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A simulation model for hedgerow light interception and growth
Agricultural and Forest Meteorology 108 (2001) 29–43
A simulation model for hedgerow light interception and growth James B. Friday a,∗ , James H. Fownes b,1 a
College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa, 875 Komohana St., Hilo, HI 96720 USA b Department of Natural Resources Conservation, University of Massachusetts, Amherst, MA 01003 USA Received 27 July 2000; received in revised form 29 December 2000; accepted 6 January 2001
Abstract In order to investigate competition for light between trees and crops in an agroforestry system, we wrote a simulation model of light interception and growth by a system of hedgerows and an interplanted crop. To calculate light interception, hedgerows are modeled as long prisms, solar angles and hedgerow shadow lengths are calculated, and light intercepted by the hedgerows and points in the alley is summed. Biomass allocation to leaves and wood and the new hedgerow dimensions are calculated from empirical allometric equations. Hedgerow shoots are modeled as a population undergoing density-dependant mortality. Parameters for the model were developed from an alley cropping experiment of hedgerows of Flemingia macrophylla, a legume shrub with broad leaves, grown alone or intercropped with maize on the island of Kauai, Hawaii. The model was tested with data from field experiments conducted in 1995 and 1996. In 1995, light interception simulated by the model for a point on the floor of the alley tracked measured light interception well over the course of the crop both when hedgerow sizes were input from field measurements and when they were simulated. Hedgerow biomass predicted by the model closely followed that measured in periodic harvests. In 1996, light interception simulated by the model tracked measured light interception well when the model was run with measured hedge dimensions, but the model under predicted hedgerow growth and, thus, over predicted transmission when growth was simulated. Radiation use efficiencies (ε) for the hedgerows over the entire cropping season were calculated by regressing harvest biomass against light interception as calculated by the model. These averaged 0.18 (S.E. 0.005) g above-ground biomass mol−1 photosynthetically active photons for both treatments in 1995 and 0.21 (S.E. 0.008) g mol−1 in 1996. While hedgerow biomass was affected by the presence of the crop, the fact that ε was the same in both treatments indicated that competition was overwhelmingly for light rather than for water or nutrients. © 2001 Elsevier Science B.V. All rights reserved. Keywords: Agroforestry; Alley cropping; Competition; Radiation use efficiency; Flemingia macrophylla
1. Introduction Competition for light from trees often limits growth of crops in agroforestry systems (Sanchez, 1995). Quantifying the severity of competition and separating above-ground competition for light from ∗ Corresponding author. Tel.: +1-808-959-9155; fax: +1-808-959-3101. E-mail addresses: [email protected] (J.B. Friday), [email protected] (J.H. Fownes). 1 Tel.: +1-413-577-0205; fax: +1-413-545-4358.
below-ground competition for water or nutrients is difficult in field experiments, however, simulation models can be used to analyze tree–crop interactions and optimize management of agroforestry systems (Anderson et al., 1993). Models developed for forest growth and crop growth may be modified and combined for use with agroforestry systems (Lawson et al., 1995). Agroforestry systems in particular require unique formulations because they are typically diverse with heterogeneous canopies and incorporate some of the attributes of forest systems and some of crop systems. We wrote a simulation model, HedgeGro,
0168-1923/01/$ – see front matter © 2001 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 8 - 1 9 2 3 ( 0 1 ) 0 0 2 2 0 - 9
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Nomenclature B D ε k L Q R T
biomass (g m−2 ) date of harvest radiation use efficiency (g above-ground biomass mol−1 photosynthetic photons) light extinction coefficient (unitless) leaf area index (m2 m−2 ) photosynthetic photon flux density (mmol m2 s−1 ) replication treatment
which combines principles used in forest growth models (radiation use efficiency, self-thinning of a stand, allometric equations describing biomass partitioning) with principles used in crop models (radiation use efficiency, light interception in a heterogeneous canopy) to model light interception and growth of hedgerows in an alley cropping system. We used the model to assess above- versus below-ground competitive effects of the crops on the trees. 1.1. Forest growth models Forest stand growth may be simulated with a computer model by calculating solar radiation intercepted by the canopy, converting the radiation into biomass by multiplying by a radiation use efficiency (ε), then allocating the new biomass to leaves, stems, and roots (Landsberg, 1986). Some models calculate absorbed radiation by subtracting radiation reflected from the canopy from that intercepted. The biomass allocated to the canopy produces new canopy dimensions, and the cycle starts again with interception of new radiation. Models patterned on this basic procedure have simulated stand growth in eucalyptus (Linder et al., 1985) and pine (McMurtrie et al., 1990; McMurtrie et al., 1994; Landsberg and Waring, 1997). 1.2. Radiation interception Jackson and Palmer (1972) created a model of light interception for a hedgerow system consisting of solid prisms of a given height and width and an infinite length. The model calculated the sun position and calculated light interception based on what fraction of the alley was shaded by the hedgerow and
