, and kept there until they 1999). Adoption of a particular type of container are transplanted. Seeds of most broadleaved tree depends on the context in which the containers are species are sown in beds, trays or directly in contain- routinely employed, because there are advantages ers. Large seeds are inserted not very deep in the and disadvantages to using various types that are growing media and covered. Small seeds (such as related to resistance to handling in the nursery and Eucalyptus sp., Canocarpus sp., Casuarina sp.) are during transport to the field, durability, and suita- thinly scattered on the growing medium and lightly bility for producing high-quality seedlings (proper covered by the medium or fine sand. This is done to shoot/root ratio, undistorted root system). Porosity avoid washing out of the seeds by irrigation water; of containers is important to allow free drainage of in such cases watering may be provided by capillary excess irrigation water and to avoid root asphyxia- ascension. When the seedlings attain appropriate tion; as a result, some containers are made of sizes, after two weeks or a month (depending on pervious materials. Impervious containers are the species), they may be transplanted or placed usually perforated to permit evacuation of excess individually in other containers, leaving one seed- water. Use of polyethylene tubes is becoming more ling per container and keeping it there until final popular, especially in dry areas, because they are delivery. light, easy to handle, durable and can retain mois- ture for long periods. Their main disadvantage, as Vegetative propagation (by cuttings, layering, with many containers, is that the thinner ones are budding, suckers) is common for tree species that pierced by roots and then need regular lifting to cut do not produce seeds or are difficult to propagate by extruding roots; thicker containers may cause coil- seeds (such as Ficus sp., Euphorbia sp.), or in order to ing of the root system. produce clones. Reliable water sources and irriga- tion systems are indispensable in any nursery. Growing media used to fill the containers are of a Permanent modern nurseries are equipped with wide variety of materials, including soils, peat, sophisticated irrigation systems, including over- or compost, sawdust, and so on. It is preferable that under-plant sprinklers or microsprinklers, surface the material selected be of good porosity (high irrigation and drip irrigation. In dry areas, it is better water retention, but allowing good aeration), light to irrigate the young seedlings with abundant water enough, fertile and free of diseases, pests and weeds several times a day; in the later stages of the life of (FAO, 1955, 1959; Landis et al., 1999). Sand and silt the seedlings, frequency of irrigation may be are the best growing media, but may need to be reduced. replenished with nutrients if seedlings will stay for a year or more in the nursery or if exigent tree Weeding is done routinely in nurseries. It is best species are raised. Clay, salty and contaminated done by hand, because herbicides are not recom- soils are not to be used as growing media. Organic mended in most cases, as the substances they materials should have the required characteristics contain may harm the seedlings, especially those of of porosity, water retention, lightness and rate of broadleaved species. Roots extruding out of the nutrient release through progressive decomposition. containers may be cut using scissors, after lifting up The major fear related to their use is the possibility the seedlings. Large, modern nurseries are equipped that they may harbour pests and diseases that would with underwire or vertical blade devices, which can 11–18 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES carry out root cutting mechanically. Before trans- harvesting operations may be difficult if soils are planting or delivery, seedlings are subjected to an too wet to sustain heavy logging machinery. operation termed hardening; this is done to make Moreover, under wet weather conditions, in order seedlings sturdy enough to withstand field condi- to avoid soil erosion and compaction and the tions in the future. Seedlings are moved out of the impact of landslides, a set of good practices should shade progressively into open, sunny yards and left be implemented. On wet sites and soils prone to to lose some of their humidity, but not to the wilt- compaction, lightweight harvesting equipment ing point. For some species (for example, Terminalia that exerts low ground pressure should be used sp., Khaya senegalensis, Tectona gandis), the tips of and/or the number of skid trails should be mini- the growing shoots are cut to allow better develop- mized; operations should be conducted preferably ment of the root system. in dry weather or when the ground is frozen.

In well-organized nurseries, records should be kept When fire danger is unusually high, fire restrictions not only for personnel purposes but also for all the and closures are declared by the agencies that have input and output items and activities. Efforts should jurisdiction. Shutting down of logging, clearing and be made to estimate the cost of all operations and some other forest operations is usually among the of the seedlings that are the product of the nursery restrictions that are enforced for high and extreme operations. danger ratings. In some countries, the danger class value for regulated forest operations must be derived from weather data representative of the site on 11.2.5 Applications of meteorology and which operations are being conducted. climatology for forestry and non- forest tree operations Stems and trunks of trees exposed to moderate and Climate and weather influence the planning, estab- persistent wind become deformed, and hurricane lishment, tending, harvesting and regeneration of force winds break or uproot trees (see 11.2.3.3). forests. Most operations conducted on non-forest Three steps are required to reduce damage produced trees, including orchards, are also affected by by strong winds: (1) assessment of the risk of wind weather, starting from the time of establishment damage; (2) prediction of the effects of wind on until the end of their productive life. trees; and (3) adoption of measures to increase the resistance of a forest to damage. Risk of wind The survival of a germinated seed or a planted seed- damage is related to regional windiness, elevation, ling depends on the microclimate in its immediate relative exposure of the site (topex), and soil nature vicinity. The forester can exert considerable control and condition as related to root distribution and over this microclimate by such cultural activities as depth. The effects of wind on forest trees depend on scarifying the soil or planting a seedling so that it is wind speed, turbulence and the dynamic response partially shaded by residual vegetation or logging of trees. The bending moment that is created and debris. The type of regeneration cut will affect the applied to the base of the trunk originates mainly microclimate at seedling level. For example, in an from the frictional drag of the tree crown and the area where frost may be a potential hazard after a weights of the crown and trunk. When the bending clear-felling, shelterwood cut may reduce the hazard moment exceeds the maximum resistive bending by diminishing the nocturnal net radiation loss moment of the trunk, it breaks. On soils where the from the ground surface. A discussion of the micro- root depth is small, because the soil is shallow or climate in relation to forest regeneration can be the root growth is restricted, it is more common found in WMO (1978a). that the roots and/or the soil break, thus uprooting the tree. Implementing appropriate practices may Harvesting is highly dependent on weather for its safeguard resistance of forest trees to damage, as efficacy and security and for the maintenance of follows: good soil conservation practices. Hence, weather is (a) Fellings should be arranged so that successive also often identified as the most important cause of adjacent areas proceed against the prevailing unused logging capacity. In order to have real-time, wind, thus avoiding the creation of significant on-site weather information, a forestry manager gaps in the forest that are exposed to the wind needs Internet access to be able to review weather (Matthews, 1991); sites and thereby assess the conditions for felling (b) Large clearings or small scattered coupes in for the period ahead. mature stands should be avoided. Instead, when necessary, narrow coupes should be Suitable soil conditions may be necessary for done at right angles to the direction of the successful harvesting of crop trees; for example, gales (Matthews, 1991); CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–19

(c) Thinning should be confined to the early millet farmers (Onyewotu et al., 2003; Stigter et al., stages of plant development and halt before 2003). Further work by Onyewotu et al. (2004) the critical height of the trees for the particu- found that crop yields may decline significantly if lar site is attained (Matthews, 1991); the shelterbelts are established too far apart, or at (d) Seedlings that are used for regeneration should the incorrect angle relative to prevailing winds. be identified and protected from competition Problems occur particularly when air is very hot, with neighbouring trees to allow their stems because increased turbulence in the unprotected to grow strongly (Matthews, 1991); wake zone (McNaughton, 1988) exacerbates soil (e) When waterlogging is limiting root depth, moisture loss and heat stress on the crops. The and soils are not too shallow or consist of conclusion is that shelterbelts in arid regions must clays with very low hydraulic conductivity, be well planned in consultation with local experts, drainage may be used to allow deeper rooting. including farmers/producers, and properly main- Also, the adoption of measures to control root- tained, if maximum benefits to crop production are rotting fungi may bring interesting results; to be realized. (f) If the wind is funnelled by the forest itself, resulting in the Venturi effect, compact Kainkwa and Stigter (1994) investigated the wind borders in the windward direction should be protection provided by a savanna woodland edge developed, thus shunting the wind up and in northern Tanzania, also showing the influence above the forest. In order to drive the air up of diminishing tree densities due to tree felling. and above, it is best to have trees of increasing Considerable initial wind tunnelling effects were height in the leeward direction (Smith et al., found due to variations in the distribution of tree 1994); biomass, but wind speed was reduced by at least 50 (g) When the funnelling of the wind is caused per cent at distances of 110 m or more from the by the form of the landscape, modifications leading edge. The saturation wind speed was the of the landscape may be undertaken, if the same at 1 m and 2.5 m heights and relatively circumstances allow it. uniform in canopy gaps as large as 50 m, due to the association with wind fields above the trees. Humans have long recognized the value of forest plots and woodlands to provide protection of soil, In some cases, studies show that shelterbelts are crops and animals from wind effects, either in the not necessarily the best solution. For example, lee of relatively closed stands, or, in more open Zhao et al. (2006), working in Inner Mongolia, stands, among the trees themselves. In hot arid found that planting perennial grasses with shrubs climates, protective shelterbelts or higher tree on shallow soils provided better soil protection densities are often essential if successful intercrop- against wind erosion than tree cover, which is ping is to be achieved (Onyewotu et al., 2004). In difficult to establish. Stigter et al. (2002), work- Kenya, tree cover and surrounding hedges prevent ing in Nigeria, suggested that higher densities of mulch from being blown away, thereby allowing scattered trees would be more effective in soil maize/bean crops to be protected from mechanical and crop protection in areas of western Africa damage (Stigter et al., 2003). In Sudan, Mohammed where parkland agroforestry is traditionally et al. (1996) described the use of an irrigated practised. Eucalyptus shelterbelt 12 km long and 300–500 m wide for combating wind-induced sand invasion The influence of weather on non-forest tree opera- into agricultural areas and irrigation canals. Careful tions is also very important and is often similar to wind observations in contrasting seasons with that reported above for forest trees. Since the opposite wind directions showed wind protection economic value of these plantations is usually from wind reduction details near the sand-facing higher, however, extra care and protective measures edge (Stigter et al., 2002). Further work by Al-Amin may be implemented. et al. (2005, 2006) has helped to identify the best species and management requirements needed to Orchard trees are often protected against frost control sand movement in regions prone to damage, using direct or indirect methods. Indirect desertification. methods include site selection and management, plant selection, canopy trees, proper pruning, cool- Rainfed shelterbelts of Eucalyptus camaldulensis were ing or use of chemicals to delay blooming, plant instrumental in reclaiming desertified land in covers, avoiding soil cultivation in the days preced- northern Nigeria, though better planning, possibly ing a frost event, removing cover crops, irrigation using alternative species or scattered trees, would prior to a frost event, painting trunks with a water- have resulted in greater economic benefits to local based latex white paint, and trunk wraps. Among 11–20 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES the direct methods, the most popular are wind After precipitation has occurred and before fruits machines and the use of sprinklers or surface irriga- are dry, harvest is not recommended. All operations tion on the frost night. All direct methods rely that involve heavy machinery, including fruit heavily on accurate frost forecasts. When there is a harvest, should consider soil conditions to avoid high probability of frost (or hail) damage to fruits, compaction and soil erosion and should not be and these are almost ripe, anticipatory harvest is carried out under wet conditions if soils are adhe- necessary to avoid severe loss of production. This is sive and prone to compaction. often difficult to accomplish on big farms, however (FAO, 2005). Orchard pest management, and hence 11.2.6 Prescribed burning the need for pesticide application, its timing and efficacy, are dependent on temperature, moisture Fire plays an important role in many forest ecosys- and wind (see 11.2.2 and 11.3.2). Frost forecast and tems. The use of controlled fire by forest managers IPM models require the availability of real-time to achieve management outcomes is well estab- weather data. lished. Examples of such uses include preparation of seedbeds, disposal of logging slash, opening of At windy sites, orchards are protected by wind- serotinus cones, removal of fuel hazards and disease breaks or shelterbelts (WMO, 1964). Windbreaks control. The meteorological controls on fire behav- may be inert or comprised of trees of various species. iour for prescribed burning operations are the same Windbreaks are positioned perpendicularly to the as for wildfire. Temperature, wind speed, atmos- wind, with the objective of reducing mechanical pheric moisture and soil moisture are factors that and physiological damage, and thus increasing fruit should be considered prior to setting a controlled production. In general, they provide for a reduction fire. Many fire weather indices have been developed in evaporation and plant transpiration, tempera- to provide fire managers with a guide to how the ture increases during the day, and shelter from cold meteorological variables are interacting and how or hot wind or from particles that are transported they may affect fire behaviour. Forecasts of these by it (for example, sand or salt). Permeable wind- indices can be produced from numerical weather breaks are more effective and allow for a significant prediction models several days in advance. End‑users reduction in wind up to 15 or 20 times their height; should ensure that they are using an index adapted impermeable windbreaks do not offer protection for local conditions and that values for weather- above 10 or 12 times their height and they generate related variables fall with prescribed burning unwanted turbulence in the leeward side. guidelines. Unfavourable effects that may occur include the loss of usable crop area, reduction of solar and net Fires produce smoke in varying quantities, radiation interception by the crop, increased risk of depending upon fuel characteristics, type of frost and dew, and use of nutrients and water by the combustion and the amount of fuel consumed. trees in the windbreak. The smoke may be a local hazard, reducing visibility and interfering with vehicular traffic or Some fruit species (for example, apples, pears, and aircraft operations, or it may be a wider regional citrus and stone fruit) need the application of community hazard. Smoke contains particulates, growth regulators to reduce the number of fruits, and approximately 90 per cent by volume are less in order to obtain bigger, high-quality fruit, and to than 1 µm in diameter. Fine particles less than overcome alternate-year or biennial bearing. 10 µm (PM10), and particularly those smaller than Several different chemicals and combinations are 2.5 μm (PM2.5), are considered potentially used during the bloom or post-bloom period. hazardous to human health. Many countries now Many factors affect the degree of thinning and the have regulatory standards for PM10 particulate effect on return bloom the following spring. The levels and place restrictions upon activities that temperature at the time of application and the result in the emission of particulates into the next days should be above a certain threshold, atmosphere. These restrictions may also apply to which depends upon the chemicals used and the the use of fire for forest management purposes. species and variety involved. High temperatures Smoke contains many chemical compounds, and slow drying conditions enhance the thinning including carbon monoxide (CO) and volatile effect and may result in over-thinning. Care should organic compounds (VOCs) such as formaldehyde, be taken to spray during the appropriate pheno- which may also affect human health. Accordingly, logical phase, and heavy rain or any operation foresters should consider the likely contribution of that washes away the product, within several hours controlled fires to local and regional air pollution after the spray dries, should be avoided (Wertheim, and plan their burning activities to minimize 1998, 2000). potential harmful community impacts. Smoke also CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–21 contains greenhouse gases, including carbon 11.2.7 Implications of climate change for dioxide (CO2) and nitrogen oxides (NOx), the forestry production production of which may have long-term implications for climate and could be subject to Climate change involves increased atmospheric future regulation. CO2 and O3 (ozone) levels, increased temperatures, changes in precipitation patterns and more frequent A general introduction to the role of the atmos- storm events. These changes will affect forest phere in dispersing pollutants is contained in two production directly, interactively and through older WMO publications: Dispersion and Forecasting myriad feedbacks involving ecosystem processes of Air Pollution (WMO-No. 319) and Application of and functions. Doubling of atmospheric CO2 is Meteorology to Atmospheric Pollution Problems expected to increase temperate forest net primary (WMO‑No. 672). Information on the effect of air production (NPP) of developing forest stands by pollutants on plants is contained in Air Pollutants, 20–25 per cent over the short term (Norby et al., Meteorology and Plant Injury (WMO-No. 234) and 2005), but in many ecosystems gains will decrease Review of the Present Knowledge of Plant Injury by Air as soil nutrients become limiting (Hungate et al., Pollution (WMO-No. 431). For its part, the World 2003). Interactions with global change-related Health Organization (WHO) has published air qual- increases in N deposition may be important, but ity guidelines for Europe. These are available online not necessarily beneficial (Bauer et al., 2004). There (http://www.euro.who.int/air/activities/2005022 is less certainty about implications for tropical 2_2) and present health risk assessments for many regions or for larger, mature stands (Korner et al., of the chemicals contained in smoke. 2005). Elevated ozone levels decrease forest produc- tion and may largely offset CO2-induced gains in The development of Web-based fire management some forest regions (King et al., 2005). resources has allowed the wide dissemination of fire- based management strategies and fire weather Global warming is expected to be greatest at higher research. The United States Forest Service has a latitudes, leading to large-scale changes in species searchable list of online publications dealing with composition, plant migration and forest produc- fire-related issues, including prescribed burning tion. Northward movement of boreal species into (http://www.treesearch.fs.fed.us/pubs). The Global the tundra and increased forest cover in the taiga Fire Monitoring Center (GFMC) Website (http:// should increase production, as should extended www.fire.uni-freiburg.de/literature/Fire-Manage growing seasons associated with warmer tempera- ment.htm) contains fire management guidelines for tures in many boreal and northern temperate forests sub-Saharan Africa and temperate, boreal and (Jarvis and Linder, 2000). This increase, however, tropical forests. This site also provides online health will be gradual, and may be limited by soil nutrient guidelines for vegetation fire events and contains and water availability, and by tree migration rates information about fire management programmes. (Starfield and Chapin, 1996; Solomon and Leemans, 1997). In drier continental regions, increased Smoke dispersion forecasts are routinely produced temperatures may induce droughty conditions, in several countries, including the United States decreasing forest production (Loustau et al., 2005) and Australia, providing information about the and encouraging the replacement of closed forest likely path followed by the smoke plume and some with grasslands, savannas or semi-desert in some indication of the expected smoke concentrations places. In other areas, agriculture may supplant (http://capita.wustl.edu/FSAN/BlueskyRAINS.htm; forest production on better soils. http://www.arl.noaa.gov/smoke). A description of the Australian smoke forecasting system, together Large-scale disturbance, including fire, insect and with validating case studies, is available online from pathogen outbreaks, drought, flooding, and wind the Bureau of Meteorology (http://www.bom.gov. and ice storms affect forest production both by au/bmrc/pubs/researchreports/RR117.pdf). damaging existing forests and by altering competi- tive dynamics. Disturbance frequency, type, Most of these smoke forecasts concentrate on intensity, size and duration are strongly affected by regional transport (1–500 km) over periods of less climate change (Dale et al., 2001), and will likely than 36 hours. As smoke particulates may remain have greater effects on overall forest production in suspension for many days, however, plumes may than climatic effects on physiological processes have impacts at locations far removed from the (Thornton et al., 2002). In many cases, climate original fire locations. The widespread haze change is expected to increase disturbance regimes, experienced in South-East Asian countries is a often reducing forest production (Flannigan et al., demonstration of this. 2001). 11–22 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Longer-term forest community response will reflect airflow). Furthermore, the effect of forest stands on tree life spans, dispersal abilities, phenotypic plastic- the terrain roughness is also a decisive determinant in ity, genetic variability, competition and disturbance. the vertical profile of the wind speed. Therefore, to Substantial lags in community response are expected: minimize the effect of forest vegetation on airflow, tree species are usually long-lived, tolerant of climatic the anemometer mast should be located in the centre variability, and often grow well in warmer tempera- of an opening in the forest with a diameter at least 20 tures, although locally adapted provenances may times the height of surrounding trees. If this is not experience growth declines. Hence, in the absence of possible, the size of the opening and height of climate-induced changes in disturbance regimes, surrounding trees should be recorded. It is not consid- catastrophic diebacks are unlikely and forest produc- ered appropriate to locate anemometers at a height of tion may remain largely unaffected as communities 10 m above the tops of the trees in a closed forest begin to reassemble (Loehle and LeBlanc, 1996). because wind profiles are significantly different from Changing disturbance regimes, however, are likely those over solid ground owing to the effect of the tree to have greater effects. For instance, changing fire surface profile. regimes, pest outbreaks or dispersal abilities may competitively disadvantage more productive species. 11.3.1.2 Precipitation This could lead to alterations in stand dynamics, successional trajectories and temporal developments Precipitation measurements for forestry operations in forest production. are important for estimating the water balance of areas of forested land, water status and water use efficiency of trees. Too much or too little precipita- tion will cause problems for foresters. Drought 11.3 METEOROLOGICAL OBSERVATIONS stress, waterlogged ground and flood conditions FOR FORESTRY APPLICATIONS can have serious consequences for the health and development of trees and commercial crop yields from trees. Measurement of precipitation in forested 11.3.1 Measurement of wind and areas is subject to many of the same difficulties as precipitation the measurement of wind speed, however. It should be noted that rainfall measurements, in general, are 11.3.1.1 Wind subject to systematic and random errors from both Commercial forestry and silviculture measurements instrumentation and sampling. The aerodynamic of wind are important for the viable production of effects of wind turbulence over raingauges produce forestry or non-forestry tree commodities (for exam- significant errors of rainfall sampling among rain- ple, timber and fruit). Wind flow, especially at gauges at a site (Rodda, 1967; Robinson and Rodda, speeds greater than 15 m s–1, can produce extremely 1969) and forests may exert a significant impact on destructive effects on a forest through tree fall precipitation measurement because of the effect of (windthrow) or snapping (windsnap). Trees exposed tree stands on wind profiles. Further errors in to consistent wind flows above 7 m –1s , on coastal precipitation measurement in forested areas may or elevated sites for example, develop differently occur when recording snowfall or rainfall at higher from trees of the same species developing under elevations (Sevruk and Nevenic, 1998). sheltered conditions, and this can potentially affect crop yields from trees. Furthermore, specialized fire The measurement of precipitation comprises two weather observations of wind speed may be used in aspects: first, the point measurement of precipitation an attempt to correlate fire spread with wind speed, at a gauge and, second, use of the catches at a number slope and fuel characteristics in areas susceptible to of gauges to estimate areal precipitation. For point forest fires (see 11.3.3). measurement of precipitation in forested areas, a precipitation gauge should be located so that Meteorological records generally describe surface surrounding objects are not closer than a distance wind characteristics in statistical terms, using average equal to four times their height. At exposed sites, the values taken over long intervals. The wind is defined effect of wind can be reduced through further tech- in terms of a vector of its direction and speed, with niques, such as construction of turf walls or use of a continuous wind measurements taken, in accordance ground-level gauge. Additional precipitation meas- with an international agreement (WMO, 2008), at a urements may also be undertaken to determine height of 10 m above the ground. Forested areas specific hydrological processes or research questions. complicate wind characteristics, however, based on To measure inputs from fog and dew, especially in airflows over the top of a stand (primary airflow) and areas prone to fog (for example, maritime areas), a the flow penetrating the trunk space (secondary number of different fog/dew gauge designs have CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–23 been used, including wire harps, cylindrical screens Temperature, humidity, rain, radiation and wind and louvred metal gauges (Bruijnzeel, 2001). are the main meteorological variables that influence the development of insects, weeds and Determination of the areal pattern and quantity of plant pathogens. Temperature is the key factor in rainfall may be achieved with a well-designed network insect development. Temperature and moisture of raingauges or by using additional information from are the major factors to be considered in the remote-sensing (such as weather radar and satellites). infection and spread of a disease. Temperature Estimation of areal precipitation using raingauges before, during and after the application of alone is difficult, as errors will occur due to the random herbicides tends to alter the susceptibility of the nature of storms and their tracking between gauges. weeds and pesticide efficacy. During herbicide In general, estimates of areal precipitation will increase spraying, wind and turbulence increase off-target in accuracy as the density of the gauging network drifts; rain during and up to some hours after increases. Broad guidelines for the minimum gauge spraying washes away the pesticide, strongly density of precipitation networks in various geograph- reducing its effectiveness (WMO, 1988). ical regions are outlined in WMO (1994b) and are presented in Table 11.1. For forestry applications, Pest and disease management, using real-time gauge density for estimation of areal precipitation will weather information, is done for fruit orchards on normally fall between 25 and 600 km2, depending on an exclusive basis. When a nearby, representative, the geographical location of forestry plantations and automated weather station is available, meteoro- non-forest tree agriculture (for instance, nurseries). logical elements may be used for the forecast and However great the density of existing precipitation management of pests and diseases. It should be kept networks, they can only give an approximation of the in mind, however, that air temperature and humid- actual spatial pattern of precipitation. Increased accu- ity obtained at such a station are likely to be rather racy and reduced error in the areal distribution of different than their canopy counterparts, and rain precipitation for the forester and agronomist can be and wind speed and direction may change abruptly achieved through a combination of rainfall calcula- over short distances. When on-site measurements tions from satellite imagery linked to measurements are not contemplated, simulation models may be at radar stations, which, in turn, are calibrated with used to generate agrometeorological variables several rainfall gauges. needed for input in the pest or disease simulators, using some of the available variables. Hence, air Further information on the location and sampling temperature and humidity in the canopy and leaf of rainfall gauges is contained in the WMO Guide to wetness may be predicted using appropriate models Meteorological Measurements and Methods of (Weiss, 1990). Observation (WMO-No. 8) and the WMO Guide to Hydrological Practices (WMO-No. 168). If a representative weather station is not availa- ble, or is not satisfactory for the research 11.3.2 Specialized observations for application or pest and disease management orchard pest and disease scheme, it is necessary to install a specialized management station. The WMO guidelines on type of instru- ment, specifications and layout of the instruments Weather governs the development of pests and for weather stations generally apply for the diseases that affect forest and non-forest trees. specialized station (WMO, 2008). Air temperature

Table 11.1. Guidelines for precipitation gauge density in precipitation networks in various geographical regions (WMO, 1994b)

Geographical region Gauge density (km2)

Small mountainous islands with irregular precipitation 25

Mountainous areas (temperate, Mediterranean, tropical climates) 100–250

Flat areas (temperate, Mediterranean, tropical climates) 600–900

Arid and polar climates 1 500–10 000 11–24 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES and humidity should, however, be measured in 11.3.3.2 A specialized fire weather network the environment where pests and diseases develop (that is, the canopy). Precipitation should be Fire weather interests in the United States have measured over a grass surface and free from the given rise to a weather network specialized for fire influence of the canopy and any other obstacles. management. Remote automatic weather observing Wind speed and direction should be measured systems are dedicated to fire danger rating through above the crop canopy and with adequate fetch strategic placement of weather stations and frequent (about 100 m upwind fetch for each metre of and consistent reporting of fire weather observations. anemometer elevation above the crop top) In the early history of fire danger rating, fire weather (Gillespie, 1994). observations were collected manually once daily, usually in the early afternoon. Now, computer- Surface wetness duration (SWD) is a specialized controlled sensors gather weather data at measurement that is very important for disease programmed intervals that can capture localized management. Modern electronic sensors were diurnal effects. Nearly 2 000 remote automatic reviewed by Sutton et al. (1984, 1988). The wide- weather stations now populate the fire weather spread principle of operation consists, basically, network in the United States (Figure 11.2). of measuring surface water deposition by a change in sensor resistance. Two or more conductors are placed alongside one another on a plate (for example, a circuit board, film or leaf), leaving a 11.4. COMPUTER SIMULATION MODELS small gap between them. When the gap is filled APPLIED TO FORESTRY AND NON- with the water from dew or rain, a resistance drop FOREST TREES is recorded. Since there is no standard sensor, numerous designs and sizes of sensors are in use The application of computer models in forestry can (Weiss and Lukens, 1981; Huband and Butler, be split broadly into two parts. First, there are numer- 1984; Weiss et al., 1988). The placement and ous different modelling approaches developed orientation of the sensors are important. In originally as research tools. These are used to consol- general, sensors should be located in representa- idate and expand scientific understanding of how tive spots in the canopy and may be wired in plant organs, entire trees and complex ecosystems parallel to save data logger channels, if necessary. respond to environmental factors – including mete- Using the worst-case scenario approach, when orological variables operating at timescales ranging the number of available sensors is small, half of from seconds (in the cases of photosynthesis and them may be located in spots of greater accumu- stomatal function) to climatic cycles and trends last- lation of dew (that is, the top part of the canopy) ing decades to centuries (in the cases of fire regimes and the remaining sensors may be deployed in and vegetation succession). Second, there are rather shady spots, located deep in the canopy, where fewer examples of models developed as decision water from rain tends to resist evaporation. Flat support tools (DSTs). In many cases these are derived sensors should be tilted at an angle to the hori- directly from the researchers’ models, although some zontal (for instance, 45°) to avoid excessive may be created from the outset as applied models for puddling of water (Gillespie, 1994). forest management.

