- Email: [email protected]
Atmospheric scales of biotic dispersal
Agricultural and Forest Meteorology 97 (1999) 263–274
Atmospheric scales of biotic dispersal J.K. Westbrook a , S.A. Isard b b
a USDA, ARS, College Station, TX, USA Department of Geography, University of Illinois, IL, USA
Accepted 21 July 1999
Abstract Recent advances in meteorological technologies and techniques are providing new insight into microscale, mesoscale, and macroscale aerobiological processes. For example, Lidar systems have identified microscale characteristics of atmospheric turbulence over agricultural fields which cannot be readily determined by conventional (site-specific) atmospheric sensors. Also, neutrally buoyant superpressure balloons (tetroons) have been tracked more than 400 km per night indicating atmospheric pathways of migrating insects between agricultural regions in south-central Texas. Such atmospheric trajectories often reveal substantial day-to-day variation of aerobiological pathways and, consequently, affect the risk of pest infestations and host infections. Further, the NEXRAD network of WSR-88D Doppler weather radars can measure the aerial abundance, speed, and displacement direction of concentrated biota over areas of >1000 km2 . Emphasis is placed on identifying biologically-relevant, temporal and spatial scales of atmospheric motion and other atmospheric variables which help control the abundance and dispersal of airborne biota, specifically insects, spores, pollen, fungi, and plant pathogens. Major technologies, including the NEXRAD network of WSR-88D Doppler weather radars, are described, and examples are presented for aerobiological applications. ©1999 Published by Elsevier Science B.V. All rights reserved. Keywords: Aerobiology; Dispersal; Atmospheric scale; Insects; Pollen; Spores; Fungi; Plant pathogens
1. Introduction The importance of movement of plant pathogens, spores, pollens, fungi, insects, and a variety of other aerobiota in the atmosphere is becoming increasingly recognized, but the aerial transport process remains poorly understood. The link between these biological systems and the atmosphere is key to understanding the population dynamics of, and diseases spread by, aerobiota. This connection is often capricious: prolific sources of insects or plant pathogens can only cause widespread plant infestations or infections when, and where, wind and other atmospheric factors are conducive for transport. Conversely, strong and persistent winds and/or zones of convergence are of no consequence to plant and animal dispersal unless there are
sources of biota ready to move in the atmosphere and appropriate hosts elsewhere. Knowledge of these biological and meteorological linkages, coupled with information on biological sources and availability and susceptibility of host species, provide the potential to understand, and prevent, dispersal episodes that result in catastrophic crop losses and animal (including human) health epidemics. We maintain that an understanding of the spatial and temporal scales of atmospheric motions and biological processes (Gage et al., 1999) provide an important framework for coupling biological and atmospheric events and processes that influence aerial dispersal of organisms. For some organisms, the energy used for take-off and ascent in the atmosphere comes from the environment, while others actively leap or fly into the air.
0168-1923/99/$ – see front matter ©1999 Published by Elsevier Science B.V. All rights reserved. PII: S 0 1 6 8 - 1 9 2 3 ( 9 9 ) 0 0 0 7 1 - 4
264
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
A large number of organisms move at night when the atmosphere is frequently stable, others utilize convective currents during daytime to ascend high in the atmosphere, while many initiate and/or continue aerial movement regardless of the time of day. For example, corn earworm moths, Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae), consistently initiate dispersal flight ca. 0.5 h after sunset; fly within the lowest 2000–3000 m of the atmosphere; and terminate flight ca. 0.5 h before sunrise. Occasionally, insects may terminate flight earlier when encountering cold air temperatures and convergent winds associated with a cold front (Symmons and Luard, 1982), or later when flying over open water before sunrise (Wolf et al., 1986b). In contrast, the release of tobacco blue mold spores, Peronospora tabacina Adam, occurs during daylight hours with a peak near mid-day when ambient relative humidity drops below 70% (Aylor and Taylor, 1983). These spores can be transported more than 100 km by synoptic scale airflow (Aylor et al., 1982). Their survival in the atmosphere is primarily affected by the ultraviolet wavelengths of solar radiation and, thus, is prolonged by cloud cover. Finally, the descent of spores to the Earth is caused by dry and wet deposition, although washout by rain is especially important for initiating tobacco blue mold epidemics (Aylor, 1986). These are only two examples where the initiation of aerial movement, the duration of transport, and the altitude of movement are biologically dependent parameters that influence the types of the motion systems encountered during atmospheric transport. Atmospheric motion occurs on a continuum of space and time scales, from seasonal global circulations to microscale eddies which ultimately dissipate kinetic energy through friction (Orlanski, 1975). Orlanski (1975) determined that, for practical reasons, the horizontal scale of motion was the best term for classifying scales of motion. Gage et al. (1999) present atmospheric scales of motion in the context of ecosystems, ranging from habitats (microscale), to landscapes and sections (mesoscale), and to divisions, domains, and continents (macroscale). It is important to consider atmospheric motion systems that occur along this continuum in order to identify potentially relevant systems and exclude others which are unimportant, for particular aerobiological processes. No single atmospheric motion system is responsible for biotic movement in the atmosphere; how-
ever, a continuum of important atmospheric motions is associated with most biological transport events. A low-level wind maximum (jet), for example, may be embedded in the flow between atmospheric high-pressure and low-pressure systems. Within this atmospheric system, turbulent eddies act to reduce the anomalous wind speed maximum, while dynamic forces accelerate winds in some areas and decelerate winds in others. Microscale and mesoscale atmospheric circulations may limit the spatial distribution of airborne biota, while the entire aerobiological system may be displaced by the macroscale atmospheric circulation. Atmospheric motion systems are generally positively correlated in space and time scales; that is, motions which occur in small volumes of air have short life spans and motions involving extensive volumes have substantially longer time periods. For example, wind blowing across a rough surface generates tiny eddies that persist for a few seconds. Insolation on a dry desert surface can cause thermal convective circulations (dust devils) which may be several meters in horizontal diameter, 100 m high, and persist for several minutes. Landscape-driven winds — such as mountain-valley and land-sea circulations — are generally diurnal, characterized by vertical and horizontal dimensions on the order of 1000 m and 10 000 m, respectively, and an abrupt change in wind direction within the diel cycle. Warm and cold airflows converging into mid-latitude cyclones that travel across continents and oceans can persist for one or two weeks. While at the largest scales, the trade winds and the westerlies span the globe and are essentially continuous in time, although their location, intensity, and direction of movement vary seasonally. Thus, the atmospheric motion systems in which particular biota disperse may require drastically different measurement protocols. Atmospheric motions transport, disperse, or concentrate biota (Gregory, 1973; Drake and Farrow, 1988; Pedgley, 1990). Theoretically, a strong laminar uniform flow across a source of spores can carry them downwind without significantly altering their concentration. However, most transport of biota in the atmosphere occurs within turbulent air flows which disperse organisms from a single source. Meteorological factors and biological behaviors can also interact to increase concentrations of biota in the atmosphere.
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
265
Aerial concentration of biota can increase when insects resist ascent into cold zones in the atmosphere or where wind converges at a gust flow or sea breeze front. Examples of the use of atmospheric scales of motion as a framework for studying aerobiological systems are presented below. Further, new technologies are described which can detect airborne biota or measure the wind field and other atmospheric variables which influence the dispersal of biota. This paper concentrates on atmospheric scales of motion contributing to the dispersal of biota above the surface layer. Atmospheric dispersal of biota is presented in three phases: take-off, transport, and termination. Atmospheric scales, processes, and technological developments are discussed with example aerobiological systems described for each of the three phases of atmospheric transport. Pre-conditioning of biota and impacts of their dispersal are covered in more detail elsewhere in this special issue.
2. Ascent and vertical distribution of biota in the atmosphere In order for the atmosphere to transport pollen, spores, and insects over long distances, the biota must first attain suitable altitudes in the atmosphere. In the case of pollen, spores, and flightless insects, convection keeps them aloft while they drift downwind. Flying insects must ascend above the insect boundary layer (Taylor, 1974) which is defined as the atmospheric layer nearest the ground where the insect’s airspeed is greater than the wind speed: hence, the insect largely controls its own flight path. This section describes detection of the ascent and vertical distribution of biota and atmospheric effects toward that end. Atmospheric mixing (forced and free convection) is necessary to lift pollen, spores, and flightless insects to altitudes sufficient for long-distance dispersal. Mixing processes are largely associated with the temperature lapse rate, wind shear, and storms. Atmospheric mixing (and distribution of biota) is mainly confined to the planetary boundary layer (PBL) which extends from the earth’s surface to the geostrophic wind level (Huschke, 1959), and varies within diurnal and seasonal cycles. Free convection due to surface heating is the major source of daytime atmospheric mixing.
Fig. 1. Annual atmospheric mixing depth (×100 m) in the continental U.S.: (a) morning, and (b) afternoon (after Holzworth, 1972).
At night, mechanical mixing (forced convection) becomes important. Mean annual maps of atmospheric mixing depth for morning and afternoon (Holzworth, 1972) are presented in Fig. 1. Stable layers, frequently inversions, suppress mixing above the mixed layer. These maps of mean annual atmospheric mixing depth suggest that pollen, spores, and insects could be readily distributed throughout the lowest 800–2600 m of the atmosphere during the day, and could be concentrated within shallower atmospheric layers during the night. Many species of insects fly to high altitudes to begin their long-distance dispersal. The monarch butterfly, Danaus plexippus (L.), and many other butterflies soar within convective thermals (≈1 m s−1 vertical velocity) to maximize their long-distance dispersal with respect to metabolic energy demands. Nocturnal convection is generally very weak, but many species of insects quickly fly from the surface to altitudes above the Planetary Boundary Layer (PBL). For example, corn earworm moths can ascend in flight at ca. 1 m s−1 (Wolf et al., 1994; Lingren et al., 1995).
266
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
Table 1 Reported flight altitudes of selected insects Species
Altitude (m AGL)
Method of collection
Reference
Pectinophora gossypiella Nilaparvata lugens Paederus fuscipes
610 450 150
airplane cannisters kytoon-towed nets kytoon-towed nets
Glick and Noble (1961) Reynolds and Riley (1997) Reynolds and Riley (1997)
Thus, atmospheric convection and active flight are often sufficient to distribute biota within the lowest 1000 m of the atmosphere within 15 min. Aylor (1986) provided a framework for studying the long-distance dispersal of fungal spores that was based on an understanding of air flow in the lower atmosphere: thus, it can be applied in a general sense to all passively-transported and weakly-flying aerobiota. Critical information for predicting ascent of organisms into the atmosphere includes: (1) the population at the source; (2) the structure of the vegetation at the source; (3) time when individuals become airborne; (4) height in the vegetation where aerial movement is initiated; (5) wind speed and direction above the vegetation; and (6) the stability of the atmosphere. The predictive capability that results from obtaining these types of information has been demonstrated for the tobacco blue mold spore system (e.g. Aylor, 1986; Davis, 1987) and has led to a World Wide Web-based forecasting system for the spread of this pathogen (Main et al., 1998). The use of entomological radar and night-vision equipment (Lingren et al., 1995) to make direct observation of insect flight has provided a number of important insights about the ascent of organisms into the PBL. For example, studies involving radar measurements of the take-off and ascent of locusts and grasshoppers in Mali (Riley, 1975; Riley and Reynolds, 1979), the African armyworm moth, Spodoptera exempta (Wlk.), in Kenya (Riley et al., 1983), and brown plant hoppers, Nilaparvata lugens (Stål), in the Philippines and China (Riley et al., 1987), have provided information on insect densities and orientation in flight, their rate of climb in the PBL, their altitude of flight (Table 1), and the role of temperature and wind on insect stratification in the lower atmosphere. Similarly, radar measurements of corn earworm moths from corn fields in the Lower Rio Grande Valley of Texas and Mexico (Wolf et al., 1990, 1994) have been used to characterize starting
Fig. 2. Vertical distribution of wind speed and the concentration of corn earworm-size insects (number per 106 m3 [MCM]) during the occurrence of a nocturnal low-level jet at La Paloma, Texas, on 4 April 1982 (after Wolf et al., 1986a).