how much ground the hedgerow itself occupied. Later modifications of their model included light transmission through the hedgerow canopy based on Beer’s law for clumped canopies (Palmer, 1977; Jackson and Palmer, 1989). In developing the light interception component of the model HedgeGro, we adapted Jackson and Palmer’s (1977) model to include hedgerows shaped as rectangular prisms with hemi-cylindrical tops (Boote and Loomis, 1991) and interception of diffuse radiation based on the fraction of sky visible from the alley (Oke, 1987). We used geometrical shapes and fraction of ground shaded as the simplest method for dealing with a heterogeneous canopy. The leaf area density within the hedgerow canopy is uniform at any one time, although it changes as the hedgerow grows. We added the ability to calculate light interception by a crop grown in the alleys and resulting shading of the hedgerows. Finally, the model calculates the sum of the radiation intercepted over the course of a single day and over a cropping season. 1.3. Radiation use efficiency and competition Radiation use efficiency may be affected by both moisture status and fertility. Drought conditions have been shown to lower ε (Harrington and Fownes, 1995). Fertilization has been shown to increase ε in spruce (Wang et al., 1991) and pine (Gholz et al., 1991; Raison and Myers, 1992), although not in eucalyptus (Linder et al., 1985). Some radiation-driven growth models start with a potential ε and then modify this based on water, temperature, and nutrient availability (Landsberg, 1986). McMurtrie et al. (1994) modeled gross primary productivity in pine stands as a function of ε, modified by factors accounting for incomplete interception of radiation, soil water deficits, water vapor saturation deficits of the air, and low temperature effects. They found that the environmental variables were necessary for the model to make accurate predications of productivity. In contrast, Linder et al. (1985) found that a simple empirical ε was sufficient to model several different stands of Eucalyptus globulus. Crop models such as CERES-Maize (Jones and Kiniry, 1986) also multiply a high potential ε by factors to account for environmental variables. Plants growth may be limited either because of lack of sufficient light, water, and nutrients in the environment or because of competition for these resources
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from other plants. Radiation use efficiency may be used as a tool to assess stress caused by below-ground competition from other plants. In an agroforestry system, if tree growth is limited by competition for nutrients or water from crops, the trees would be expected to have a lower ε than trees grown alone. Radiation use efficiencies of trees grown with and without crops can be compared to determine the severity of competition. Since the calculation of ε explicitly takes the difference in light environments into account, the difference can then be attributed to below-ground competition. In our field experiments, we grew hedgerows with and without interplanted crops. We calculated ε for the hedgerows using the model and compared ε of the sole hedgerow with ε of the alley crop to assess how and if the crops competed with the hedgerow. 1.4. Hedgerow growth The models MPTGro (Fownes and Harrington, 1990) and 3-PG (Landsberg and Waring, 1997) allocate new growth to wood or leaf biomass based on diameter to leaf area allometric equations developed from harvest data. Our field work has shown that the hedgerow canopy changes in leaf area density and in the ratio of leaf biomass to woody biomass as it grows (Friday, 1998). We modeled the hedgerow as a population of shoots undergoing density-dependant mortality (self-thinning) as they grow according to the −0.5 power law (Westoby, 1984). Average shoot size is calculated from the biomass and the number of shoots, and shoot allometry developed from field experiments determines the hedgerow dimensions. Landsberg and Waring (1997) similarly calculate the average stem size of trees in a stand based on a thinning relationship and use the average stem size to calculate the leaf area. New biomass in HedgeGro is calculated by multiplying light intercepted by an empirical ε (Russell et al., 1989). 1.5. Development of model parameters and testing Allometric equations and values for ε used in the model HedgeGro were developed from an alley cropping experiment on the island of Kauai, Hawaii, in 1995. The model was tested against biomass data and independent light interception data from the experiment in 1995 and again in 1996.