The following sections offer an outline of the range of 11.3.3 Specialized fire weather computer models currently used in both forest observations research and forest management, subject to the important criterion that they require some form of 11.3.3.1 Weather data for fire management climatic or meteorological input data (or “forcing”). Fire managers need weather data to determine The discussion therefore excludes conventional, primarily the ignition and spread potential of a statistically derived growth and yield models fire on a given landscape. Many of the weather constructed from mensuration data alone. These variables that are recorded, such as hourly temper- growth and yield models treat climate as a compo- ature, relative humidity, global radiation, wind nent of site quality, and hence implicitly assume that speed and precipitation, are common to agricul- the mean climate at any site does not change over tural interests. What makes fire weather periods of a stand rotation or longer. Such models observations unique is the type of locations at have served the practising forester well in the past. which the data are usually required. These tend to be remote, uninhabited areas, more often than not Global atmospheric concentrations of some in complex terrain. greenhouse gases (GHGs) have increased CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–25 significantly since 1850, however; in 2006, carbon continental) vegetation models, which attempt to dioxide (CO2) concentration was close to 40 per integrate the effects of all the important climate- cent higher. It is now generally accepted by the dependent processes affecting forest structure and scientific community that these increases in GHG function. concentrations have already contributed to appreciable changes in annual mean temperature 11.4.1 Growth and production models and rainfall patterns in many parts of the world (IPCC, 2001a). In addition, higher CO levels may 2 11.4.1.1 Canopy process models have possible direct effects on photosynthesis. Simulations of future climate carried out using The primary function of a plant canopy is to inter- global models of atmospheric and ocean circulation, cept and use solar energy to create carbohydrates forced by projected increases in GHGs due to from CO2 and water. Understanding of leaf-level burning of fossil fuels and land-use change biochemistry has advanced greatly over the last 30 (primarily tropical deforestation), indicate that years. Physiological models developed by Farquhar greater climatic changes will inevitably occur within and co-workers (for example, Farquhar et al., 1980) the twenty-first century. This need not imply that are at the core of many present-day canopy process all growth and yield models are now useless, but it models. These biochemical models also provide the does bring their application for forecasting future basis for a mechanistic representation of stomatal timber yields into question (for example, see Matala functioning that operates as the primary control of et al., 2003; Hall et al., 2006). This section attempts transpiration. Scaling up from the leaf to stand level to address this issue by highlighting some recent is accomplished by some representation of canopy examples of process-based “hybrid” approaches to light interception, integrated over space and time. yield modelling, as described by Landsberg (2003a), This may be the simple Beer’s Law approach, first in which the traditional approach is merged with proposed by Monsi and Saeki (1953), which some form of climate sensitivity. The vast literature expresses light absorption as an exponentially on dendrochronology, in which regression models decreasing function of leaf area index (LAI, that is, are frequently used to relate interannual and longer- total foliage area expressed per unit of ground area). term variations in annual diameter increment to More detailed light interception models account for historical climate trends, is excluded. vertical profiles in structural variables, including leaf angle distribution and specific leaf area, and The categorization used in the following sections is the separation of incident short-wave radiation into intended to identify the major types of models that beam and diffuse components, which are in turn have been developed, but inevitably many omissions reflected and backscattered within the canopy. will occur. There will also be overlaps, particularly Other important canopy variables include photo- in the description of larger-scale (landscape to synthetic capacity (often correlated to foliar

Station locations as catalogued in the Weather Information Management System (WIMS): 05 Aug 06

Legend

• RA WS NFDRAS station ▲ Manual NFDRS station (Inv. Dist. Interp.)

Figure 11.2. Fire weather station locations in the continental United States (left). Most of the stations are automated, like the one shown (right), a necessity in the remote areas in which they are located. 11–26 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES nitrogen (N) concentrations), and the gradients in Semenov and Barrow, 1997; see also Semenov et al., temperature, humidity and leaf boundary layer 1998). Clearly, measurements are preferable to conductance, resulting from the turbulent modelled data, but the latter can often provide exchanges of heat, water vapour and wind energy. acceptable results, particularly if observed variances can be used to influence the distributions of Cannell and Thornley (1998) provide a useful simulated extremes, and the covariances of the review of the interacting effects of temperature, simulated variables (radiation and precipitation, for irradiance and CO2 responses of leaf and canopy instance) can be preserved. gross photosynthesis in C3 plants, which are key to understanding the principles of canopy process Other canopy process models developed over the models applied to forests. More detailed explana- last 15 years or so include: MAESTRO (for example, tions of these principles and their applications in Wang and Jarvis, 1990), FOREST-BGC (for example, models can be found in Landsberg and Gower Running and Gower, 1991; Running and Hunt, (1997) or Landsberg (1986). Many of these models 1993), PnET (for example, Aber and Federer, 1992), are developed and validated in conjunction with TREGRO (Constable and Retzlaff, 2000), BEPS (for detailed measurements of canopy level exchanges example, Liu et al., 1997, 2002) and CABALA of heat, water vapour and CO2. The models can (Mummery et al., 2002). Grant’s ecosys model (for then be used to fill in periods of missing data, or to example, Grant et al., 2001) has been applied predict canopy responses for combinations of envi- successfully to a wide range of crops and forest ronmental factors not observed in reality, including systems, and is arguably one of the most detailed scaling up in time and space. Examples include: process models currently available, although it does (1) the CANOAK model of Baldocchi and Wilson not presently account for competition among (2001), which is used to estimate fluxes of CO2, species. water and energy over multiple years; it captured 80 per cent of observed variance when forced by hourly 11.4.1.2 Hydrological models meteorological data and demonstrated the impor- tance of leaf clumping and growing season duration Vegetation cover provides a crucial link in the in annual net ecosystem exchange (NEE); (2) a water cycle between soil and atmosphere. Surface model reported by Williams et al. (1998), who hydrology models therefore often include a compared eddy covariance measurements with a canopy process component as a control on model applied to undisturbed rainforest in Brazil, evapotranspiration, which may range from a obtaining good agreement and providing a physical simple empirical representation to a fully coupled explanation of dry season fluxes; (3) the use of a model of canopy photosynthesis and stomatal suite of models by Arneth et al. (1999) to simulate control. A distinct subgroup is known as soil– NEE of young Pinus radiata at a drought-prone site vegetation–atmosphere transport (SVAT) models, in New Zealand, finding it was sensitive to changes which simulate water movement via roots, stems in PAR on short timescales, but inter­annual varia- and canopy, but typically lack a detailed repre- tions were related to humidity deficit and soil water sentation of photosynthesis and carbon allocation as affected by summer rainfall; and (4) Wang et al. (for example, Williams et al., 2001, who simu- (2004), who combined measurements in a P. sylves- lated drought responses of sap flow in ponderosa tris stand in Finland over three years with a model pine trees of different ages and sizes). The follow- of canopy transfer resistance and energy balance to ing discussion focuses on the important linkage assess intra- and interannual variations in fluxes of between vegetation and surface hydrology. water, heat and net radiation at the forest floor. The Penman–Monteith equation (P–M) (Monteith, The required inputs to such models vary, but will 1964) is perhaps the most famous and most widely typically include daily or hourly temperature, used example of a biophysical model. Its represen- radiation and humidity, as well as some tation of stomatal conductance (at the leaf or representation of available soil water. In most cases, canopy level) is necessarily simplistic, meaning biophysical variables, such as plant and soil that it needs to be parameterized for application to hydraulic characteristics, must be prescribed, but specific conditions, but the equation is theoreti- others, such as leaf area index and foliar nitrogen cally correct in its combination of radiative and content, may be simulated. Various “weather convective drivers of evapotranspiration (ET). generators” have been developed to disaggregate There are numerous derivatives of the P–M, which climate data recorded at daily or longer time steps have been applied to forest systems in many differ- into high-frequency meteorology (for example, ent ways (for example, Bosveld and Bouten, 2003; Richardson, 1981; Geng et al., 1985; Wilks, 1992; Hogg, 1994, 1997; Irvine et al., 1998; Martin et al., CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–27

1989; Spittlehouse and Black, 1981). One modifi- forest engineering problems, and management of cation that has been used successfully for many riparian and freshwater habitats (see 11.4.1.8). vegetated systems is the Priestley and Taylor (1972) Approaches to modelling forest hydrology are formulation of potential evapotranspiration (PET). similarly varied, but generally require some Originally developed for irrigated agricultural representation of the water balance applied to the crops, it has since been applied to natural ecosys- region of interest. Reviews by Xu (1999) and Xu tems, including forests, with relatively and Singh (2004) discuss traditional methods (going straightforward calibration of its alpha parameter. back to Thornthwaite’s original approach to Fisher et al. (2005) provide a comparison of PET estimating ET, as reported, for example, in models, noting that soil moisture controls are Thornthwaite and Mather, 1957), and compare crucial for correct estimation of evapotranspira- these to the newer generation of spatially distributed tion. It should also be noted that ET models derived hydrological models. They also discuss the need for from the P–M generally require measurements or validation methods suited to the target application, estimates of net radiation above the canopy. citing as an example a model developed as part of the Scandinavian NOrthern hemisphere climate Hatton et al. (1993) modified FOREST–BGC to Processes land-surface EXperiment (NOPEX) account for evaporation from the soil and from wet programme (Xu et al., 1996). canopies (following McNaughton and Black, 1973). They applied this model to Eucalyptus forests in Recent developments in Geographical Information south-eastern Australia, validating it against data Systems and the easy access to high-resolution for both coastal and inland semi-arid forests. The digital elevation models now allow accurate predicted water deficits agreed well with observed prediction of catchment-scale water balances from data in both systems, suggesting that the model relatively few weather inputs. Some of the many could be used to estimate impacts of changes in spatialized forest hydrology models available, land cover or climate on water balances over large focused at the watershed or catchment scale, regions. include: the Regional Hydro-ecologic Simulation System (RHESSys) model (Coughlan and Running, Statistical correlations between ET and productiv- 1997; Baron et al., 1998); the Forest Hydrology ity have been noted for some time, while recent Model, or ForHyM (Arp and Yin, 1992; see also advances in modelling the linkage between leaf- Balland et al., 2006, for coupling of soil hydrology level photosynthesis and stomatal functioning to thermodynamics); the Distributed Hydrology provide strong theoretical support. Spittlehouse Soil Vegetation Model, or DHSVM (for example, (2003) developed a simple approach to modelling Storck et al., 1998); and a watershed‑scale hydrologic the dependence of forest productivity on growing model called DRAINWAT (Amatya et al., 2006). season moisture availability computed from rain- fall and soil data. He used this approach to 11.4.1.3 Soil decomposition models correlate site characteristics to site productivity and then infer the site-level sensitivity to climate Many models of forest ecosystems require a change, based on projected changes in rainfall representation of soil decomposition processes. and ET (as a function of temperature). Richardson These accept simulated litterfall from above- and et al. (2002) used a simple water balance model to below-ground components of the forest, and then explain effects of broom understorey on the simulate heterotrophic decomposition of the litter growth of P. radiata in New Zealand. Broom was material, typically as a function of soil temperature removed from some plots and this evidently and moisture content, splitting it into multiple resulted in greater water availability, supported pools, decaying at different rates, and classified by model and nitrogen probe measurements. according to substrate quality and/or chemical Similar work was carried out in western Canada composition. These pools then transfer carbon by Kelliher et al. (1986), who investigated the content to the simulated soil profile, with the net effects of an ericaceous understorey shrub (salal, rates of C accumulation contributing to the Gaultheria shallon) on water relations and growth calculation of net ecosystem productivity. of Douglas-fir (Pseudotsuga menziesii). Given the incomplete knowledge, and considerable Forest hydrology is concerned with aspects of water complexity, of soil decomposition processes, these movement within and through forested catchments, models are often used as much to test ideas as to with applications including water management make predictions. Some notable examples include (quality and quantity), erosion control (for example, CENTURY of Parton and co-workers (for example, Benda and Dunne, 1997; Connolly et al., 1999), Parton et al., 1992); the RothC model from the 11–28 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

United Kingdom (used by Jones et al. (2005), for climates. They are also important components of example), coupled to different general circulation large-scale vegetation models to determine the models (GCMs); the models of Verberne et al. approximate timing of leaf emergence and leaf fall (1990), as used in the Integrated Biosphere Simulator of deciduous tree species. (IBIS) dynamic vegetation model reported by Kucharik et al. (2000); and ROMUL of Chertov et al. The continental phenology model of White et al. (2001). Falloon et al. (2002) used both RothC and (1997), applied initially to the continental United CENTURY to compare estimates of C uptake under States, has potential application to other regions, different land uses, including afforestation, with a although regionally specific parameterization and regression model, finding some major differences. validation (using satellite remote-sensing data) will The Q model of Ågren and Bosatta (1998) is rather be required. De Melo-Abreu et al. (2004) compared different in that it treats the organic component as several models of flowering phenology in different a substrate that changes continuously in quality olive varieties in Spain, of which a “chill–heating and over time (rather than as discrete pools in model” gave the most plausible predictions and which decomposition is a simple first-order decay should be applicable to other woody species. Arora function of the current pool size). and Boer (2005) developed a new approach to predicting leaf phenology, in which leaf appearance Closely related to models like CENTURY are the occurs only when environmental conditions would Peat Decomposition Model (PDM) and Peatland result in carbon gain. Conversely, leaf fall is caused Carbon Simulator (PCARS) models of peat accumu- by unfavourable conditions that cause C losses, lation and decomposition in peatland ecosystems, including shorter days, suboptimal temperature and developed by Frolking et al. (2001, 2002), and drought conditions. This representation is consid- Wetland–DNDC, which refers to DeNitrification- ered sufficiently robust to work at global scales and DeComposition (for example, Zhang et al., 2002). in simulations of transient climate change. These models are specifically designed to account for the annual deposition and anaerobic decompo- 11.4.1.5 Population models (single-tree, sition of organic material characteristic of wetland gap-phase dynamics) ecosystems. The DNDC model of Cui et al. (2005) simulates dynamics of forested wetlands in response Simulation of forest stands and forests as collec- to environmental and plant physiological factors, tions of individual trees has been of interest for as well as decomposition processes. almost as long as digital computers have existed. Adopting this approach, the ground-breaking Numerous models also exist that link soil decompo- JABOWA model of Botkin et al. (1972) led to the sition to nitrogen cycling and hence provide development of an entire class of forest stand feedbacks to forest productivity at stand-level or models used mainly for representing growth larger scales. Examples include VEGIE (Aber et al., dynamics of natural or extensively managed forests, 1991), work by Kang et al. (2003), the spatial model over long periods, and under projections of climate of Fan et al. (1998), the submodel for IBIS devel- change. More recent examples include FORSKA oped by Liu et al. (2005) and EFIMOD (Chertov et (Prentice et al., 1993), FinnFor (Vaisanen et al., al., 2003; Komarov et al., 2003), which is based in 1994), FORCLIM (Fischlina et al., 1995; Bugmann part on ROMUL. and Solomon, 1995), GUESS (Smith et al., 2001), SORTIE (for example, Canham et al., 2004) and 11.4.1.4 Phenology models PICUS (for example, Lexer and Hönninger, 2001). A key feature of many of these models (though not Models of plant phenology typically operate on the all) is that trees of multiple species are simulated basis of degree-day sums starting from the begin- within small (ca. 0.1 ha) sample plots, without ning of the year (or 1 July in the southern predetermined spacing or timing. They are allowed hemisphere), although other climatic criteria may to seed, grow, compete for environmental resources, also be used, including soil temperature, soil water including light, water and nutrients, and ultimately status and day length. Tree growth processes that die (leaving gaps for regeneration). This contrasts may be predicted include emergence from with the rather smaller group of spatially explicit dormancy, seed germination, leaf expansion, flow- stand simulators (such as TASS, DFSIM), which ering, leaf fall and the onset and cessation of height attempt to model the inter­actions among individ- growth. Phenology models are useful as predictors ual trees in a managed even-aged stand, predicting of tree or crop suitability for particular regions, both effects on stem form, branchiness and wood quality for present-day management and for assessing how within a single rotation and validated against suitability might change with possible future detailed measurements. Almost certainly, however, CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–29 some models bridge the divide between these spatial covariance functions to analyse the endemic contrasting approaches. spatial distribution of spruce bark beetles with climate. They found inverse relationships with Recent reviews of many of the features of the current latitude (implying that temperature is an important generation of gap-phase dynamics models are factor), as well as correlations with forest provided in a collection of papers edited by productivity and drought-prone soils, and the Bugmann et al. (2001). Inputs to these models typi- occurrence of windthrow events. In Canada, cally include mean temperature and temperature Fleming and Candau (1998) adopted a process- range (that is, maximum minus minimum), precip- based perspective on factors controlling spruce itation, and cloud cover fraction (if not solar budworm (SBW) outbreaks, including natural radiation), although other inputs, including humid- selection, extreme weather events, phenology, ity, are possible. Monthly data are typically used, interactions between pest and host, and “threshold but some studies have shown that daily input can behaviour” (the factors causing the shift from produce rather different results – suggesting that endemic levels to serious outbreaks). these are to be preferred if available. More recently, Candau and Fleming (2005) used clas- sification and regression tree (CART) models to 11.4.1.6 Disturbance models analyse high-resolution spatial data and determine Disturbances to managed and unmanaged forest climatic controls on SBW defoliations. Climate ecosystems include wildfire, outbreaks of insect warming is now considered a significant factor influ- pests, and storms and floods. Of these, fire models encing many of these processes, with profound are also discussed in 11.4.3, and therefore will not implications for natural biodiversity and forest be addressed further here. management. Williams and Liebhold (2000) investi- gated spatial and temporal correlations of SBW outbreaks in eastern North America for 1945–1988, 11.4.1.6.1 Insects finding that synchrony approaches zero at distances It is possible that the great biodiversity of tropical over 2 000 km. The east–west pattern correlated to ecosystems, supported by relatively even seasonal monthly temperature and precipitation data over temperature regimes, serves to protect them from the same period, but this also decreased with increas- major insect epidemics. Insect-driven disturbance ing distances. They then developed a spatially events are certainly more common at higher lati- explicit lattice model for a single pest species occu- tudes, particularly in mid-continental boreal pying multiple patches of forest, using this to ecosystems. Boreal forests typically are composed of determine that observed distributions of SBW relatively few tree species (for example, see Nikolov outbreaks are synchronized through a combination and Helmisaari, 1992) and are subjected to very of high dispersal rates with a spatially autocorrelated cold winters and short summers, which impose a Moran effect (local and regional stochasticity). Gray strong seasonality on insect life cycles. (2004) developed a model of gypsy moth phenology tested at 4 500 locations and found that the north- Moreover, stands are often large and more or less ern and southern limits of its range would likely shift continuous across the landscape – which contrib- northward with climate warming. utes to the propagation of the next stand-replacing disturbance. But this large-scale contiguous nature A recent huge outbreak of the mountain pine beetle also results partly from the important role that (MPB) in central British Columbia (in which several natural disturbances, both fire and insects, play in million hectares of forest were destroyed) has also boreal stand regeneration and development. It is been attributed in part to recent climate warming. for these reasons that much of the interest in models Carroll et al. (2003) combined a model of climate of forest insect disturbance originates in boreal impacts on conditions favouring MPB with a nations – where calculated commercial losses due spatially explicit climate simulator. Analysis of to insect pests can be comparable to those from historical climate then showed a clear increase in fire. benign beetle habitats over the period 1921–2000, which evidently explains observed occupations of Malmström and Raffa (2000) present a review of new areas by MPB and suggests that further climate modelling approaches and point to the need to warming will allow a wider spread into eastern and represent disturbances as dynamic responses to northern Canada and to higher elevations. climate, particularly those caused by insects. Examples of these approaches include Økland and Stahl et al. (2006) investigated the role of synoptic- Bjørnstad (2003), who have used non-parametric scale circulation and large-scale climatic modes as 11–30 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES factors causing MPB mortality events in British where not all trees are damaged in the same storm Columbia. They found that the occurrences of daily event). The model accounts for wind gusting and minimum temperatures had not reached those predicts stem breakage or uprooting from needed for 100 per cent MPB mortality at several comparisons to data on critical bending moments climate stations in recent years, which was related and critical compressive stresses, respectively. The to reduced occurrence of winter outflows of frigid FOREOLE simulations of critical wind speeds Arctic air affecting central British Columbia. This compared favourably to other models, including behaviour appears to be due to increased frequency HWIND, and indicated that irregular stands suffer of strongly positive Pacific Decadal Oscillation scattered damage at a range of wind speeds, events, and of corresponding negative phases of the whereas regular even-aged stands tend to fail as a Arctic Oscillation, which may in turn be a conse- single entity once the critical wind speed is quence of a global warming trend. exceeded.

Olofsson and Blennow (2005) have developed a 11.4.1.6.2 Storm damage prototype decision support tool to identify spruce Hall et al. (1992) were early users of spatially explicit stands at high risk of damage in southern Sweden. information to model responses of tropical forests Decision trees were calibrated for a 1 200 ha forest in Puerto Rico to climate and hydrology (including based on stand-specific factors, including mean hurricanes), as influenced by topography, soils, stem taper, gap sizes at the stand edge and direction land use and vegetation type. They were able to of wind exposure. Independent testing of the model show that over several centuries, after taking hurri- at a separate site showed only limited success in cane damage into account, these ecosystems application, considered to be due to its failure to effectively “pump” carbon from the atmosphere to capture the underlying complexity of causes of the ocean at an average rate of ~90 kg C ha–1 yr–1. wind damage.