time, duration of the take-off event, ascent rate, numbers of the moths in the PBL, mean altitude of flight, and the relationship between meteorological features (e.g. wind speed maximum, wind shear, and cloud cover) and these aerobiological factors (Fig. 2). There is little comparable research, however, on the role of atmospheric motions on the process of atmospheric ascent in other aerobiological systems. Far more effort has been focused on determining the types, number, and vertical distributions of organisms in the atmosphere, with little reference to the atmospheric factors that influenced these distributions. It has long been recognized that daytime convection mixes pollen, spores, wingless insects, and weakly flying insects throughout the PBL (e.g. Gregory, 1973; Johnson, 1969; Pedgley, 1982). Callahan et al. (1972) collected nearly 3000 corn earworm moths in light traps mounted between 108 and 349 m above ground level (AGL) during two years of sampling. Aircraft mounted devices have collected many such organisms
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
within the lowest 3 km AGL (e.g. Coad, 1931; Glick, 1939; Hirst and Hurst, 1967; Raynor et al., 1974; Beerwinkle et al., 1989; Isard et al., 1990). Knowledge of vertical distribution of organisms is important to predicting long-distance aerial movement of passive and weak-flying insects that remain aloft after sunset and are carried for long distances downwind in the stable nocturnal PBL, especially if they are in fast-moving airflows (e.g. nocturnal low-level jets) which may develop above a surface-based or elevated temperature inversion (e.g. Barry and Taylor, 1968; Johnson, 1969; Irwin and Thresh, 1988). Two relatively new technologies have increased the capacity to study microscale atmospheric motions that assist the ascent of biota into the atmosphere: lidar instrumentation and acoustic radar. Lidar instrumentation can measure microscale atmospheric motions in the surface boundary layer and PBL (Cohn et al., 1998). For example, Cooper et al. (1992) measured the vertical and horizontal heterogeneity of water vapor concentration over an irrigated field of alfalfa, Medicago sativa L., during periods of high transpiration rates using a Raman Lidar. They found rising and sinking moist air plume structures (≈30-m diameter) that lasted for 3 to 10 min. A Raman Lidar also identified coherent (highly organized) structures in the water-vapor concentration over an irrigated orchard during periods of high transpiration rates (Cooper et al., 1994). When compared with time-series analysis of point-instrument data, Cooper et al. (1994) determined that asymmetrical ramp structures of 20 to 30 m had lifetimes of 20 to 30 s. Thus, lidar measurements of microscale convective plumes might also identify the propensity of pollen, spores, and flightless insects to be entrained into the atmosphere. Acoustic radars have been extremely valuable in monitoring the vertical structure of the lowest 1000 m of the PBL. From continuous recordings of acoustic radar signals, Cronenwett et al. (1972) identified vertical and temporal characteristics of atmospheric phenomena including thermal convection, stratus clouds, passage of a cold front, unstable Kelvin–Helmholtz waves, a persistent temperature inversion, and airborne biota. Continuous operation of acoustic radars has been extremely useful in studies of the diel evolution of the PBL. Thus, lidar and acoustic radars provide capabilities for spatial imaging of microscale atmospheric structures in the surface boundary layer and
267
vertical structures in the PBL. If coupled with entomological measurements and/or microbiota sampling, these relatively new technologies could provide an exciting avenue to further explore the role of atmospheric structures to the initiation of movement in the atmosphere by organisms.
3. Transport of airborne biota The vertical profile of wind throughout the PBL substantially determines the rate and direction of displacement of biota. Thus, thermodynamic and kinematic forces not only affect wind velocity but also the dispersal of biota. The Coriolis force acts on the horizontal wind velocity to affect the vertical profile of wind direction through a depth of the PBL known as the Ekman layer (Wyngaard, 1988). As wind speed increases with height above the ground due to diminished frictional forces, the Coriolis force increasingly deflects the wind clockwise for a total of ca. 45◦ until the wind is in geostrophic balance with the wind above the PBL. The Ekman layer approximation is usually a good representation of the stable PBL, but is less representative of the neutral PBL and convective PBL. The vertical gradient of wind speed and wind direction generates shear forces which lead to atmospheric mixing and the dissipation of kinetic energy. The size of the turbulent eddies involved in atmospheric mixing increases for deeper PBLs. Shallow PBLs, capped by a strong inversion, severely limit the maximum size of turbulent eddies. Temporal and spatial variability of the vertical transfer (flux) of momentum is governed by the vertical profiles of wind speed and wind direction, as well as atmospheric stability and convective heat flux. Estimates of biotic dispersal have generally been derived from vertical profiles of wind velocity and other atmospheric variables recorded by National Weather Service (NWS) rawinsondes. The NWS rawinsondes provide data twice daily within a network of stations spaced ≈400 km apart. Alternatively, some research studies have used instrumented towers as high as ≈300 m AGL. Radar wind profilers (i.e. wind profilers) are now deployed within an operational network in the Central U.S. and also by individual scientists. Wind profilers provide continuous wind
268
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
speed and direction data which is often statistically summarized at ≈15-min intervals from ca. 250 to 2000 m AGL. The spatiotemporal resolution of wind profiler measurements could significantly improve the accuracy of aerobiological dispersion models. Rapid technological developments in computing power have markedly improved the utility and availability of atmospheric transport and dispersion models, especially for mesoscale and macroscale processes. Many of these models, such as the HYsplit model (Draxler and Hess, 1997) were developed for general applications in atmospheric science, and have been adapted for specific applications including atmospheric chemical transport and deposition, dispersion of smoke from forest fires and volcanoes, and dispersion of radioactive material from accidental releases. These models may be able to accommodate passive dispersants, such as plant pathogens and wingless insects, and may be useful with modification for modeling the dispersion of flying insects (Scott and Achtemeier, 1987) and other organisms (Davis, 1987). The use of atmospheric trajectory and dispersion measurements and models can be applied diagnostically or predictively. Sea-breeze and slope circulations are derived from the cycle of diurnal heating, and consequently concentrate airborne biota and reverse the direction of biotic transport within a diurnal period. For example, the sea-breeze circulation consists of an afternoon on-shore surface wind when the land is warmer than the coastal water, and a morning off-shore surface wind when the coastal water is warmer than the land. The sea-breeze circulation typically has a vertical depth of 1–2 km and a horizontal width of ca. 20–100 km perpendicular to the coastline. Upper-level winds complete the sea-breeze circulation in an opposite direction relative to the surface winds. Weakly-flying insects were detected by Doppler radar to amass high concentrations along the Atlantic coast of Florida before dispersing inland following the onset of the sea breeze (Russell and Wilson, 1996). The dispersal of small insects away from the Atlantic coastline of France, and their possible deposition into the Atlantic Ocean, occurred in the evening (off-shore) land-breeze (Sauvageot and Despaux, 1996). Slope circulations are similar to the sea-breeze circulations, except that the magnitude of the slope is a major cause of horizontal temperature
gradients. Differential heating and cooling of slopes within a mountain valley cause slope winds to rise or sink, respectively. Model calculations and field observations indicated that mountain-valley slope flow circulations displaced gypsy moth larvae from one ridgeline to the next (Mason and McManus, 1981). Thunderstorm circulations and other highly convergent mesoscale flows are often responsible for concentrating airborne biota. Dickison et al. (1983) found that large aerial concentrations of spruce budworm moths, Choristoneura fumiferana (Clemens), were associated with wind flow in thunderstorm systems. Additional case studies (Dickison et al., 1986) showed that large concentrations of spruce budworm moths were found between thunderstorm cells at heights greater than 600 m AGL. Cold thunderstorm outflow winds may induce aerodynamic bores ca. 45 km wide and 4 km high which propagate solitary waves (e.g. 5 solitary waves in 3 h) (Locatelli et al., 1998). Drake (1985b) detected concentration lines of insects within such solitary waves. Aerobiologists have given much attention to the continental transport of biota by low-level wind maxima, especially the nocturnal low-level jet (LLJ) in the Central U.S. (Johnson, 1995). The Central U.S. between the Rocky and Appalachian Mountains has few obstacles to impede the northward transport of biota. Wind maxima often form under clear skies after sunset when radiative cooling creates a stable PBL which decreases frictional deceleration of the prevailing winds aloft. Bonner (1968) prepared a climatological study based on selected criteria of the magnitude and vertical shear associated with low-level wind maxima to define an LLJ which occurs most frequently along a south-southwesterly to north-northeasterly axis through Oklahoma (Fig. 3). The LLJ jet can accelerate to a maximum speed of 28 m s−1 , and usually develops between 700 m and 1000 m AGL. Surface winds are often light and variable under an LLJ, which is generally characterized by a vertical half-width of ≈100 to 200 m. In the study, Bonner (1968) established vertical and horizontal dimensions, geographic distribution, and frequency of occurrence of the LLJ. McCorcle (1988) described the influence of soil moisture on the development of the LLJ. Radar studies have often found that insects concentrate their flight at the altitude of the LLJ, or other low-level wind maxima (Wolf et al., 1986a; Drake,
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
269
Table 2 Reported atmospheric dispersal distances of selected insects Species
Distancea (km)
Method of determination
Reference
Helicoverpa zea Helicoverpa zea Agrotis ipsilon
661 230 1142
external pollen identification internal spore identification internal dye marker
Westbrook et al., 1998a Westbrook et al., 1998a Showers et al., 1989
a
The estimated duration of flight ranged from one to three successive nights.
Fig. 3. Envelope containing the low-level jet axes in 26 out of 28 cases of strongest jet occurrence in the Central U.S. (after Bonner, 1968).
1985a), perhaps to take advantage of high-speed transport. Landscape-driven mesoscale atmospheric circulations are important to the first occurrence and outbreak of many plant pest invasions. Historically, this association has been determined by collecting biota in various types of traps or collection devices (Hartstack et al., 1982; Goodenough et al., 1988), and computing wind trajectories between source areas and collection sites. Occasionally, insects have been marked, released, and recaptured to validate flight trajectories with respect to prevailing synoptic weather conditions and computed wind trajectories. Neutrally buoyant weather balloons have also been used to measure the wind trajectory at the altitude of maximum concentration of flying insects (Westbrook et al., 1995a). Mesoscale moth flight trajectory calculations were validated by the capture of moths marked naturally with unique pollen (Lingren
Fig. 4. Image of (a) a corn earworm moth, Helicoverpa zea (Boddie), and (b) a scanning electron micrograph of two Citrus sp. pollen grains (C) on the proboscis (P) of a corn earworm moth. A moth scale (S) can be seen in the micrograph. The white bar represents 10 mm. (Micrograph courtesy Dr. Gretchen D. Jones and Kim D. Ostiguin, USDA, ARS, Areawide Pest Management Research Unit).
et al., 1994) and artificially marked with unique spores (Westbrook et al., 1998a). Examples of long-distance atmospheric dispersal of selected biota are listed in Table 2. An example of mesoscale transport of a flying insect species (i.e. corn earworm) illustrates the scale and variability of atmospheric transport conditions (Westbrook et al., 1998a). A corn earworm moth is shown in Fig. 4(a). Citrus pollen found on the proboscis of many corn earworm moths (Fig. 4(b)) indicated that many captured moths had flown hundreds of kilometers from the nearest commercial citrus orchards.
270
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
Fig. 5. Areas (shaded) of daily capture of unmarked and marked corn earworm moths exceeding 10 moths per pheromone trap in Texas on 20 March 1995. Squares indicate locations of pheromone traps. Solid circles indicate locations where pheromone traps captured citrus pollen-contaminated corn earworm moths. Synoptic weather conditions were valid at 0600 Central Standard Time.