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2. The model 2.1. Input The hedgerow system is set-up based on a file containing the basic characteristics of the site. Hedgerow growth can be simulated or interpolated from a table of periodic field measurements containing hedge height, width, leaf area, biomass, and number of shoots per linear meter. When hedgerow growth is to be simulated, another input file consisting of allometric equations for the hedgerow is required. This file includes a radiation use efficiency, the slope and intercept for a self-thinning line relating the hedgerow shoot density to biomass, and coefficients and exponents for equations pertaining to the hedgerow dimensions. If a crop between the hedgerows is simulated, the model calls for input files containing arrays of crop heights and leaf areas for each row of the crop. The model requires a weather file which contains the day of year, the hour, and hourly values for total incident photosynthetic photon flux density and diffuse photosynthetic photon flux density (Q and Qdiff , mmol m−2 s−1 ). Direct beam radiation is calculated as the total radiation less the diffuse radiation. 2.2. Output HedgeGro creates an output file including the hourly photosynthetic photon flux density (Q, mol m−2 h−1 ) incident at the sensor position and hourly Q intercepted by each row of the crop in the alley. The daily summary file includes the daily total photon flux intercepted by the hedgerows (mol m−2 day−1 ), the total incident at the sensor position, and the total intercepted by each row of the crop. 2.3. Calculations of intercepted radiation HedgeGro calculates the solar zenith angle and azimuth at 6 min intervals from the hour angle, solar declination, and the latitude using standard solar geometry equations (Sellers, 1965). To calculate intercepted diffuse radiation, HedgeGro calculates the fraction of the sky visible from each point of interest (crop position, sensor position, or location in the alley) by using the equations for view factors given
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by Oke (1987). Diffuse radiation is assumed to be isotropic, therefore, the diffuse radiation incident at one point is that point’s view factor times the total diffuse radiation. Both direct beam and diffuse light transmission through the hedgerow canopy are calculated with a modification of Beer’s Law to account for clumped canopies (Jackson and Palmer, 1989). Light intercepted by the hedgerow, the crop, or bare soil is calculated as the sum of incident direct and diffuse radiation, less that transmitted through the canopy. 2.4. Hedgerow growth simulation HedgeGro simulates hedgerow growth by converting the radiation intercepted (Qi ) to biomass (B) through a radiation use efficiency (ε) Bn = B + εQi
(1)
The new biomass (Bn ) must be partitioned into wood and leaves. The first step is to calculate the number of shoots in the plot, HedgeGro inverts the classic self-thinning relationship between population density and biomass Number of shoots = aBb
Fig. 1. Flow chart of growth simulation sub-model.
at the Wailua Experiment Station of University of Hawaii, Kapaa, Kauai, Hawaii, longitude 22◦ N, latitude 159◦ W. Elevation at the station is 160 m and annual rainfall averages 2500 mm (Ikawa et al., 1985). The soil is Halii gravelly silty clay and is classed as an anionic acroperox, fine, ferruginous, and isothermic (Soil Survey Staff, 1996). 3.2. Hedgerows
(2)
where a and b are empirically derived constants. In this case, both number of shoots and biomass are divided by the hedgerow drip line area (m2 ), defined as the width of the hedgerow multiplied by the length of the plot. An average shoot biomass is then calculated by dividing the biomass by the number of shoots. Hedge dimensions needed to model light interception are then calculated based on several allometric equations, all of the form Y = aXb . The average shoot biomass is related to an average shoot length, and the average shoot length in turn to the hedgerow height and width. The average shoot biomass also is used to calculate a wood to leaf ratio, which is then used in calculating a leaf area (Fig. 1).