Winter storms are a major concern at high latitudes. 11.4.1.7 Biogeography models For example, Peltola et al. (1997) developed the HWIND model to calculate critical combinations of The emergence of biogeography models goes back snow loading and wind speed for boreal tree species to the mid-1980s, when the feedbacks of terrestrial in Finland. They found that less-tapered trees were vegetation to global climate were first being consid- more vulnerable to damage and that snow loading ered in GCMs. Important questions included the was more important than wind speed. Evergreen role of forests compared with deserts or grasslands, conifers were much more susceptible to damage and the feedback effects resulting from tropical than deciduous birch. Other work from Finland deforestation (for example, Henderson-Sellers et al., includes that of Jalkanen and Mattila (2000), who 1988; Shuttleworth et al., 1989). Models such as used logistic regression models to predict suscepti- BATS (Dickinson et al., 1993), SiB (Sellers et al., bility of stands to combined effects of wind and 1989), LSM (Bonan, 1996) and CLASS (for example, snow loading. Bartlett et al., 2003) were important developments that indicated how vegetation characteristics could Talkkari et al. (2000) have developed an integrated affect global climate. Wang et al. (2001) enhanced suite of models at tree, stand and regional scales to the CLASS model to account for canopy photosyn- assess risks of wind damage at forest margins. The thesis, N uptake, respiration and senescence, system includes a mechanistic model to predict the explaining 80 per cent of observed variance (eddy critical wind speeds needed to cause damage (using covariance data) over a three-week period, and 85 tree height, DBH and stand density as inputs), a per cent over two years at a boreal deciduous forest regional wind climate model (based on site loca- site in central Canada. Some researchers have used tion, topography and surface roughness, and using such models to investigate the sensitivity of global climate station records), and GIS data on the proba- climate to large-scale changes in forest cover, nota- bility distribution of extreme wind speeds. The bly Bonan et al. (1992) for deforestation and Betts integrated approach appears to have great potential (2000) for afforestation. for predicting areas at risk and hence for targeting silvicultural prescriptions to reduce damage in high- While the initial focus for GCMs was on static vege- risk areas. tation schemes (that is, parameterized with constants for the key variables), parallel develop- Ancelin et al. (1999) developed the mechanistic ments led to a series of continental-scale vegetation individual tree-based FOREOLE model to simulate models that would respond to climatic drivers. effects of wind on heterogeneous stands (that is, These included “equilibrium projection” models, CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–31 which correlate vegetation distribution to climatol- feedbacks to the atmosphere (water vapour, heat, ogy, such as BIOME (Prentice et al., 1992), as well as momentum transfer, reflected and re-emitted radia- large-scale derivatives of stand-level canopy process tion, GHGs) at hourly timescales. The objective is models (notably BIOME-BGC, derived from to increase understanding of the role of forests and Running’s FOREST-BGC), and the EXE model of other vegetation in maintaining the global envi- Martin (1992), which links physiology, water ronment, and to assess the impacts of human-caused balance and ecosystem dynamics to couple to changes in land use (such as deforestation and larger-scale climate models. afforestation) on atmospheric composition (GHGs and other pollutants). The global equilibrium projection models were designed to be computationally efficient and capa- 11.4.1.8 Biodiversity and habitat models ble of simulating responses to scenarios of future (including riparian systems) (stabilized) climate. But a major limitation in the concept of the equilibrium distribution of vegeta- Globally, forests, and particularly tropical rainfor- tion is that it would likely take centuries for full ests, provide habitat for a greater number of animal adjustment to new conditions to occur (for exam- and plant species than any other terrestrial ecosys- ple, see Overpeck et al., 1991), even if the notion of tems. This is largely because a mature forest protects a “constant climate” were plausible. Hence, these its inhabitants from climatic extremes, while models are not suitable for projecting the short- providing a range of microhabitats and food sources. term transitional responses of forests to a changing Hence, there is wide interest in modelling the effects climate, which are needed to assess near-future of forest cover on microclimate, particularly as it impacts and to plan management adaptations. affects habitats for fish and wildlife. In general, the models are empirical, relying on statistical relation- Other models, such as CENTURY (for example, ships. Examples include principal component Parton et al., 1992) and the Terrestrial Ecosystem analysis applied to genetic variation of Lupinus Model, or TEM (Raich et al., 1991; McGuire et al., species in Mt Hood National Forest in the United 1993), were more focused on biochemical processes States, with topography and climate found to be contributing to nutrient cycling and vegetation key variables (Doede, 2005). Working in mountain productivity, but could be applied at continental to ranges in Nevada, Fleishman and co-workers, (for global scales given appropriate climatic data. By the example, Fleishman et al., 2001, 2003; mid-1990s, dynamic vegetation models (DVMs) Mac Nally and Fleishman, 2004) used a variety of were being developed to address these limitations. statistical approaches, with GIS-based digital terrain Such models include many of the principles embed- data and microclimatic models, to predict resident ded in the biogeochemistry models, together with butterfly populations in the state. Statistically ecosystem responses analogous to those captured significant models were developed for 64 per cent in forest gap models. Their objective is to simulate of 56 species, and elevation was found to be signifi- the short-term transitional effects of a variable and cant in more than half. These models were found to changing climate, so that vegetation responses can be applicable outside the range in which the statis- be projected over periods of years to decades, rather tical relationships were derived. than centuries to millenniums. In Washington State, Sridhar et al. (2004) developed These models also integrate more or less detailed a physically based model to predict stream temper- representations of canopy processes and phenologi- atures in forested watersheds in the Cascade cal controls, as well as litter and soil decomposition Mountains. The model uses GIS databases to esti- and nutrient cycling, and possibly surface hydrol- mate low flows, which are normally correlated to ogy. Most also attempt to account for the effects of higher stream temperatures. The worst-case scenario disturbances operating over periods of decades to combines low flow conditions with high irradiance centuries. Examples include later versions of TEM and air temperature. The model can then be used to (for example, Tian et al., 2000; McGuire et al., determine effects of forest structure and stream 2001), as well as IBIS (Foley et al., 1996; Kucharik buffer width on water temperature. Adams and et al., 2000), MC1 (Neilson, 1995), Hybrid (Friend Bury (2002) investigated factors influencing abun- et al., 1997), LPJ (Sitch et al., 2003) and CTEM (for dances of stream amphibians in Olympic National example, Arora and Boer, 2006). An intercompari- Park, also in Washington State. Three species were son of six different dynamic models was reported found to be associated with climatic gradients. In by Cramer et al. (2001) for the global scale. Some of Sweden, Eggers et al. (2005) found that daily nest these models are now routinely “coupled” to GCMs survival rates of Siberian jays decreased with reduced – to simulate transient (continuous) vegetation vegetation cover in northern Sweden due to habitat 11–32 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES loss. The causes included greater exposure to low period. This approach is analogous to that of an temperatures and increased losses due to corvids. In empirical growth and yield model used in a wood the Brindabella Range of south-eastern Australia, supply calculation. Shine et al. (2002) investigated the effects of forest clearing on egg-laying reptiles. In this case, reduced The alternative approach is to use a combination of vegetation cover increased radiation loads and process models, such as CENTURY, and/or a temperatures at potential nest sites, generally rais- bio­geography model, forced by soils data and ing the upper elevational limit (that is, hatching historical records of climate and disturbance events. and survival increased), and possibly leading to In general, the bookkeeping model will produce changes in genetic structure and demography of smaller errors when the estimates are verified inde- populations. pendently, but the process-based method has the advantage that it can be used more easily to project future changes in response to scenarios of climate 11.4.1.9 Carbon budget models change. Churkina et al. (2003) used BIOME-BGC to A carbon budget model seeks to track some or all of perform regional C budget analyses of four European the processes contributing to net changes in ecosys- forests, on daily and annual timescales, while tem carbon pools occurring over measured time attempting to account for the uncertainties result- periods (typically one year). The realization that the ing from inadequate data. They found that the global community needs to reduce its emissions of model could underestimate respiration rates, possi- greenhouse gases, followed by binding interna- bly exaggerating its estimates of a net C sink. The tional commitments imposed by the Kyoto Protocol, results were sensitive to N and CO2 fertilization has contributed to widespread interest in the use of levels, which are likely to be important factors in forests as a temporary means of offsetting a portion projecting future forest C balances. Vetter et al. of global GHG emissions. Forest carbon budget (2005) also used BIOME-BGC to investigate the C models are a crucial element in determining both budget of conifer forests in Thuringia. Like CBM- the actual and potential carbon sequestration CFS, a particular feature of this model is that it capacities of forests, because they must be applied accounts for the “legacy effect” of the present-day at large scales (regional to national or larger), while age-class distribution. Results indicated that net providing acceptably small error limits that can be biomass increment increased over the period 1982– verified if the model results are audited. 2001, turning the system into a C sink, which was attributed to pollutant N deposition in high- Carbon budget models typically fall into one of two elevation systems and to CO2 fertilization at lower classes, although many models have features taken elevations. The results agreed closely with average from both. On the one hand, there are stock-based biomass growth rates estimated from inventories. “bookkeeping” models, of which the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS), Tian et al. (2000) applied the transient version of developed by Kurz and Apps (1999), is a well- TEM to assess C storage in undisturbed Amazon established example. The CBM-CFS is now freely ecosystems. They found that about 83 per cent of available in a user-friendly format and has been total uptake occurs in tropical evergreen forest, applied to forested regions around the world. The typically split 3:1 between vegetation and reactive model enables effects of different management soil organic matter. These ecosystems sequestered options and natural disturbance scenarios to be about 0.2 Pg C yr–1 between 1980 and 1994, investigated. For example, Price et al. (1997) exam- although deciduous forests actually take up more ined the responses of a managed boreal forest in carbon per unit area. Interannual variations in western Canada to different rates of harvesting, fire precipitation were evidently the major cause of losses and soil decomposition rates, and concluded interannual variations in annual net ecosystem that management would likely contribute to an exchange. Interestingly, Tian et al. (2000) recom- increase in the long-term accumulation of soil mended that C budget studies should extend over carbon. Such models rely on large-scale inventory at least one El Niño–Southern Oscillation (ENSO) databases (often spatialized), including forest inven- event cycle to account for interannual variability. tories, soils classification data and records of planting, harvesting and losses due to forest fires 11.4.1.10 Applications to agroforestry and non- and other natural disturbances. The data are used in forest trees combination with a forest growth model and soil organic matter decomposition model to estimate There is a wealth of literature on modelling agro­ changes in carbon pools (for example, soils, litter, forestry systems that takes account of the biomass, harvested products) over a specified physiological and ecological aspects previously CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–33 discussed, in addition to forcing meteorology (partic- input are developed as part of understanding ularly of radiative distribution below the tree canopy, various aspects of forest science. Specific models as in Zhao et al., 2003, for instance). Nygren et al. that have been applied, or that could have direct (1996) reported a whole-canopy CO2 exchange application, to solving problems in forest model, driven by standard meteorological input, to management will now be discussed. simulate changes in canopy structure and its effects on canopy assimilation of poro (a leguminous forage 11.4.2.1 Growth and yield models tree of Central America, Erythrina peoppigiana) under different pruning regimes. De Reffye et al. (2004) Landsberg (2003a, 2003b) has reviewed the poten- describe several complementary approaches used to tial application of forest process models to growth model growth of tree architecture to better capture and yield modelling, and has often highlighted the interactions between canopy structure and environ- distinctions between site-specific empirical (statisti- mental factors, while van Noordwijk and cal growth and yield, G and Y) models and Purnomosidhi (1995) and Ozier-Lafontaine et al. mechanistic models, such as the canopy process (1999) have used fractal branching models to predict models described earlier (see also Landsberg and root growth in a range of species. Gower, 1997, or Landsberg, 1986). He argues that most process models contain too many poorly Not surprisingly, agroforestry models are most known parameters to be useful for practical applica- frequently applied to tropical systems. Van tion in forestry. Research over the last 30 years, Noordwijk and co-workers have applied their however, has uncovered general principles relating comprehensive WaNuLCAS (“water, nutrient and to canopy light interception, photosynthesis, light capture in agroforestry systems”) model to a stomatal functioning, water relations and nutrition, wide variety of agroforestry systems in South-East which can be combined to develop practical proc- Asia (for example, van Noordwijk and Lusiana, ess-based models useful for forest management 2004). Kusumandari and Mitchell (1997) assessed applications. Conventional forest mensuration data soil erosion in West Java using the Agricultural will still be required to validate such models, but it Non-point Source Pollution (AGNPS) model, may be possible to maintain fewer sample plots concluding that agroforestry was an optimal land (perhaps measured to higher standards) to support use to minimize soil loss. G and Y models that will be generally applicable over much larger regions and will also be respon- In Costa Rica, Mialet-Serra et al. (2001) worked on sive to changes in environmental conditions, such cocoa (Theobroma cacao) and coconut (Cocos nuci- as climate change. Landsberg concludes that the fera) systems and Beer et al. (1990) on cocoa and future lies in hybrid models where weather data, poro. In Africa, McIntyre et al. (1996) applied the GIS-based inventories and multitemporal remote- EPIC (Environmental Policy Integrated Climate, sensing products (for instance, of leaf area index formerly Erosion Productivity Impact Calculator) and species composition) are all used as inputs. model to simulate canopy light interception and hence estimate transpiration rates in different crop- In general, these models are developed by ping systems of cowpea (Vigna unguiculata), maize researchers aiming to explain the processes by and cassia (Senna spectabilis) in semi-arid Kenya. which photosynthetic uptake of CO2 is trans- Cannell et al. (1998) (see also Mobbs et al., 1998) formed and allocated into harvestable material. used a detailed process model to simulate relation- Hence, many of the studies reported here link ships between light interception and water in West field measurements and meteorological datasets Africa, finding that in regions with less than with assessments of model performance, often 800 mm annual rainfall, agroforestry may improve involving comparison with traditional G and Y overall water use, though it is unlikely to increase predictions. Some researchers also point to the crop productivity. On the other hand, Wallace et al. need for continued monitoring to support further (1999), also working in Kenya, constructed a simple model testing. water balance model to predict soil evaporation in systems with and without tree cover, and they The Physiological Principles Predicting Growth concluded as well that trees can contribute to water (3‑PG) model of Landsberg and Waring (1997) is conservation. based on a radiation use efficiency (RUE) approach, in which maximum net primary productivity (NPP) is expressed as a simple product of absorbed photo- 11.4.2 Management models synthetically active radiation (APAR) and an The previous sections have examined some of the adjustable coefficient, often denoted ε. Haxeltine many ways in which models requiring meteorological and Prentice (1996) also proposed that variations in 11–34 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES foliar N and carboxylase activity over time and and yield have been constructed and used mainly within the canopy tend to support a simple rela- by researchers and seldom by farm advisers tionship between APAR and NPP. Reductions in (Grossman and DeJong, 1994). productivity from maximum, for instance, due to water stress or nutrient limitations, can then be 11.4.2.2 Fire ecology and fuels management represented as simple multipliers between one and zero. The 3-PG model is easily calibrated to differ- Many of the gap models described earlier have ent sites and source code is freely available via the been adapted for fire management applications. Internet. Both these factors contribute to its wide The Landscape Disturbance and Succession adoption and modification for numerous species (LANDIS) model (He and Mladenoff, 1999) simu- around the world, with applications in Australia, lates effects of fire, windthrow and harvesting on Brazil (for example, Almeida et al., 2004), Canada species-level succession, using a stochastic (Bernier et al., 2002; Hall et al., 2006), South Africa approach to simulating patterns over long times- (Dye, 2001) and the United States (for example, cales. When applied to six different landscapes in Coops and Waring, 2001). northern Wisconsin (United States), each with different species environments and different fire Many researchers working in this field attempt to return intervals, the model predicted responses at link high-quality measurements at specific sites different temporal scales, ranging from stand- with remote-sensing data as a means of scaling level succession up to big fires, causing a productivity estimates. Examples include Chen and coarse-grained pattern that persists over long co-workers, who developed the Boreal Ecosystems periods. Productivity Simulator (BEPS) model for Canada (for example, Liu et al., 1997, 2005), and Law et al. The authors concluded that this approach should (2001, 2004), who have worked with BIOME-BGC be applicable to the investigation of landscape- and data obtained from eddy covariance measure- scale responses to management, as well as changes ment sites across Oregon. A major problem though due to human land-use pressures and global is that accurate measurements of forest NPP are warming. Miller and Urban (2000) developed a difficult to make and are rarely available in suffi- spatially explicit gap model that simulates tree cient quantity to validate the models adequately. growth and litter production. They used it to Coops and Waring (2001) used 3-PG, and Hall et al. examine management alternatives for restoring (2006) used StandLEAP (a variant of 3-PG developed forests in the Sierra Nevada region, where 100 by Raulier et al., 2000), combining satellite remote- years of fire suppression has resulted in unnatu- sensing with forest sample plot and inventory rally large fuel accumulations (see also articles by data. Bridge et al., 2005, and Schoennagel et al., 2004). Similarly, Stephens (1998) applied the Fire Area Other work in this area includes that of Rötzer et al. Simulator (FARSITE) spatial fire behaviour model (2005), who used field data to validate a process- to Yosemite National Park (United States) to assess based tree-growth model called BALANCE, which different methods of controlling fuel build-ups, was applied to several sites in southern Germany. and hence determine best methods to limit Agreement with tree mensurational data was varia- uncontrolled fire hazards. ble among species but proved generally acceptable over several simulated years, while the water balance Other models are frequently used in fire manage- submodel evidently produced very good results at ment, both in assessing hazards and during active all sites. Briceño-Elizondo (2006) used a process- fire suppression. Fuel loadings are often related to based model to compare interacting effects of the current moisture status of surface litter or management and climate variations on productiv- upper soil layers. Goodrick (2002) modified the ity and carbon sequestration of boreal forests in Fosberg Fire Weather Index (FFWI), based on northern and southern Finland. Tharakan et al. temperature, relative humidity and wind speed, (2000) reviewed process-based growth and yield to account for precipitation effects by incorporat- modelling of Salix plantations in the eastern United ing the Keetch–Byram Drought Index (KBDI) to States. Peng et al. (2002), working in Ontario, linked formulate “fuel availability”. This improved the three separate models (3-PG, CENTURY and the relationship between the FFWI and areas burned TREEDYN3 model of Bossel (1996)) to create a new in Florida. Kafka et al. (2000), working in south- integrated model called TRIPLEX, which has been ern Alberta, used climate station input, used successfully to predict biomass and wood topographic data and fuel distributions to volume production of jack pine (P. banksiana). compute potential head fire intensity (HFI) for Models for the simulation of non-forest tree growth every day, or for percentiles of occurrence. The CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–35 resulting quantitative maps can be used to iden- yellow-bellied gliders (Petaurus australis), which tify areas of extreme fire behaviour potential for feed on the sap of five different tree species and fire and forest management – either before or whose conservation is considered an important during a fire. management objective. These authors found that flowering, productivity and stand density were important determinants of tree use, and hence 11.4.2.3 Insect pest management were able to make recommendations for local Harrington et al. (2001) present a valuable review of forest management of these food resources. the role of models in large-scale insect pest manage- ment. Although these authors focus on the Optimal habitat requirements for protecting the sensitivity of insect pests to a warming climate, cinereous vulture, a species at risk in the Republic many of the principles are applicable to variations of Georgia, were determined using GIS-based data in climate (primarily temperature) as a driver for and logistic regression models (Gavashelishvili insect attacks. For a more detailed discussion of et al., 2006). The best sites were relatively dry, models applied to insect pest management, see also north-facing slopes of more than 30°, close to exist- 11.2.2.5. ing protected areas, and remote from humans. Low rainfall areas were found to provide better condi- tions for soaring and breeding. The researchers 11.4.2.4 Storm damage control concluded that breeding ranges might be expanded Models have been applied to the operational prob- if seasonal grazing areas were also managed lem of determining stand vulnerability to windstorm appropriately. effects (see the discussion of the United Kingdom windthrow hazard classification under 11.2.1.4.2), 11.4.2.6 Soil erosion assessment and control and to the question of determining how natural forests subjected to storm damage should be The model of Connolly et al. (1999) was developed managed. For such a determination, Kramer et al. to study rain erosion of forest roads in subtropical (2001) applied a GIS-based model to pristine temper- Queensland. It includes a rainfall generator and ate rainforest on Kuiu Island, Alaska, to simulate outputs information on particle size distribution in long-term windthrow effects at landscape scale. gravel and dirt roads, and how these change with Slope, elevation, soil stability and exposure were different rainfall intensities. This model has direct inputs, and effects on stand age and structure were management implications for road maintenance in considered. The model was validated against inde- high rainfall areas, and can be used to assess the pendent windthrow data from a nearby island, effects of alternative approaches to reducing sedi- correctly classifying 72 per cent of landscape. They ment movement, for example, through stand-level concluded that large-scale stand replacement is a manipulations to increase water infiltration on natural process in areas prone to catastrophic hillslopes. windthrow (see also Grove et al., 2000), suggesting that harvesting in such areas should “emulate” 11.4.2.7 Regeneration these natural disturbance events. The model developed by Childs et al. (1987) does a good job of simulating site water balances with 11.4.2.5 Habitat, biodiversity management minimal inputs. They used this model to investi- Chen et al. (1996) modelled air temperature, wind gate the impact of various options for re­forestation speed, and direct solar radiation effects on the treatments (such as shading, mulching, vegetation biological processes of managed Douglas-fir in the control), comparing their effects on seedling water North American Pacific North-west region, conclud- stress to those occurring with normal planting. ing that the resulting landscape structure depends on transfers of energy and mass, as well as species 11.4.2.8 Climate change impacts and interactions, all of which need to be captured in adaptation models or assessment methods. They argued that such information is useful for habitat management 11.4.2.8.1 Productivity, drought and losses due to and species conservation. disturbance events In the eucalypt forests of south-eastern Queensland Romme and Turner (1991) were among the first (Australia), Eyre and Goldingay (2003) used researchers to attempt the application of a concep- Poisson regression to detect the influence of tual model to assess impacts of different plausible climate and other habitat factors on activity by future climate scenarios on vegetation structure, 11–36 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES and hence biodiversity and management, in the future climate. The results indicated that these Yellowstone region (United States). One of their forests would increase water use at the northern principal outcomes was to suggest monitoring edge of their range, but suffer declines in much of approaches to detect ecosystem responses to a the southern region, where loblolly pine was not changing climate, something that is as relevant sustainable. today as it was then. The need for continued moni- toring exists not least because it must be understood The Lund–Potsdam–Jena (LPJ) dynamic vegetation that models cannot be relied upon to predict model was developed for global-scale applications, changes in forest characteristics in uncertain future but has its metaphorical roots in gap models such as environments. Much of the debate concerning FORSKA. A variant of this model, LPJ-GUESS (Smith climate change results from uncertainties, such as et al., 2001) is suited for stand- to landscape-scale those related to projecting how greenhouse gas applications and has the capability to parameterize emissions may progress, and those arising from the individual species. For example, Hickler et al. (2004) incomplete collective understanding of the applied it to the Great Lakes region of North America, responses of the physical climate to changes in finding that disturbances (wind and fire) are major atmospheric composition. Using ecological models controls on species composition and biomass produc- to predict responses of forests to these climatic tion. The model can be used to investigate climate changes adds a third level of uncertainty. It is widely change impacts on these processes. accepted that one approach, possibly the only approach, to addressing these uncertainties is to In Europe, Nabuurs et al. (2002) compared multiple perform factorial intercomparisons of models process-based models driven by a single climate driven by multiple climate scenarios. scenario and alternative management scenarios at 14 forest sites. The results were used as input to the In central Germany, work by Lindner and European Forest Information Scenario (EFISCEN) colleagues focused on the application of a modi- model, designed for large-scale forest resources, to fied version of the FORSKA gap model linked to project climate change impacts over 50 years for GIS and driven by gridded climate data to investi- 130 Mha of forest. gate risks and adaptation potential of natural forests, and hence to assist in making management 11.4.2.8.2 Carbon management decisions. In Lindner et al. (1997), two gap models, FORSKA-M and FORCLIM (for example, Bugmann The extensive work of Kurz and Apps (1999) has and Solomon, 1995) were compared to assess been targeted at the development of a comprehen- responses to multiple scenarios of future climate. sive tool for assessing forest carbon budgets and They concluded that FORSKA was better at repre- providing direct input to management and policy senting the role of soil water in determining the development questions. This work is now encapsu- potential natural vegetation, whereas FORCLIM lated in the user-friendly CBM-CFS3, which is was better at imposing climate limits on species applicable at the scale of forest management units distributions. Later they used FORSKA-M to inves- and may be downloaded from the Canadian Forest tigate risks for the long-term management rotations Service’s Website. under a combination of two climate scenarios and three management scenarios for the period 1990– Other work previously mentioned has also investi- 2100 (Lindner et al., 2000; see also Lasch et al., gated the potential impacts of forest management 1999, for a description of the statistical method for scenarios on GHG mitigation at national to global developing climate scenarios). In general, the scales (for example, Betts, 2000; Falloon et al., 2002; results showed that increasing drought would Turner et al., 2004; Vetter et al., 2005; Briceño- likely result in appreciable changes in forest Elizondo, 2006). composition, requiring adjustments to manage- ment and wood production planning. 11.4.3 Fire weather applications and models United States forest researchers have used PnET-IIS (a process model running on a monthly time step) 11.4.3.1 Fire danger rating and fire behaviour to assess effects of climate change on water use by prediction loblolly pine forest in the south-eastern United States (McNulty et al., 1997). They validated simu- In the United States and elsewhere, good fire lated results against observed historical variations weather information is crucial for fire management of forcing climate and drainage responses and then planning under two different circumstances. Before investigated responses to two GCM scenarios of any fires occur, the risks posed by the fire CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–37 environment – basically the combination of fuel, model from Pennsylvania State University (Anthes topographic and weather conditions in a given area and Warner, 1978). MM5 generates most of the – are assessed by means of fire danger rating. After weather data needed by NFDRS in the surface layer an active fire is identified, on the other hand, its of the model. A post-processor extracts the weather growth potential and the consequent risks are data at hourly intervals of a 48-hour forecast period assessed by a fire behaviour prediction system, and computes the corresponding NFDRS indices which also depends on fuel, topographic and over the area of interest. This process requires weather inputs. In either case, various mathematical topographic and fuels data on the same grid as the models relate fire potential or fire behaviour weather data. characteristics to observable characteristics of the fire environment. The predominant fire danger Studies of the MM5 applications so far have had rating tool in the United States is the National Fire mixed results. Mass et al. (2002) examined MM5 Danger Rating System (NFDRS), described in section performance in predicting surface temperature, 11.5 below. A relatively new system deployed in the wind, pressure and 24-hour precipitation over the United States for fire behaviour prediction is United States Pacific North-west. They found that FARSITE, which inherited the core fire model used decreasing the model’s horizontal grid spacing from in NFDRS. As a result, NFDRS and FARSITE share 36 km to 12 km significantly improved forecast the same weather data requirements in many accuracy, but that a further decrease of spacing to 4 respects. On the other hand, these requirements km did not. They noted, however, that the differ radically in terms of spatial and temporal 4 km simulations produced more realistic meso­scale resolution. This section compares how weather data structures. With smaller and more pronounced are used in each system. features, they suggested that timing errors in fore- casting the movement of the features might have degraded the skill scores. Yang et al. (2005) compared 11.4.3.2 An evolving fire danger rating system MM5 simulations for the island of Hawaii at grid The Forest Service of the United States Department intervals down to 3 km with mesoscale data of Agriculture (USDA) introduced NFDRS for collected for the Hawaiian Rainband Project in the national application in the United States in 1972 1990 summer. They concluded that the model did (Deeming et al., 1972). Major modifications well overall in representing thermal, wind and occurred in 1978 (Deeming et al., 1977) and 1988 precipitation fields, but local errors occurred for (Burgan, 1988). Changes since then have been various reasons, including misspecifications of the evolutionary, and have been based on improve- initial fields and land-surface characteristics. ments in information processing and dissemination resulting from progress in computing and tele­ Hoadley et al. (2006) used the Pacific North‑west communications technologies. Section 11.3.3 MM5 simulations to compute NFDRS indices for describes how remote automatic weather stations Idaho and Montana during the 2000 fire season. have improved fire danger rating. This technology They found that the 4 km grid spacing improved takes advantage of satellite communications and predicted indices compared with the computer-controlled monitoring of weather 36 km grid interval, but the predictions were conditions. consistently low. The simulations represented the trends well, which is an important consideration for fire management applications. 11.4.3.3 High-resolution fire danger rating A secondary benefit that fire danger rating has 11.4.3.4 Fire behaviour prediction derived from computing advances is the prolifera- tion of high-resolution weather forecasts resulting The near future will likely see increasing use of fire from accessible supercomputing. In 2001, the USDA behaviour prediction systems capable of simulat- Forest Service funded five prototype high- ing the growth of fires on the landscape. High- resolution weather modelling centres to support resolution weather data are critical for this fire and air quality managers in the United States. application. In the United States, the FARSITE They produce experimental gridded fire danger system is now being introduced in operations for forecasts down to a 4 km grid interval in selected wildfire incident management. The weather data areas of the country (see http://www.fs.fed.us/ requirement for FARSITE defines a key role for fcamms/). high-resolution weather modelling, but an inte- grated fire weather/fire behaviour modelling The modelling centres independently run the MM5 system for operational use is still in the research weather model, which has its origins in a research and development phase. A significant gap exists 11–38 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES between the grid spacing of the weather fields serious challenge in this study. Under these (4 km) and the typical FARSITE terrain and fuels conditions, it is important to predict both wind data (30 m). At the given resolution of the weather speed and direction accurately, because fire spread field, it is currently assumed that weather condi- depends critically on wind/slope interactions. tions are uniform over the more detailed subgrid Moreover, even a 2 km grid interval might be of the fuels and terrain data. This problem requires inadequate for a weather model in steep terrain more research. with narrow canyons and valleys. The study described statistical methods to quantify the fire A case study by Fujioka (2002) compared the growth simulation errors. Uncertainties in fire observed growth of a Southern California fire with spread predictions are represented by probability- an integrated weather/fire simulation of the fire in weighted error bounds. This kind of information its early pre-suppression phase. He used a mesoscale will be needed to qualify fire spread predictions, spectral weather model (MSM) adapted from a given the complexity of fire growth modelling. regional model operated by the United States National Weather Service (Juang, 2000), with a horizontal grid spacing of 2 km. FARSITE simulated the fire growth with the weather fields from MSM 11.5 FUEL STATE ASSESSMENT FOR and gridded terrain and fuels data spaced at 30 m FOREST, BUSH AND GRASS FIRES intervals. The simulated fire perimeters can be displayed graphically with the input wind field 11.5.1 Introduction (Figure. 11.3). Wildland fires, including bush, forest and grass fires, The simulated fire growth compared marginally intrinsically involve agricultural meteorology and with the actual fire growth. Neither the magnitude the operational tailoring of meteorological forecasts nor the direction of fire growth was well to suit the needs of firefighting agencies. In addition represented. The complexity of the real fire to accidental or unscheduled fires, there is also a environment, especially the steep terrain, posed a need for prescribed fires, which, in some ecosystems,

Figure 11.3. MSM/FARSITE simulation of the Bee Fire, 29 June 1996, in the San Bernardino National Forest, California. The vectors in the left frame represent the wind field from the MSM model and the closed loops are the simulated perimeters over time. CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–39 form an important element in the management of fire behaviour. A fire has been found to change the ecology, economy and protection of forests and from two to three dimensions when the energy other ecosystems, including agricultural and pasto- conversion rate in the convection column as a ral systems. The task of the agricultural meteorologist function of height above the fire (for a height of is to understand the role of weather and climate in about 300 m) exceeds the rate of flow of kinetic the production of fuel such as grass, bushes and energy in the wind field (Davis, 1959). A firestorm forests, as well as the weather-related needs of all fire is a blow-up of such size and intensity that it can management agencies. be considered as a heat cyclone with cyclonic wind circulation evident in the indraughts. The The necessary ingredients to maintain a fire are convection column may be capped with a cumu- given in a fire triangle concept; this concept portrays lonimbus anvil. The best-known example is the a triangle with each side sequentially labelled fuel, “Hamburg firestorm” described by Ebert (1963). A oxygen and heat. The absence of fuel, oxygen or large forest fire experiment conducted in Siberia the heat produced causes the fire to burn out. (the 1993 Bor Forest Island Fire Experiment) Firefighting methods are based on breaking the generated a firestorm described by the Fire triangle by cooling the heat component, smother- Research Campaign Asia-North (FIRESCAN) ing the oxygen or removing fuel. Science Team (1996). The provision of a meteoro- logical service to assist firefighting and fire Nature provides omnipresent oxygen and can also management organizations in fire-prone areas is provide a source of ignition, for instance, the strike probably the most important application of oper- of lightning; however, humans can sometimes ational agrometeorology. control the fuel component. The controllability of fuel highlights the importance of fuel in all fire 11.5.2 Weather-related elements management considerations. Of all the factors listed by both Foster (1967) and Fires can be considered in either of two broad McArthur (1962), the two most important weather categories: aspects, or weather-related elements, affecting the (a) Those whose behaviour can be predicted behaviour and rate of spread of wildland fires are with some success taking account of weather, undoubtedly wind velocity and fuel moisture. The terrain, and so forth; main effects of the wind include acceleration of the (b) Those whose behaviour is erratic or unpredict- supply of oxygen and movement of combustion able. products, thereby increasing fire intensity and spread, and a fanning and bending over of flames, It is convenient to define wildland fires, either which in turn focuses radiation onto unburnt fuel, controlled or uncontrolled, as: greatly increasing the rate of spread of a fire. In the (a) Ground fires, such as those burning at or case of large fires with active convection columns, below ground level in organic soil, peat, tree the transport by wind of burning embers from the roots, or coal or sulphur seams; top of the convection column (generally with the (b) Surface fires that burn in grass, scrub or forest velocity of the low-level jet, possibly 500 m high) litter; causes spot fires ahead of the main fire front. (c) Dependent crown fires that burn in treetops supported by surface fires directly below; they Byram (1954) states that the most consistent feature do not progress ahead of the main surface of the wind field associated with extreme fire behav- fire; iour is a low-level wind jet. Because wind varies (d) Independent or running crown fires that burn during the day and from one day to another, Byram in treetops without the support of ground fire classifies wind profiles into about ten categories; a and progress independently from and ahead feature of most profiles is the low-level jet, which of the initial surface fire. implies a layer of decreasing wind speed with height, namely, a negative wind shear above the jet Each type of fire can display a varying degree of stream. The most dangerous profiles can be consid- intensity, for example, when the geometry of a ered to have a jet close to the ground. Byram wind fire changes from an essentially two-dimensional profiles vary diurnally and in highlands may have a surface fire to a three-dimensional crown fire. different classification due to elevation. Because of Extreme fire activity may be termed a “blow-up inherent difficulties in forecasting, the Byram wind fire”. The essential characteristics of a blow-up profiles have been used more to explain a past event fire are violent convection and extensive spot- than to facilitate the forecasting process. Perhaps ting, together with uncontrollable and anomalous when fire weather meteorologists regularly attend 11–40 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES fires and measure winds in situ, more use will be atmosphere; if this dry air subsidence reaches the made of the Byram classification (see also ground at night, wildland fires often burn as actively 11.5.7.3). overnight as during the day.