Pheromone traps on 17 March 1995 failed to capture corn earworm moths marked with Citrus pollen >330 km north of the commercial Citrus production area in the Lower Rio Grande Valley (LRGV) of southern Texas. However, northward atmospheric transport in advance of an approaching cold front was associated with the capture of citrus-marked moths as far as 660 km from the LRGV on 20 March 1995 (Fig. 5). Distance and direction of atmospheric trajectories are often highly variable, even over the course of several successive days and could profoundly increase the dispersal of corn earworm moths and other airborne biota (Westbrook et al., 1995b). The NEXRAD system of WSR-88D Doppler weather radars has detected atmospheric dispersal of concentrations of insects as well as birds and bats. Westbrook et al. (1998b) found a high correlation between the aerial concentration of corn earworm-size targets and WSR-88D base reflectivity measurements. The NEXRAD system was implemented to detect mesoscale and macroscale atmospheric circulations and precipitation systems, which are important factors for the aerial dispersal of biota. The NEXRAD system of WSR-88D Doppler weather radars provides nearly complete spatial coverage of the atmosphere at 3000 m AGL over the continental U.S. (NOAA, 1990; Klazura and Imy, 1993; Crum and Alberty, 1993). These Doppler radars can detect the distribu-
tion of precipitation rates, biota, and particulates over areas of ≈100–10 000 km2 . Additionally, Doppler radars can detect the velocity of the wind and flying organisms. The NEXRAD system records the spatial distribution of these aerobiological parameters every 6–10 min throughout the day and night. Muller and Willis (1983) defined a set of synoptic weather features that could be related to the climatological potential for insect migration over the southern U.S. (Muller, 1985). Favorable wind conditions for northward migration occurred when the Bermuda High was located in the southeastern U.S. and a low-pressure system developed along the Front Range (eastern side) of the Rocky Mountains. Often a low-pressure cell develops along a frontal system in the central U.S., drawing warm southerly wind over much of the south-central U.S. Synoptic climatology has identified temporal scales of atmospheric circulations which affect the potential for migration events. Southward (long-distance return) migration has been identified in several species of insects. Autumnal migrations of monarch butterflies, thousands of kilometers from Canada to overwintering habitats in Mexico, are well documented, primarily because this conspicuous butterfly often flies in the lowest 10–30 m of the daytime PBL. However, the flight altitude during migration is often 300 m or higher (Gibo, 1986). Noctuid moths may also fly southward in autumn toward warmer habitats by flying in northerly wind, especially behind southward-moving cold fronts (Sparks et al., 1986; Pair et al., 1987; Showers et al., 1993).
4. Termination of atmospheric dispersal of biota 4.1. Gravitational settling All organisms possess mass and are thereby subject to the force of gravity. In the absence of flight, these organisms settle out of the atmosphere when the gravitational force exceeds the sum of the forces due to friction and convective lift. Settling velocities, or terminal velocities, have been calculated using Stoke’s law for many wingless organisms, and velocities range from 0.002 to 0.02 m s−1 (Gregory, 1973). Stoke’s law is applicable to smooth spherical objects in still air; however, most plant pathogen spores or propagules are not
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
smooth spheres, but instead are aspherical, textured, or covered with spines (Pedgley, 1982). Ambient atmospheric water-vapor pressure affects the water content of airborne biota and can also affect the settling velocity of the organism. For example, urediospores of Puccinia graminis f. sp. tritici, the cause of wheat stem rust, have spine-like structures which increase aerodynamic drag and decrease the rate of descent (Pedgley, 1982). Also, larvae of spruce budworm (and many other species of insects and spiders) produce a silk thread which acts like a sail and parachute increasing the effect of wind on their dispersal (McManus and Mason, 1983). Spines, non-spherical shapes, and silk threads increase aerodynamic drag, causing these organisms to remain airborne longer, descend more slowly, and displace farther. Gravitational settling has also been reported for winged insects (i.e. grasshoppers) which apparently folded their wings when encountering strong updrafts associated within a gust flow (Achtemeier, 1991). Oscillatory wave motions may occur under stable atmospheric stratification near vegetation, and decrease settling velocities (Lee et al., 1997; Stout et al., 1995). However, gustiness under unstable atmospheric stratification can increase settling velocities (Miller et al., 1996).
4.2. Impaction Flightless biota may be deposited on the surface of vegetation, land, or sea. When flightless biota move in air flow that is deflected around objects, such as leaves, trees, or hills, the organisms may be carried by inertia to contact the surface. Convective currents, such as thunderstorm downdrafts can force flightless biota to impact the ground. The angle of impact and characteristics of the surface determine whether the organism remains on the surface or rebounds back into the air. The mass of airborne spores contributes to their impaction efficiency. Smaller spores have small settling velocities but are easily caught in low winds by plants. Larger spores, on the other hand, have large settling velocities but may be more likely to rebound after contact with the plant surface. The greater the inertia of an airborne organism, the more likely it will impact the ground or plant surface rather than be swept around obstacles by the surface wind flow. Convective eddies and lee-side eddies can significantly increase the
271
local impaction efficiency of airborne biota. More information on impaction may be found in Slinn (1982), Bache (1979), and Wiman and Ågren (1985). 4.3. Active flight Most medium-size or larger winged insects can control the duration of their flight. Day-flying insects generally stop flying ca. 0.5 h before sunset. Weak-flying insects, such as aphids, often get trapped above temperature inversions, and are dispersed day and night until convection erodes the inversions, allowing these insects to descend to the surface. Aphids generally do not attempt to land in the dark and, if aloft in the evening, continue to stay aloft until dawn (Hendrie et al., 1985). Noctuids, such as corn earworm moths, generally terminate migratory flight ca. 0.5 h before sunrise, perhaps to avoid predators or stresses associated with insolation. However, many noctuid species continue flight after sunrise when crossing large bodies of water (Wolf et al., 1986a; Drake, 1985a). 4.4. Rainout and washout Precipitation is an effective mechanism for removing biota from the atmosphere. Starr (1967) calculated that a rain of 5 mm h−1 could washout half of the airborne organisms of 10 m diameter in 0.25 h. Matthias-Maser and Jaenicke (1992) reported that biological aerosols, including bacteria, spores, and pollen, act as condensation nuclei for cloud droplets and raindrops. Alternatively, raindrops may entrain biological aerosols on contact. Collection of organisms in rain water and hailstones indicates the effectiveness of precipitation to remove plant pathogens and insects. Hailstones have provided rare but convincing evidence for washout of airborne insects (Knight and Knight, 1978). Probably triggered by negative barometric pressure tendency, some insects land at the onset of rain.
5. Conclusions Dispersal of airborne biota links biological activity and atmospheric parameters to move organisms, including plant pathogens and insects, from one habitat to another. An abundant population of one species
272
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
without the proper atmospheric conditions will not lead to substantial dispersal of the species, or subsequently to infestation or infection within its host range. Alternatively, proper atmospheric conditions without an available population of a species, or of a particular stage and readiness of the species for dispersal, will not contribute significantly to dispersal of the species. Also, one section of the continuum of atmospheric motions may play a unique role in the dispersal of plant pathogens, while another may be significant in the dispersal of flying insects. Therefore, it is important that atmospheric and biological measurements be adequate to resolve biologically meaningful characteristics of airborne dispersal processes. References Achtemeier, G.L., 1991. The use of insects as tracers for clear-air boundary-layer studies by Doppler radar. J. Atmos. Ocean. Technol. 8, 746–765. Aylor, D.E., 1986. A framework for examining inter-regional aerial transport of fungal spores. Agric. Forest Meteorol. 38, 263–288. Aylor, D.E., Taylor, G.S., 1983. Escape of Peronospora tabacina spores from a field of diseased tobacco plants. Ecol. Epidemiol. 73, 525–529. Aylor, D.E., Taylor, G.S., Raynor, G.S., 1982. Long-range transport of tobacco blue mold spores. Agric. Meteorol. 27, 217–232. Bache, D.H., 1979. Particle transport within plant canopies I. A framework for analysis. Atmos. Environ. 13, 1257–1262. Barry, R.E., Taylor, L.R., 1968. High-altitude migration of aphids in maritime and continental climates. J. Anim. Ecol. 37, 713– 722. Beerwinkle, K.R., Lopez, J.D., Bouse, L.F., Brusse, J.C., 1989. Large helicopter−towed net for sampling airborne arthropods, Trans. Am. Soc. Agric. Engrs. 32, pp. 1847–1852. Bonner, W.D., 1968. Climatology of the low level jet. Mon. Wea. Rev. 96, 833–850. Callahan, P.S., Sparks, A.N., Snow, J.W., Copeland, W., 1972. Corn earworm moth: vertical distribution in nocturnal flight. Environ. Entomol. 1, 497–503. Coad, B.R., 1931. Insects captured by airplane are found at surprising heights. Yearbook of Agriculture 1931, U.S. Department of Agriculture, pp. 320–323. Cohn, S.A., Mayor, S.D., Grund, C.J., Weckwerth, T.M., Senff, C., 1998. The Lidars in Flat Terrain Experiment. Bull. Am. Meteorol. Soc. 79, 1329–1343. Cooper, D.I., Eichinger, W.E., Holtkamp, D.B., Karl Jr., R.R., Quick, C.R., Dugas, W.A., Hipps, L., 1992. Spatial variability of water vapor turbulent transfer within the boundary layer. Boundary-Layer Meteorol. 61, 389–405. Cooper, D.I., Eichinger, W.E., Hof, D.E., Seville-Jones, D., Quick, C.R., Tiee, J., 1994. Observations of coherent structures from a scanning lidar over an irrigated orchard. Agric. Forest Meteorol. 67, 239–252.
Cronenwett, W.T., Walker, G.B., Inman, R.L., 1972. Acoustic sounding of meteorological phenomena in the planetary boundary layer. J. Appl. Meteorol. 11, 1351–1358. Crum, T.L., Alberty, R.L., 1993. The WSR−88D and the WSR−88D Operational Support Facility, Bull. Am. Meteorol. Soc. 74, pp. 1669–1687. Davis, J.M., 1987. Modeling the long-range transport of plant pathogens in the atmosphere. Ann. Rev. Phytopathol. 25, 169– 188. Dickison, R.B.B., Haggis, M.J., Rainey, R.C., 1983. Spruce budworm moth flight and storms: case study of a cold front system. J. Clim. Appl. Meteorol. 22, 278–286. Dickison, R.B.B., Haggis, M.J., Rainey, R.C., Burns, L.M.D., 1986. Spruce budworm moth flight and storms: further studies using aircraft and radar. J. Clim. Appl. Meteorol. 25, 1600–1608. Drake, V.A., 1985a. Radar observations of moths migrating in a nocturnal low-level jet. Ecol. Entomol. 10, 259–265. Drake, V.A., 1985b. Solitary wave disturbances of the nocturnal boundary layer revealed by radar observations of migrating insects. Boundary-Layer Meteorol. 31, 269–286. Drake, V.A., Farrow, R.A., 1988. The influence of atmospheric structure and motions on insect migration. Ann. Rev. Entomol. 33, 183–210. Draxler, R.R., Hess, G.D., 1997. Description of the HYsplit 4 modeling system. NOAA Tech. Memo. ERL ARL-224, 24 p. Gage, S.H., Isard, S.A., Colunga-G., M., 1999. Ecological scaling of aerobiological dispersal processes. Agric. For. Meteorol. 97, 249–261. Gibo, D.L., 1986. Flight strategies of migrating monarch butterflies (Danaus plexippus L.) in southern Ontario, In Danthanarayana, W. (Ed.), Insect Flight: Dispersal and Migration. Springer Verlag, pp. 172–184. Glick, P.A., 1939. The Distribution of Insects, Spiders, and Mites in the Air. U.S. Department of Agriculture Tech. Bull. 673. Washington, DC, 150 p. Glick, P.A., Noble, L.W., 1961. Airborne movement of the pink bollworm and other arthropods. U.S. Department of Agriculture, Tech. Bull.1255., Washington, D.C., pp. 20. Goodenough, J.L., Witz, J.A., Lopez, J.D., Hartstack, A.W., 1988. Patterns of occurrence of Heliothis spp. Lepidoptera: Noctuidae, 1983–1985. J. Econ. Entomol. 81, 1624–1630. Gregory, P.H., 1973. The Microbiology of the Atmosphere. Wiley & Sons, New York, NY, 377 p. Hartstack, A.W., Lopez, J.D., Muller, R.D., Sterling, W.L., King, E.G., Witz, J.A., Eversull, A.C., 1982. Evidence of long-range migration of Heliothis zea (Boddie) into Texas and Arkansas. Southwest. Entomol. 7, 188–201. Hendrie, L.K., Irwin, M.E., Liquido, N.J., Ruesink, W.G., Mueller, E.A., Voegtlin, D.J., Achtemeier, G.L., Steiner, W.W., Scott, R.W., 1985. Conceptual approach to modeling aphid migration. In: Mackenzie, D.R., Barfield, C.S., Kennedy, G.G., Berger (Eds.), The Movement and Dispersal of Agriculturally Important Biotic Agents. Claitor’s Publ., Baton Rouge, LA, pp. 541–582. Hirst, J.M., Hurst, G.W., 1967. Long-distance spore transport. In: Gregory, P.H., Monteith, J.L. (Eds.), Airborne Microbes, Cambridge, UK, pp. 307–345.