Two treatments, hedgerows with and without an intercrop of maize, were replicated four times in a randomized complete block design. Seedlings of Flemingia macrophylla were outplanted between November 1993 and January 1994. Hedgerows were spaced 5.33 m apart and oriented at an azimuth of 4◦ east of north (orientation was chosen to run basically north–south while following the borders of the available field). Each plot consisted of three parallel hedgerows, with all experimental measurements being taken on the center hedgerow. Trimmings were discarded throughout the experiment to avoid confounding effects on soil fertility. 3.3. 1995 crop
3. Methods 3.1. Site for field experiment Parameters for HedgeGro were developed and the model was tested on an alley cropping experiment
The hedges were cut to a height of 1 m in March 1995, 2 weeks prior to planting the crop. Fertilizer was applied to the alleys between the hedges for both the crop and sole hedge treatments at a rate of 150 kg/ha N, 400 kg/ha P, 200 kg/ha K, and 55.6 kg/ha of granusol, a micro-nutrient mix. For the crop treatment, six rows
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of maize were planted, with the first row 1 m from the center of the hedgerow. 3.4. Meteorological data A micro-meteorological station immediately outside the field recorded weather data on a CR21x datalogger (Campbell Scientific, Inc., Logan, Utah, USA). Hourly measurements were taken of photosynthetic photon flux density (Q, mmol m−2 s−1 ) and diffuse Q with LI190SB quantum sensors (LI-COR Inc., Lincoln, Nebraska, USA). The quantum sensor used to measure diffuse light was outfitted with a homemade shade ring which blocked the direct beam
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radiation (Oke, 1987, p. 368). The shade ring was adjusted weekly to keep it aligned with the solar path and values for diffuse radiation were multiplied by a factor of 1.08 to account for the fraction of the sky blocked by the shade band (Robinson and Stoch, 1964). Daily maximum, minimum, and average temperature were recorded along with daily precipitation, average wind speed, and wind direction. In order to have independent observations with which to test the model, light transmission was measured to a point on the floor of the alley continuously throughout the crop. A line quantum analyzer (LI191SA, LI-COR Inc., Lincoln, Nebraska, USA) which measures the average Q along a 1 m length was
Fig. 2. Hedgerow growth and model predictions compared with measurements in 1995 for: (a) hedgerow shoot biomass; and (b) number of shoots in hedgerow. Error bars indicate standard deviations.
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installed in one plot of each treatment running north to south, parallel to the hedgerows. The sensors were 1.67 m from the center line of the hedgerow, which in the alley crop was at the base of the second row of maize. A third line quantum analyzer was placed above the crop canopy to record incident radiation. Percent light transmitted to the sensor was calculated by dividing the Q of the below canopy sensor by the Q of the above canopy sensor. Light transmission in each subplot was measured for 2 weeks prior to the harvest of that subplot. Moving the sensors after each harvest served to average out spatial variability along the hedge.
3.5. Harvest procedure In each main plot, harvest subplots 2 m long were randomly selected from the middle hedgerow. The first cut was made 3 weeks from the date of the maize planting (4 weeks from the time the hedgerows were trimmed). Subsequent subplots were harvested every 2 weeks until the final crop harvest, for a total of eight harvests. At each harvest, hedgerow height, width, fresh shoot biomass, and number of shoots were measured. Hedges were cut at 1 m height. In the alley cropping plots, maize height and total above-ground fresh
Fig. 3. Hedgerow growth and model predictions compared with measurements in 1996 for: (a) hedgerow shoot biomass; and (b) number of shoots in hedgerow. Error bars indicate standard deviations.
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Fig. 4. Leaf area index (L) for hedgerows and alley crop in 1995. L for hedgerows is calculated as m2 leaf area m−2 ground actually covered by the canopy of the hedgerows.
biomass for each row were recorded in the field. Subsamples of both maize plants and hedgerow shoots were taken for determination of biomass, leaf area, average shoot length, and wet to dry ratios. Leaf area was determined for green leaves with a LI-COR LI-3100 Leaf Area Meter.
3.6. 1996 crop A second maize crop was planted in 1996, 5 weeks after the hedges had been cut back to 1 m in height This resulted in hedgerows which were considerably larger relative to the crop in 1996 than they had been
Fig. 5. Leaf area index (L) for hedgerows and alley crop in 1996.
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in 1995. Plots were harvested every 4 weeks in 1996 and were 4 m long rather than 2 m. 3.7. Calculation of results and model parameters The constants for the allometric equations were all derived from the field experiments (Friday, 1998). Only the data from 1995 were used so that the 1996 data would be completely independent for model validation. Separate allometric equations relating average shoot length to hedgerow width were used for
the alley crop and the sole hedge treatment. Specific leaf area is kept constant at 0.0225 m2 g−1 . The hedgerow light extinction coefficient k was calculated as 0.9 for the Flemingia hedgerows based on a separate set of instantaneous measures of light transmission with the line quantum analyzers on a sunny day and leaf area based on a harvest The model follows the CERES model in using a k of 0.65 for maize (Jones and Kiniry, 1986). Because the hedgerows were not harvested at the time the crop was planted in 1996, biomass and leaf
Fig. 6. Transmittance of light to a sensor on the floor of the alley: (a) percent transmittance on a sunny day; (b) total light incident on the same day; (c) percent transmittance on an overcast day.