When air flows from higher to lower elevations as Atmospheric instability and cloud formation can with a foehn wind, air that has lost moisture on the result in lightning strikes, which are extremely windward side of a mountain range warms adiabat- important for fire occurrence, especially in ically on descent on the lee side and can cause inaccessible, high-elevation and high-latitude severe fire weather conditions. Local winds such as localities during the fire season. sea breezes and upslope and downslope winds, together with those funnelled through mountain Countries that are threatened by wildfires have barriers, all play a part in fire weather (see also adopted or developed fire danger indices that 11.5.7.2). usually combine elements such as wind speed, air temperature and humidity, along with fuel state Relative humidity may vary greatly from one spot to and quantity, to give an indication of the rate of another depending on topography and the presence spread of a fire once it has been started. It is obvious of irrigated fields, streams and other features. Beneath that not all salient features of fire spread are a temperature inversion, relative humidity, for contained in the fire danger indices. For this reason, instance, generally decreases with height. Byram ancillary comments/forecasts, and preferably a (1957) points out a dual role for relative humidity in briefing to fire authorities, must accompany each the rate of spread of a fire in certain types of extreme statement passed to firefighting organizations. As behaviour (through its influence on fuel moisture stated in Systems for Evaluating and Predicting the content), such as the effect on fuel combustion rate Effects of Weather and Climate on Wildland Fires and the rate of spread of the flame front, as well as (WMO-No. 496), the physical laws that control the increasing or decreasing the probability of ignition behaviour of wildland fires are the same in both from spotting and hence, the acceleration of rate of tropical and subtropical areas. The main difference spread and intensity of a fire. is the relative importance of natural and man-made fires. A review entitled Wildland Fires Particularly in The ignition probability for most fuel can be essen- Tropical Regions (WMO, 1982) reports that over 90 tially zero at 25 to 30 per cent relative humidity and per cent of fires are caused by human activities. reach the maximum for oven-dried material. Low ambient relative humidity helps to bring fuel 11.5.3 Grassland fuel state assessment toward the latter state. On bad fire days it is usual for relative humidity to be very low and tempera- 11.5.3.1 Growth of fuel ture to be high. The combination of low relative humidity and high temperature promotes the rapid The fuel component of the fire triangle merits loss of water from dead fuels and can also lead to a consideration because it lends itself to modification high transpiration rate for living vegetation, which at all times of the year. Oxygen is always available, will lower fuel moisture content drastically, espe- but its supply is enhanced by certain stability and cially if the available soil moisture is near wind situations; the source of heat is generally an depletion. imposed factor, such as lightning, and does not lend itself to overall control. The climate of a region Although high ambient air temperature has some determines the type, amount, distribution and state effect in raising fuel temperature, insolation is of fuel available for the outbreak of fires. Fuels are much more important in this respect; air tempera- found in almost infinite combinations; any organic ture acts indirectly on fire behaviour through material that will burn can be considered as fuel, thermal turbulence. As a general rule, convective whether it is below or at ground level, such as peat, activity is greater on hot days, facilitating the coal or sulphur seams; at surface level, such as removal of combustion products from a fire and grasses and shrubs; or above the ground, as with hence favouring its development, and creating forests and trees. Every fuel has an inherent inflam- updraughts to carry burning embers well above the mability potential, which can generally be realized, fire tops. depending primarily upon the amount of water in the fuel. It is necessary to consider both living and Atmospheric stability in the lower layers is closely dead fuel and the role played by water in each type. related to fire behaviour and it may either suppress In living plants, the interaction of the environment or promote vertical air motion. Air mass subsidence with plant function and structure is basic to an can bring very dry air from high to low levels in the understanding of fuel production. CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–41

growth. Herbaceous plants have only primary 11.5.3.1.1 Plant function growth; grasses, for example, have meristems Plants are composed of microscopic cells, each with located at the base of their leaves and this enables its own specific function; an interaction of these grass to produce new tissue after being cut or grazed cells is necessary for the survival and growth of each by livestock. plant. A typical plant cell has a rigid surrounding wall made of cellulose, which encases a pliable In other plants, the cambium provides for lateral membrane; within the membrane there is a nucleus growth, increasing the diameter of roots, branches that regulates the activity of all the cellular and stems; this is termed secondary growth. The structures, such as the chloroplast, which is growth of woody perennials that develop into trees associated with photosynthesis, and the is dependent on the deposition of new tissue over mitochondrion, which regulates the respiratory old. The old system ceases to function and forms functions of the plant. Most cells also contain a the older wood at the centre of the tree, while the centrally located, large fluid-filled sac within the old phloem, which is no longer functional, is shed membrane, which is called the vacuole. Each cell by many plants as bark. Parts of plants may cease to entity is interconnected with others by small strands grow and may be shed by abscission; although this that pass through the rigid cell wall, allowing fluids commonly occurs in leaves, flowers and roots, the to pass from one cell to another. In order to survive, shedding of branches may also occur. plants must collect and retain water and be able to exchange gases and produce their own food and The moisture content of all new foliage is highest at energy. Water is the vehicle by which nutrients are the time of emergence; it is commonplace for the transported from the root system throughout the moisture content of new foliage to be two or three entire plant. In the leaves some of the water is used times that of the dry weight. Moisture content in the production of plant material as a result of normally declines rapidly during leaf growth and photosynthesis; some of the water then transfers development, with a subsequent slower decline as the manufactured hydrocarbons to growing tissues leaves become drier. In an annual species the plant and storage points. Some water is also transpired dies, while in deciduous shrub and tree species the through leaf pores in the form of water vapour. foliage dies. In evergreens, only some leaves die and fall away over a given period. A plant, on reaching In order to perform essential functions, plants have maturity, may remain at that stage for days, weeks developed three basic structures: roots, leaves and or even decades, depending upon the species. When stems. The leaf structure may vary from plant to a plant becomes overmature either in total or in plant, but it must carry out the essential functions part, deterioration begins in both the structure and of the exchange of gases, photosynthesis and tran- function of the plant and its tissues. When this spiration. The roots absorb water and minerals from process, known as senescence, occurs, the plant the soil and transport them to stems and leaves; begins contributing to the dead fuel load. they also provide storage and act as a support system for plants. The stem supports foliage, provides stor- 11.5.3.1.2 Live fuel moisture age, trans­ports substances between foliage and roots, and also absorbs gases from the atmosphere. It is important to note that any living vegetation Transport within the plant occurs via the xylem or can be burnt, provided that the associated fire has phloem; the latter transports more complex materi- sufficient intensity. Nevertheless, it is generally als such as sugars, while the xylem transports water accepted that green fuel does not significantly and any dissolved substances. Xylem tissue is often contribute to the rate of spread of fires. The called wood and has been referred to as the “plumb- Australian McArthur Grassland Fire Danger Meter ing” of the plant. The phloem operates in parallel (Mark 4), for instance, only features a degree of with the xylem system and transports materials in curing between 70 and 100 per cent. At 70 per cent many directions throughout the plant according to cured, with an air temperature of 41°C, a relative supply and demand. humidity of 10 per cent and a wind of 25 km/h, the rate of spread of a fire, on the McArthur scale, only The energy for growth comes from the carbo­ reaches the upper limits of moderate, or a rate of hydrates that are produced in photosynthesis, less spread of a little less than 1 km/h. the energy needed for respiration. Plant cells divide and form two new cells, identical with the parent, Finocchiaro et al. (1969) reported on grass fires that through the process of mitosis occurring at the tips occurred in Victoria, Australia, on 8 January 1969. of stems, branches and roots, and in various buds. The fires were unusual in that they occurred after This type of plant growth is known as primary three weeks of cool weather with considerable 11–42 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES rainfall. The grass fuel report on 6 January 1969 was carefully examined and the degree of curing finally at least 50 per cent green over the fire site; these established and reported on a weekly basis. A space grass fires caused the loss of 22 lives and a great on the card is provided for general comments such amount of property damage, and they burned out as “the dry spell during the past week has acceler- approximately 3 000 km2 of grassland. Schroeder ated curing”. An operational agrometeorologist and Buck (1970) stated that after the moisture then examines all the cards and assigns a curing content of grass has dropped to 30 or 40 per cent status to each region under his control after liaison during the curing stage, grass will burn on a good with all relevant fire authorities. As an approxima- burning day. The severity of the 8 January 1969 fire, tion, fully cured grass is once more considered to be considering the fuel state, was most unexpected 100 per cent cured within hours after rainfall has and demonstrates the need for continued research cleared. into fire behaviour. 11.5.3.3 Weighing methods Annuals, such as grasses, have a limited growth season and are much more sensitive to seasonal Another method employed by fire authorities to and short-term weather variations than most other assess fuel quantity and state is that of weighing fuels. Grasses have shallow roots and primarily the amount of grass per unit area. In general, a depend on adequate surface soil moisture for full relatively large area of grassland that can be top development; these grasses have a limited regarded as representative of a particular region is growth season, reach maturity, then come to seed selected. From this selected area, a random point is and subsequently cure or dry. Whenever surface obtained by an observer who simply throws an moisture at the beginning of the season is deficient object over his shoulder and uses this as a central or depleted by a spell of hot, dry weather, the point to place a prepared frame that measures one growing season is shortened markedly; in this case square metre; all of the grass within this frame is the curing season may range from three weeks to collected and placed within a labelled plastic bag two months, depending upon prevailing weather. for weighing. For analysis purposes, this process is Grasses may reach a highly inflammable stage repeated within the region over a number of places. while broadleaf foliage is still in prime growth. Each plastic bag (with contents) is weighed before and after drying. The accepted method to measure Perennial grasses have deeper and stronger root the moisture content of a fuel is to express as a systems than annual grasses and are thus less sensi- percentage the deduced amount of water in the tive to short-term surface-soil moisture depletion. fuel, divided by the oven-dry weight of the fuel. In climates that have a marked growing season From such observations it is possible to provide limited by hot, dry weather, however, the cycle of information such as: perennial grasses is similar to annual grasses, but (a) Average height of fuel (from observation); only the leaves and stems down to the root base (b) Average tonnes of fuel per hectare; are affected. Normally, the moisture in live fuel (c) Average fuel moisture content. acts as a sink for energy produced by the parent fire and consequently the overall heat of the fire is 11.5.3.4 Satellite-derived vegetation indices reduced. Some live fuel absorbs nearly as much heat to vaporize the water content of the fuel as With the advance of satellite technology, it is that produced from the combustion of the live now possible to use satellite images to evaluate fuel. the curing of herbaceous fuels over an extended area. For herbaceous vegetation, the drying of plants follows a decrease in chlorophyll activity, 11.5.3.2 Initial measurement practices which can be monitored from satellite images Practices associated with the measurement of grass- using standard vegetation indices. The most land fuel state and amount have evolved slowly. common are those that measure the spectral The earliest assessment of fuel state in Australia contrast between the red (600–700 nm) and the begins with a visual appraisal, usually by a long- near-infrared reflectance (700–900 nm). Other term resident of the area. The Bureau of Meteorology indices that are more related to plant water sends out a supply of prepaid and addressed cards; content use the spectral contrast between the the observer only has to tick an appropriate box to near-infrared and the short-wave infrared (1 200– signify whether the fuel is partially or totally cured 2 500 nm). Until a few years ago, the most in steps of about 20 to 25 per cent. A small bundle commonly used sensor for fuel moisture estima- of grass that is representative of the surrounding tion was the Advanced Very High Resolution countryside has to be selected; the sample is then Radiometer (AVHRR) on satellites operated by the CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–43

United States National Oceanic and Atmospheric empirical model has been established, operational Administration (NOAA), with 1.1 km resolution aspects of the model can be used to advantage. for vertical observations. More recently, the Moderate Resolution Imaging Spectroradiometer Radiation is the principal component of the energy (MODIS) sensor on board the Terra and Aqua balance equation as applied to the calculation of satellites, with 500 m resolution and additional evapotranspiration. The most accurate way to spectral bands, has been providing more precise obtain the net radiation component at a point is by information for fuel water estimation. To reduce measurement with a net radiometer. Because this the effects of clouds in the images, processing of approach is quite impractical on a scale required for both AVHRR and MODIS is commonly based on fuel state consideration, an approximate value must multiday composites (between 10 and 15 days be used. The outgoing long-wave radiation is being the most common). These composites are approximated by the Stefan–Boltzmann equation; created by selecting the less cloudy pixel within the incoming global radiation, derived from satel- the daily series, which frequently entails identifi- lite imagery, can be obtained within 10 or 15 per cation of the day with the maximum vegetation cent of the actual value. Thus a field of evapo­ index value in the daily series. Both AVHRR and transpiration for grassland could be approximated MODIS provide daily world coverage, by compar- and a good estimate of wilting point or moisture ison with the 16-day cycle of LANDSAT or other loss obtained. medium-resolution satellites, which may be reduced in cloudy areas. Ground-truth observa- 11.5.3.6 Estimating dead fuel moisture tions are needed to validate estimations of fuel moisture content provided by satellite imagery. It is not convenient to measure dead fuel moisture in the field directly, so it is usually estimated indirectly by various methods. Very fine dead fuels such as 11.5.3.5 Use of fields of solar radiation cured grass, well-aerated pine needles and the surface Solar radiation is the ultimate cause of vegetation layer of larger fuels may be in approximate equilib- growth and also of the drying out of annual grasses rium with the immediate environment. It is possible and other fuels. Solar radiation supplies the energy to use either actual or prognostic values of environ- to change liquid water into vapour in evaporation mental air temperature and humidity to obtain a and evapotranspiration and to build chemical reasonably accurate estimate of the moisture content energy into carbohydrates that later can be released of this type of fuel and hence its inflammability. as heat in a bush fire. 11.5.4 Forest fuel state assessment Solar radiation over large areas has been estimated in the past from observations such as cloud cover Moisture content is important in determining and sunshine hours. There have, of course, been whether fuels will ignite and burn and thus strongly routine point measurements of direct and diffuse influence fire behaviour. Fuels are found in a great global radiation, but the density of observations number of combinations of shape, size, amount, has always been too sparse to extrapolate the results arrangement and species. Variations in climatic over significant areas. Extraterrestrial radiation for factors, along with local factors such as latitude, all latitudes and longitudes has been tabulated in slope, aspect, soil types and hence vegetation, have the past, but never before has such comprehensive ensured that many countries have developed their cloud coverage been available. Cloud coverage from own means of assessing forest fuel states. The nature geostationary satellites can now generally be of the problem has meant that countries concerned obtained at least once or twice a day and possibly with fires have also developed their own systems every hour or half-hour during daylight hours. and consequently, the transfer of a method devel- Computer programs exist that can be used in oped for a particular latitude or country, in all conjunction with satellite imagery to provide a field probability, will not totally solve the problem for a of total daily radiation. If the amount of radiation different latitude or country. A number of indices that is reflected back to the satellite by cloud cover will be considered. is assessed and subtracted from the extraterrestrial value, a field of global radiation can be deduced 11.5.4.1 Keetch–Byram index from satellite cloud imagery. This index (Keetch and Byram, 1968) was devel- The energy field obtained on a daily or weekly basis, oped from a theoretical basis for a subtropical apart from being invaluable for climatological reasons, summer rainfall forest or wildland area in the can be used to estimate drying stages of fuel. Once an south-eastern United States. The Keetch and 11–44 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Byram method makes several assumptions in index and the Keetch–Byram estimate. Tables were developing equations to describe the degree of compiled to provide daily estimates of evaporation drought or soil moisture deficiency. The assump- and daily maximum temperatures. The meteoro- tions include: logical input is similar to that required for the (a) No loss by runoff when the soil is below field Keetch–Byram index. capacity; (b) The significant moisture relationship that Judging by the observed runoff, the soil dryness exists in the upper soil–duff layer has a field index gives a better result than the Keetch–Byram capacity of about 200 mm; it is assumed that index for mid-latitudes. The approximation for 200 mm of rain would completely saturate the evapotranspiration can be estimated by using a soil; Thornthwaite type of equation on a daily basis, or a (c) The lowest soil–duff moisture content level is long-term monthly evaporation pan value adjusted at wilting point; this layer is assumed to gain for daily values. Both methods indicate areas where moisture by rainfall and lose it by evapora- improvements could be made to reflect daily tion; evapotranspiration better. (d) The vegetation density is a function of annual rainfall amount, and this determines the rate 11.5.4.3 The Palmer index at which vegetation can remove moisture from the soil–duff layer when weather vari- Palmer (1964) developed a meteorological drought ables are constant; index that is calculated weekly during the growing (e) No evapotranspiration takes place below 10°C season in the United States. Palmer notes that an (probably because that is about the minimum arid region can always use more rain and his drought dewpoint for places such as Florida); index is given for a particular location. The Palmer (f) A uniform allowance is made for interception index is based on Thornthwaite’s method of esti- of the first 5 mm per rain period; mating potential evapotranspiration. The index is (g) Once interception is separated from evapotran- directly propor­tional to the previous index on a spiration, there is no evidence to justify the given timescale, plus a moisture anomaly index. assumption of greater evapotranspiration This index is proportioned to precipitation minus with higher annual rainfall. normalized values of evapotranspiration, soil recharge, runoff and loss (that is, moisture is The basic idea behind the Keetch–Byram index is removed if there is no rainfall). The Palmer drought that evapotranspiration losses are related to daily index can range from values greater than 4, which maximum temperature. This approach seems to is extremely wet, through 0, where values are near have worked fairly well in practice, even though in normal, to negative values. A value below –1 is a theory the simple input, which is similar to the mild drought, below –2 indicates a moderate Thornthwaite and Holzman equation drought, below –3 a severe drought and below –4 (Thornthwaite and Holzman, 1939), should not be an extreme drought. Negative values of the Palmer used for periods of less than a season or even a year. drought index lend themselves to a measure of dryness that can be applied to fuel on a broad The Keetch–Byram index was incorporated by scale. McArthur (1967) into his Forest Fire Danger Meter (Mark 4) in 1966. The daily meteorological input 11.5.4.4 Other methods required is maximum temperature and rainfall. Despite the lack of theoretical soundness, the 11.5.4.4.1 Fuel moisture indicator sticks Keetch–Byram index is still being used, even in non- forested areas, by some Australian fire authorities. A practical means of estimating the moisture content of medium-sized fuels can be achieved by using wood moisture indicator sticks. Generally, 11.5.4.2 Tasmanian soil dryness index the indicator sticks chosen consist of a set of four Mount (1972), using the Keetch–Byram index as a cylindrical pieces weighing about 100 g and meas- base, derived an index of soil dryness that estimated uring approximately 500 mm × 12.5 mm; these the amount of rain needed to bring the soil profile sticks are spaced about 6 mm apart and are back to field capacity. Mount used the difference suspended in the open on a wire rack exposing between the observed rainfall and the observed them about 250 mm above a typical bed of forest runoff as a true measure of the soil dryness before litter. The sticks are weighed on a daily basis and onset of the rain. Observed runoff was used to the moisture content of the fuel is then estimated compare estimates made from the soil dryness from the known oven-dry weight of the indicator CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–45 sticks. Trends of moisture content are used along 0.63 (28 – 5.5) = 14.2, thus the moisture content with derived empirical relationships involving would be reduced from 28 to 13.8 per cent. Similarly, precipitation, number of days without rain, daily at the end of the next time-lag period, the moisture drying conditions, and so forth, to assess moisture content would be 8.6 per cent. The moisture content content of large fuels. at the end of five or six time-lag periods very closely approximates the equilibrium moisture content. For a fine fuel such as grass, the average time period 11.5.4.4.2 Direct measurement in this case would be a matter of minutes, while for A pamphlet issued by the USDA points out that logs of 115 cm diameter the time lag is on the order microwave ovens can be used to dry fuel, if care is of 36 days. Cured grass with a short time-lag period taken to prevent charring (McGreight, 1981). can be expected to achieve an equilibrium moisture content in a relatively short time after rain has 11.5.5 Treatment of fuel state after completely dried from the surface. This illustrates precipitation the contradictory use of soil moisture as an indica- tor of grassland fuel state. Even though fine cured Even though a fuel has been completely dried out, grass is considered to dry rapidly after heavy rain, compensation may have to be made for the amount there is still the problem of a saturated soil beneath of moisture incorporated into the fuel after precipi- the dry grass, which is not accounted for in esti- tation. It is possible for a dry fuel to be considered mates of fuel moisture that are used in the 100 per cent cured one day and then, after precipi- calculation of fire danger. tation, as the equivalent of a 100 per cent green fuel. Then, as drying occurs, the fuel progressively If a fire burns dry grass above a very moist soil, some contains less moisture until it is again considered energy from the fire would no doubt be used to 100 per cent dry. The time taken for a fine cured evaporate the moisture in the soil into vapour and fuel to dry out again after rain is considered to be a thus have some effect on the fire. In general, at least matter of hours, while heavy fuel can take days or one or two days elapse after precipitation before even months. dangerous fire weather recurs; by this time there is probably a fine, dry tilth on top of the moist soil and a fire would be reasonably well insulated from 11.5.5.1 Grassland fuel moisture a previously wetted subsoil. Dew plays an impor- Schroeder and Buck (1970) also provided a method tant role in wetting fine fuel such as grass in early that they called the time-lag principle, which morning situations (Hicks, 1983). Fire danger expressed absorption and drying rates based on meters, such as the McArthur Grassland Fire Danger both equilibrium moisture content and fuel charac- Meter, use mid-afternoon meteorological values teristics. According to this principle, the approach and assume that any moisture has been dried from to equilibrium values from mois­ture content either the fuel. Whenever the grass temperature falls above or below equilibrium follows a logarithmic below dewpoint, dew can be expected to form on rather than a linear path, as long as liquid water is grassland vegetation; this is a frequent occurrence not present on the surface of the fuel. If a fuel is in mid-latitudes. Cheney and Sullivan (1997) exposed in an atmosphere of constant temperature provide further information on weather, grass fuel and humidity, the time needed to reach equilib- moisture and its impact on grassland fire rium may be divided into periods in which the behaviour. moisture change (1 – 1/e) = 0.63 of the departure from equilibrium, where e is the base of natural 11.5.5.2 Forest fuel moisture logarithms, 2.7183. The duration of these periods is a function of the fuel and is referred to as the time- When senescence (or browning) affects an entire lag period. It is pointed out that although successive plant, although growth and water circulation cease, time-lag periods for a particular fuel are not exactly the resultant dead vegetation retains the original equal, the principle is a useful method for express- structure of cells, intercellular spaces and capillar- ing fuel moisture responses if average time-lag ies, or “plumbing”. The processes described below periods are used. are explained by Schroeder and Buck (1970). Dead vegetation can soak up water like blotting paper An example is given where a fuel with a moisture until all spaces are filled, although the process is content of 28 per cent is exposed in an environ- much slower. The next, equally important aspect of ment in which the equilibrium moisture content is fuel wetting is the fact that materials constituting 5.5 per cent. At the end of the first time-lag period, dead cell walls are hygroscopic; these dead cells the initial moisture content would be reduced by have an affinity for water, which makes it possible 11–46 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES for them to absorb water vapour directly from the moisture removal progresses below the fibre atmosphere. The latter process is one of chemical saturation point, the bound-water vapour pressure bonding. The hygroscopic character of the cell gradient declines and as a consequence, the outward material attracts water vapour and causes several vapour pressure gradient is gradually reduced. molecular layers of atmospheric water to adhere to Either of two conditions must prevail to assure the cell walls; there molecular layers are called continued significant drying: bound water. The layer of water molecules immedi- (a) Maintenance of a surrounding ambient ately adjacent to the cell wall has the strongest vapour pressure appreciably below the declin- bond and the lowest water vapour pressure; succes- ing bound-water vapour pressure; sive molecular layers have progressively weaker (b) Heating of the fuel at a rate that will increase bonds and higher water vapour pressure until the its temperature and correspondingly its cell walls become saturated. bound-water vapour pressure, so as to main- tain the outward gradient. At the level of saturation, the vapour pressure in the outer molecular layer of water on the wall is Both processes operate in real-life situations, some- equal to the vapour pressure of free water and is times in the same direction, as for a bush fire when thus at saturation vapour pressure. This amount of the fuel is heated by radiant heat from the fire, bound water at the fibre saturation point varies increasing the bound-water vapour pressure. The with different materials, but for most plant ambient vapour pressure is reduced by the marked substances it is in the range of 30 to 35 per cent of drying associated with the fire. the dry fuel weight. It is not possible for free water to persist in a cell until the bonding phenomenon 11.5.6 Discussion of climate-based has been completed; it is then possible for free water indices to pass through the cell wall by the process of osmo- sis. Before saturation level is reached, moisture is Climate-based fire danger rating systems attempt to evaporated from cell walls of higher moisture provide an answer to the following questions: content and taken up by dry cell walls of lower (a) How serious is the danger of fire starting? moisture content until an equilibrium vapour pres- (b) How fast will it spread? sure is achieved. This process is characteristic of (c) How much damage will it cause? moisture transfer within fuels in the vapour phase and always operates in the direction of equalizing “The process of systematically evaluating and inte- the moisture throughout a particular fuel sample. grating the individual and combined factors influencing fire danger is referred to as fire danger The reverse process of drying wetted dead fuel takes rating. Fire danger rating systems attempt to provide place in three distinct phases. In effect, essentially qualitative and/or numerical indices for fire potential each phase is accomplished by evaporation in a drying that are used as a guide in a variety of land manage- atmosphere, in which the direction of the vapour ment activities” (Stocks et al., 1988). Fire danger rating pressure gradient is essentially outward from the wet is concerned with those elements that cause day-to- fuel to the surrounding atmosphere. The moisture day changes in fire danger. Constant factors are can potentially be raised to 30 per cent of dry weight normally built into the index/meter and although by contact with liquid water (rain or dew, for instance). they vary from place to place, include items such as: The first phase proceeds independently of both the (a) Fuel type characteristics, for example, quan- actual moisture content and the hygroscopic nature tity, size, arrangement and inflammability; of the fuel. Drying takes place by evaporation at the (b) Topography, for example, slope, aspect, same rate as that from a free water surface. Although elevation; wind speed does increase the rate of evaporation, it (c) Ignition sources. does not affect the amount of evaporation required to reach the end-point of this first phase. The intermedi- Variable fire danger rating factors can include: ate phase is a transition step in which there is a (a) Fuel moisture content; variable change in moisture-loss rate. The rate begins (b) Wind velocity; changing slowly, within the defined limits of the (c) Air temperature; linear rate of the first phase, to the orderly decreasing (d) Relative humidity; rate characteristic of the last phase. (e) Recent rainfall effects; (f) Condition of the subordinate vegetation. The final phase depends totally upon an outward gradient between the bound-water vapour pressure The following subsection presents the most and the existing ambient vapour pressure. As commonly used climate-based fire danger systems CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–47 and, in particular, the meteorological aspects of wildfire field data. The CFFDRS currently has four these systems. subsystems (Figure 11.4): (a) Canadian Forest Fire Weather Index (FWI) System; 11.5.6.1 Historical perspective (b) Canadian Forest Fire Behaviour Prediction There have been three broad phases in the develop- (FBP) System; ment of fire danger rating systems. Objective (c) Canadian Forest Fire Occurrence Prediction assessment began in the late 1920s when Gisborne (FOP) System; (1928) developed a fire danger meter in the United (d) Accessory Fuel Moisture System. States. Similar fire danger meters were developed in Canada in the early 1930s. These provided national The FWI System (Van Wagner, 1987; Van Wagner assessments until the late 1940s, when regional and Pickett, 1985) was the first subsystem devel- systems were developed for different United States oped in the CFFDRS and it provides numerical and Canadian forest/climate types. In the late ratings of landscape-level, relative fire potential 1960s, national systems were developed in each of based solely on weather observations. The FWI these countries, and these systems have gone System has been in use throughout Canada since through minor revisions over the last two decades. 1970. The second major subsystem is the FBP Other significant fire danger systems were devel- System (Forestry Canada Fire Danger Group, oped in Australia in the 1960s by McArthur (1966) 1992), which was first introduced in 1984. It inte- and by Peet (1965). grates the effects of fuel type, weather (using FWI System outputs) and topography to predict stand- level fire behaviour, including fire rate of spread, 11.5.6.2 Canadian system fuel consumption and head fire intensity. The Canadian fire danger research began in the mid- FBP System also provides secondary outputs 1920s, and the Canadian Forest Fire Danger Rating related to fire spread distances, perimeter and System (CFFDRS) has been under development by area growth. The FOP System and Accessory Fuel the Canadian Forest Service since 1968 (Canadian Moisture System are under development. Forestry Service, 1984, 1987). The Canadian system was built using an empirical approach to fire danger The FWI System uses four daily weather inputs rating, based primarily on experimental burn and collected at noon local solar time (LST): temperature,