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274 Holzworth, G.C., 1972. Mixing heights, wind speeds, and potential for urban air pollution throughout the contiguous United States. U.S. Environmental Protection Agency, Office of Air Programs. Publ. No. AP-101. Huschke, R.E. (Ed.), 1959. The Glossary of Meteorology. Amer. Meteorol. Soc., Boston, MA, 638 p. Irwin, M.E., Thresh, J.M., 1988. Long-range aerial dispersal of cereal aphids as virus vectors in North America. Phil. Trans. Roy. Soc. Lond. B 321, 421–446. Isard, S.A., Irwin, M.E., Hollinger, S.E., 1990. Vertical distribution of aphids (Homoptera, Aphididae) in the planetary boundary layer. Environ. Entomol. 19, 1473–1484. Johnson, C.G., 1969. Migration and Dispersal of Insects by Flight. Methuen Publ., London, UK, 763 p. Johnson, S.J., 1995. Insect migration in North America: synoptic-scale transport in a highly seasonal environment. In: Drake, V.A., Gatehouse, A.G. (Eds.), Insect Migration: Tracking Resources through Space and Time. Cambridge University Press, UK, pp. 31–66. Klazura, G.E., Imy, D.A., 1993. A description of the initial set of analysis products available from the NEXRAD WSR-88D system. Bull. Am. Meteorol. Soc. 74, 1293–1311. Knight, N.C., Knight, C.A., 1978. Some observations on foreign material in hailstones. Bull. Am. Meteorol. Soc. 59, 282–286. Lee, X., Neumann, H.H., Den Hartog, G., Fuentes, J.D., Black, T.A., Mickle, R.E., Yang, P.C., Blanken, P.D., 1997. Observation of gravity waves in a boreal forest. Boundary-Layer Meteorol. 84, 383–398. Lingren, P.D., Westbrook, J.K., Bryant Jr., V.M., Raulston, J.R., Esquivel, J.F., Jones, G.D., 1994. Origin of corn earworm (Lepidoptera: Noctuidae) migrants as determined by Citrus pollen markers and synoptic weather systems. Environ. Entomol. 23, 562–570. Lingren, P.D., Raulston, J.R., Popham, T.W., Wolf, W.W., Lingren, P.S., Esquivel, J.F., 1995. Flight behavior of corn earworm (Lepidoptera: Noctuidae) moths under low wind speed conditions. Environ. Entomol. 24, 851–860. Locatelli, J.D., Stoelinga, M.T., Hobbs, P.V., Johnson, J., 1998. Structure and evolution of an undular bore on the High Plains and its effects on migrating birds. Bull. Am. Meteorol. Soc. 79, 1043–1060. Main, C.E., Keever, Z.T., Davis, J.M., 1998. Forecasting long-distance movement of plant pathogenic fungal spores and managing epidemic spread. Preprints of the 13th Conference on Biometeorology and Aerobiology, Am. Meteorol. Soc., 2–6 November 1998, Albuquerque, NM. Mason, C.J., McManus, M.L., 1981. In: Doane, C. (ed.), The Gypsy Moth: Research Toward Integrated Pest Management. U.S. Department of Agriculture. Tech. Bull. 1584. Washington, D.C., pp. 161–202. Matthias-Maser, S., Jaenicke, R., 1992. Identification and size distribution of biological aerosol particles with radius >0.2 m. In: Fukuta, N., Wagner. P.E. (Eds.), Nucleation and Atmospheric Aerosols. A. Deepak Publ., Hampton, VA, 523 p. McCorcle, M.D., 1988. Simulation of surface moisture effects on the Great Plains low-level jet. Mon. Wea. Rev. 116, 1705–1720. McManus, M.L., Mason, C.J., 1983. Determination of the settling velocity and its significance to larval dispersal of the gypsy
273
moth (Lepidoptera: Lymantriidae). Environ. Entomol. 12, 270– 272. Miller, D.R., Wang, Y., Ducharme, K.M., Yang, X., Mierzejewski, K., McManus, M.A., Reardon, R.E., 1996. Some atmospheric turbulence and stability effects on aerial spray penetration into hardwood forest canopies. For. Sci. 42, 93–101. Muller, R.A., 1985. The potential for the atmospheric transport of moths from the perspective of synoptic climatology. In: MacKenzie, D.R., Barfield, C.S., Kennedy, G.G., Berger, R.D. (Eds.), The Movement and Dispersal of Agriculturally Important Biotic Agents. Claitor’s Publ., Baton Rouge, LA, pp. 179–202. Muller, R.A., Willis, J.E., 1983. New Orleans Weather: A Climatology by Means of Synoptic Weather Types. Misc. Publ. 83-1. School of Geoscience, Louisiana State University, Baton Rouge, LA. National Oceanic and Atmospheric Administration, 1990. Doppler Radar Meteorological Observations; Part B: Doppler Radar Theory and Meteorology (Interim Version One). National Oceanic and Atmospheric Administration, U.S. Dept. of Commerce, Washington, D.C. Orlanski, I., 1975. A rational subdivision of scales for atmospheric processes. Bull. Am. Meteor. Soc. 56, 529–530. Pair, S.D., Raulston, J.R., Rummel, D.R., Westbrook, J.K., Wolf, W.W., Sparks, A.N., Schuster, M.F., 1987. Development and production of corn earworm and fall armyworm in the Texas High Plains: evidence for reverse fall migration. Southwest. Entomol. 12, 89–99. Pedgley, D.E., 1982. Windborne Pests and Diseases: Meteorology of Airborne Organisms. Ellis Horwood, Chichester, UK, 250 p. Pedgley, D.E., 1990. Concentration of flying insects by the wind. Phil. Trans. Roy. Soc. Lond. B 328, 631–653. Raynor, G.S., Hayes, J.V., Ogden, E.C., 1974. Mesoscale transport and dispersion of airborne pollens. J. Appl. Meteorol. 13, 87– 95. Reynolds, D.R., Riley, J.R., 1997. Flight Behavior and Migration of Insect Pests: Radar Studies in Developing Countries. NRI Bulletin 71, Natural Resources Institute, Chatham, UK, 114 p. Riley, J.R., 1975. Collective orientation in night-flying insects. Nature 253, 113–114. Riley, J.R., Reynolds, D.R., 1979. Radar-based studies of the migratory flight of grasshoppers in the middle Niger area of Mali. Proc. Royal Soc. B 204, 67–82. Riley, J.R., Reynolds, D.R., Farmery, M.J., 1983. Observations of the flight behaviour of the armyworm moth, Spodoptera exempta, at an emergence site using radar and infra-red optical techniques. Ecol. Entomol. 8, 395–418. Riley, J.R., Reynolds, D.R., Farrow, R.A., 1987. The migration of Nilaparvata lugens (Stål) (Delphacidae) and other Hemiptera associated with rice, during the dry season in the Philippines: a study using radar, visual observations, aerial netting and ground trapping. Bull. Entomol. Res. 77, 145–169. Russell, R.W., Wilson, J.W., 1996. Aerial plankton detected by radar. Nature 381, 200–201. Sauvageot, H., Despaux, G., 1996. The clear-air coastal vespertine radar bands. Bull. Am. Meteorol. Soc. 77, 673–681.
274
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
Scott, R.W., Achtemeier, G.L., 1987. Estimating pathways of migrating insects carried in atmospheric winds. Environ. Entomol. 16, 1244–1254. Showers, W.B., Smelser, R.B., Keaster, A.J., Whitford, F., Robinson, J.F., Lopez, J.D., Taylor, S.E., 1989. Recapture of marked black cutworm (Lepidoptera: Noctuidae) males after long-range transport. Environ. Entomol. 18, 447–458. Showers, W.B., Keaster, A.J., Raulston, J.R., Hendrix III, W.H., Derrick, M.E., McCorcle, M.D., Robinson, J.F., Way, M.O., Wallendorf, M.J., Goodenough, J.L., 1993. Mechanism of southward migration of a noctuid moth [Agrotis ipsilon (Hufnagel)]: a complete migrant. Ecology 74, 2303–2314. Slinn, W.G.N., 1982. Predictions for particle deposition to vegetative canopies. Atmos. Environ. 16, 1785–1794. Sparks, A.N., Jackson, R.D., Carpenter, J.E., Muller, R.A., 1986. Insects captured in light traps in the Gulf of Mexico. Ann. Entomol. Soc. Am. 79, 132–139. Starr, J.R., 1967. Deposition of particulate matter by hydrometeors. Quart. J. Roy. Meteorol. Soc. 93, 516–521. Stout, J.E., Arya, S.P., Genikhovich, E.L., 1995. The effect of nonlinear drag on the motion and settling velocity of heavy particles. J. Atmos. Sci. 52, 3836–3848. Symmons, P.M., Luard, E.J., 1982. The simulated distribution of night-flying insects in a wind convergence. Aus. J. Zool. 30, 187–198. Taylor, L.R., 1974. Insect migration, flight periodicity, flight periodicity and the boundary layer. J. Anim. Ecol. 43, 225–238. Westbrook, J.K., Eyster, R.S., Wolf, W.W., Lingren, P.D., Raulston, J.R., 1995a. Migration pathways of corn earworm (Lepidoptera: Noctuidae) indicated by tetroon trajectories. Agric. Forest Meteorol. 73, 67–87. Westbrook, J.K., Raulston, J.R., Wolf, W.W., Pair, S.D., Eyster, R.S., Lingren, P.D., 1995b. Field observations and simulations of atmospheric transport of noctuids from northeastern Mexico and the south-central U.S. Southwestern Entomol. Suppl. 18, 25–44.
Westbrook, J.K., Esquivel, J.F., Lopez Jr., J.D., Jones, G.D., Wolf, W.W., Raulston, J.R., 1998a. Validation of bollworm migration across south-central Texas in 1994–1996. Southwest. Entomol. 23, 209–219. Westbrook, J.K., Wolf, W.W., Allen, S., Ward, J.D., 1998b. NEXRAD Doppler weather radar network: potential for areawide surveillance of pest insect migrations. In: Proc. Beltwide Cotton Conf., 7–9 Jan. 1998, San Diego, CA, pp. 1304–1310. Wiman, B.L.B., Ågren, G.I., 1985. Aerosol depletion and deposition in forests — a model analysis. Atmos. Environ. 19, 335–347. Wolf, W.W., Westbrook, J.K., Sparks, A.N., 1986a. Relationship between radar entomological measurements and atmospheric structure in south Texas during March and April 1982. In: Sparks, A.N. (Ed.), Long-Range Migration of Moths of Agronomic Importance to the United States and Canada: Specific Examples of Occurrence and Synoptic Weather Patterns Conducive to Migration. USDA-ARS−43, pp. 84–97. Wolf, W.W., Sparks, A.N., Pair, S.D., Westbrook, J.K., Truesdale, F.M., 1986b. Radar observations and collections of insects in the Gulf of Mexico. pp. 221–234, In Danthanarayana, W. (Ed.), Insect Flight: Dispersal and Migration. Springer-Verlag, 289 p. Wolf, W.W., Westbrook, J.K., Raulston, J., Pair, S.D., Hobbs, S.E., 1990. Recent airborne radar observations of migrant pests in the United States. Phil. Trans. Royal Soc. London B 328, 619– 630. Wolf, W.W., Westbrook, J.K., Raulston, J. R., Pair, S.D., Lingren, P.D., 1994. Radar detection of ascent of Helicoverpa zea (Lepidoptera: Noctuidae) moths from corn in the Lower Rio Grande Valley of Texas. In: Barthakur, N.N. (Ed.), Proc. 13th Intl. Congr. on Biometeorology, Calgary, Canada, 12–18 September 1993. Wyngaard, J.C. (Ed.), 1988. Structure of the PBL. In: Venkatram, A., Wyngaard, J.C. (Eds.), Lectures in Air Pollution Meteorology, Am. Meteorol. Soc., Boston, MA, pp. 9–61.