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area were estimated from the hedgerow height based on allometric relationships developed from the 1995 data for the start of the 1996 simulations. In testing for differences in hedgerow growth, hedgerow biomass and leaf area were log-transformed to homogenize variances. An analysis of variance was done for each year using the model Y = T + R + TR(error) + D + DR(error) +DT + DTR(error)
(3)
where Y = ln of biomass or leaf area, T = treatment,
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R = replication, and D = harvest date. The split block model was used instead of the split plot because both biomass and leaf area are not randomly distributed but increase throughout the growing season. Hedgerow leaf area indices were calculated as leaf area divided by the total ground area occupied by the hedgerow, which increased as the hedgerows grew. Radiation use efficiency (ε) was calculated by regressing the light intercepted by the hedgerows against the biomass harvested. The model was run to calculate cumulative intercepted radiation for each plot based on field measurements of hedgerow dimensions.
Fig. 7. Measurements and model simulations of percent light transmitted to sensor on the floor of the alley over the entire cropping season for 1995 in: (a) sole hedgerows; and (b) alley crop.
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Biomass measurements were independent since separate subplots were harvested at each interval, but since the hedges continued growing each harvest was greater than the preceding ones. The intercepted radiation calculated was cumulative for each replication. There is, therefore, some autocorrelation in the measurements of ε, although less so than in forestry experiments where the same trees are repeatedly measured (Russell et al., 1989). Using a general linear model with treatment and year as categorical variables and intercepted radiation as a covariate, we tested for differences among the slopes of the regressions by the F-tests for the interactions of treatment by radiation and year by radiation (Wilkinson et al., 1992).
actions were significant in each year (P = 0.001 in 1995 and P = 0.004 in 1996). Leaf area indices for the hedgerows in the alley cropping treatment also decreased relative to those in the sole hedgerow plots as the maize canopy developed (Figs. 4 and 5). The 1995 maize crop was P deficient in some plots and additional P was applied in 1996. Precipitation was also greater and more evenly distributed in 1996. During a dry spell in 1995, there were 9 weeks in a row during the season where the daily average precipitation was less than 3 mm, while in 1996, only 3 weeks in a row had average daily precipitation of less than 3 mm. Average daily rainfall in 1996 was 1.4 times that of 1995. 4.2. Partial validation for 1995 season
4. Results 4.1. Hedgerow and crop growth The maize alley crop clearly competed with the hedgerows. Hedgerow biomass was greater in the sole hedgerow plots than in the alley cropping plots after 13 weeks after the initial cut (11 weeks after the crop was planted) in 1995 and after 24 weeks after the initial cut (9 weeks after the crop was planted) in 1996 (Figs. 2a and 3a). Treatment by harvest inter-
HedgeGro accurately predicts the light incident at a given point in the alley over the course of a day. Fig. 6a shows the percentage of the total light transmitted through or past the hedgerows and crop and incident on the sensor for a clear day, June 24. The sensor was in the shade of the hedgerow until 10:00, then emerged into the sun. In the sole hedge plot, the shadow of the hedge actually became darker as the sun rose in the morning since the light passed through more of the hedgerow canopy. Cloudiness at midday
Fig. 8. Radiation use efficiency of hedgerows in 1995. Regression line is for all points.
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decreased the percentage of light incident at the sensor because much of the diffuse radiation, which is distributed evenly over the sky, was blocked by the hedgerows. Finally, the sensor was again in the shadow of the hedgerow after 16:00. The sensor in the alley cropped plot showed relatively little light transmitted through the mature maize canopy. The model successfully predicted all these trends. Predictions of the total light incident at the sensor on the same day closely follow the measured light (Fig. 6b). The percentage of light incident at the sensor varied little over the course of an overcast day, May 12 (Fig. 6c).
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Over the entire growing season, HedgeGro predicted the day to day variation in the average daily percent of incident light transmitted to the sensor in the alley when hedge sizes were read in from data tables (Fig. 7). Sensor calibration problems probably caused the spurious measurements of >100% transmittance in the first week. Percent transmittance declined sharply under the maize in the alley crop for the first 6 weeks, as predicted by HedgeGro (Fig. 7). The predictions of transmittance at the end of the crop were high probably because HedgeGro does not account for light interception by stalks, dead leaves, and ears.