Risk (lightning and Weather Topography Fuels Inputs hu man-caused)

Canadian Forest Fire Weather Index (FWI) System

Canadian Forest Canadian Forest Fire Occurrence Accessory Fuel Fire Behaviour Prediction (FOP) Moisture System Prediction (FBP) System System

CFFDRS

Figure 11.4. Structure of the Canadian Forest Fire Danger Rating System (CFFDRS) (Canadian Forestry Service, 1987) 11–48 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES relative humidity, 24-hour cumulative rainfall and many different countries (Taylor and Alexander, 10 m open wind speed (Figure 11.5). The FWI 2006). System component values are valid for the heat of the day (approximately 1 500–1 700 h). 11.5.6.3 United States system Computation depends on the previous days’ output, so daily readings must be taken. The FWI Fire scientists in the United States began exploring System is comprised of six components, including the relationship of fire danger and hazard with three fuel moisture codes representing different weather, fuel moisture and ignition probabilities as layers in the forest floor, and three fire behaviour early as 1916 (Hardy, 1983). A national system was indices: the Fine Fuel Moisture Code, a numerical first introduced in 1964. The current version of the rating of the moisture content of surface litter and United States National Fire Danger Rating System other cured fine fuels on the forest floor; the Duff (NFDRS) was implemented in 1978 (Deeming et al., Moisture Code, a numerical rating of the average 1977), with optional revisions in 1988 (Burgan, moisture content of loosely compacted organic 1988). A simplified diagram of NFDRS is given in layers of moderate depth in the forest floor; the Figure 11.6. NFDRS provides an indication of Drought Code, a numerical rating of the average seasonal fire potential for large administrative areas. moisture content of deep, compacted organic layers NFDRS is a climatology-based system, and as such, in the forest floor; the Initial Spread Index, a analysis of historical fire danger is required for numerical rating of the expected rate of fire spread; proper interpretation and application of indices. the Buildup Index, a numerical rating of the total amount of fuel available for combustion; and the Fire behaviour prediction calculations were first FWI, a numerical rating of fire intensity that is used made available to the field as nomograms (Albini, as a general indicator of fire danger. As stated by 1976). Current fire behaviour prediction systems, Stocks et al. (1988), however, it is almost impossible including the BehavePlus fire modelling system to communicate a complete picture of daily fire (Andrews et al., 2005) and the FARSITE fire area potential in a single number. The FWI System has simulator (Finney, 1998), are designed to model been applied or adapted widely around the world in time and site-specific fire characteristics, such as

Fire Temperature, Wind Temperature, Temperature, weather relative humidity, speed relative humidity, rain observations wind speed, rain rain

Fuel Fine Fuel Duff Moisture Drought moisture Moisture Code Code Code codes (FFMC) (DMC) (DC)

Initial Spread Buildup Index Index (ISI) (BUI) Fire behaviour indices Fire Weather Index (FWI)

Figure 11.5. Structure of the Canadian Forest Fire Weather Index (FWI) System (Canadian Forestry Service, 1984) CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–49 rate of spread, intensity, flame length, spotting influenced most by the moisture content of fine distance and fire growth. dead fuel (1-h), and wind speed is included in the calculations. On the other hand, calculation of the Both fire danger rating and fire behaviour predic- Energy Release Component (ERC) is weighted tion systems are used in the United States to support towards heavy dead fuels (100-h and 1 000-h), and fire management decision-making in fire preven- wind is not part of the calculation. SC therefore tion, fire suppression and fire use (Andrews, 2005). reflects daily variations in fine fuel moisture and The basis of both fire danger and fire behaviour wind, and ERC reflects longer-term drying. The systems is a physically based mathematical fire Burning Index is related to flame length and is a spread model (Rothermel, 1972). Differences lie in function of SC and ERC. the source and resolution of the inputs and inter- pretation of the outputs. The Wildland Fire Assessment System (WFAS) is an Internet system that provides maps of seasonal fire NFDRS provides a systematic way to integrate and potential on the basis of a network of fire weather interpret seasonal weather trends; fuel and terrain stations and remote-sensing (Jolly et al., 2005). factors are essentially held constant. NFDRS uses Integration of National Weather Service gridded daily weather observations and next-day forecasts weather forecasts into the WFAS is under to produce indices (Figure 11.6). Weather readings development. are taken daily at the same time and location. Fuel moisture values are calculated for live grasses and 11.5.6.4 Australian system shrub foliage and several size classes of dead fuel. The fuel moisture values are then used to calculate The fire danger rating systems used in Australia are the indices. The Spread Component (SC) is those developed by McArthur (1967) for forests and

NFDRS System (simplified) Site Afternoon 24-hour Fuel moisture (FM) description weather weather carry-over values

Fuel model Relative humidity Max / min 100–h FM Relative humidity Slope class Temperature 1 000–h FM Max / min Cloudiness Temperature

Precipitation Live FM Wind speed duration

Fuel stick moisture

1–h FM 10–h FM 100–h FM 1 000–h FM Live FM

Spread Component Burning Index Energy Release (SC) (BI) Component (ERC)

Figure 11.6. Simplified information flow for the United States National Fire Danger Rating System. Weather data and site descriptors are utilized to calculate fuel moisture values, which are used to derive indices. The wedges indicate the weighting of the dead fuel moisture size classes in the calculation. 11–50 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES grasslands, and the Western Australia forest fire The drought index, combined with cumulative danger rating system for jarrah forests developed by rainfall over the last several days, defines the Peet (1965). The most widely used are the Mark 5 drought factor. Once the drought factor is set, the forest (McArthur, 1975) and Mark 4 grassland other meteorological variables used are air tempera- (McArthur, 1973) systems, which predict a rate of ture, relative humidity and wind velocity measured spread of fires in a standard fuel. Extensive descrip- in an open exposure at 10 m. Fuel moisture content tions of the McArthur system are given in McArthur (FMC) is indirectly computed by the relationship (1967), Bureau of Meteorology (1964) and Luke and among temperature, relative humidity and the McArthur (1978). drought factor. The FMC incorporated in the meters is based on clear sky conditions and temperature and humidity conditions prevailing between about 11.5.6.4.1 McArthur forest fire danger rating 1 p.m. and 4 p.m. local time. system The index used in the system is based empirically Short-term drying effects are based on the expected on several thousand experimental fires in dry changes in moisture content of surface litter less sclero­phyll forest with a 12.5 t ha–1 fine fuel rating. than 6 mm in smallest dimension. The wind speed A schematic diagram representing the Australian value is an average value over at least five minutes. system and the various inputs is shown in The relationship between the fire danger index and Figure 11.7. The Forest Fire Danger Rating (FFDR) wind is not linear and the index increases rapidly System uses the following elements of fire danger: with increasing wind speed. The indicator is (a) Long-term seasonal dryness, which is expressed designed to measure fire danger on a linear scale so by a drought index; that ignition probability and rate of spread are (b) Short-term rainfall effects based on quantity directly related to the index. Thus, the chances of a of rain and when it fell; fire starting, the rate of spread and the difficulty of (c) Temperature; suppression are exactly doubled at an index of 50 (d) Relative humidity; compared with one at 25. The index represents rate (e) Wind. of spread and thus is a measure of fire line intensity. The flame height is directly determined by the fire Long-term seasonal dryness effects are incorporated intensity. by the use of a drought index system developed by Keetch and Byram (1968) that requires measure- 11.5.6.4.2 Grassland fire danger rating system ment of daily rainfall and maximum temperature. While it may be criticized on theoretical grounds, it This system is designed for use in temperate regions does give a practical measure of soil moisture defi- with relatively finely textured annual grasslands ciency and the drying rates of various types of fuels. that go through a curing process. The meter applies

Rain Temp days since Rain RH rain temp

1 100 1 000

Fine fuel Drought moisture factor

Drought index

Wind

Fire danger

Figure 11.7. Australian forest fire danger rating system (McArthur, 1967) CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–51 to fairly dense stands of improved pastures carrying The effect of increasing wind velocity can be a total fuel loading of 4–5 t ha–1. The effects of summarized as follows: recent rain, which can be significant when grasses (a) Flames tilt forward and provide more effective are fully cured, are not taken into account by the radiation to the unburnt fuel. This causes the meter. Fully cured grass is considered to return to its unburnt fuels to pre-heat, thereby reducing pre-precipitation cured value as soon as precipita- fuel moisture; tion ceases. This leads to overestimation of fire (b) The convection column shifts to the head of danger for several days after significant precipita- the fire and the spotting process begins; tion has fallen. (c) An optimum oxygen supply is maintained in the combustion zone; (d) Flame contact with unburnt fuel is maintained; 11.5.6.5 Comparison of fire danger rating (e) The rate of spread appears to vary as the square systems of the wind speed – except at low and very Valentine (1978) compared the Australian, Canadian high wind speeds. and United States systems in a review of the New Zealand fire danger rating system in place at that 11.5.7.2 Topography time. Some pertinent findings are: (a) All the systems are hierarchical, but the Cana- A fire ignited on level ground with no wind and an dian and United States ones are more sophis- even fuel distribution will burn outwards in a circle. ticated and elemental in nature; If a slope is encountered, the shape will elongate in (b) The United States system is quasi-theoretical, the upslope direction. McArthur (1967) states that a while the Australian and Canadian systems 10° slope will double the rate of spread of fire and a are empirically based; 20° slope will increase the spread four times. (c) The Canadian and Australian systems are Similarly, each 10° downslope will halve the forward similar in response and differ from the United rate of spread. This can be explained physically by States system in several ways; the pre-heating of fuels by radiation due to the (d) NFDRS, in spite of its variety of fuel models, decreased flame angle. Also, convective heat trans- is best suited to grassy open forests, while the fer is increased and burning embers are blown into Canadian system is suited to forests with a full the fuel ahead of the fire. The rate of spread is much canopy and substantial duff layer; slower on downslopes, as the flame angle is gener- (e) The Australian system is probably most rele- ally negative. vant to Mediterranean and subtropical climate forest types. Topography greatly influences wind, channelling winds into preferred directions and increasing or Additional reviews of fire danger rating systems for decreasing wind speed, depending on atmospheric other global regions are provided by Viegas et al. stability. In mountainous areas, the prevailing (1999) and Lin (2000). winds are often the result of this channelling by the physical features of the landscape.­ Mountain passes, 11.5.7 Phenomena associated with fires stream beds and valleys serve as routes for moving air and often develop localized circulation patterns dominated by the topography. 11.5.7.1 Curing of fuel by radiation from ongoing fires Some of the most severe fire weather in the world Any fire burning in dry conditions in a prolonged occurs in foehn wind and mountain wave situa- drought period can be brought under control as tions. Physical barriers modify the wind fields in long as strong winds do not occur. Once wind speed these situations to produce warm, dry, gusty increases, fire behaviour changes dramatically. winds on the lee side of the barrier (see also Wind velocity gives a fire forward momentum and 11.5.2). In addition to these mechanical effects, it acquires dynamic forward progress. In no-wind topography is also responsible for differential conditions, the flames tilt slightly backwards heating in mountainous areas, resulting in local towards the centre of the burning area and the circulations such as katabatic (downslope) and resulting convection column is located over the anabatic (upslope) winds. At low speeds these centre of the burning area. The convection column systems dominate the wind flow in mountain draws wind into the base of the rising air and the areas. fire spreads outward in a circular pattern. When wind increases, the fire pattern becomes increas- The differential heating affects diurnal changes in ingly elliptical in shape. the stability of the lower atmosphere, as well as 11–52 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES changes in relative humidity. In spring, lower of the layer can range from 300 to 2 500 m or elevations warm and dry earlier than higher eleva- more. Extreme fire behaviour is associated with tions. In the southern hemisphere, north-facing low-level jets at a height of 450 m or less above slopes dry faster than south-facing slopes, and the the fire. opposite is true in the northern hemisphere. Differences based on slope, aspect and elevation The low-level jet is not a necessary condition for a diminish as the season progresses from spring to major fire to maintain its intensity, but it is thought late summer. In mountainous areas, the range of to be a necessary condition for a small fire to blow relative humidity is greatest in the valley bottoms up. Byram (1954) found the critical height to be and least at higher elevations. These effects have around 450 m, with wind speeds in the 19 to important consequences for fire behaviour; fires at 29 km h–1 range. Other factors, such as wind speed low elevations may burn better during the day at the elevation of the fire, wind speed at the jet than at night, while those at higher elevations stream maximum, and the quantity and degree of may continue to burn well because humidity inflammability of the fuels, were also considered to remains low, temperatures remain relatively warm be critical in determining the optimum height of and wind speed due to exposure is generally the low-level jet. higher. Aronovitch (1989) showed that Byram’s negative wind profile was favourable to wildfire blow-up condi- 11.5.7.3 Spotting and low-level jet streams tions. Using ground and aerial data from the Idaho One of the most important factors affecting fire Butte Fire (August 1985) and the Sundance Fire behaviour is the mechanism of heat transfer. (September 1967), Aronovitch showed that it may be According to Luke and McArthur (1978), tree bark possible to routinely forecast whether or not a wildfire characteristics are the dominant factor influencing will blow up by determining the ratio of rate of spotting; but the quantity and continuity of surface conversion of thermal to kinetic energy in the column fuels, arrangement of aerial fuels, atmospheric of a wildfire to the rate of flow of kinetic energy in the stability and upper winds should also be consid- wind field at some elevation above the fire. ered, as well as the convective driving force of the fire intensity. Byram’s work demonstrates the importance of low-level wind observations above fires and reveals Under severe conditions, spotting has been reported the general inadequacy of synoptic observations up to 24 to 32 km ahead of the main fire front; in for fire weather forecasting. Full use of this research Australian eucalypt forests, fires and spotting to will be possible only if specialized fire weather 3.5 km is not unusual. The major factors that affect forecasters are available at large fire sites. the spotting process may be summarized as follows: 11.5.7.4 Fire whirlwinds (a) Tree species – any forest composed of a species that produces large quantities of loose bark Spontaneous overturning of the atmosphere can that is light and has good aerodynamic prop- occur when the lowest layers of the atmosphere in erties can contribute to long-distance spot- contact with the ground have an autoconvective lapse ting; rate (about 36°C/km, or three times the dry adiabatic (b) Rate of energy release – the higher the combus- lapse rate). Superheated air columns or chimneys tion rate, the faster crown fire formation will develop and entrainment from sides of the columns occur, with an associated strong convection initiates a spiralling motion because this horizontally column lifting burning embers high into the moving air is out of balance. Whirlwinds result and atmosphere. may remain stationary or move, but die out when they lose their source of energy. The size can vary but Byram (1954), while studying atmospheric condi- is generally on the order of 3 to 30 m in diameter and tions related to “blow-up”, drew attention to the can reach up to 3 km in height. Velocities are usually importance of a negative wind profile (see also in excess of 10 m s–1 but can reach 25 m s–l, and 11.5.2). Ordinarily, wind speed increases with upward currents of 10 to 15 m s–1 are adequate to lift height (positive wind shear). Byram found that large debris. Whirlwinds are common in recently the most consistent feature of the wind associ- burned areas and often on the lee side of ridges. They ated with extreme fire behaviour is the low-level can be caused by topographic as well as atmo­spheric jet stream. The existence of a low-level jet implies variations. Whirlwinds have been well documented a layer of decreasing wind speed with height, that as well as mathematically modelled and duplicated in is, negative wind shear above the jet. The depth laboratory experiments (Byram and Martin, 1970; CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–53

Church and Dessens, 1980). Attention has also been appears as visible smoke that is white or grey in focused on horizontal vortices in fire (Haines et al., colour due to the particles produced, which are 1987). These vortices can generate large-scale second- poor in elemental carbon (soot-free). Those parti- ary flows capable of transporting firebrands and cles are mainly fine (diameter <2.5 μm). The more therefore are an important consideration for fire- inefficient the burning, the greater the production fighter safety. of smoke because of incomplete combustion. The heat release of a smouldering fire is seldom suffi- cient to sustain a convection column. 11.5.7.5 Smoke production and smoke management In the final phase (glowing combustion), carbon The burning process can be divided into four monoxide and carbon dioxide are the main prod- phases that produce various emissions, some of ucts. Although the burning process can be described which are visible as smoke. These phases are in terms of the four phases of combustion, it is described as pre-ignition, flaming, smouldering important to recognize that combustion in forest and glowing. Generally in a vegetation fire, the fires is not a chemically efficient process. The smoke produced consists of water vapour, gases combustion temperature is reduced through mois- (CO2, CO, NOx, SO2), volatile organic compounds ture in the fuel and heat lost to the soil and to fresh (VOCs), such as methane and other hydrocar- air movement in and around the fire. bons (aliphatics or aromatics, such as ethane, benzene, toluene, xylene), oxygenated A large proportion (by mass) of vegetation fire compounds (alcohols, aldehydes, ketones, such smoke is composed of particulate matter finer than as phenol, as well as guaiacol, acetaldehyde, 2.5 µm (PM2.5). Exposure to particles in this size formaldehyde, acrolein, 2-butanone, furans, range has been identified in several studies as being carboxylic acids and esters), and halogenated linked to respiratory diseases such as asthma, and compounds (such as chloromethane), semi-vola- to increases in hospital admissions (Core and tile organic compounds (SVOCs), such as Peterson, 2001; Johnston et al., 2002). Health polyaromatic hydrocarbons (for example, impacts are more severe for the firefighters and the benzo[a]pyrene), and particulate matter (PM10, sensitive groups in the general population (infants, PM2.5), which usually consists of absorbed or children, people with respiratory problems, the condensed organic and inorganic compounds. elderly, pregnant women) (Breysse, 1984; Goldammer and Statheropoulos, 2008). Air quality Specifically, in the pre-ignition phase, fuels ahead standards in many countries now impose limits on of the fire are heated, leading to evaporation of PM2.5 concentrations, thus necessitating improve- water vapour and drying. As the temperature rises, ments in smoke management practices. parts of the wood decompose, releasing a stream of combustible organic gases and vapours. When the Smoke management is the combined use of hot gases from the pre-ignition phase mix with meteorology, fuel moisture, fuel loading and fire oxygen, they ignite and the burning process moves management techniques to keep visibility and air- to the flaming combustion phase. The products of quality impacts of smoke within acceptable limits. flaming combustion are predominantly carbon Anyone who uses prescribed fire should consider dioxide (CO2) and water vapour. The water vapour smoke management practices. is not the result of fuel dehydration as in the pre- ignition phase, but of chemical reactions in the The National Wildfire Coordination Group in the burning process. Molecules with higher molecular United States has published an extensive smoke weights are produced and many molecules of low management guide (Hardy et al., 2001), which molecular weight remain as gases and move down- summarizes strategies to manage smoke from wind. Some compounds with higher molecular prescribed fires. Other sources, including theHealth weights cool and condense into tar droplets and Guidelines for Vegetation Fire Events (Schwela et al., solid soot particles (aerosol). These particles make 1999), are listed in 11.2.6 above. While many up visible smoke, which is usually black due to the recommendations are focused on fuel management, presence of elemental carbon. During flaming attention to meteorological factors can assist in combustion, most of the particles produced are redistributing the smoke through: coarse (diameter >10 μm). (a) Avoidance: conduct prescribed burning on days when smoke intrusion into sensitive During the smouldering (slow flameless combus- areas is highly unlikely, that is, when transport tion) phase, the temperature drops and some of the winds will carry smoke away from sensitive vapours condense. The resulting condensation also areas; 11–54 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

(b) Dilution: reduce smoke concentration by System, in spite of its variety of fuels, is best suited mixing it through a greater volume of air, to grassy open fires. The Canadian system is best either by scheduling burns during periods suited to forests with a full canopy and substantial of good vertical dispersion, or by burning at duff layers. The McArthur system is probably most slower rates. relevant to Mediterranean and subtropical climate forest types. 11.5.8 Conclusion In general, derived weather indices do not take into A review of any system inevitably results in the account important factors such as the curing of fuel discovery of a need to maintain research into the from ongoing fire radiation, upper-wind profiles or application of modern techniques to improve the the instability of the atmosphere, nor do these calcu- system. Of the three components of the fire lations indicate the occurrence of fire whirlwinds or triangle, the element most susceptible to control is the transition of a fire from a two-dimensional to a fuel; hence the need to understand the processes three-dimensional fire, namely, crowning. There are associated with fuel curing, fuel build-up and other meteorologically related aspects that require decay, and also the processes involving wetting face-to-face briefing to be effective. The value of a and drying of fuel. Remote-sensing can be used to fire weather meteorologist on site using direct help establish vegetation indices, radiation fields communications with the main forecast centre and fields of evaporation, all of which can be used cannot be overestimated. Sudden wind changes can to deduce fuel states. Methods used to deduce threaten the lives of firefighters and other persons moisture in forest fuels such as the Keetch–Byram who are involved with ongoing fires. and the Tasmanian soil dryness indices appear to be over-simplifications and should be improved In the tropics, most fires are used by humans as an through research. important tool in land management. In the subtrop- ics, lightning is one of the main causes of fire Fuel state is the only element in weather meters outbreaks, while in the tropics fires started from that is not forecast, while wind speed and fuel state lightning are rare. Whether fires occur in the trop- are the two most influential weather-related ics or subtropics, the same physical laws controlling elements affecting fire behaviour using derived wildfire behaviour still apply. The awareness level indices. The meter used in the United States is a of the damage that can result from the indiscrimi- theoretical unit and can accommodate 13 to 20 fuel nate use of fire is very low in certain areas, especially models. The McArthur-type meter uses only two from the environmental viewpoint, as stated in basic fuel models, one for grass and one for forest. WMO (1982). The need for supplementary fire The United States National Fire Danger Rating weather observations exists in many places.