Atmospheric scales of biotic dispersal J.K. Westbrook a , S.A. Isard b b
a USDA, ARS, College Station, TX, USA Department of Geography, University of Illinois, IL, USA
Accepted 21 July 1999
Abstract Recent advances in meteorological technologies and techniques are providing new insight into microscale, mesoscale, and macroscale aerobiological processes. For example, Lidar systems have identified microscale characteristics of atmospheric turbulence over agricultural fields which cannot be readily determined by conventional (site-specific) atmospheric sensors. Also, neutrally buoyant superpressure balloons (tetroons) have been tracked more than 400 km per night indicating atmospheric pathways of migrating insects between agricultural regions in south-central Texas. Such atmospheric trajectories often reveal substantial day-to-day variation of aerobiological pathways and, consequently, affect the risk of pest infestations and host infections. Further, the NEXRAD network of WSR-88D Doppler weather radars can measure the aerial abundance, speed, and displacement direction of concentrated biota over areas of >1000 km2 . Emphasis is placed on identifying biologically-relevant, temporal and spatial scales of atmospheric motion and other atmospheric variables which help control the abundance and dispersal of airborne biota, specifically insects, spores, pollen, fungi, and plant pathogens. Major technologies, including the NEXRAD network of WSR-88D Doppler weather radars, are described, and examples are presented for aerobiological applications. ©1999 Published by Elsevier Science B.V. All rights reserved. Keywords: Aerobiology; Dispersal; Atmospheric scale; Insects; Pollen; Spores; Fungi; Plant pathogens
1. Introduction The importance of movement of plant pathogens, spores, pollens, fungi, insects, and a variety of other aerobiota in the atmosphere is becoming increasingly recognized, but the aerial transport process remains poorly understood. The link between these biological systems and the atmosphere is key to understanding the population dynamics of, and diseases spread by, aerobiota. This connection is often capricious: prolific sources of insects or plant pathogens can only cause widespread plant infestations or infections when, and where, wind and other atmospheric factors are conducive for transport. Conversely, strong and persistent winds and/or zones of convergence are of no consequence to plant and animal dispersal unless there are
sources of biota ready to move in the atmosphere and appropriate hosts elsewhere. Knowledge of these biological and meteorological linkages, coupled with information on biological sources and availability and susceptibility of host species, provide the potential to understand, and prevent, dispersal episodes that result in catastrophic crop losses and animal (including human) health epidemics. We maintain that an understanding of the spatial and temporal scales of atmospheric motions and biological processes (Gage et al., 1999) provide an important framework for coupling biological and atmospheric events and processes that influence aerial dispersal of organisms. For some organisms, the energy used for take-off and ascent in the atmosphere comes from the environment, while others actively leap or fly into the air.
0168-1923/99/$ – see front matter ©1999 Published by Elsevier Science B.V. All rights reserved. PII: S 0 1 6 8 - 1 9 2 3 ( 9 9 ) 0 0 0 7 1 - 4
264
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
A large number of organisms move at night when the atmosphere is frequently stable, others utilize convective currents during daytime to ascend high in the atmosphere, while many initiate and/or continue aerial movement regardless of the time of day. For example, corn earworm moths, Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae), consistently initiate dispersal flight ca. 0.5 h after sunset; fly within the lowest 2000–3000 m of the atmosphere; and terminate flight ca. 0.5 h before sunrise. Occasionally, insects may terminate flight earlier when encountering cold air temperatures and convergent winds associated with a cold front (Symmons and Luard, 1982), or later when flying over open water before sunrise (Wolf et al., 1986b). In contrast, the release of tobacco blue mold spores, Peronospora tabacina Adam, occurs during daylight hours with a peak near mid-day when ambient relative humidity drops below 70% (Aylor and Taylor, 1983). These spores can be transported more than 100 km by synoptic scale airflow (Aylor et al., 1982). Their survival in the atmosphere is primarily affected by the ultraviolet wavelengths of solar radiation and, thus, is prolonged by cloud cover. Finally, the descent of spores to the Earth is caused by dry and wet deposition, although washout by rain is especially important for initiating tobacco blue mold epidemics (Aylor, 1986). These are only two examples where the initiation of aerial movement, the duration of transport, and the altitude of movement are biologically dependent parameters that influence the types of the motion systems encountered during atmospheric transport. Atmospheric motion occurs on a continuum of space and time scales, from seasonal global circulations to microscale eddies which ultimately dissipate kinetic energy through friction (Orlanski, 1975). Orlanski (1975) determined that, for practical reasons, the horizontal scale of motion was the best term for classifying scales of motion. Gage et al. (1999) present atmospheric scales of motion in the context of ecosystems, ranging from habitats (microscale), to landscapes and sections (mesoscale), and to divisions, domains, and continents (macroscale). It is important to consider atmospheric motion systems that occur along this continuum in order to identify potentially relevant systems and exclude others which are unimportant, for particular aerobiological processes. No single atmospheric motion system is responsible for biotic movement in the atmosphere; how-
ever, a continuum of important atmospheric motions is associated with most biological transport events. A low-level wind maximum (jet), for example, may be embedded in the flow between atmospheric high-pressure and low-pressure systems. Within this atmospheric system, turbulent eddies act to reduce the anomalous wind speed maximum, while dynamic forces accelerate winds in some areas and decelerate winds in others. Microscale and mesoscale atmospheric circulations may limit the spatial distribution of airborne biota, while the entire aerobiological system may be displaced by the macroscale atmospheric circulation. Atmospheric motion systems are generally positively correlated in space and time scales; that is, motions which occur in small volumes of air have short life spans and motions involving extensive volumes have substantially longer time periods. For example, wind blowing across a rough surface generates tiny eddies that persist for a few seconds. Insolation on a dry desert surface can cause thermal convective circulations (dust devils) which may be several meters in horizontal diameter, 100 m high, and persist for several minutes. Landscape-driven winds — such as mountain-valley and land-sea circulations — are generally diurnal, characterized by vertical and horizontal dimensions on the order of 1000 m and 10 000 m, respectively, and an abrupt change in wind direction within the diel cycle. Warm and cold airflows converging into mid-latitude cyclones that travel across continents and oceans can persist for one or two weeks. While at the largest scales, the trade winds and the westerlies span the globe and are essentially continuous in time, although their location, intensity, and direction of movement vary seasonally. Thus, the atmospheric motion systems in which particular biota disperse may require drastically different measurement protocols. Atmospheric motions transport, disperse, or concentrate biota (Gregory, 1973; Drake and Farrow, 1988; Pedgley, 1990). Theoretically, a strong laminar uniform flow across a source of spores can carry them downwind without significantly altering their concentration. However, most transport of biota in the atmosphere occurs within turbulent air flows which disperse organisms from a single source. Meteorological factors and biological behaviors can also interact to increase concentrations of biota in the atmosphere.
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
265
Aerial concentration of biota can increase when insects resist ascent into cold zones in the atmosphere or where wind converges at a gust flow or sea breeze front. Examples of the use of atmospheric scales of motion as a framework for studying aerobiological systems are presented below. Further, new technologies are described which can detect airborne biota or measure the wind field and other atmospheric variables which influence the dispersal of biota. This paper concentrates on atmospheric scales of motion contributing to the dispersal of biota above the surface layer. Atmospheric dispersal of biota is presented in three phases: take-off, transport, and termination. Atmospheric scales, processes, and technological developments are discussed with example aerobiological systems described for each of the three phases of atmospheric transport. Pre-conditioning of biota and impacts of their dispersal are covered in more detail elsewhere in this special issue.
2. Ascent and vertical distribution of biota in the atmosphere In order for the atmosphere to transport pollen, spores, and insects over long distances, the biota must first attain suitable altitudes in the atmosphere. In the case of pollen, spores, and flightless insects, convection keeps them aloft while they drift downwind. Flying insects must ascend above the insect boundary layer (Taylor, 1974) which is defined as the atmospheric layer nearest the ground where the insect’s airspeed is greater than the wind speed: hence, the insect largely controls its own flight path. This section describes detection of the ascent and vertical distribution of biota and atmospheric effects toward that end. Atmospheric mixing (forced and free convection) is necessary to lift pollen, spores, and flightless insects to altitudes sufficient for long-distance dispersal. Mixing processes are largely associated with the temperature lapse rate, wind shear, and storms. Atmospheric mixing (and distribution of biota) is mainly confined to the planetary boundary layer (PBL) which extends from the earth’s surface to the geostrophic wind level (Huschke, 1959), and varies within diurnal and seasonal cycles. Free convection due to surface heating is the major source of daytime atmospheric mixing.
Fig. 1. Annual atmospheric mixing depth (×100 m) in the continental U.S.: (a) morning, and (b) afternoon (after Holzworth, 1972).
At night, mechanical mixing (forced convection) becomes important. Mean annual maps of atmospheric mixing depth for morning and afternoon (Holzworth, 1972) are presented in Fig. 1. Stable layers, frequently inversions, suppress mixing above the mixed layer. These maps of mean annual atmospheric mixing depth suggest that pollen, spores, and insects could be readily distributed throughout the lowest 800–2600 m of the atmosphere during the day, and could be concentrated within shallower atmospheric layers during the night. Many species of insects fly to high altitudes to begin their long-distance dispersal. The monarch butterfly, Danaus plexippus (L.), and many other butterflies soar within convective thermals (≈1 m s−1 vertical velocity) to maximize their long-distance dispersal with respect to metabolic energy demands. Nocturnal convection is generally very weak, but many species of insects quickly fly from the surface to altitudes above the Planetary Boundary Layer (PBL). For example, corn earworm moths can ascend in flight at ca. 1 m s−1 (Wolf et al., 1994; Lingren et al., 1995).
266
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
Table 1 Reported flight altitudes of selected insects Species
Altitude (m AGL)
Method of collection
Reference
Pectinophora gossypiella Nilaparvata lugens Paederus fuscipes
610 450 150
airplane cannisters kytoon-towed nets kytoon-towed nets
Glick and Noble (1961) Reynolds and Riley (1997) Reynolds and Riley (1997)
Thus, atmospheric convection and active flight are often sufficient to distribute biota within the lowest 1000 m of the atmosphere within 15 min. Aylor (1986) provided a framework for studying the long-distance dispersal of fungal spores that was based on an understanding of air flow in the lower atmosphere: thus, it can be applied in a general sense to all passively-transported and weakly-flying aerobiota. Critical information for predicting ascent of organisms into the atmosphere includes: (1) the population at the source; (2) the structure of the vegetation at the source; (3) time when individuals become airborne; (4) height in the vegetation where aerial movement is initiated; (5) wind speed and direction above the vegetation; and (6) the stability of the atmosphere. The predictive capability that results from obtaining these types of information has been demonstrated for the tobacco blue mold spore system (e.g. Aylor, 1986; Davis, 1987) and has led to a World Wide Web-based forecasting system for the spread of this pathogen (Main et al., 1998). The use of entomological radar and night-vision equipment (Lingren et al., 1995) to make direct observation of insect flight has provided a number of important insights about the ascent of organisms into the PBL. For example, studies involving radar measurements of the take-off and ascent of locusts and grasshoppers in Mali (Riley, 1975; Riley and Reynolds, 1979), the African armyworm moth, Spodoptera exempta (Wlk.), in Kenya (Riley et al., 1983), and brown plant hoppers, Nilaparvata lugens (Stål), in the Philippines and China (Riley et al., 1987), have provided information on insect densities and orientation in flight, their rate of climb in the PBL, their altitude of flight (Table 1), and the role of temperature and wind on insect stratification in the lower atmosphere. Similarly, radar measurements of corn earworm moths from corn fields in the Lower Rio Grande Valley of Texas and Mexico (Wolf et al., 1990, 1994) have been used to characterize starting
Fig. 2. Vertical distribution of wind speed and the concentration of corn earworm-size insects (number per 106 m3 [MCM]) during the occurrence of a nocturnal low-level jet at La Paloma, Texas, on 4 April 1982 (after Wolf et al., 1986a).