Fig. 9. Measurements and model simulations of percent light transmitted to sensor on the floor of the alley over the entire cropping season for 1996 in: (a) sole hedgerows; and (b) alley crop.
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4.2.1. Radiation use efficiency The hedgerow biomass at each harvest was linearly related to the accumulated intercepted radiation as calculated by the model (r 2 = 0.95, P < 0.001, Fig. 8). There was no significant difference between the slopes of the lines for the alley crop and the sole hedge treatment. The average of the two slopes gave a value of ε of 0.176 g biomass mol−1 photons, and this value was used in subsequent calculations. When the hedgerow growth was simulated, the model tracked the day to day fluctuations in the transmittance to the sensor in the alley but consistently predicted greater transmittance than when it was run using measured hedgerow dimensions (Fig. 7). The model drastically under predicted growth if the simulation was started at the time of the initial cut, therefore, simulations were only started after the first 2-week growth interval. The difference between the predictions of the two modes of the model increased with time. HedgeGro predicted the hedgerow biomass within one standard deviation for each harvest interval except for the last harvests (Fig. 2a). The increasing hedgerow biomass drives the shoot thinning process, and HedgeGro predicted the number of shoots in the harvest plots to within one standard deviation (Fig. 2b). The model correctly predicted that the hedgerows in the alley crop will be smaller and have more shoots per linear meter than the sole hedgerows.
4.3. Validation for 1996 season HedgeGro also closely predicted the magnitude and daily fluctuations in light incident on the sensor between the hedgerows in 1996 when the hedgerow dimensions were read in from data files (Fig. 9a). Predictions for light transmitted through the maize crop were also generally accurate when hedgerow size data was read in from tables, with the exception that the model over predicted transmittance late in the maize crop, probably due to not taking stover, ears, and dead leaves into account (Fig. 9b). When hedgerow growth was simulated, however, the model over predicted the light to the alley (Fig. 9). Correspondingly, it also under predicted the biomass in both the alley cropping treatment and in the sole hedge treatment (Fig. 3a). 4.3.1. Radiation use efficiency Biomass growth was linearly related to radiation intercepted (r 2 = 0.96, P < 0.001, Fig. 10). Radiation use efficiency was significantly greater in 1996 than in 1995 (0.21 versus 0.18 g above-ground biomass mol−1 photosynthetic photons, P = 0.012). There was no significant difference between treatments, although the alley crop hedgerows had a lower ε both in 1995 and in 1996.
Fig. 10. Radiation use efficiency of hedgerows in 1996. Regression line is for all points.
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5. Conclusions 5.1. Light interception and growth predictions HedgeGro accurately predicted the light interception on the floor of the alley between the hedgerows and, thus, by inference light intercepted by the hedgerows and crops. We did not attempt any more direct measurements of light interception by the plants, since such measurements would have necessitated a large array of sensors and detailed models for interpolation. Some agroforestry experiments (Lawson and Kang, 1990; Howard et al., 1995; Miah et al., 1995) have only measured light transmission on a few single days over the cropping season. The effect of day to day variability in sky conditions makes the accuracy of such measurements suspect. Howard et al. (1995) found that the fraction of light intercepted by trees in a hedgerow–maize intercrop as measured by above and below canopy ceptometers was 10–20% greater when the sky was clear than when it was overcast, and in this study transmittance to the alley floor varied by 10–20% over the course of a few days (Fig. 7). Two or three single day measurements in a heterogeneous canopy system are not likely to give a good estimate of crop light interception. The smaller biomass of the hedgerows in the alley crop indicates that the crop competed significantly with the hedgerows. The differences in hedgerow growth, however, may be explained solely on the basis of differences in radiation intercepted. In the model, the hedgerows in the alley cropping treatment were shaded by the maize and so received less light and grew less. HedgeGro correctly predicted these differences (Figs. 2a and 3a). The difference in number of shoots between the two treatments was correctly predicted by the model in 1995 (Fig. 2b) but over predicted in 1996 (Fig. 3b), indicating that a different self-thinning line (Eq. (2)) may be needed. Data from hedgerow harvests for 1996 (Friday, 1998), which were not used to create the model, indicate that the self-thinning line in 1996 may have had a steeper slope or higher intercept. 5.2. Radiation use efficiency The increase in ε in 1996 accounts for over half the difference between the model predictions of biomass