REFERENCES

Aber, J.D., J.M. Melillo, K.J. Nadelhoffer, J. Pastor International Symposium on Forest Fire Protection. and R.D. Boone, 1991: Factors controlling nitro- Tokyo, Mitaka. gen cycling and nitrogen saturation in northern Andrews, P.L., C.D. Bevins and R.C. Seli, 2005: temperate forest ecosystems. Ecol. Appl., BehavePlus Fire Modeling System, Version 3.0: 1:303–315. User’s Guide, Rep. RMRS-GTR-106WWW, Achim, A., J.C. Ruel and B.A. Gardiner, 2005: Revised. Ogden, Forest Service, USDA. Evaluating the effect of precommercial thin- Anthes, R.A. and T.T. Warner, 1978: Development ning on the resistance of balsam fir to windthrow of hydrostatic models suitable for air pollution through experimentation, modelling, and and other mesometeorological studies. Monthly development of simple indices. Can. J. For. Res., Weather Rev., 106:1045–1078. 35:1844–1853. Arbaugh, M.J., D.W. Johnson and W.M. Pulliam, Adams, M.J. and B.R. Bury, 2002: The endemic 1999: Simulated effects of N deposition, ozone headwater stream amphibians of the American injury and climate change on a forest stand in Northwest: associations with environmental the San Bernardino Mountains. In: Oxidant Air gradients in a large forested preserve. Global Pollution Impacts in the Montane Forests of Ecol. Biogeogr., 11:169–178. Southern California: A Case Study of the San Ågren, G.I. and E. Bosatta, 1998: Theoretical Bernardino Mountains. (P.R. Miller and Ecosystem Ecology: Understanding Element Cycles. J.R. McBride, eds). Ecological Studies, Vol. 134. Cambridge, Cambridge University Press. New York, Springer. Al-Amin, N.K.N., K. Stigter, M.A.M. Elagab and M.B. Arneth, A., F.M. Kelliher, T.M. McSeveny and Hussein, 2005: Combating desert encroach- J.N. Byers, 1999: Assessment of annual carbon ment by guiding people, wind and sand. J. Agric. exchange in a water-stressed Pinus radiata Meteor. (Japan), 60:349–352. plantation: an analysis based on eddy covari- Al-Amin, N.K.N., C.J. Stigter and A.E. Mohammed, ance measurements and an integrated 2006: Establishment of trees for sand settlement biophysical model. Global Change Biol., in a completely desertified environment. Arid 5:531–545. Land Res. Manage., 20:309–327. Aronovitch, B.B., 1989: Forecasting wildfire “blow- Albini, F.A., 1976: Estimating Wildfire Behavior and up”. In: Proceedings of the Tenth Conference on Effects. Report INT-30. Ogden, Forest Service, Forest and Fire Meteorology, Ottawa, 17–21 April USDA. 1989. Ottawa, Forestry Canada. Almeida, A.C., J.J. Landsberg and P.J. Sands, 2004: Arora, V.K. and G.J. Boer, 2006: Simulating compe- Parameterisation of 3-PG model for fast grow- tition and coexistence between plant functional ing Eucalyptus grandis plantations. For. Ecol. types in a dynamic vegetation model. Earth Manage., 193:179–196. Interactions, 10, Paper 10. Amatya, D.M., G. Sun, R.W. Skaggs, G.M. Chescheir Arp, P.A. and X. Yin, 1992: Predicting water fluxes and J.E. Nettles, 2006: Hydrologic effects of through forests from monthly precipitation global climate change on a large drained pine and mean monthly air temperature records. forest. In: Hydrology and Management of Forested Can. J. For. Res., 22:864–877. Wetlands: Proceedings of the International Asher, J.E., 1956: Observation and Theory on X-Disease Conference, New Bern, North Carolina, or Needle Dieback. Arrowhead Ranger District, 8–12 April 2006. St Joseph, ASABE. San Bernardino National Forest. USDA Forest Ancelin, P., B. Courbaud and T. Fourcaud, 1999: Service Report. Development of an individual tree-based Aubrun, S., R. Koppmann, B. Leitl, M. Möllmann- mechanical model to predict wind damage Coers and A. Schaub, 2005: Physical modelling within forest stands. For. Ecol. Manage., of a complex forest area in a wind tunnel: 203:101–121. comparison with field data.Agric. For. Meteorol., Anderson, W.P., 1983: Weed Science: Principles. 129:121–135. Second edition. St Paul, West Publishing. Ayres, M.P. and M.J. Lombardero, 2000: Assessing Andrews, P.L., 2005: Fire danger rating and fire the consequences of climate change for forest behavior prediction in the United States. In: herbivores and pathogens. Sci. Tot. Environ., Proceedings of the Fifth NRIFD Symposium – 262:263–286. 11–56 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Baldocchi, D.D. and K.B. Wilson, 2001: Modeling Boulder, National Center for Atmospheric CO2 and water vapor exchange of a temperate Research. broadleaved forest across hourly to decadal time Bonan, G.B., D. Pollard and S.L. Thompson, 1992: scales. Ecol. Model., 142:155–184. Effects of boreal forest vegetation on global Balland, V., J. Bhatti, R. Errington, M. Castonguay climate. Nature, 359:716–718. and P.A. Arp, 2006: Modeling snowpack and Borchert, R. and G. Rivera, 2001: Photoperiodic soil temperature and moisture conditions in a control of seasonal development and dormancy jack pine, black spruce and aspen forest stand in tropical stem-succulent trees. Tree Physiol., in central Saskatchewan (BOREAS SSA). Can. J. 21:201–212. Soil Sci., 86:203–217. Borthwick, H.A., 1957: Light effects on tree growth Baron, J.S., M.D. Hartman, T.G.F. Kittel, L.E. Band, and seed germination. Ohio J. Sci., 57:357–364. D.S. Ojima and R.B. Lammers, 1998: Effects of Bossel, H., 1996: TREEDYN3 forest simulation land cover, water redistribution, and tempera- model. Ecol. Model., 90:187–227. ture on ecosystem processes in the South Platte Bosveld, F.C. and W. Bouten, 2003: Evaluating a basin. Ecol. Appl., 8:1037–1051. model of evaporation and transpiration with Bartlett, P.A., J.H. McCaughey, P.M. Lafleur and D.L. observations in a partially wet Douglas-fir forest. Verseghy, 2003: Modelling evapotranspiration Boundary-Layer Meteorology, 108:365–396. at three boreal forest stands using CLASS: Tests Botkin, D.B., J.F. Janak and J.R. Wallis, 1972: Some of parameterizations for canopy conductance ecological consequences of a computer model and soil evaporation. Int. J. Climatol., of forest growth. J. Ecol., 60:849–872. 23:427–451. Branford, D., D. Fowler and M.V. Moghaddam, Bauer, G., F.A. Bazzaz, R. Minocha, S. Long, A. Magill, 2004: Study of aerosol deposition at a wind J. Aber and G.M. Berntson, 2004: Effects of exposed forest edge using 210Pb and 137Cs soil chronic N additions on tissue chemistry, photo- inventories. Water Air Soil Pollut., 157:107–116. synthetic capacity, and carbon sequestration Brewer, C.W. and N.E. Linnartz, 1973: The Recovery potential of a red pine (Pinus resinosa Ait.) stand of Hurricane-bent Loblolly Pine. LSU Forestry Note in NE United States. For. Ecol. Manage., No. 104. Baton Rouge, Louisiana State 196:173–186. University. Beer, J.A., A. Bonnemann, W. Chaves, H.W. Breysse, P.A., 1984: Health hazards of smoke. J. Fassbender, A.C. Imbach and I. Martel, 1990: Forestry, 82:89. Modelling agroforestry systems of cacao Briceño-Elizondo, E., 2006: Stand Level Analysis on (Theobroma cacao) with laurel (Cordia alliodora) the Effects of Management and Climate Change or poro (Erythrina poeppigiana) in Costa Rica. on the Growth and Timber Yield with Implications V. Productivity indices, organic material models on Carbon Stocks in Boreal Forest Ecosystem: A and sustainability over ten years. Agroforestry Model-Based Approach. PhD. University of Systems, 12:229–249. Joensuu. Benda, L. and T. Dunne, 1997: Stochastic forcing of Bridge, S.R.J., K. Miyanishi and E.A. Johnson, 2005: sediment supply to channel networks from A critical evaluation of fire suppression effects landsliding and debris flow. Water Resources in the boreal forest of Ontario. Forest Science, Research, 33:2849–2863. 51:41–50. Bernier, P.Y., N. Bréda, A. Granier, F. Raulier and Bruijnzeel, L.A., 2001: Forest hydrology. In: The F. Mathieu, 2002: Validation of a canopy gas Forests Handbook. Vol. I (J. Evans, ed.). Oxford, exchange model and deviation of a soil water Blackwell Science. modifier for transpiration for sugar maple (Acer Bugmann, H.K.M., 2001: A review of forest gap saccharum Marsh) using sap flow density models. Climatic Change, 51:259–305. measurements. For. Ecol. Manage., 119:51–62. Bugmann, H.K.M., J.F. Reynolds and L.F. Pitelka, Betts, R.A., 2000: Offset of the potential carbon sink 2001: How much physiology is needed in forest from boreal forestation by decreases in surface gap models for simulating long-term vegetation albedo. Nature, 408:187–190. response to global change? Climatic Change, Biona, C.B., A. Druilhet, B. Benech and R. Lyra, Vol. 51, Special Issue. 2001: Diurnal cycle of temperature and wind Bureau of Meteorology, 1964: Manual of Meteorology: fluctuations within an African equatorial rain Fire Weather Supplement. Melbourne, Australian forest. Agric. For. Meteorol., 109:135–141. Bureau of Meteorology. Bonan, G.B., 1996: A Land Surface Model (LSM Version Burgan, R.E., 1988: 1988 Revisions to the 1978 1.0) for Ecological, Hydrological, and Atmospheric National Fire Danger Rating System. Research Studies: Technical Description and User’s Guide. Paper SE-273. Asheville, Forest Service, NCAR Technical Note, NCAR/TN-417+STR. USDA. CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–57

Byram, G.M., 1954: Atmospheric Conditions Related Carroll, A.L., S.W. Taylor, J. Régnière and to Blow-up Fires. Paper No. 35. Asheville, L. Safranyik, 2003: Effects of climate change on Southeastern Forest Experiment Station, Forest range expansion by the mountain pine beetle Service, USDA. in British Columbia. In: Proceedings of the ———, 1957. Some principles of combustion and Mountain Pine Beetle Symposium: Challenges and their significance in forest fire behavior. Fire Solutions, Kelowna, British Columbia, 30–31 Control Notes, 18(2):47–57. Reprinted in: Fire October 2003 (T.L. Shore, J.E. Brooks and Management Today, 64(1):37–44. J.E. Stone, eds). Information Report BC-X-399. Byram, G.M. and R.E. Martin, 1970: The modelling Victoria, Natural Resources Canada, Canadian of fire whirlwinds.Forest Science, 16:386–399. Forest Service, Pacific Forestry Centre. Bytnerowicz, A., N. Grulke, M. Fenn, M. Poth, Castelli, J.P., B.B. Casper, J.J. Sullivan and P. Temple and P. Miller, 1999: Wet and dry R.E. Latham, 1999: Early understory succession pollutant deposition to the mixed conifer forest. following catastrophic wind damage in a decid- In: Oxidant Air Pollution Impacts in the Montane uous forest. Can. J. For. Res., 29:1997–2002. Forests of Southern California: A Case Study of the Chang, J.-H., 1974: Climate and Agriculture. Chicago, San Bernardino Mountains. (P.R. Miller and Aldine Publishing. J.R. McBride, eds). Ecological Studies, Vol. 134. Charles Edwards, D.A. and M.R. Thorpe, 1976: New York, Springer. Interception of diffuse and direct-beam radia- Campbell, G.S. and J.M. Norman, 1998: An tion by a hedgerow apple orchard. Ann. Bot., Introduction to Environmental Biophysics. Second 40:603–613. edition. New York, Springer. Chase, T.N., R.A. Pielke, T. Kittel, R. Nemani and Campbell, R.K. and A.I. Sugano, 1975: Phenology S. Running, 1996: Sensitivity of a general circu- of bud burst in Douglas-fir related to prove- lation model to global changes in leaf area nance, photoperiod, chilling, and flushing index. J. Geophys. Res.-Atmos., 101:7393–7408. temperature. Botanical Gazette, 136:290–298. Chen, J., J.F. Franklin and S. Lowe, 1996: Comparison Canadian Forestry Service, 1984: Tables for the of abiotic and structurally defined patch patterns Canadian Forest Fire Weather Index System. in a hypothetical forest landscape. Conservation Forestry Technical Report 25. Fourth edition. Biology, 10:854–862. Ottawa, Environment Canada. Cheney, N.P. and A. Sullivan, 1997: Grassfires: Fuel, ———, 1987: Canadian Forest Fire Danger Rating Weather and Fire Behaviour. Melbourne, CSIRO System – User’s Guide. Ottawa, Environment Publishing. Canada, Canadian Forestry Service Fire Danger Chertov, O., A. Komarov, M. Kolström, S. Pitkänen, Group. H. Strandman, S. Zudin and S. Kellomäki, ———, 2001: Natural Resources Canada: State of 2003: Modelling the long-term dynamics of Canada’s Forests 2000–2001: Forests in the New populations and communities of trees in boreal Millennium. http://adaptation.nrcan.gc.ca/ forests based on competition for light and nitro- perspective/forest_3_e.php. gen. For. Ecol. Manage., 176:355–369. Candau, J.-N. and R.A. Fleming, 2005: Landscape- Chertov, O.G., A.S. Komarov, M.A. Nadporozhskaya, scale spatial distribution of spruce budworm S.A. Bykhovets and S.L. Zudin, 2001: ROMUL – defoliation in relation to bioclimatic condi- a model of forest soil organic matter dynamics tions. Can. J. For. Res., 35:2218–2232. as a substantial tool for forest ecosystem model- Canham, C.D., P.T. LePage and K.D. Coates, 2004: A ling. Ecol. Model., 138:289–308. neighborhood analysis of canopy tree competi- Childs, S.W., C. Costello and A.L. Flint, 1987: A soil tion: effects of shading versus crowding. Can. J. water balance model for partitioning water use For. Res., 34:778–787. among crop trees, evaporation, and competing Cannell, M.G.R., D.C. Mobbs and G.J. Lawson, vegetation. In: Forest Hydrology and Watershed 1998: Complementarity of light and water use Management. Proceedings of the Vancouver in tropical agroforests. II. Modelled theoretical Symposium, August 1987. Publication No.167. tree production and potential crop yield in arid Wallingford, Oxfordshire, International to humid climates. For. Ecol. Manage., Association of Hydrological Sciences. 102:275–282. Church, C.R. and J. Dessens, 1980: Intense atmo- Cannell, M.G.R. and J.H.M. Thornley, 1998: spheric vortices associated with a 1 000 MW Temperature and CO2 responses of leaf and fire.Bull. Amer. Meteor. Soc., 61:682–694. canopy photosynthesis: A clarification using Churkina, G., J. Tenhunen, P. Thornton, E.M. Falge, the non-rectangular hyperbola model of photo- J.A. Elbers, M. Erhard, T. Grünwald, A.S. synthesis. Ann. Bot., 82:883–892. Kowalski, Ü. Rannik and D. Sprinz, 2003: 11–58 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Analyzing the ecosystem carbon dynamics of of forested wetland using a biogeochemical four European coniferous forests using a biogeo- process model. Global Change Biol., chemistry model. Ecosystems, 6:168–184. 11:278–289. Colbert, J.J. and K.A. Sheehan, 1995: Description of Dale, V.H., L.A. Joyce, S. McNulty, R.P. Neilson, the Stand-Damage Model: A Component of the M.P. Ayres, M.D. Flannigan, P.J. Hanson, Gypsy Moth Life System Model. General Technical L.C. Irland, A.E. Lugo, C.J. Peterson, Report NE-208. Radnor, Forest Service, USDA. D. Simberloff, F.J. Swanson, B.J. Stocks and Connolly, R.D., A. Costantini, R.J. Loch and M. Wotton, 2001: Climate change and forest R. Garthe, 1999: Sediment generation from disturbances. BioScience, 51:723–734. forest roads: bed and eroded sediment size Davis, K.R., 1959: Forest Fire: Control and Use. New distributions, and runoff management strate- York, McGraw-Hill. gies. Aust. J. Soil Res., 37:947–964. Day, W.R. and T.R. Peace, 1946: Spring Frosts. Forestry Constable, H. and A. Retzlaff, 2000: Asymmetric Commission Bulletin 18. London, Her Majesty’s day/night temperature elevation: growth impli- Stationery Office. cations for yellow-poplar and loblolly pine de Melo-Abreu, J.P., D. Barranco, A.M. Cordeiro, using simulation modeling. Forest Science, J. Tous, B.M. Rogado and F.J. Villalobos, 2004: 46:248–257. Modelling olive flowering date using chilling Cooper-Ellis, S., D.R. Foster, G. Carlton and for dormancy release and thermal time. Agric. A. Lezberg, 1999: Forest response to catastrophic For. Meteorol., 125:117–127. wind: results from an experimental hurricane. de Reffye, P., F. Houllier, F. Blaise, D. Barthelemy, Ecology, 80:2683–2696. J. Dauzat and D. Auclair, 2004: A model simu- Coops, N.C. and R.H. Waring, 2001: Assessing forest lating above- and below-ground tree architecture growth across Southwestern Oregon under a with agroforestry applications. Agrofor. Syst., range of current and future global change 30:175–197. scenarios using a process model, 3-PG. Global Deeming, J.E., R.E. Burgun and J.D. Cohan, 1977: Change Biol., 7:15–29. The National Fire Danger Rating System – 1978. Cordero, R.A., 1999: Ecophysiology of Cecropia General Technical Report INT-39. Ogden, schreberiana saplings in two wind regimes in an International Forest and Range Experiment elfin cloud forest: growth, gas exchange, archi- Station, Forest Service, USDA. tecture and stem biomechanics. Tree Physiol., Deeming, J.E., J.W. Lancaster, M.A. Fosberg, 19:153–163. W.R. Furman, R. William and M.J. Schroeder, Core, J.E. and J.L. Peterson, 2001: Public health and 1972: The National Fire-Danger Rating System. exposure to smoke. In: Smoke Management Guide Research Paper RM–84, revised 1974. Fort for Prescribed and Wildland Fire (C.C. Hardy, Collins, Rocky Mountain Forest and Range R.D. Ottmar, J.L. Peterson, J.E. Core and Experiment Station, Forest Service, USDA. P. Seamon, eds). PMS 420–2, NFES 1279. Boise, Díaz-Delgado, J., F. Lloret, X. Pons and J. Terradas, National Wildfire Coordination Group. 2002: Satellite evidence of decreasing Coughlan, J.C. and S.W. Running, 1997: Regional resilience in Mediterranean plant communities ecosystem simulation: a general model for after recurrent fires. Ecology, 83:2293– simulating snow accumulation and melt in 2303. mountainous terrain. Landscape Ecology, Dickinson, R.E., A. Henderson-Sellers and 12:119–136. P.J. Kennedy, 1993: Biosphere-Atmosphere Transfer Coutts, M.P. and J. Grace (eds), 2005: Wind and Scheme (BATS) Version 1e as Coupled to the NCAR Trees. Cambridge, Cambridge University Press. Community Climate Model. Technical Note Cramer, W., A. Bondeau, F.I. Woodward, I.C. NCAR/TN-387+STR. Boulder, Climate and Prentice, R. Bettes, V. Brovkin, P. Cox, V. Fisher, Global Dynamics Division, National Center for J. Foley, A. Friend, C. Kucharik, M. Lomas, Atmospheric Research. N. Ramankutty, S. Sitch, B. Smith, A. White and Doede, D.L., 2005: Genetic variation in broadleaf C. Young-Molling, 2001: Global response of lupine (Lupinus latifolius) on the Mt Hood National terrestrial ecosystem structure and function to Forest and implications for seed collection and CO2 and climate change: results from six deployment. Native Plants J., 6:36–48. dynamic global vegetation models. Global Downs, R.J. and H.A. Borthwick, 1956: Effects of Change Biol., 7:357–373. photoperiod on the growth of trees. Botanical Cruden, D.M., 1991: A simple definition of a land- Gazette, 117:310–326. slide. Bull. Int. Assoc. Eng. Geol., 43:27–29. Dye, P.J., 2001: Modelling growth and water use in Cui, J., C. Li and C. Trettin, 2005: Analyzing the four Pinus patula stands with the 3-PG model. ecosystem carbon and hydrologic characteristics South. Afr. Forest. J., 191:53–63. CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–59

Dyer, J.M. and P.R. Baird, 1997: Wind disturbance Flannigan, M., I. Campbell, B.M. Wotton, in remnant forest stands along the prairie–forest C. Carcaillet, P. Richard and Y. Bergeron, 2001: ecotone, Minnesota, USA. Plant Ecology, Future fire in Canada’s boreal forest: paleo­ 29:121–134. ecology results and general circulation Ebert, H.L.V., 1963: The meteorological factor in model–regional climate model simulations. the Hamburg fire storm. Weatherwise, Can. J. For. Res., 31:854–864. 16:70–76. Fleishman, E., R. Mac Nally and J.P. Fay, 2003: Eggers, S., M. Griesser, T. Andersson and J. Ekman, Validation tests of predictive models of 2005: Nest predation and habitat change inter- butterfly occurrence based on environmental act to influence Siberian jay numbers. Oikos, variables. Conserv. Biol., 17:806–817. 111:150–158. Fleishman, E., R. Mac Nally, J.P. Fay and Evans, J., 1982: Plantation Forestry in the Tropics. D.D. Murphy, 2001: Modeling and predicting New York, Oxford University Press. species occurrence using broad-scale environ- Eyre, T.J. and R.L. Goldingay, 2003: Use of sap trees mental variables: an example with butterflies by the yellow-bellied glider near Maryborough of the Great Basin. Conserv. Biol., in south-east Queensland. Wildlife Research, 15:1674–1685. 30:229–236. Fleming, R.A. and J.-N. Candau, 1998: Influences of Falloon, P., P. Smith, J. Szabó and L. Pásztor, 2002: climatic change on some ecological processes of Comparison of approaches for estimating an insect outbreak system in Canada’s boreal carbon sequestration at the regional scale. Soil forests and the implications for biodiversity. Use and Management, 18:164–174. Environ. Monit. Assess., 49:1573–2959. Fan, W., J.C. Randolph, and J.L. Ehman, 1998: Flesch, T.K. and J.D. Wilson, 1999a: Wind and Regional estimation of nitrogen mineralization remnant tree sway in forest cutblocks. in forest ecosystems using geographic informa- I. Measured winds in experimental cutblocks. tion systems. Ecol. Appl., 8:734–747. Agric. For. Meteorol., 93:229–242. Farquhar, G.D., S. von Caemmerer and J.A. Berry, ———, 1999b: Wind and remnant tree sway in 1980: A biochemical model of photosynthetic forest cutblocks. II. Relating measured tree sway CO2 assimilation in leaves of C3 species. Planta, to wind statistics. Agric. For. Meteorol., 149:78–90. 93:243–258. Fenn, M.E. and M.A. Poth, 1999: Temporal and Foley, J.A., I.C. Prentice, N. Ramankutty, S. Levis, spatial trends in stream water nitrate concentra- D. Pollard, S. Sitch, A. Haxeltine, 1996: An inte- tions in the San Bernardino Mountains, grated biosphere model of land surface processes, Southern California. J. Environ. Qual., terrestrial carbon balance, and vegetation 28:822–836. dynamics. Global Biogeochem. Cycles, Finney, M.A., 1998: FARSITE: Fire Area Simulator – 10:603–623. Model Development and Evaluation. RP-RMRS-4. Fons, W.L., 1940: Influence of forest cover Missoula, Rocky Mountain Research Station, on wind velocity. J. Forestry, 38:481–486. Forest Service, USDA. Food and Agriculture Organization of the United Finocchiaro, N., D.J. Linforth and B.T. Shields, 1969: Nations (FAO), 1955: Tree Planting Practices for Report on the Meteorological Aspects of the Extensive Arid Areas (L. Leloup). FAO Forestry Development Grass Fires in Victoria on 8 January 1969. Met. Note. Paper No. 6. Rome, FAO. Melbourne, Australian Bureau of Meteorology. ———, 1959: Tree Planting Practices in Temperate FIRESCAN Science Team, 1996: Fire in ecosystems of Asia, Burma-India-Pakistan (E. Glesinger). FAO boreal Eurasia: The Bor Forest Island Fire Forestry Development Paper No. 14. Rome, Experiment, Fire Research Campaign Asia-North FAO. (FIRESCAN). In: Biomass Burning and Global ———, 2005: Frost Protection: Fundamentals, Practice Change. Vol. II. (J.S. Levine, ed.). Cambridge, and Economics. Vol. I. (R.L. Snyder and Massachusetts, MIT Press. J.P. de Melo-Abreu). Rome, FAO. Fischlin, A., H. Bugmann and D. Gyalistras, 1995: Forestry Canada Fire Danger Group, 1992: Sensitivity of a forest ecosystem model to Development and Structure of the Canadian Forest climate parameterization schemes. Environ. Fire Behavior Prediction System. Report ST-X-3. Pollut., 87:267–282. Ottawa, Forestry Canada. Fisher, J.B., T.A. DeBiase, Y. Qi, M. Xu and Foster, T., 1967: Bushfire: History, Prevention and A.H. Goldstein, 2005: Evapotranspiration Control. Sydney, Australia, A.H. and A.W. Reed. models compared on a Sierra Nevada forest Fowells, H.A. and J.E. Means, 1990: The tree and its ecosystem. Environ. Model. Software, environment. In: Silvics of North America. Vol. 1. 20:783–796. Conifers. Agricultural Handbook 654 11–60 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

(R.M. Burns and H. Honkala, eds). Washington, Goldammer, J.G., M. Statheropoulos and M.O. DC, Forest Service, USDA. Andreae, 2008: Impacts of vegetation fire emis- Friend, A.D., A.K. Stevens, R.G. Knox and M.G.R. sions on the environment, human health and Cannell, 1997: A process-based, terrestrial security – A global perspective. In: Wildland biosphere model of ecosystem dynamics (Hybrid Fires and Air Pollution (A. Bytnerowicz, v3.0). Ecol. Model., 95:249–287. M. Arbaugh, A. Riebau and C. Andersen, eds). Fritschen, L.J., 1985: Characterization of boundary Amsterdam, Elsevier. conditions affecting forest environmental Goodrick, S.L., 2002. Modification of the Fosberg phenomena. In: The Forest–Atmosphere fire weather index to include drought. Int. J. Interaction: Proceedings of Forest Environmental Wildland Fire, 11:205–211. Measurements Conference, Oak Ridge, Tennessee, Gottschalk, K., S.J. Thomas, D.B. Twardus, J.H. Ghent, 23–28 October 1983 (B.A. Hutchison and B.B. J.J. Colbert and M.E. Teske, 1996: GypsES: A deci- Hicks, eds). Dordrecht, Reidel. sion support system for gypsy moth management. Fritschen, L.J., L. Cox and R. Kinearson, 1973: In: Decision Support Systems for Forest Pest A 28-meter Douglas-fir in a weighing lysimeter. Management. Proceedings of the Entomological Forest Science, 19:256–261. Society of Canada Annual Meeting, Victoria, BC, Frolking, S., N.T. Roulet, T.R. Moore, P.M. Lafleur, 17 October 1995 (T. Shore and D. MacLean, eds). J.L. Bubier and P.M. Crill, 2002: Modeling British Columbia Forest Resource Development seasonal to annual carbon balance of Mer Bleue Agreement Report No. 260. Bog, Ontario, Canada. Global Biogeochem. Cycles, Gower, S.T., C.J. Kucharik and J.M. Norman, 1999: 16:1030–1051. Direct and indirect estimation of leaf area index, Frolking, S., N.T. Roulet, T.R. Moore, P.J.H. Richard, fAPAR and net primary production of terrestrial M. Lavoie and S.D. Muller, 2001: Modeling ecosystems. Rem. Sens. Environ., 70:29–51. northern peatland decomposition and peat Grace, J., 1977: Plant Response to Wind. London, accumulation. Ecosystems, 4:479–498. Academic Press. Fujioka, F.M., 2002: A new method for the analysis Grant, R.F., M.L. Goulden, S.C. Wofsy and J.A. Berry, of fire spread modeling errors. Int. J. Wildland 2001: Carbon and energy exchange by a black Fire, 11:193–203. spruce–moss ecosystem under changing climate: Gardiner, B., H. Peltola and S. Kellomäki, 2000: Testing the mathematical model ecosys with Comparison of two models for predicting the data from the BOREAS experiment. J. Geophys. critical wind speeds required to damage conifer- Res., 106:33605–33621. ous trees. Ecol. Model., 129:1–23. Gray, D.R., 2004: The gypsy moth life stage model: Gavashelishvili, A., M.J. McGrady and landscape-wide estimates of gypsy moth estab- Z. Javakhishvili, 2006: Planning the conserva- lishment using a multi-generational phenology tion of the breeding population of cinereous model. Ecol. Model., 176:155–171. vultures Aegypius monachus in the Republic of Greene, D.F. and E.A. Johnson, 1989: A model of Georgia. Oryx, 40:76–83. wind dispersal of winged or plumed seeds. Geng, S., F.W.T. Penning de Vries and L. Supit, 1985: Ecology, 70:339–347. A simple method for generating rainfall data. Grossman, Y.L. and T.M. DeJong, 1994: PEACH: A Agric. For. Meteorol., 36:363–376. model of reproductive and vegetative growth in Gillespie, T.J., 1994: Pest and disease relationships. peach trees. Tree Physiol., 14:329–345. In: Handbook of Agrometeorology (J.F. Griffiths, Grove, S.J., S.M. Turton and D.T. Siegenthaler, 2000: ed.). Oxford, Oxford University Press. Mosaics of canopy openness induced by tropi- Gillham, J.H., A.L. Hild, J.H. Johnson, E.R. Hunt cal cyclones in lowland rain forests with and T.D. Whitson, 2004: Weed Invasion contrasting management histories in northeast- Susceptibility Prediction (WISP) model for use ern Australia. J. Trop. Ecol., 16:883–894. with geographic information systems. Arid Land Grulke, N.E., 1999: Physiological responses of Res. Manage., 18:1–12. ponderosa pine to gradients of environmental Gisborne, H.T., 1928: Measuring Forest Fire Danger in stressors. In: Oxidant Air Pollution Impacts in the Northern Idaho. Misc. Publ. 29. Washington, DC, Montane Forests of Southern California: A Case USDA. Study of the San Bernardino Mountains. (P.R. Miller ———, 1941: How the Wind Blows in the Forests of and J.R. McBride, eds). Ecological Studies, Northern Idaho. Missoula, Northern Forest Fire Vol. 134. New York, Springer. Laboratory, Northern Rocky Mountain Forest Grulke, N.E., C.P. Andersen, M.P. Fenn and P.R. and Range Experiment Station, Division of Miller, 1998: Ozone and nitrogen deposition Forest Protection, Forest Service, USDA. reduces root biomass of ponderosa pine in the CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–61