time, duration of the take-off event, ascent rate, numbers of the moths in the PBL, mean altitude of flight, and the relationship between meteorological features (e.g. wind speed maximum, wind shear, and cloud cover) and these aerobiological factors (Fig. 2). There is little comparable research, however, on the role of atmospheric motions on the process of atmospheric ascent in other aerobiological systems. Far more effort has been focused on determining the types, number, and vertical distributions of organisms in the atmosphere, with little reference to the atmospheric factors that influenced these distributions. It has long been recognized that daytime convection mixes pollen, spores, wingless insects, and weakly flying insects throughout the PBL (e.g. Gregory, 1973; Johnson, 1969; Pedgley, 1982). Callahan et al. (1972) collected nearly 3000 corn earworm moths in light traps mounted between 108 and 349 m above ground level (AGL) during two years of sampling. Aircraft mounted devices have collected many such organisms
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
within the lowest 3 km AGL (e.g. Coad, 1931; Glick, 1939; Hirst and Hurst, 1967; Raynor et al., 1974; Beerwinkle et al., 1989; Isard et al., 1990). Knowledge of vertical distribution of organisms is important to predicting long-distance aerial movement of passive and weak-flying insects that remain aloft after sunset and are carried for long distances downwind in the stable nocturnal PBL, especially if they are in fast-moving airflows (e.g. nocturnal low-level jets) which may develop above a surface-based or elevated temperature inversion (e.g. Barry and Taylor, 1968; Johnson, 1969; Irwin and Thresh, 1988). Two relatively new technologies have increased the capacity to study microscale atmospheric motions that assist the ascent of biota into the atmosphere: lidar instrumentation and acoustic radar. Lidar instrumentation can measure microscale atmospheric motions in the surface boundary layer and PBL (Cohn et al., 1998). For example, Cooper et al. (1992) measured the vertical and horizontal heterogeneity of water vapor concentration over an irrigated field of alfalfa, Medicago sativa L., during periods of high transpiration rates using a Raman Lidar. They found rising and sinking moist air plume structures (≈30-m diameter) that lasted for 3 to 10 min. A Raman Lidar also identified coherent (highly organized) structures in the water-vapor concentration over an irrigated orchard during periods of high transpiration rates (Cooper et al., 1994). When compared with time-series analysis of point-instrument data, Cooper et al. (1994) determined that asymmetrical ramp structures of 20 to 30 m had lifetimes of 20 to 30 s. Thus, lidar measurements of microscale convective plumes might also identify the propensity of pollen, spores, and flightless insects to be entrained into the atmosphere. Acoustic radars have been extremely valuable in monitoring the vertical structure of the lowest 1000 m of the PBL. From continuous recordings of acoustic radar signals, Cronenwett et al. (1972) identified vertical and temporal characteristics of atmospheric phenomena including thermal convection, stratus clouds, passage of a cold front, unstable Kelvin–Helmholtz waves, a persistent temperature inversion, and airborne biota. Continuous operation of acoustic radars has been extremely useful in studies of the diel evolution of the PBL. Thus, lidar and acoustic radars provide capabilities for spatial imaging of microscale atmospheric structures in the surface boundary layer and
267
vertical structures in the PBL. If coupled with entomological measurements and/or microbiota sampling, these relatively new technologies could provide an exciting avenue to further explore the role of atmospheric structures to the initiation of movement in the atmosphere by organisms.
3. Transport of airborne biota The vertical profile of wind throughout the PBL substantially determines the rate and direction of displacement of biota. Thus, thermodynamic and kinematic forces not only affect wind velocity but also the dispersal of biota. The Coriolis force acts on the horizontal wind velocity to affect the vertical profile of wind direction through a depth of the PBL known as the Ekman layer (Wyngaard, 1988). As wind speed increases with height above the ground due to diminished frictional forces, the Coriolis force increasingly deflects the wind clockwise for a total of ca. 45◦ until the wind is in geostrophic balance with the wind above the PBL. The Ekman layer approximation is usually a good representation of the stable PBL, but is less representative of the neutral PBL and convective PBL. The vertical gradient of wind speed and wind direction generates shear forces which lead to atmospheric mixing and the dissipation of kinetic energy. The size of the turbulent eddies involved in atmospheric mixing increases for deeper PBLs. Shallow PBLs, capped by a strong inversion, severely limit the maximum size of turbulent eddies. Temporal and spatial variability of the vertical transfer (flux) of momentum is governed by the vertical profiles of wind speed and wind direction, as well as atmospheric stability and convective heat flux. Estimates of biotic dispersal have generally been derived from vertical profiles of wind velocity and other atmospheric variables recorded by National Weather Service (NWS) rawinsondes. The NWS rawinsondes provide data twice daily within a network of stations spaced ≈400 km apart. Alternatively, some research studies have used instrumented towers as high as ≈300 m AGL. Radar wind profilers (i.e. wind profilers) are now deployed within an operational network in the Central U.S. and also by individual scientists. Wind profilers provide continuous wind
268
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
speed and direction data which is often statistically summarized at ≈15-min intervals from ca. 250 to 2000 m AGL. The spatiotemporal resolution of wind profiler measurements could significantly improve the accuracy of aerobiological dispersion models. Rapid technological developments in computing power have markedly improved the utility and availability of atmospheric transport and dispersion models, especially for mesoscale and macroscale processes. Many of these models, such as the HYsplit model (Draxler and Hess, 1997) were developed for general applications in atmospheric science, and have been adapted for specific applications including atmospheric chemical transport and deposition, dispersion of smoke from forest fires and volcanoes, and dispersion of radioactive material from accidental releases. These models may be able to accommodate passive dispersants, such as plant pathogens and wingless insects, and may be useful with modification for modeling the dispersion of flying insects (Scott and Achtemeier, 1987) and other organisms (Davis, 1987). The use of atmospheric trajectory and dispersion measurements and models can be applied diagnostically or predictively. Sea-breeze and slope circulations are derived from the cycle of diurnal heating, and consequently concentrate airborne biota and reverse the direction of biotic transport within a diurnal period. For example, the sea-breeze circulation consists of an afternoon on-shore surface wind when the land is warmer than the coastal water, and a morning off-shore surface wind when the coastal water is warmer than the land. The sea-breeze circulation typically has a vertical depth of 1–2 km and a horizontal width of ca. 20–100 km perpendicular to the coastline. Upper-level winds complete the sea-breeze circulation in an opposite direction relative to the surface winds. Weakly-flying insects were detected by Doppler radar to amass high concentrations along the Atlantic coast of Florida before dispersing inland following the onset of the sea breeze (Russell and Wilson, 1996). The dispersal of small insects away from the Atlantic coastline of France, and their possible deposition into the Atlantic Ocean, occurred in the evening (off-shore) land-breeze (Sauvageot and Despaux, 1996). Slope circulations are similar to the sea-breeze circulations, except that the magnitude of the slope is a major cause of horizontal temperature
gradients. Differential heating and cooling of slopes within a mountain valley cause slope winds to rise or sink, respectively. Model calculations and field observations indicated that mountain-valley slope flow circulations displaced gypsy moth larvae from one ridgeline to the next (Mason and McManus, 1981). Thunderstorm circulations and other highly convergent mesoscale flows are often responsible for concentrating airborne biota. Dickison et al. (1983) found that large aerial concentrations of spruce budworm moths, Choristoneura fumiferana (Clemens), were associated with wind flow in thunderstorm systems. Additional case studies (Dickison et al., 1986) showed that large concentrations of spruce budworm moths were found between thunderstorm cells at heights greater than 600 m AGL. Cold thunderstorm outflow winds may induce aerodynamic bores ca. 45 km wide and 4 km high which propagate solitary waves (e.g. 5 solitary waves in 3 h) (Locatelli et al., 1998). Drake (1985b) detected concentration lines of insects within such solitary waves. Aerobiologists have given much attention to the continental transport of biota by low-level wind maxima, especially the nocturnal low-level jet (LLJ) in the Central U.S. (Johnson, 1995). The Central U.S. between the Rocky and Appalachian Mountains has few obstacles to impede the northward transport of biota. Wind maxima often form under clear skies after sunset when radiative cooling creates a stable PBL which decreases frictional deceleration of the prevailing winds aloft. Bonner (1968) prepared a climatological study based on selected criteria of the magnitude and vertical shear associated with low-level wind maxima to define an LLJ which occurs most frequently along a south-southwesterly to north-northeasterly axis through Oklahoma (Fig. 3). The LLJ jet can accelerate to a maximum speed of 28 m s−1 , and usually develops between 700 m and 1000 m AGL. Surface winds are often light and variable under an LLJ, which is generally characterized by a vertical half-width of ≈100 to 200 m. In the study, Bonner (1968) established vertical and horizontal dimensions, geographic distribution, and frequency of occurrence of the LLJ. McCorcle (1988) described the influence of soil moisture on the development of the LLJ. Radar studies have often found that insects concentrate their flight at the altitude of the LLJ, or other low-level wind maxima (Wolf et al., 1986a; Drake,
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
269
Table 2 Reported atmospheric dispersal distances of selected insects Species
Distancea (km)
Method of determination
Reference
Helicoverpa zea Helicoverpa zea Agrotis ipsilon
661 230 1142
external pollen identification internal spore identification internal dye marker
Westbrook et al., 1998a Westbrook et al., 1998a Showers et al., 1989
a
The estimated duration of flight ranged from one to three successive nights.
Fig. 3. Envelope containing the low-level jet axes in 26 out of 28 cases of strongest jet occurrence in the Central U.S. (after Bonner, 1968).
1985a), perhaps to take advantage of high-speed transport. Landscape-driven mesoscale atmospheric circulations are important to the first occurrence and outbreak of many plant pest invasions. Historically, this association has been determined by collecting biota in various types of traps or collection devices (Hartstack et al., 1982; Goodenough et al., 1988), and computing wind trajectories between source areas and collection sites. Occasionally, insects have been marked, released, and recaptured to validate flight trajectories with respect to prevailing synoptic weather conditions and computed wind trajectories. Neutrally buoyant weather balloons have also been used to measure the wind trajectory at the altitude of maximum concentration of flying insects (Westbrook et al., 1995a). Mesoscale moth flight trajectory calculations were validated by the capture of moths marked naturally with unique pollen (Lingren
Fig. 4. Image of (a) a corn earworm moth, Helicoverpa zea (Boddie), and (b) a scanning electron micrograph of two Citrus sp. pollen grains (C) on the proboscis (P) of a corn earworm moth. A moth scale (S) can be seen in the micrograph. The white bar represents 10 mm. (Micrograph courtesy Dr. Gretchen D. Jones and Kim D. Ostiguin, USDA, ARS, Areawide Pest Management Research Unit).
et al., 1994) and artificially marked with unique spores (Westbrook et al., 1998a). Examples of long-distance atmospheric dispersal of selected biota are listed in Table 2. An example of mesoscale transport of a flying insect species (i.e. corn earworm) illustrates the scale and variability of atmospheric transport conditions (Westbrook et al., 1998a). A corn earworm moth is shown in Fig. 4(a). Citrus pollen found on the proboscis of many corn earworm moths (Fig. 4(b)) indicated that many captured moths had flown hundreds of kilometers from the nearest commercial citrus orchards.
270
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
Fig. 5. Areas (shaded) of daily capture of unmarked and marked corn earworm moths exceeding 10 moths per pheromone trap in Texas on 20 March 1995. Squares indicate locations of pheromone traps. Solid circles indicate locations where pheromone traps captured citrus pollen-contaminated corn earworm moths. Synoptic weather conditions were valid at 0600 Central Standard Time.