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and the average measured values. If the model is run with ε set at 0.207 g biomass mol−1 photons, the average of the two treatments in 1996, instead of 0.176 g mol−1 , final hedgerow biomass in the sole hedge treatment is predicted to be 882 g m−2 instead of 735 g m−2 , in comparison with a measured value of 1015 g m2 . Although ε for the hedgerows was less in the alley crop in both years, the differences were not significant. Had the differences in ε been significant, the difference would have been an indication that the crop competed with the hedgerows below-ground. The competitive effect of the crop on the hedgerows in this experiment, therefore, is significant, as shown from the biomass growth data, but overwhelmingly above-ground rather than below-ground. In this experiment the maize crop was almost as tall as the hedgerows, so crop competition for light would be expected to affect hedgerow growth. In other cases, such as with tall hedgerows and low stature crops such as rice or vegetables, or with full grown trees grown as widely spaced windbreaks with many rows of crops between, the effect of the crop on the hedgerows may be negligible. The higher ε in 1996 may be attributed to improved nutrient or moisture status. Hedgerows presumably benefited from the additional P application in 1996 and may also have benefited from the more evenly distributed rainfall. The radiation use efficiency of the Flemingia in this experiment was relatively low compared with other tropical fast-growing trees (Corlett et al., 1992; Harrington and Fownes, 1995) and willow cuttings grown in Scotland (Cannell et al., 1987) (Table 1). Coppicing trees, including cutting hedgerows, may result in root dieback (Fownes and Anderson, 1991; Nygren and Campos, 1995), and much of the biomass produced by the hedgerows may have been root re-growth, which was not measured in this study. The shoot to root ratio as different species grow back after coppicing is variable (Fownes and Anderson, 1991; Ruhigwa et al., 1992) and Flemingia may allocate a relatively large amount of biomass below-ground. Fownes and Harrington (1995), however, did not find any difference in ε between planted and coppiced trees in their study. Also not measured in this study were litterfall and biomass increment of the 1 m tall stumps, although these are probably small relative to the overall biomass.
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Table 1 Radiation use efficiencies (ε) of coppiced treesa Species
ε
Location
Source
Flemingia macrophylla Acacia auriculiformis Eucalyptus camaldulensis Gliricidia sepium Leucaena diversifolia Salix viminalis Leucaena leucocephala
0.40 0.87 0.81 0.65 0.37 0.99 0.80
Hawaii Hawaii Hawaii Hawaii Hawaii Scotland India
This study Harrington and Fownes Harrington and Fownes Harrington and Fownes Harrington and Fownes Cannell et al. (1987) Corlett et al. (1992)
(1995) (1995) (1995) (1995)
a g above-ground biomass MJ−1 total intercepted radiation, assuming a conversion ratio of 2.1 mol photons MJ−1 for data for this study (Oke, 1987; Landsberg et al., 1996)
Absorbed radiation, defined as intercepted radiation minus radiation reflected from the canopy, may be less than intercepted radiation by about 10% (Boote and Loomis, 1991; Demetriades-Shah et al., 1992). Estimates of ε based on absorbed radiation will, thus, be greater than estimates based on intercepted radiation, The empirical extinction coefficient k in this study included the effect of light transmitted through the leaves but did not account for light reflected by the canopy. Radiation use efficiencies for woody plants tend to be lower than those for herbaceous crops because of respiration by woody tissue and may be lower for legumes because of the energy cost of maintaining N-fixing bacteria (Russell et al., 1989). The Flemingia in this study was observed to nodulate in the field.
fruitful discussions, R. de la Peña for the use of his laboratory facilities, and T. Giambelluca, J. Silva, G. Tsuji, and R. Yost for comments on the manuscript. This research was partly supported by USDA CSRS Special Grant in Tropical and Subtropical Agriculture No. 90-34135-5341 and partly by the US AID Soil Management Collaborative Research Support Program (TropSoils). We thank Pioneer Hi-Bred International Inc. for supplying maize seed free of charge and on short notice. This paper is College of Tropical Agriculture and Human Resources Journal Series No. 4530.