San Bernardino Mountains, California. Environ. Heide, O.M. and A.K. Prestrud, 2005: Low Pollut., 103:63–73. temperature, but not photoperiod, controls Grulke, N.E. and L. Balduman, 1999: Deciduous growth cessation and dormancy induction and conifers: High N deposition and exposure effects release in apple and pear. Tree Physiol., on growth and biomass allocation in ponderosa 25:109–114. pine. Water Air Soil Pollut., 116:235–248. Heinselman, M.L., 1981: Fire intensity and Gur, A., 1985: Rosaceae – deciduous fruit trees. In: frequency as factors in the distribution and Handbook of Flowering. Vol. I (A.H. Halevy, ed.). structure of northern ecosystems. In: Fire Boca Raton, CRC Press. Regimes and Ecosystem Properties (H.A. Mooney, Haines, D.A., M.C. Smith and A.J. Simand, 1987: J.M. Bonnicksen, N.L. Christiansen, J.E. Logan Horizontal vortices in wildland fires. In: and W.A. Reiners, eds). General Technical Proceedings of the Ninth National Conference on Report WO–26. Washington, DC, Forest Service, Fire and Forest Meteorology, San Diego, California, USDA. 21–24 April 1987. Boston, American Henderson-Sellers, A., R.E. Dickinson and M.F. Meteorological Society. Wilson, 1988: Tropical deforestation: Important Hall, C.A.S., M.R. Taylor and E. Everham, 1992: A processes for climate models. Climatic Change, geographically-based ecosystem model and its 13:43–67. application to the carbon balance of the Luquillo Hessburg, P.F., B.G. Smith, C.A. Miller, S.D. Kreiter, Forest, Puerto Rico. Water Air Soil Pollut., R.B. Salter and R. Brion, 1999: Modeling Change 64:385–404. in Potential Landscape Vulnerability to Forest Insect Hall, R.J., F. Raulier, D.T. Price, E. Arsenault, P.Y. and Pathogen Disturbances: Methods for Forested Bernier, B.S. Case and X. Guo, 2006: Integrating Subwatersheds Sampled in the Midscale Interior remote sensing and climate data with process Columbia River Basin Assessment. General models to map forest productivity within west- Technical Report PNW-GTR-454. Portland, central Alberta’s boreal forest: Ecoleap-West. Oregon, Pacific Northwest Research Station, Forestry Chronicle, 82:159–176. Forest Service, USDA. Hardy, C.C., R.D. Ottmar, J.L. Peterson, J.E. Core Hickler, T., B. Smith, M.T. Sykes, M.B. Davis, S. Sugita and P. Seamon (eds), 2001: Smoke Management and K. Walker, 2004: Using a generalized Guide for Prescribed and Wildland Fire. PMS 420– vegetation model to simulate vegetation 2. NFES 1279. Boise, National Wildfire dynamics in northeastern USA. Ecology, Coordination Group. 85:519–530. Hardy, C.E.M., 1983: The Gisborne Era of Forest Fire Hicks, B., 1983: A study of dewfall in arid regions. Research: Legacy of a Pioneer. Missoula, Northern An analysis of Wangara data. Q. J. Roy. Meteor. Forest Fire Laboratory. Soc., 109:900–904. Harper, M.J., M.A. McCarthy and R. van der Ree, Hoadley, J.L., M.L. Rorig, L. Bradshaw, S.A. Ferguson, 2005: The abundance of hollow-bearing K.J. Westrick, S.L. Goodrick and P. Werth, 2006: trees in urban dry sclerophyll forest and the Evaluation of MM5 model resolution when effect of wind on hollow development. Biol. applied to prediction of National Fire Danger Conserv., 122:181–192. Rating Indexes. Int. J. Wildland Fire, Harrington, R., R.A. Fleming and I.P. Woiwod, 2001: 15:147–154. Climate change impacts on insect management Hogg, E.H., 1994: Climate and the southern limit of and conservation in temperate regions: can the western Canadian boreal forest. Can. J. For. they be predicted? Agric. For. Entomol., Res., 24:1835–1845. 3:233–240. ———, 1997: Temporal scaling of moisture and the Hatton, T.J., L.L. Pierce and J. Walker, 1993: forest–grassland boundary in western Canada. Ecohydrological changes in the Murray–Darling Agric. For. Meteorol., 84:115–122. Basin. II. Development and tests of a water Huband, N.D.S. and D.R. Butler, 1984: A comparison balance model. J. Appl. Ecol., 30:274–282. of wetness sensors for use with computer or Haxeltine, A. and I.C. Prentice, 1996: BIOME3: an microprocessor systems designed for disease equilibrium terrestrial biosphere model based forecasting. Proceedings of the British Crop on ecophysiological constraints, resource avail- Protection Conference – Pests and Diseases 2, ability, and competition among plant functional Brighton, 19–22 November 1984. types. Global Biogeochem. Cycles, 10:693–709. Hungate, B.A., J.S. Dukes, M.R. Shaw, Y. Luo and He, H.S. and D.J. Mladenoff, 1999: Spatially explicit C.B. Field, 2003: Nitrogen and climate change. and stochastic simulation of forest-landscape Science, 302:1512–1513. fire disturbance and succession. Ecology, Hutchison, B.A. and B.B. Hicks (eds), 1985: The 80:81–99. Forest–Atmosphere Interaction. Proceedings of the 11–62 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Forest Environmental Measurements Technologies and Ecological Principles for a New Conference, Oak Ridge, Tennessee, 23–28 Age in Fire Management (L.F. Neuenschwander October 1983. Dordrecht, Reidel. and K.C. Ryan, eds). Vol. 1. Moscow, University Intergovernmental Panel on Climate Change of Idaho. (IPCC), 2001a: IPCC Third Assessment Report. Kainkwa, R.M.R. and C.J. Stigter, 1994: Wind reduc- Climate Change 2001: The Scientific Basis. tion downwind from a savanna woodland edge. (J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, Neth. J. Agr. Sci., 42:145–157. P.J. van der Linden, X. Dai, K. Maskell and C.A. Kang, S., S. Doh, D. Lee, D. Lee, V.L. Jin and Johnson, eds). Cambridge, Cambridge J.S. Kimball, 2003: Topographic and climatic University Press. controls on soil respiration in six temperate ———, 2001b: IPCC Third Assessment Report. Climate mixed-hardwood forest slopes, Korea. Global Change 2001: Impacts, Adaptation Change Biol., 9:1427–1437. and Vulnerability. (J.J. McCarthy, O.F. Canziani, Karlman, M., 2001: Risks associated with the intro- N.A. Leary, D.J. Dokken and K.S. White, eds). duction of Pinus contorta in northern Sweden Cambridge, Cambridge University Press. with respect to pathogens. For. Ecol. Manage., Irvine, M.R., B.A. Gardiner and A.P. Morse, 141:97–105. 1998: Energy partitioning influenced Keetch, J.J. and G.M. Byram, 1968: A Drought Index by tree spacing. Agroforestry Systems, 39:211–224. for Forest Fire Control. Forest Service Research Jalkanen, A. and U. Mattila, 2000: Logistic regres- Paper SE–38. Asheville, Southeastern Forest sion models for wind and snow damage in Experiment Station, Forest Service, USDA. northern Finland based on the National Forest Kelliher, F.M., T.A. Black and D.T. Price, 1986: Inventory data. For. Ecol. Manage., Estimating the effects of understory removal 135:315–330. from a Douglas-fir forest using a two-layer James, K.R., N. Haritos and P.K. Ades, 2006: canopy evapotranspiration model. Water Mechanical stability of trees under dynamic Resources Research, 22:1891–1899. loads. Am. J. Bot., 93:1522–1530. King, J., M.E. Kubiske, K.S. Pregitzer, G.R. Hendrey, Jarvis, P. and S. Linder, 2000: Constraints to growth E.P. McDonald, C.P. Giardina, V.S. Quinn and of boreal forests. Nature, 405:904–905. D.F. Karnosky, 2005: Tropospheric O3 compro- Johannessen, M. and A. Henriksen, 1978: Chemistry mises net primary production in young stands of snow meltwater: changes in concentration of trembling aspen, paper birch and sugar maple during melting. Water Resources Research, in response to elevated atmospheric CO2. New 14:615–619. Phytologist, 168:623–636. Johnston, F.H., A.M. Kavanagh, D.M.J.S. Bowman Komarov, A., O. Chertov, S. Zudin, and R.K. Scott, 2002: Exposure to bushfire M. Nadporozhskaya, A. Mikhailov, S. Bykhovets, smoke and asthma: an ecological study. Med. J. E. Zudina and E. Zoubkova, 2003: EFIMOD 2 – A Aust., 176:535–538. model of growth and elements cycling in boreal Jolly, W.M., P.L. Andrews and L.S. Bradshaw, 2005: forest ecosystems. Ecol. Model., 170:373–392. The Wildland Fire Assessment System (WFAS): a Korner, C., R. Asshoff, O. Bignucolo, web-based resource for decision support. In: S. Hättenschwiler, S.G. Keel, S. Peláez-Riedl, EastFIRE Conference Proceedings, Fairfax, Virginia, S. Pepin, R.T.W. Siegwolf and G. Zotz, 2005: 11–13 May 2005. Carbon flux and growth in mature deciduous Jones, C., C. McConnell, K. Coleman, P. Cox, forest trees exposed to elevated CO2. Science, P. Falloon, D. Jenkinson and D. Powlson, 2005: 309:1360–1362. Global climate change and soil carbon stocks: Koski, V. and J. Selkäinaho, 1982: Experiments on predictions from two contrasting models for the joint effect of heat sum and photoperiod on the turnover of organic carbon in soil. Global seedlings of Betula pendula. Communicationes Change Biol., 11:154–166. Instituti Forestalis Fenniae, 105:1–34. Jones, H.G., 1992: Plants and Microclimate. Koski, V. and R. Sievänen, 1985: Timing of growth Cambridge, Cambridge University Press. cessation in relation to variations in the grow- Juang, H.-M.H., 2000: The NCEP mesoscale spectral ing season. In: Crop Physiology of Forest Trees model: a revised version of the nonhydrostatic (P.M.A. Tigerstedt, P. Puttonen and V. Koski, regional spectral model. Monthly Weather Rev., eds). Helsinki, Helsinki University Press. 133:279–294. Kramer, M.G., A.J. Hansen, M.L. Taper and Kafka, V., C. Tymstra, K. Hirsch and M. Flannigan, E.J. Kissinger, 2001: Abiotic controls on long- 2000: Assessing fire behavior potential: a term windthrow disturbance and temperate comparative analysis of two spatial techniques. rain forest dynamics in southeast Alaska. In: Crossing the Millenium: Integrating Spatial Ecology, 82:2749–2768. CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–63

Kucharik, C.J., J.A. Foley, C. Delire, V.A. Fisher, successional stages and management regimes in M.T. Coe, J.D. Lenters, C. Young-Molling, Oregon. Agric. For. Meteorol., 108:1–14. N. Ramankutty, J.M. Norman and S.T. Gower, Lexer, M.J. and K. Hönninger, 2001: A modified 3D- 2000: Testing the performance of a Dynamic patch model for spatially explicit simulation of Global Ecosystem Model: water balance, carbon vegetation composition in heterogeneous land- balance, and vegetation structure. Global scapes. For. Ecol. Manage., 144:43–65. Biogeochem. Cycles, 14:795–825. Likens, G.E. and F.H. Bormann, 1995: Biogeochemistry Kurz, W.A. and M.J. Apps, 1999: A 70-year retro- of a Forested Ecosystem. Second edition. New spective analysis of carbon fluxes in the York, Springer. Canadian forest sector. Ecol. Appl., 9:526–547. Lin, C.C., 2000: The development, systems, and Kusumandari, A. and B. Mitchell, 1997: Soil erosion evaluation of forest fire danger rating: a review. and sediment yield in forest and agroforestry Taiwan J. For. Sci., 15:507–520. areas in West Java, Indonesia. J. Soil Water Linacre, E., 1992: Climate Data and Resources: A Conservat, 52:376–380. Reference and Guide. London, Routledge. Landis, T.D., R.W. Tinus and J.P. Barnett, 1999: The Lindner, M., H. Bugmann, P. Lasch, M. Flechsig and Container Tree Nursery Manual. Vol. 6: Seedling W. Cramer, 1997: Regional impacts of climatic Propagation. Agricultural Handbook No. 674. change on forests in the state of Brandenburg, Washington, DC, Forest Service, USDA. Germany. Agric. For. Meteorol., 84:123–135. Landsberg, J., 2003a: Modelling forest ecosystems: Lindner, M., P. Lasch and M. Erhard, 2000: state of the art, challenges, and future direc- Alternative forest management strategies under tions. Can. J. For. Res., 33:385–397. climatic change – prospects for gap model appli- ———, 2003b: Physiology in forest models: history cations in risk analyses. Silva Fennica, and the future. For. Biometry Model. Inf. Sci., 34:101–111. 1:46–63. Liu, J., J.M. Chen, J. Cihlar and W. Chen, 2002: Landsberg, J.J., 1986: Physiological Ecology of Forest Remote sensing based estimation of net primary Production. London, Academic Press. productivity over Canadian landmass. Global Landsberg, J.J. and S.T. Gower, 1997: Applications of Ecol. Biogeogr., 11:115–129. Physiological Ecology to Forest Management. San Liu, J., J.M. Chen, J. Cihlar and W. Park, 1997: A Diego, Academic Press. process-based boreal ecosystems productivity Landsberg, J.J. and R.H. Waring, 1997: A generalised simulator using remote sensing inputs. Rem. model of forest productivity using simplified Sens. Environ., 62:158–175. concepts of radiation-use efficiency, carbon Liu, J., D.T. Price and J.M. Chen, 2005: Nitrogen balance and partitioning. For. Ecol. Manage., controls on ecosystem carbon sequestration: a 95:209–228. model implementation and application to Lasch, P., M. Lindner, B. Ebert, M. Flechsig, Saskatchewan, Canada. Ecol. Model., F.W. Gerstengarbe, F. Suckow and P.C. Werner, 186:178–195. 1999: Regional impact analysis of climate Loehle, C. and D. LeBlanc, 1996: Model-based change on natural and managed forests in the assessments of climate change effects on forests: Federal State of Brandenburg, Germany. Environ. a critical review. Ecol. Model., 90:1–31. Model. Assess., 4:273–286. Logan, J.A., J. Régnière and J.A. Powell, 2003: Latimer, W.H., 1950: General meteorological prin- Assessing the impacts of global warming on ciples. In: Handbook on Aerosols. Chapters from forest pest dynamics. Front. Ecol. Environ., the Summary Technical Report of Division 10, 1:130–137. National Defense Research Committee, Selected López, L.G.G., 1989: Meteorología: Aplicación especial and Published by the U.S. Atomic Energy al microclima del bosque. Medellín, Universidad Commission. United States Office of Scientific Nacional de Colombia. Research and Development. Washington, DC, Loustau, D., A. Bosc, A. Colin, J. Ogée, H. Davi, United States Government Printing Office. C. François, E. Dufrêne, M. Déqué, E. Cloppet, Law, B.E., D. Turner, J. Campbell, O.J. Sun, S. Van D. Arrouays, C. Le Bas, N. Saby, G. Pignard, Tuyl, W.D. Ritts and W.B. Cohen, 2004: N. Hamza, A. Granier, N. Bréda, P. Ciais, Disturbance and climate effects on carbon N. Viovy and F. Delage, 2005: Modeling climate stocks and fluxes across Western Oregon, USA. change effects on the potential production of Global Change Biol., 10:1429–1444. French plains forests at the sub-regional level. Law, B.E., S. Van Tuyl, A. Cescatti and D.D. Baldocchi, Tree Physiol., 25:813–823. 2001: Estimation of leaf area index in open- Luke, R.H. and A.G. McArthur, 1978: Bush Fires in canopy ponderosa pine forests at different Australia. Canberra, Department of Primary 11–64 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Industry Forestry and Timber Bureau/CSIRO McGreight, R.W., 1981: Microwave Ovens for Drying Division of Forest Research. Live Wildland Fuels: An Assessment. Res. Note Mac Nally, R. and E. Fleishman, 2004: A successful PSW-349. Berkeley, Pacific Southwest Forest and predictive model of species richness based on Range Experimental Station, USDA. indicator species. Conserv. Biol., 18:646–654. McGuire, A.D., L.A. Joyce, D.W. Kicklighter, Malmström, C.M. and K.F. Raffa, 2000: Biotic distur- J.M. Melillo, G. Esser and C.J. Vörösmarty, 1993: bance agents in the boreal forest: considerations Productivity response of climax temperate for vegetation change models. Global Change forests to elevated temperature and carbon Biol., 6:35–48. dioxide: a North American comparison between Mariscal, M.J., F. Orgaz and F.J. Villalobos, 2000: two global models. Climatic Change, Modelling and measurements of radiation inter- 24:287–310. ception by olive canopies. Agric. For. Meteorol., ———, 2001: Carbon balance of the terrestrial 100:183–197. biosphere in the twentieth century: analyses of ———, 2004: Light-transmission profiles in an old- CO2, climate and land-use effects with four growth forest canopy: simulations of process-based ecosystem models. Global photosynthetically active radiation by using Biogeochem. Cycles, 15:183–206. spatially explicit radiative transfer models. McIntyre, B.D., S.J. Riha and C.K. Ong, 1996: Light Ecosystems, 7:454–467. interception and evapotranspiration in hedge- Martin, P., 1992: EXE: a climatically sensitive model row agroforestry systems. Agric. For. Meteorol., to study climate change and CO2 enhancement 81:31–40. effects on forest. Aust. J. Bot., 40:717–735. McNaughton, K.G., 1988: Effects of windbreaks on Martin, P., N.J. Rosenberg and M.S. McKenney, turbulent transport and microclimate. Agric. 1989: Sensitivity of evapotranspiration in a Ecosyst. Environ., 22/23:17–36. wheat field, a forest, and a grassland to changes McNaughton, K.G. and T.A. Black, 1973: A study of in climate and direct effects of carbon dioxide. evapotranspiration from a Douglas-fir forest Earth Environ. Sci., 14:117–151. using the energy balance approach. Water Mass, C.F., D. Ovens, K. Westrick and B.A. Colle, Resources Research, 9:1579–1590. 2002: Does increasing horizontal resolution McNulty, S.G., J.M. Vose and W.T. Swank, 1997: produce more skillful forecasts? Bull. Amer. Regional hydrologic response of loblolly pine Meteor. Soc., 83:407–430. to air temperature and precipitation changes. J. Matala, J., J. Hynynen, J. Miina, R. Ojansuu, Amer. Water Res. Assoc., 33:1011–1022. H. Peltola, R. Sievänen, H. Väisänen and Mialet-Serra, I., J. Dauzat and D. Auclair, 2001: S. Kellomäki, 2003: Comparison of a physiolog- Using plant architectural models for estimation ical model and a statistical model for prediction of radiation transfer in a coconut-based agro­ of growth and yield in boreal forests. Ecol. forestry system. Agrofor. Syst., 53:141–149. Model., 161:95–116. Miller, C. and D.L. Urban, 2000: Modeling the Matthews, J.D., 1991: Silvicultural Systems. Oxford, effects of fire management alternatives on Sierra Oxford University Press. Nevada mixed-conifer forests. Ecol. Appl., Mayer, H., 1989: Windthrow. Phil. Trans. Royal Soc. 10:85–94. Lond. B, 324:267–281. Miller, H.G., 1983: Water in forests. Scottish Forestry, Maywald, G.F. and R.W. Sutherst, 1989: User’s Guide 38:165–181. to CLIMEX, a Computer Program for Comparing Miller, P.R. and J.R. McBride (eds), 1999: Oxidant Air Climates in Ecology. CSIRO Division of Pollution Impacts in the Montane Forests of Entomology Report No. 35. Second edition. Southern California: A Case Study of the San Canberra, CSIRO. Bernardino Mountains. Ecological Studies, Vol. McArthur, A.G., 1962: Control Burning in Eucalypt 134. New York, Springer. Forests. Leaflet. Canberra, Australia Forestry and Miller, P.R., J.R. Parmeter, O.C. Taylor and Timber Bureau. E.A. Cardiff, 1963: Ozone injury to the foliage ———, 1966: Weather and Grassland Fire Behaviour. of Pinus ponderosa. Phytopathol., 53:1072–1076. Leaflet. Canberra, Australia Forestry and Timber Mitchell, R.G., 1990: Effects of prescribed fire on Bureau. insect pests. In: Natural and Prescribed Fire in ———, 1967: Fire Behaviour in Eucalypt Forests. Pacific Northwest Forests (J.D. Walstad, Leaflet No. 107. Canberra, Australia Forestry S.R. Radosevich and D.V. Sandberg, eds). and Timber Bureau. Corvallis, Oregon State University Press. McCullough, D., 1998: Fire and insects in northern Mobbs, D.C., M.G.R. Cannell, N.M.J. Crout, boreal forest ecosystems of North America. Ann. G.J. Lawson, A.D. Friend and J. Arah, 1998: Rev. Entomol., 43:107–127. Complementarity of light and water use in CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–65

tropical agroforests. I. Theoretical model southeastern Slovenia. Can. J. For. Res., outline, performance and sensitivity. For. Ecol. 36:629–638. Manage., 102:259–274. Navratil, S., 1995: Minimizing Wind Damage in Mohammed, A.E., C.J. Stigter and H.S. Adam, 1996: Alternative Silviculture Systems in Boreal On shelterbelt design for combating sand inva- Mixedwoods. Edmonton, Canadian Forest sion. Agr. Ecosyst. Environ., 57:81–90. Service, Northern Forestry Centre. Mols, P.J.M. and D. Diederik, 1996: INSIM: a simu- Neal, C. (ed.), 1997: Water quality of the Plynlimon lation environment for pest forecasting and catchments (UK). Hydrol. Earth Syst. Sci. (Special simulation for pest–natural enemy interaction. Issue), 1:381–764. Acta Horticulturae (ISHS), 416:255–262. Neilson, R.P., 1995: A model for predicting Monsi, M. and T. Saeki, 1953: Über den Lichtfaktor continental-scale vegetation distribution and in den Pflanzengesellschaften und seine water balance. Ecol. Appl., 5:362–385. Bedeutung für die Stoffproduktion. J. Jpn. Bot., Netherer, S., J. Pennerstorfer, P. Baier, E. Fuhrer and 14:22–52. A. Schopf, 2003: Monitoring and risk assessment Monteith, J.L., 1964: Evaporation and environ- of the spruce bark beetle, Ips typographus. In: ment. In: The State and Movement of Water in Proceedings: Ecology, Survey and Management of Living Organisms. Proceedings of the 19th Forest Insects, Kraków, Poland, 1–5 September Symposium of the Society of Experimental Biology 2002. (M.L. McManus and A.M. Liebhold, eds). (G.E. Fogg, ed.). Cambridge, Cambridge General Technical Report NE-311. Newtown University Press. Square, Northeastern Research Station, Forest ———, 1977: Climate and the efficiency of crop Service, USDA. production in Britain. Phil. Trans. Roy. Soc. Lond. Ní Dhubháin, A. and J.J. Gardiner, 2004: B, 281:277–294. Weather and forestry. In: Climate, Weather Monteith, J.L. and M.H. Unsworth, 1990: Principles and Irish Agriculture (T. Keane and J.F. Collins, eds). of Environmental Physics. Second edition. Second edition. Dublin, Agmet, Met Éireann. London, Edward Arnold. Nikolov, N. and H. Helmisaari, 1992: Silvics of Morison, J.I.L., 1987: Intercellular CO2 concentra- circumpolar boreal forest trees. In: A Systems tion and stomatal response to CO2. In: Stomatal Analysis of the Global Boreal Forest (H.H. Shugart, Function (E. Zeiger, G.D. Farquhar and I.R. R. Leemans and G.B. Bonan, eds). Cambridge, Cowan, eds). Stanford, Stanford University Cambridge University Press. Press. Nizinski, J.J. and B. Saugier, 1988: A model of leaf Mount, A.B., 1972: The Derivation and Testing of a budding and development for a mature Quercus Soil Dryness Index Using Runoff Data. Bulletin forest. J. Appl. Ecol., 25:643–652. No. 4. Hobart, Tasmanian Forestry Norby, R.J., E.H. DeLucia, B. Gielen, C. Calfapietra, Commission. C.P. Giardina, J.S. King, J. Ledford, H.R. Muller-Edzardz, C., J.-W. Erisman, W. de Vries and McCarthy, D.J.P. Moore, R. Ceulemans, M.S. Ghosh (eds), 1997: Ten Years of Monitoring P. De Angelis, A.C. Finzi, D.F. Karnosky, M.E. Forest Condition in Europe. Studies on Temporal Kubiske, M. Lukac, K.S. Pregitzer, G.E. Scarascia- Development, Spatial Distribution and Impacts of Mugnozza, W.H. Schlesinger and R. Oren, 2005: Natural and Anthropogenic Stress Factors. Overview Forest response to elevated CO2 is conserved Report. Brussels, European Commission; Geneva, across a broad range of productivity. Proc. Natl. United Nations Economic Commission for Acad. Sci. USA, 102:18052–18056. Europe. Norman, J.M. and J.M. Welles, 1983: Radiative Mummery, D., M. Battaglia, C. Beadle and P. Sands, transfer in an array of canopies. Agron. J., 2002: Significance of rainfall distribution in 75:481–488. predicting eucalypt plantation growth, manage- Nygren, P., P. Kiema and S. Rebottaro, 1996: Canopy ment options, and risk assessment using the development, CO2 exchange and carbon process-based model CABALA. For. Ecol. Manage., balance of a modeled agroforestry tree. Tree 193:283–296. Physiol., 16:733–745. Nabuurs, G.-J., A. Pussinen, T. Karjalainen, M. Erhard Oke, T.R., 1987: Boundary Layer Climates. London, and K. Kramer, 2002: Stemwood volume Routledge. increment changes in European forests due to Oker Blom, P., M.R. Kaufmann and M.G. Ryan, climate change: a simulation study with the 1991: Performance of a canopy light intercep- EFISCEN model. Global Change Biol., tion model for conifer shoots, trees and stands. 8:304–316. Tree Physiol., 9:227–243. Nagel, T.A. and J. Diaci, 2006: Intermediate wind Økland, B. and O.N. Bjørnstad, 2003: Synchrony disturbance in an old-growth beech–fir forest in and geographical variation of the spruce bark 11–66 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

beetle (Ips typographus) during a non-epidemic Peterson, C.J., 2000: Damage and recovery of tree period. Pop. Ecol., 45:213–219. species after two different tornadoes in the same Olofsson, E. and K. Blennow, 2005: Decision support old growth forest: a comparison of infrequent for identifying spruce forest stand edges with wind disturbances. For. Ecol. Manage., high probability of wind damage. For. Ecol. 135:237–252. Manage., 207:87–98. Pielke, R.A., Sr, 2001: Influence of the spatial distri- Onyewotu, L.O.Z., C.J. Stigter, A.M. Abdullahi, bution of vegetation and soils on the prediction J.A. Ariyo, E.O. Oladipo and J.J. Owonubi, 2003: of cumulus convective rainfall. Rev. Geophys., Reclamation of desertified farmlands and conse- 39:151–177. quences for its farmers in semiarid northern Prentice, I.C., W. Cramer, S.P. Harrison, R. Leemans, Nigeria: a case study of Yambawa rehabilitation R.A. Monserud and A.M. Solomon, 1992: A scheme. Arid Land Res. Manage., 17:85–101. global biome model based on plant physiology Onyewotu, L.O.Z., C.J. Stigter, E.O. Oladipo and and dominance, soil properties and climate. J.J. Owonubi, 2004: Air movement and its J. Biogeogr., 19:117–134. consequences around a multiple shelterbelt Prentice, I.C., M.T. Sykes and W. Cramer, 1993: A system under advective conditions in semi- simulation model for the transient effects of arid northern Nigeria. Theor. Appl. Climatol., climate change on forest landscapes. Ecol. 79:255–262. Model., 65:51–70. Overpeck, J.T., P.J. Bartlein and T. Webb III, 1991: Price, D.T., D.H. Halliwell, M.J. Apps, W.A. Kurz and Potential magnitude of future vegetation S.R. Curry, 1997: Comprehensive assessment of change in Eastern North America: Comparisons carbon stocks and fluxes in a boreal forest with the Past. Science, 254:692–695. management unit. Can. J. For. Res., Ozier-Lafontaine, H., F. Lecompte and J. Sillon, 27:2005–2016. 1999: Fractal analysis of the root architecture of Priestley, C.H.B. and R.J. Taylor, 1972: On the assess- Gliricidia sepium for the spatial prediction of ment of surface heat flux and evaporation using root branching, size and mass: model large-scale parameters. Monthly Weather Rev., development and evaluation in agroforestry. 100:81–92. Plant and Soil, 209:167–179. Proctor, J., Q. Brearley, H. Dunlop, K. Proctor and Palmer, W.C., 1964: Meteorological Drought. Research D. Taylor, 2001: Local wind damage in Barito Paper No. 45. Washington, DC, United States Ulu, Central Kalimantan: a rare but essential Weather Bureau. event in a lowland dipterocarp forest? J. Trop. Parton, W.J., R. McKeown, V. Kirchner and D. Ojima, Ecol., 17:473–475. 1992: CENTURY Users’ Manual. Ft Collins, Puigdefabregas, J., F. Gallart, O. Biaciotto, M. Allogia Natural Resource Ecology Laboratory, Colorado and G. del Barrio, 1999: Banded vegetation State University. patterning in a subantarctic forest of Tierra del Peet, G.B., 1965: A Fire Danger Rating and Controlled Fuego, as an outcome of the interaction between Burning Guide for the Northern Jarrah (Euc. margi- wind and tree growth. Acta Oecologica, nata Sm.) Forest of Western Australia. Bulletin 20:135–146. No. 74. Perth, Western Australia Forests Pyne, S.J., P.L. Andrews and R.D. Laven, 1996: Department. Introduction to Wildland Fire. Second edition. Pellikka, P. and E. Järvenpää, 2003: Forest stand New York, John Wiley and Sons. characteristics and snow and wind induced Quine, C.P., M. Coutts, B. Gardiner and G. Pyatt, 1995: forest damage in boreal forests. In: Wind Effects Forests and Wind: Management to Minimize on Trees (B. Ruck, ed.). Karlsruhe, University of Damage. Forestry Commission Bulletin No. 114. Karlsruhe. London, Her Majesty’s Stationery Office. Peltola, H., M.-L. Nykanen and S. Kellomaki, 1997: Quine, C.P. and I.M.S. White, 1993: Revised Model computations on the critical combina- Windiness Scores for the Windthrow Hazard tion of snow loading and wind speed for snow Classification. The Revised Scoring Method. damage of Scots pine, Norway spruce and birch Research Information Note No. 230. Edinburgh, sp. at stand edge. For. Ecol. Manage., 95:229–241. Forestry Commission. Peng, C., J. Liu, Q. Dang, M.J. Apps and H. Jiang, Radosevich, S. and K. Osteryoung, 1987: Principles 2002: TRIPLEX: a generic hybrid for predicting governing plant–enviroment interactions. In: forest growth and carbon and nitrogen dynam- Forest Vegetation Management for Conifer ics. Ecol. Model., 154:109–130. Production (J. Walstad and P. Kuch, eds). New Pereira, A.R., L.R. Angelocci and P.C. Sentelhas, York, John Wiley and Sons. 2002: Agrometeorologia: Fundamentos e Aplicações Raich, J.W., E.B. Rastetter, J.M. Melillo, Práticas. Guaíba, Editora Agropecuária. D.W. Kicklighter, P.A. Steudler, B.J. Peterson, CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–67