Pheromone traps on 17 March 1995 failed to capture corn earworm moths marked with Citrus pollen >330 km north of the commercial Citrus production area in the Lower Rio Grande Valley (LRGV) of southern Texas. However, northward atmospheric transport in advance of an approaching cold front was associated with the capture of citrus-marked moths as far as 660 km from the LRGV on 20 March 1995 (Fig. 5). Distance and direction of atmospheric trajectories are often highly variable, even over the course of several successive days and could profoundly increase the dispersal of corn earworm moths and other airborne biota (Westbrook et al., 1995b). The NEXRAD system of WSR-88D Doppler weather radars has detected atmospheric dispersal of concentrations of insects as well as birds and bats. Westbrook et al. (1998b) found a high correlation between the aerial concentration of corn earworm-size targets and WSR-88D base reflectivity measurements. The NEXRAD system was implemented to detect mesoscale and macroscale atmospheric circulations and precipitation systems, which are important factors for the aerial dispersal of biota. The NEXRAD system of WSR-88D Doppler weather radars provides nearly complete spatial coverage of the atmosphere at 3000 m AGL over the continental U.S. (NOAA, 1990; Klazura and Imy, 1993; Crum and Alberty, 1993). These Doppler radars can detect the distribu-
tion of precipitation rates, biota, and particulates over areas of ≈100–10 000 km2 . Additionally, Doppler radars can detect the velocity of the wind and flying organisms. The NEXRAD system records the spatial distribution of these aerobiological parameters every 6–10 min throughout the day and night. Muller and Willis (1983) defined a set of synoptic weather features that could be related to the climatological potential for insect migration over the southern U.S. (Muller, 1985). Favorable wind conditions for northward migration occurred when the Bermuda High was located in the southeastern U.S. and a low-pressure system developed along the Front Range (eastern side) of the Rocky Mountains. Often a low-pressure cell develops along a frontal system in the central U.S., drawing warm southerly wind over much of the south-central U.S. Synoptic climatology has identified temporal scales of atmospheric circulations which affect the potential for migration events. Southward (long-distance return) migration has been identified in several species of insects. Autumnal migrations of monarch butterflies, thousands of kilometers from Canada to overwintering habitats in Mexico, are well documented, primarily because this conspicuous butterfly often flies in the lowest 10–30 m of the daytime PBL. However, the flight altitude during migration is often 300 m or higher (Gibo, 1986). Noctuid moths may also fly southward in autumn toward warmer habitats by flying in northerly wind, especially behind southward-moving cold fronts (Sparks et al., 1986; Pair et al., 1987; Showers et al., 1993).
4. Termination of atmospheric dispersal of biota 4.1. Gravitational settling All organisms possess mass and are thereby subject to the force of gravity. In the absence of flight, these organisms settle out of the atmosphere when the gravitational force exceeds the sum of the forces due to friction and convective lift. Settling velocities, or terminal velocities, have been calculated using Stoke’s law for many wingless organisms, and velocities range from 0.002 to 0.02 m s−1 (Gregory, 1973). Stoke’s law is applicable to smooth spherical objects in still air; however, most plant pathogen spores or propagules are not
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
smooth spheres, but instead are aspherical, textured, or covered with spines (Pedgley, 1982). Ambient atmospheric water-vapor pressure affects the water content of airborne biota and can also affect the settling velocity of the organism. For example, urediospores of Puccinia graminis f. sp. tritici, the cause of wheat stem rust, have spine-like structures which increase aerodynamic drag and decrease the rate of descent (Pedgley, 1982). Also, larvae of spruce budworm (and many other species of insects and spiders) produce a silk thread which acts like a sail and parachute increasing the effect of wind on their dispersal (McManus and Mason, 1983). Spines, non-spherical shapes, and silk threads increase aerodynamic drag, causing these organisms to remain airborne longer, descend more slowly, and displace farther. Gravitational settling has also been reported for winged insects (i.e. grasshoppers) which apparently folded their wings when encountering strong updrafts associated within a gust flow (Achtemeier, 1991). Oscillatory wave motions may occur under stable atmospheric stratification near vegetation, and decrease settling velocities (Lee et al., 1997; Stout et al., 1995). However, gustiness under unstable atmospheric stratification can increase settling velocities (Miller et al., 1996).
4.2. Impaction Flightless biota may be deposited on the surface of vegetation, land, or sea. When flightless biota move in air flow that is deflected around objects, such as leaves, trees, or hills, the organisms may be carried by inertia to contact the surface. Convective currents, such as thunderstorm downdrafts can force flightless biota to impact the ground. The angle of impact and characteristics of the surface determine whether the organism remains on the surface or rebounds back into the air. The mass of airborne spores contributes to their impaction efficiency. Smaller spores have small settling velocities but are easily caught in low winds by plants. Larger spores, on the other hand, have large settling velocities but may be more likely to rebound after contact with the plant surface. The greater the inertia of an airborne organism, the more likely it will impact the ground or plant surface rather than be swept around obstacles by the surface wind flow. Convective eddies and lee-side eddies can significantly increase the
271
local impaction efficiency of airborne biota. More information on impaction may be found in Slinn (1982), Bache (1979), and Wiman and Ågren (1985). 4.3. Active flight Most medium-size or larger winged insects can control the duration of their flight. Day-flying insects generally stop flying ca. 0.5 h before sunset. Weak-flying insects, such as aphids, often get trapped above temperature inversions, and are dispersed day and night until convection erodes the inversions, allowing these insects to descend to the surface. Aphids generally do not attempt to land in the dark and, if aloft in the evening, continue to stay aloft until dawn (Hendrie et al., 1985). Noctuids, such as corn earworm moths, generally terminate migratory flight ca. 0.5 h before sunrise, perhaps to avoid predators or stresses associated with insolation. However, many noctuid species continue flight after sunrise when crossing large bodies of water (Wolf et al., 1986a; Drake, 1985a). 4.4. Rainout and washout Precipitation is an effective mechanism for removing biota from the atmosphere. Starr (1967) calculated that a rain of 5 mm h−1 could washout half of the airborne organisms of 10 m diameter in 0.25 h. Matthias-Maser and Jaenicke (1992) reported that biological aerosols, including bacteria, spores, and pollen, act as condensation nuclei for cloud droplets and raindrops. Alternatively, raindrops may entrain biological aerosols on contact. Collection of organisms in rain water and hailstones indicates the effectiveness of precipitation to remove plant pathogens and insects. Hailstones have provided rare but convincing evidence for washout of airborne insects (Knight and Knight, 1978). Probably triggered by negative barometric pressure tendency, some insects land at the onset of rain.
5. Conclusions Dispersal of airborne biota links biological activity and atmospheric parameters to move organisms, including plant pathogens and insects, from one habitat to another. An abundant population of one species
272
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
without the proper atmospheric conditions will not lead to substantial dispersal of the species, or subsequently to infestation or infection within its host range. Alternatively, proper atmospheric conditions without an available population of a species, or of a particular stage and readiness of the species for dispersal, will not contribute significantly to dispersal of the species. Also, one section of the continuum of atmospheric motions may play a unique role in the dispersal of plant pathogens, while another may be significant in the dispersal of flying insects. Therefore, it is important that atmospheric and biological measurements be adequate to resolve biologically meaningful characteristics of airborne dispersal processes. References Achtemeier, G.L., 1991. The use of insects as tracers for clear-air boundary-layer studies by Doppler radar. J. Atmos. Ocean. Technol. 8, 746–765. Aylor, D.E., 1986. A framework for examining inter-regional aerial transport of fungal spores. Agric. Forest Meteorol. 38, 263–288. Aylor, D.E., Taylor, G.S., 1983. Escape of Peronospora tabacina spores from a field of diseased tobacco plants. Ecol. Epidemiol. 73, 525–529. Aylor, D.E., Taylor, G.S., Raynor, G.S., 1982. Long-range transport of tobacco blue mold spores. Agric. Meteorol. 27, 217–232. Bache, D.H., 1979. Particle transport within plant canopies I. A framework for analysis. Atmos. Environ. 13, 1257–1262. Barry, R.E., Taylor, L.R., 1968. High-altitude migration of aphids in maritime and continental climates. J. Anim. Ecol. 37, 713– 722. Beerwinkle, K.R., Lopez, J.D., Bouse, L.F., Brusse, J.C., 1989. Large helicopter−towed net for sampling airborne arthropods, Trans. Am. Soc. Agric. Engrs. 32, pp. 1847–1852. Bonner, W.D., 1968. Climatology of the low level jet. Mon. Wea. Rev. 96, 833–850. Callahan, P.S., Sparks, A.N., Snow, J.W., Copeland, W., 1972. Corn earworm moth: vertical distribution in nocturnal flight. Environ. Entomol. 1, 497–503. Coad, B.R., 1931. Insects captured by airplane are found at surprising heights. Yearbook of Agriculture 1931, U.S. Department of Agriculture, pp. 320–323. Cohn, S.A., Mayor, S.D., Grund, C.J., Weckwerth, T.M., Senff, C., 1998. The Lidars in Flat Terrain Experiment. Bull. Am. Meteorol. Soc. 79, 1329–1343. Cooper, D.I., Eichinger, W.E., Holtkamp, D.B., Karl Jr., R.R., Quick, C.R., Dugas, W.A., Hipps, L., 1992. Spatial variability of water vapor turbulent transfer within the boundary layer. Boundary-Layer Meteorol. 61, 389–405. Cooper, D.I., Eichinger, W.E., Hof, D.E., Seville-Jones, D., Quick, C.R., Tiee, J., 1994. Observations of coherent structures from a scanning lidar over an irrigated orchard. Agric. Forest Meteorol. 67, 239–252.
Cronenwett, W.T., Walker, G.B., Inman, R.L., 1972. Acoustic sounding of meteorological phenomena in the planetary boundary layer. J. Appl. Meteorol. 11, 1351–1358. Crum, T.L., Alberty, R.L., 1993. The WSR−88D and the WSR−88D Operational Support Facility, Bull. Am. Meteorol. Soc. 74, pp. 1669–1687. Davis, J.M., 1987. Modeling the long-range transport of plant pathogens in the atmosphere. Ann. Rev. Phytopathol. 25, 169– 188. Dickison, R.B.B., Haggis, M.J., Rainey, R.C., 1983. Spruce budworm moth flight and storms: case study of a cold front system. J. Clim. Appl. Meteorol. 22, 278–286. Dickison, R.B.B., Haggis, M.J., Rainey, R.C., Burns, L.M.D., 1986. Spruce budworm moth flight and storms: further studies using aircraft and radar. J. Clim. Appl. Meteorol. 25, 1600–1608. Drake, V.A., 1985a. Radar observations of moths migrating in a nocturnal low-level jet. Ecol. Entomol. 10, 259–265. Drake, V.A., 1985b. Solitary wave disturbances of the nocturnal boundary layer revealed by radar observations of migrating insects. Boundary-Layer Meteorol. 31, 269–286. Drake, V.A., Farrow, R.A., 1988. The influence of atmospheric structure and motions on insect migration. Ann. Rev. Entomol. 33, 183–210. Draxler, R.R., Hess, G.D., 1997. Description of the HYsplit 4 modeling system. NOAA Tech. Memo. ERL ARL-224, 24 p. Gage, S.H., Isard, S.A., Colunga-G., M., 1999. Ecological scaling of aerobiological dispersal processes. Agric. For. Meteorol. 97, 249–261. Gibo, D.L., 1986. Flight strategies of migrating monarch butterflies (Danaus plexippus L.) in southern Ontario, In Danthanarayana, W. (Ed.), Insect Flight: Dispersal and Migration. Springer Verlag, pp. 172–184. Glick, P.A., 1939. The Distribution of Insects, Spiders, and Mites in the Air. U.S. Department of Agriculture Tech. Bull. 673. Washington, DC, 150 p. Glick, P.A., Noble, L.W., 1961. Airborne movement of the pink bollworm and other arthropods. U.S. Department of Agriculture, Tech. Bull.1255., Washington, D.C., pp. 20. Goodenough, J.L., Witz, J.A., Lopez, J.D., Hartstack, A.W., 1988. Patterns of occurrence of Heliothis spp. Lepidoptera: Noctuidae, 1983–1985. J. Econ. Entomol. 81, 1624–1630. Gregory, P.H., 1973. The Microbiology of the Atmosphere. Wiley & Sons, New York, NY, 377 p. Hartstack, A.W., Lopez, J.D., Muller, R.D., Sterling, W.L., King, E.G., Witz, J.A., Eversull, A.C., 1982. Evidence of long-range migration of Heliothis zea (Boddie) into Texas and Arkansas. Southwest. Entomol. 7, 188–201. Hendrie, L.K., Irwin, M.E., Liquido, N.J., Ruesink, W.G., Mueller, E.A., Voegtlin, D.J., Achtemeier, G.L., Steiner, W.W., Scott, R.W., 1985. Conceptual approach to modeling aphid migration. In: Mackenzie, D.R., Barfield, C.S., Kennedy, G.G., Berger (Eds.), The Movement and Dispersal of Agriculturally Important Biotic Agents. Claitor’s Publ., Baton Rouge, LA, pp. 541–582. Hirst, J.M., Hurst, G.W., 1967. Long-distance spore transport. In: Gregory, P.H., Monteith, J.L. (Eds.), Airborne Microbes, Cambridge, UK, pp. 307–345.
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274 Holzworth, G.C., 1972. Mixing heights, wind speeds, and potential for urban air pollution throughout the contiguous United States. U.S. Environmental Protection Agency, Office of Air Programs. Publ. No. AP-101. Huschke, R.E. (Ed.), 1959. The Glossary of Meteorology. Amer. Meteorol. Soc., Boston, MA, 638 p. Irwin, M.E., Thresh, J.M., 1988. Long-range aerial dispersal of cereal aphids as virus vectors in North America. Phil. Trans. Roy. Soc. Lond. B 321, 421–446. Isard, S.A., Irwin, M.E., Hollinger, S.E., 1990. Vertical distribution of aphids (Homoptera, Aphididae) in the planetary boundary layer. Environ. Entomol. 19, 1473–1484. Johnson, C.G., 1969. Migration and Dispersal of Insects by Flight. Methuen Publ., London, UK, 763 p. Johnson, S.J., 1995. Insect migration in North America: synoptic-scale transport in a highly seasonal environment. In: Drake, V.A., Gatehouse, A.G. (Eds.), Insect Migration: Tracking Resources through Space and Time. Cambridge University Press, UK, pp. 31–66. Klazura, G.E., Imy, D.A., 1993. A description of the initial set of analysis products available from the NEXRAD WSR-88D system. Bull. Am. Meteorol. Soc. 74, 1293–1311. Knight, N.C., Knight, C.A., 1978. Some observations on foreign material in hailstones. Bull. Am. Meteorol. Soc. 59, 282–286. Lee, X., Neumann, H.H., Den Hartog, G., Fuentes, J.D., Black, T.A., Mickle, R.E., Yang, P.C., Blanken, P.D., 1997. Observation of gravity waves in a boreal forest. Boundary-Layer Meteorol. 84, 383–398. Lingren, P.D., Westbrook, J.K., Bryant Jr., V.M., Raulston, J.R., Esquivel, J.F., Jones, G.D., 1994. Origin of corn earworm (Lepidoptera: Noctuidae) migrants as determined by Citrus pollen markers and synoptic weather systems. Environ. Entomol. 23, 562–570. Lingren, P.D., Raulston, J.R., Popham, T.W., Wolf, W.W., Lingren, P.S., Esquivel, J.F., 1995. Flight behavior of corn earworm (Lepidoptera: Noctuidae) moths under low wind speed conditions. Environ. Entomol. 24, 851–860. Locatelli, J.D., Stoelinga, M.T., Hobbs, P.V., Johnson, J., 1998. Structure and evolution of an undular bore on the High Plains and its effects on migrating birds. Bull. Am. Meteorol. Soc. 79, 1043–1060. Main, C.E., Keever, Z.T., Davis, J.M., 1998. Forecasting long-distance movement of plant pathogenic fungal spores and managing epidemic spread. Preprints of the 13th Conference on Biometeorology and Aerobiology, Am. Meteorol. Soc., 2–6 November 1998, Albuquerque, NM. Mason, C.J., McManus, M.L., 1981. In: Doane, C. (ed.), The Gypsy Moth: Research Toward Integrated Pest Management. U.S. Department of Agriculture. Tech. Bull. 1584. Washington, D.C., pp. 161–202. Matthias-Maser, S., Jaenicke, R., 1992. Identification and size distribution of biological aerosol particles with radius >0.2 m. In: Fukuta, N., Wagner. P.E. (Eds.), Nucleation and Atmospheric Aerosols. A. Deepak Publ., Hampton, VA, 523 p. McCorcle, M.D., 1988. Simulation of surface moisture effects on the Great Plains low-level jet. Mon. Wea. Rev. 116, 1705–1720. McManus, M.L., Mason, C.J., 1983. Determination of the settling velocity and its significance to larval dispersal of the gypsy
273
moth (Lepidoptera: Lymantriidae). Environ. Entomol. 12, 270– 272. Miller, D.R., Wang, Y., Ducharme, K.M., Yang, X., Mierzejewski, K., McManus, M.A., Reardon, R.E., 1996. Some atmospheric turbulence and stability effects on aerial spray penetration into hardwood forest canopies. For. Sci. 42, 93–101. Muller, R.A., 1985. The potential for the atmospheric transport of moths from the perspective of synoptic climatology. In: MacKenzie, D.R., Barfield, C.S., Kennedy, G.G., Berger, R.D. (Eds.), The Movement and Dispersal of Agriculturally Important Biotic Agents. Claitor’s Publ., Baton Rouge, LA, pp. 179–202. Muller, R.A., Willis, J.E., 1983. New Orleans Weather: A Climatology by Means of Synoptic Weather Types. Misc. Publ. 83-1. School of Geoscience, Louisiana State University, Baton Rouge, LA. National Oceanic and Atmospheric Administration, 1990. Doppler Radar Meteorological Observations; Part B: Doppler Radar Theory and Meteorology (Interim Version One). National Oceanic and Atmospheric Administration, U.S. Dept. of Commerce, Washington, D.C. Orlanski, I., 1975. A rational subdivision of scales for atmospheric processes. Bull. Am. Meteor. Soc. 56, 529–530. Pair, S.D., Raulston, J.R., Rummel, D.R., Westbrook, J.K., Wolf, W.W., Sparks, A.N., Schuster, M.F., 1987. Development and production of corn earworm and fall armyworm in the Texas High Plains: evidence for reverse fall migration. Southwest. Entomol. 12, 89–99. Pedgley, D.E., 1982. Windborne Pests and Diseases: Meteorology of Airborne Organisms. Ellis Horwood, Chichester, UK, 250 p. Pedgley, D.E., 1990. Concentration of flying insects by the wind. Phil. Trans. Roy. Soc. Lond. B 328, 631–653. Raynor, G.S., Hayes, J.V., Ogden, E.C., 1974. Mesoscale transport and dispersion of airborne pollens. J. Appl. Meteorol. 13, 87– 95. Reynolds, D.R., Riley, J.R., 1997. Flight Behavior and Migration of Insect Pests: Radar Studies in Developing Countries. NRI Bulletin 71, Natural Resources Institute, Chatham, UK, 114 p. Riley, J.R., 1975. Collective orientation in night-flying insects. Nature 253, 113–114. Riley, J.R., Reynolds, D.R., 1979. Radar-based studies of the migratory flight of grasshoppers in the middle Niger area of Mali. Proc. Royal Soc. B 204, 67–82. Riley, J.R., Reynolds, D.R., Farmery, M.J., 1983. Observations of the flight behaviour of the armyworm moth, Spodoptera exempta, at an emergence site using radar and infra-red optical techniques. Ecol. Entomol. 8, 395–418. Riley, J.R., Reynolds, D.R., Farrow, R.A., 1987. The migration of Nilaparvata lugens (Stål) (Delphacidae) and other Hemiptera associated with rice, during the dry season in the Philippines: a study using radar, visual observations, aerial netting and ground trapping. Bull. Entomol. Res. 77, 145–169. Russell, R.W., Wilson, J.W., 1996. Aerial plankton detected by radar. Nature 381, 200–201. Sauvageot, H., Despaux, G., 1996. The clear-air coastal vespertine radar bands. Bull. Am. Meteorol. Soc. 77, 673–681.
274
J.K. Westbrook, S.A. Isard / Agricultural and Forest Meteorology 97 (1999) 263–274
Scott, R.W., Achtemeier, G.L., 1987. Estimating pathways of migrating insects carried in atmospheric winds. Environ. Entomol. 16, 1244–1254. Showers, W.B., Smelser, R.B., Keaster, A.J., Whitford, F., Robinson, J.F., Lopez, J.D., Taylor, S.E., 1989. Recapture of marked black cutworm (Lepidoptera: Noctuidae) males after long-range transport. Environ. Entomol. 18, 447–458. Showers, W.B., Keaster, A.J., Raulston, J.R., Hendrix III, W.H., Derrick, M.E., McCorcle, M.D., Robinson, J.F., Way, M.O., Wallendorf, M.J., Goodenough, J.L., 1993. Mechanism of southward migration of a noctuid moth [Agrotis ipsilon (Hufnagel)]: a complete migrant. Ecology 74, 2303–2314. Slinn, W.G.N., 1982. Predictions for particle deposition to vegetative canopies. Atmos. Environ. 16, 1785–1794. Sparks, A.N., Jackson, R.D., Carpenter, J.E., Muller, R.A., 1986. Insects captured in light traps in the Gulf of Mexico. Ann. Entomol. Soc. Am. 79, 132–139. Starr, J.R., 1967. Deposition of particulate matter by hydrometeors. Quart. J. Roy. Meteorol. Soc. 93, 516–521. Stout, J.E., Arya, S.P., Genikhovich, E.L., 1995. The effect of nonlinear drag on the motion and settling velocity of heavy particles. J. Atmos. Sci. 52, 3836–3848. Symmons, P.M., Luard, E.J., 1982. The simulated distribution of night-flying insects in a wind convergence. Aus. J. Zool. 30, 187–198. Taylor, L.R., 1974. Insect migration, flight periodicity, flight periodicity and the boundary layer. J. Anim. Ecol. 43, 225–238. Westbrook, J.K., Eyster, R.S., Wolf, W.W., Lingren, P.D., Raulston, J.R., 1995a. Migration pathways of corn earworm (Lepidoptera: Noctuidae) indicated by tetroon trajectories. Agric. Forest Meteorol. 73, 67–87. Westbrook, J.K., Raulston, J.R., Wolf, W.W., Pair, S.D., Eyster, R.S., Lingren, P.D., 1995b. Field observations and simulations of atmospheric transport of noctuids from northeastern Mexico and the south-central U.S. Southwestern Entomol. Suppl. 18, 25–44.
Westbrook, J.K., Esquivel, J.F., Lopez Jr., J.D., Jones, G.D., Wolf, W.W., Raulston, J.R., 1998a. Validation of bollworm migration across south-central Texas in 1994–1996. Southwest. Entomol. 23, 209–219. Westbrook, J.K., Wolf, W.W., Allen, S., Ward, J.D., 1998b. NEXRAD Doppler weather radar network: potential for areawide surveillance of pest insect migrations. In: Proc. Beltwide Cotton Conf., 7–9 Jan. 1998, San Diego, CA, pp. 1304–1310. Wiman, B.L.B., Ågren, G.I., 1985. Aerosol depletion and deposition in forests — a model analysis. Atmos. Environ. 19, 335–347. Wolf, W.W., Westbrook, J.K., Sparks, A.N., 1986a. Relationship between radar entomological measurements and atmospheric structure in south Texas during March and April 1982. In: Sparks, A.N. (Ed.), Long-Range Migration of Moths of Agronomic Importance to the United States and Canada: Specific Examples of Occurrence and Synoptic Weather Patterns Conducive to Migration. USDA-ARS−43, pp. 84–97. Wolf, W.W., Sparks, A.N., Pair, S.D., Westbrook, J.K., Truesdale, F.M., 1986b. Radar observations and collections of insects in the Gulf of Mexico. pp. 221–234, In Danthanarayana, W. (Ed.), Insect Flight: Dispersal and Migration. Springer-Verlag, 289 p. Wolf, W.W., Westbrook, J.K., Raulston, J., Pair, S.D., Hobbs, S.E., 1990. Recent airborne radar observations of migrant pests in the United States. Phil. Trans. Royal Soc. London B 328, 619– 630. Wolf, W.W., Westbrook, J.K., Raulston, J. R., Pair, S.D., Lingren, P.D., 1994. Radar detection of ascent of Helicoverpa zea (Lepidoptera: Noctuidae) moths from corn in the Lower Rio Grande Valley of Texas. In: Barthakur, N.N. (Ed.), Proc. 13th Intl. Congr. on Biometeorology, Calgary, Canada, 12–18 September 1993. Wyngaard, J.C. (Ed.), 1988. Structure of the PBL. In: Venkatram, A., Wyngaard, J.C. (Eds.), Lectures in Air Pollution Meteorology, Am. Meteorol. Soc., Boston, MA, pp. 9–61.