A.L. Grace, B. Moore III and C.J. Vörösmarty, Rötzer, T., R. Grote and H. Pretzsch, 2005: Effects of 1991: Potential net primary productivity in environmental changes on the vitality of forest South America: application of a global model. stands. Eur. J. Forest Res., 124:349–362. Ecol. Appl., 1:399–429. Ruck, B., C. Kottmeier, C. Mattheck, C. Quine and Raulier, F., P.Y. Bernier and C. Ung, 2000: Modeling G. Wilhelm (eds), 2003: Wind Effects on Trees. the influence of temperature on monthly gross Proceedings of the International Conference, primary productivity of sugar maple stands. Karlsruhe, Germany, 16–18 September 2003. Tree Physiol., 20:333–345. Karlsruhe, University of Karlsruhe. Régnière, J., B.J. Cooke and V. Bergeron, 1995: BioSIM: Rudnicki, M., V.J. Lieffers and U. Silins, 2003: Stand A Computer-based Decision Support Tool for Seasonal structure governs the crown collisions of lodge- Planning of Pest Management Activities. User’s pole pine. Can. J. For. Res., 33:1238–1244. Manual. Canadian Forest Service Laurentian Rudnicki, M., U. Silins, V.J. Lieffers and G. Josi, Forestry Centre Information Report LAU-X-116. 2001: Measure of simultaneous tree sways Sainte-Foy, Natural Resources Canada. and estimation of crown interactions among a Reifsnyder, W.E., 1955: Wind profiles in a small group of trees. Trees Struct. Funct., 15:83–90. isolated forest stand. Forest Science, 1:289–297. Running, S.W. and S.T. Gower, 1991: FOREST BGC, Richards, B.L., O.C. Taylor, G.F. Edmunds, 1968: a general model of forest ecosystem processes Ozone needle mottle of pine in Southern for regional applications. II. Dynamic carbon California. J. Air Pollut. Contr. Assoc., 18:73–77. allocation and nitrogen budgets. Tree Physiol., Richardson, B., D. Whitehead and I.J. McCracken, 9:147–160. 2002: Root-zone water storage and growth of Running, S.W. and E.R. Hunt Jr, 1993: Generalization Pinus radiata in the presence of a broom of a forest ecosystem process model for other understorey. NZ J. For. Sci., 32:208–220. biomes, BIOME-BGC, and an application for Richardson, C., 1981: Stochastic simulation of daily global-scale models. In: Scaling Physiological precipitation, temperature, and solar radiation. Processes: Leaf to Globe (J.R. Ehleringer and Water Resources Research, 17:182–190. C. Field, eds). San Diego, Academic Press. Riehl, H., 1971: An unusual Chinook case. Weather, Salisbury, F.B. and C.W. Ross, 1992: Plant Physiology. 26:241–246. Fourth edition. Belmont, California, Rivera, G. and R. Borchert, 2001: Induction of flow- Wadsworth. ering in tropical trees by a 30-min reduction in Scheller, R.M. and D.J. Mladenoff, 2005: A spatially photoperiod: Evidence from field observations interactive simulation of climate change, and herbarium specimens. Tree Physiol., harvesting, wind, and tree species migration 21:201–212. and projected changes to forest composition Robinson, A.C. and J.C. Rodda, 1969: Rain, wind and biomass in northern Wisconsin, USA. and the aerodynamic characteristics of rain- Global Change Biol., 11:307–321. gauges. Meteorological Magazine, 98:113–119. Schoennagel, T., T.T. Veblen and W.H. Romme, Robinson, M., 1998: 30 years of forest hydrology 2004: The interaction of fire, fuels, and climate changes at Coalburn: water balance and extreme across Rocky Mountain forests. BioScience, flows.Hydrol. Earth Syst. Sci, 2:233–238. 54:661–676. Robinson, M., R.E. Moore, T.R. Nisbet and Schroeder, M.S. and C.C. Buck, 1970: Fire Weather. A J.R. Blackie, 1998: From Moorland to Forest: The Guide for Application of Meteorological­ Information Coalburn Catchment Experiment. Report No. 133. to Forest Fire Control Operations. Forest Service Wallingford, Oxfordshire, Institute of Agric. Handbook No. 360. Washington, DC, Hydrology. Forest Service, USDA. Rodda, J.C., 1967: The systematic error in rainfall Schwela, D.H., J.G. Goldammer, L.H. Morawska and measurement. J. Inst. Wat. Eng., 21:173–177. O. Simpson, 1999: Health Guidelines for Vegetation Romme, W.H. and M.G. Turner, 1991: Implications Fire Events. Published on behalf of UNEP, WHO of global climate change for biogeographic and WMO by the Institute of Environmental patterns in the Greater Yellowstone Ecosystem. Epidemiology, Singapore Ministry of the Conserv. Biol., 5:373–386. Environment. Singapore, Double Six Press. Ross, J. , 1981: The Radiation Regime and Architecture Sellers, P.J., W.J. Shuttleworth, J.L. Dorman, of Plant Stands. The Hague, Dr W. Junk A. Dorcher and J.M. Roberts, 1989: Calibrating Publishers. the Simple Biosphere Model for Amazonian Rothermel, R.C., 1972: A Mathematical Model for tropical forest using field and remote sensing Predicting Fire Spread in Wildland Fuels. RP-INT- data. Part I: Average calibration with field data. 115. Ogden, Forest Service, USDA. J. Appl. Meteorol., 28:727–759. 11–68 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

Semenov, M.A. and E.M. Barrow, 1997: Use of a Solomon, A.M. and R. Leemans, 1997: Boreal forest stochastic weather generator in the develop- carbon stocks and wood supply: past, present ment of climate change scenarios. Climatic and future responses to changing climate, agri- Change, 35:397–414. culture and species availability. Agric. For. Semenov, M.A., R.J. Brooks, E.M. Barrow and Meteorol., 84:137–151. C.W. Richardson, 1998: Comparison of the Speight, M.R. and D. Wainhouse, 1989: Ecology and WGEN and LARS-WG stochastic weather gener- Management of Forest Insects. Oxford, Oxford ators in diverse climates. Climate Research, University Press. 10:95–107. Spittlehouse, D.L., 2003: Water availability, climate Senn, J., 1999: Tree mortality caused by Gremmeniella change and the growth of Douglas-fir in the abietina in a subalpine afforestation in the Georgia Basin. Can. Water Res. J., 28:673–688. central Alps and its relationship with duration Spittlehouse, D.L. and T.A. Black, 1981: A growing of snow cover. Eur. J. Forest Pathol., 29:65–74. season water balance model applied to two Sevruk, B. and M. Nevenic, 1998: The geography Douglas-fir stands. Water Resources Research, and topography effects on the areal pattern of 17:1651–1656. precipitation in a small pre-Alpine basin. Water Squire, G.R., 1990: The Physiology of Tropical Crop Sci. Technol., 37:163–170. Production. Wallingford, Oxfordshire, CABI. Sheehan, K.A., 1992: User’s Guide for GMPHEN: Sridhar, V., A. Sansone, J. Lamarche, T. Dubin and Gypsy Moth Phenology Model. General Technical D.P. Lettenmaier, 2004: Prediction of stream Report NE–158. Washington, DC, Forest Service, temperature in forested watersheds. J. Amer. USDA. Water Res. Assoc., 40:197–213. Shine, R., E.G. Barrott and M.J. Elphick, 2002: Some Staelens, J., L. Nachtergale, S. Luyssaert and N. Lust, like it hot: effects of forest clearing on nest 2003: A model of wind-influenced leaf litterfall temperatures of montane reptiles. Ecology, in a mixed hardwood forest. Can. J. For. Res., 83:2808–2815. 33:201–209. Shuttleworth, W.J., R. Leuning, T.A. Black, J. Grace, Stahl, K., R.D. Moore and I.G. McKendry, 2006: P.G. Jarvis, J. Roberts and H.G. Jones, 1989: Climatology of winter cold spells in relation Micrometeorology of temperate and tropical to mountain pine beetle mortality in forest: discussion. Phil. Trans. Roy. Soc. Lond. B, British Columbia, Canada. Climate Research, 324:299–334. 32:13–23. Sitch, S., B. Smith, I.C. Prentice, A. Arneth, Starfield, A.M. and F.S. Chapin, 1996: Model of A. Bondeau, W. Cramer, J. Kaplan, S. Levis, transient changes in arctic and boreal vegeta- W. Lucht, M.T. Sykes, K. Thonicke and tion in response to climate and land use change. S. Venevsky, 2003: Evaluation of ecosystem Ecol. Appl., 6:842–864. dynamics, plant geography and terrestrial Stathers, R.J., T.P. Rollerson and S.J. Mitchell, 1994: carbon cycling in the LPJ dynamic global Windthrow Handbook for British Columbia Forests. vegetation model. Global Change Biol., Working Paper 9401. Victoria, British Columbia 9:161–185. Ministry of Forests. Skarby, L., H. Ro-Poulsen, F.A.M. Wellburn and Stephens, S.L., 1998: Evaluation of the effects of L.J. Sheppard, 1998: Impacts of ozone on forests: silvicultural and fuels treatments on potential a European perspective. New Phytologist, fire behaviour in Sierra Nevada mixed-conifer 139:109–122. forests. For. Ecol. Manage., 105:21–35. Smith, B., C. Prentice and M. Sykes, 2001: Stewart, R.E., 1987: Seeing the forest for the weeds: Representation of vegetation dynamics in the A synthesis of forest vegetation management. modelling of terrestrial ecosystems: comparing In: Forest Vegetation Management for Conifer two contrasting approaches within European Production (J. Walstad and P. Kuch, eds). New climate space. Global Ecol. Biogeogr., York, John Wiley and Sons. 10:621–637. Stigter, C.J., N.K.N. Al-Amin, S.B.B. Oteng’i, R.M.R. Smith, D.H., W.H. Smith and W. Reifsnyder, 1994: Kainkwa and L.O.Z. Onyewotu, 2003: Scattered Silviculture, pests and disease, forest and wild- trees and wind protection under African condi- land fires. In: Handbook of Agrometeorology tions. In: Wind Effects on Trees. Proceedings of the (J.F. Griffiths, ed.). Oxford, Oxford University International Conference, Karlsruhe, Germany, Press. 16–18 September 2003. (B. Ruck, C. Kottmeier, Smith, K.D., P.B. May and G.M. Moore, 2001: The C. Mattheck, C. Quine and G. Wilhelm, eds). influence of water logging on the establishment Karlsruhe, University of Karlsruhe. of four Australian landscape trees. J. Arboriculture, Stigter, C.J., A.E. Mohammed, N.K.N. Al-Amin, 27:49–56. L.O.Z. Onyewotu, S.B.B. Oteng’i and CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–69

R.M.R. Kainkwa, 2002: Agroforestry solutions Taylor, S.W. and M.E. Alexander, 2006: Science, to some African wind problems. J. Wind Eng. technology, and human factors in fire danger Ind. Aerod., 90:1101–1114. rating: the Canadian experience. Int. J. Wildland Stigter, C.J., L.O.Z. Onyewotu and N.K.N. Al-Amin, Fire, 15:121–135. 2005: Wind and agriculture; an essential subject Taylor, S.W., B.M. Wotton, M.E. Alexander and of the African Participatory Research Agenda. G.N. Dalrymple, 2004: Variation in wind and Paper No. 103. In: Fourth European and African crown fire behaviour in a northern jack pine– Conference on Wind Engineering, Prague, 11–15 black spruce forest. Can. J. For. Res., July 2005 (J. Naprstek and C. Fischer, eds). 34:1561–1576. Prague, ITAMAS. Tharakan, P.J., C.A. Nowak and L.P. Abrahamson, 2000: Stocks, B.J., B.D. Lawson, M.E. Alexander, Modeling growth and biomass production in C.E. Van Wagner, R.S. McAlpine, T.J. Lynham willow plantations in the northeastern and mid- and D.E. Dubé, 1988: The Canadian system of Atlantic United States. In: Proceedings of Bioenergy forest fire danger rating. In: Conference on 2000: Moving Technology into the Marketplace, Bushfire Modelling and Fire Danger Rating System: Buffalo, New York, 15–19 October 2000. Proceedings. Collingwood, CSIRO. Washington, DC, CONEG Policy Research Center. Storck, P., L. Bowling, P. Wetherbee and Thornthwaite, C.W. and B. Holtzman, 1939: The D. Lettenmaier, 1998: Application of a GIS- determination of evaporation from land and based distributed hydrology model for water surfaces. Monthly Weather Rev., 67:4–11. prediction of forest harvest effects on peak Thornthwaite, C.W. and J.R. Mather, 1957: stream flow in the Pacific Northwest. Hydrolog. Instructions and tables for computing potential Process., 12:889–904. evapotranspiration and the water balance. Publ. Sutherst, R.W. and G.F. Maywald, 1985: A comput- Climatol., 3:183–311. erised system for matching climates in ecology. Thornton, P.E., B.E. Law, H.L. Gholz, K.L. Clark, Agric. Ecosyst. Environ., 13:281–99. E. Falge, D.S. Ellsworth, A.H. Goldstein, Sutherst, R.W., G.F. Maywald and B.L. Russell, 1999: R.K. Monson, D. Hollinger, M. Falk, J. Chen CLIMEX: Predicting the Effects of Climate on Plants and J.P. Sparks, 2002: Modeling and measuring and Animals. CD-ROM and User Guide. the effects of disturbance history and climate Collingwood, CSIRO. on carbon and water budgets in evergreen ———, 2000: Estimating vulnerability under global needleleaf forests. Agric. For. Meteorol., change: modular modelling of pests. Agric. 113:185–222. Ecosyst. Environ., 82:303–319. Tian, H., J.M. Melillo, D.W. Kicklighter, Sutton, J.C., T.J. Gillespie and P.D. Hildebrand, A.D. McGuire, J. Helfrich III, B. Moore III and 1984: Monitoring weather factors in relation to C.J. Vörösmarty, 2000: Climatic and biotic plant disease. Plant Disease, 68:78–84. controls on annual carbon storage in Amazonian Sutton, J.C., T.J. Gillespie and T.D.W. James, 1988: ecosystems. Global Ecol. Biogeogr., 9:315–336. Electronic monitoring and use of microproces- Turner, D.P., M. Guzy, M.A. Lefsky, W.D. Ritts, sors in the field. In: Experimental Techniques in S. Van Tuyl and B.E. Law, 2004: Monitoring Plant Disease Epidemiology (J. Krantz and forest carbon sequestration with remote sens- J. Rotem, eds). New York, Springer. ing and carbon cycle modeling. Environ. Tainter, F.H. and F.A. Baker, 1996: Principles of Forest Manage., 33:457–466. Pathology. New York, John Wiley and Sons. Vaisanen, H., H. Strandman and S. Kellomaki, 1994: Takemoto, B.K., A. Bytnerowicz and M.E. Fenn, 2001: A model for simulating the effects of changing Current and future effects of ozone and atmo- climate on the functioning and structure of the spheric nitrogen deposition on California’s mixed boreal forest ecosystem: an approach based on conifer forests. For. Ecol. Manage., 144:159–73. object-oriented design. Tree Physiol., Talkkari, A., H. Peltola, S. Kellomäki and 14:1081–1095. H. Strandman, 2000: Integration of component Valentine, J.M., 1978: Fire Danger Rating in New models from the tree, stand and regional levels Zealand: Review and Evaluation. Forest to assess the risk of wind damage at forest Establishment Report No. 123, New Zealand margins. For. Ecol. Manage., 135:303–313. Forest Service. Rotorua, Forest Research Tausz, M., A. Bytnerowicz, W. Weidner, Institute. M.J. Arbaugh, P. Padgett and D. Grill, 2000: van Noordwijk, M. and B. Lusiana, 2004: WaNuLCAS, Changes in free-radical scavengers describe the a model of water, nutrient and light capture in susceptibility of Pinus ponderosa to ozone in agroforestry systems. Agrofor. Syst., 43:217–242. southern Californian forests. Water Air Soil van Noordwijk, M. and P. Purnomosidhi, 1995: Pollut., 116:249–254. Root architecture in relation to tree–soil–crop 11–70 GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES

interactions and shoot pruning in agroforestry. Wang, Y.P. and P.G. Jarvis, 1990: Description and Agrofor. Syst., 30:161–173. validation of an array model – MAESTRO. Agric. Van Wagner, C.E., 1987: Development and Structure For. Meteorol., 51:257–280. of the Canadian Forest Fire Weather Index System. Weber, M.G. and S.W. Taylor, 1992: The use of Forestry Technical Report No. 35. Ottawa, prescribed fire in the management of Canada’s Canadian Forest Service. forested lands. Forestry Chronicle, 68:324–34. Van Wagner, C.E. and T.L. Pickett, 1985: Equations Weiss, A., 1990: Leaf wetness: Measurements and and FORTRAN Program for the Canadian Forest Fire models. Rem. Sens. Rev., 5:115–124. Weather Index System. Forestry Technical Report Weiss, A. and D.L. Lukens, 1981: Electronic circuit No. 33. Ottawa, Canadian Forest Service. for detecting leaf wetness and comparison of Verberne, E.L.J., J. Hassink, P. de Willigen, two sensors. Plant Disease, 65:41–43. J.J.R. Groot and J.A. van Veen, 1990: Modelling Weiss, A., D.L. Lukens and J.R. Steadman, 1988: A organic matter dynamics in different soils. Neth. sensor for the direct measurement of leaf J. Agric. Sci., 38:221–238. wetness: construction techniques and testing Vetter, M., C. Wirth, H. Böttcher, G. Churkina, under controlled conditions. Agric. For. Meteorol., E.-D. Schulze, T. Wutzler and G. Weber, 2005: 43:241–249. Partitioning direct and indirect human-induced Wermelinger, B., 2004: Ecology and management effects on carbon sequestration of managed of the spruce bark beetle Ips typographus – a coniferous forests using model simulations and review of recent research. For. Ecol. Manage., forest inventories. Global Change Biol., 202:67–82. 11:810–827. Wertheim, S.J., 1998: Chemical thinning of decidu- Viegas, D.X., B. Sol, G. Bovio, A. Nosenzo and ous fruit trees. Acta Horticulturae, 463:445–462. A.D. Ferreira, 1999: Comparative study of vari- ———, 2000: Developments in the chemical thin- ous methods of fire danger evaluation in southern ning of apple and pear. Plant Growth Regul., Europe. Int. J. Wildland Fire, 9:235–246. 31:85–100. Viereck, L.A., 1973: Wildfire in the taiga of Alaska. Whicker, J.J., J.E. Pinder and D.D. Breshears, 2006: Quat. Res., 3:465–495. Increased wind erosion from forest Volney, W.J.A. and R.A. Fleming, 2000: Climate wildfire: Implications for contaminant-related change and impacts of boreal forest insects. risks. J. Environ. Qual., 35:468–478. Agric. Ecosyst. Environ., 82:283–294. White, M.A., P.E. Thornton and S.W. Running, Wake, C.M.F. and A. Fennell, 2000: Morphological, 1997: A continental phenology model for moni- physiological and dormancy responses of three toring vegetation responses to interannual Vitis genotypes to short photoperiod. Physiologia climate variability. Global Biogeochem. Cycles, Plantarum, 109:203–210. 11:217–234. Wallace, J.S., N.A. Jackson, and C.K. Ong, 1999: Wikler, K., A.J. Storer, W. Newman, T.R. Gordon and Modelling soil evaporation in an agroforestry D.L. Wood, 2003: The dynamics of an intro- system in Kenya. Agric. For. Meteorol., duced pathogen in a native Monterey pine 94:189–202. (Pinus radiata) forest. For. Ecol. Manage., Walstad, J., M. Newton and D. Gjerstad, 1987: 179:209–221. Overview of vegetation management Wilks, D.S., 1992: Adapting stochastic weather alternatives. In: Forest Vegetation Management for generation algorithms for climate change stud- Conifer Production (J. Walstad and P. Kuch, eds). ies. Climatic Change, 22:67–84. New York, John Wiley and Sons. Williams, D.W. and A.M. Liebhold, 2000: Climate Wang, H. and E.S. Tackle, 1997: Model-simulated change and the outbreak ranges of two North influence of shelterbelt shape on wind shelter- American bark beetles. Agric. For. Entomol., ing efficiency.J. Appl. Meteorol., 36:697–704. 4:87–99. Wang, K.-Y., S. Kellomäki, T. Zha and H. Peltola, Williams, M., B.J. Bond and M.G. Ryan, 2001: 2004: Seasonal variation in energy Evaluating different soil and plant hydraulic and water fluxes in a pine forest: an constraints on tree function using a model and analysis based on eddy covariance and an inte- sap flow data from ponderosa pine. Plant Cell grated model. Ecol. Model., 179:259–279. Environ., 24:679–690. Wang, S., R.F. Grant, D.L. Verseghy and T.A. Black, Williams, M., Y. Malhi, A.D. Nobre, E.B. Rastetter, 2001: Modelling plant carbon and nitrogen J. Grace and M.G.P. Pereira, 1998: Seasonal varia- dynamics of a boreal aspen forest in CLASS : the tion in net carbon exchange and evapotranspiration Canadian Land Surface Scheme. Ecol. Model., in a Brazilian rain forest: a modelling analysis. 142:135–154. Plant Cell Environ., 21:953–968. CHAPTER 11. APPLICATIONS OF METEOROLOGY FOR FORESTRY AND NON-FOREST TREES 11–71

Wilson, J.D. and T.K. Flesch, 1999: Wind and Xu, C.-Y., 1999: Operational testing of a water remnant tree sway in forest cutblocks. III. A balance model for predicting climate change windflow model to diagnose spatial variation. impacts. Agric. For. Meteorol., 98:295–304. Agric. For. Meteorol., 93:259–282. Xu, C.-Y., J. Seibert and S. Halldin, 1996: Regional Wise, M., G. Moore and D. VanDine (eds), 2004: water balance modelling in the NOPEX area: Landslide Risk Case Studies in Forest Development development and application of monthly water Planning and Operations. Land Management balance models. J. Hydrol., 180:211–236. Handbook No. 56. Victoria, British Columbia Xu, C.-Y. and V.P. Singh, 2004: Review on regional Ministry of Forests. water resources assessment under stationary Wisse, J.A. and K. Stigter, 2007: Wind engineering and changing climate. Water Resources in Africa. J. Wind Eng. Ind. Aerod., 95:908–927. Management, 18:591–612. World Meteorological Organization, 1964: Yang, Y., Y.-L. Chen and F.M. Fujioka, 2005: Windbreaks and Shelterbelts (J. Van Eimern, Numerical simulations of the island-induced R. Karschon, L.A. Razumova and G.W. circulations over the island of Hawaii during Robertson) (WMO-No. 147), Geneva. HaRP. Monthly Weather Rev., 133:3693–3713. ———, 1978a: Symposium on Forest Meteorology, Zeng, H., H. Peltola, A. Talkkari, A. Venalainen, Ottawa, Canada, 21–25 August 1978 (WMO- H. Strandman, S. Kellomaki and K. Wang, 2004: No. 527), Geneva. Influence of clear-cutting on the risk of wind ———, 1978b: Systems for Evaluating and Predicting damage at forest edges. For. Ecol. Manage., the Effects of Weather and Climate on Wildland 203:77–88. Fires (W.E. Reifsnyder). Special Environmental Zhang, Y., C. Li, C.C. Trettin, H. Li and G. Sun, Report No. 11 (WMO-No. 496), Geneva. 2002: An integrated model of soil, hydrology, ———, 1982: Wildland Fires Particularly in Tropical and vegetation for carbon dynamics in wetland Regions (A.B. Oguntala). CAgM Report No. 10, ecosystems. Global Biogeochem. Cycles, 16:1–17. Geneva. Zhao, C., D. Zheng, C.J. Stigter, W. He, D. Tuo and ———, 1988: Agrometeorological Aspects of Operational P. Zhao, 2006: An index guiding temporal Crop Protection (WMO-No. 687), Geneva. planting policies for wind erosion reduction. ———, 1994a: Guide to Hydrological Practices. Fifth Arid Land Res. Manage., 20:233–244. edition (WMO-No. 168), Geneva. Zhao, W., R.J. Qualls and P.R. Berliner, 2003: ———, 1994b: Systems for Evaluating and Predicting Modeling of the short wave radiation distribu- the Effects of Weather and Climate on Wild-land tion in an agroforestry system. Agric. For. Fires (W.E. Reifsnyder and B. Albers). Second Meteorol., 118:185–206. edition (WMO-No. 496), Geneva. Zhu, J., Y. Gonda, T. Matsuzaki and M. Yamamoto, ———, 2000: Climate Variability, Agriculture and 2003: Modeling relative wind speed by optical Forestry: Towards Sustainability (M.J. Salinger, stratification porosity within the canopy of a R.L. Desjardins, H. Janzen, P.H. Karing, coastal protective forest at different stem densi- S. Veerasamy and G. Zipoli) (WMO-No. 928), ties. Silva Fennica, 37:189–204. Geneva. Zhu, J., X. Li, Z. Liu, W. Cao, Y. Gonda and T. Matsuzaki, ———, 2008: Guide to Meteorological Measurements 2006: Factors affecting the snow and wind induced and Methods of Observation. Seventh edition damage of a montane secondary forest in north- (WMO-No. 8), Geneva. eastern China. Silva Fennica, 40:37–51.