5.3. Simulating hedgerow growth
Anderson, L.S., Muetzelfeldt, R.I., Sinclair, F.L., 1993. An integrated research strategy for modelling and experimentation in agroforestry. Commonwealth Forestry Rev. 72, 166–174. Boote, K.J., Loomis, R.S., 1991. The prediction of canopy assimilation. In: Modeling Crop Photosynthesis — From Biochemistry to Canopy. CSSA Special Publication No. 19, Crop Science Society of America, Madison, WI, pp. 109–140. Cannell, M.G.R., Milne, R., Sheppard, L.J., Unsworth, M.H., 1987. Radiation interception and productivity of willow. J. Appl. Ecology 24, 261–278. Corlett, J.E., Black, C.R., Ong, C.K., Monteith, J.L., 1992. Above- and below-ground interactions in a leucaena/millet alley cropping system. Part II. Light interception and dry matter production. Agric. Forest Meteorol. 60, 73–91. Demetriades-Shah, T.H., Fuchs, M., Kanemasu, E.T., Flitcroft, I., 1992. A note of caution concerning the relationship between cumulated intercepted solar radiation and crop growth. Agric. Forest Meteorol. 58, 193–207. Friday, J.B., 1998. Competition for light between Flemingia macrophylla and Zea mays in an agroforestry system. PhD dissertation, Dept. of Agronomy and Soil Science, Univ. of Hawaii, Honolulu, HI.
The use of an empirical radiation use efficiency limits the ability of the model to predict growth under conditions where environmental variables such as temperature, water, or nutrient status are different than in the original experiment (Demetriades-Shah et al., 1992). HedgeGro could be linked with water or nutrient models to calculate a maximum potential ε and modify growth based on nutrient and water availability (Landsberg, 1986; McMurtrie et al., 1994).
Acknowledgements We thank J. Ornellas and the staff of the Kauai Branch Station for assistance in field work, J. Brewbaker, R. Ogoshi, J. Ooka, and M. Willanison for
References
J.B. Friday, J.H. Fownes / Agricultural and Forest Meteorology 108 (2001) 29–43 Fownes, J.H., Harrington, R.A., 1990. Modelling growth and optimal rotations of tropical multipurpose trees using unit leaf rate and leaf area index. J. Appl. Ecology 27, 886–896. Fownes, J.H., Anderson, D.G., 1991. Changes in nodule and root biomass of Sesbania sesban and Leucaena leucocephala following coppicing. Plant and Soil 38, 9–16. Gholz, H.L., Vogel, S.A., Cropper Jr., W.P., McKelvey, K., Ewel, K.C., 1991. Dynamics of canopy structure and light interception in Pinus elliottii stands, North Florida. Ecological Monographs 16, 33–51. Harrington, R.A., Fownes, J.H., 1995. Radiation interception and growth of planted and coppice stands of four fast-growing tropical trees. J. Appl. Ecology 32, 1–8. Howard, S.B., Ong, C.K., Rao, M.R., Mathuva, M., Black, C.R., 1995. The partitioning of light and water in Leucaena-maize agroforestry systems. In: H. Sinoquet, P. Cruz (Eds.), Ecophysiology of Tropical Intercropping. Institut de la Recherche Agronomique, Paris, pp. 123–135. Ikawa, H., Sato, H.H., Chang, A.K.S., Nakamura, S., Robello Jr., E., Periaswamy, S.P., 1985. Soils of the Hawaii Agricultural Experiment Station, University of Hawaii. Soil Survey, Laboratory Data, and Soil Descriptions. Benchmark Soils Project Technical Report No. 4, HITAHR Research Extension Series 022, Honolulu, HI. Jackson, J.E., Palmer, J.W., 1972. Interception of light by model hedgerow orchards in relation to latitude, time of year, and hedgerow configuration and orientation. J. Appl. Ecology 9, 341–357. Jackson, J.E., Palmer, J.W., 1989. Light availability at the tree/crop interface. In: Reifsnyder, W.S., Darnhofer, T.O. (Eds.), Meteorology and Agroforestry. ICRAF, Nairobi, pp. 391–400. Jones, C.A., Kiniry, J.R., 1986. CERES-Maize: A Simulation Model of Maize Growth and Development. Texas A&M University Press, College Station, TX. Landsberg, J.J., 1986. Physiological Ecology of Forest Production. Academic Press, San Diego. Landsberg, J.J., Waring, R.H., 1997. A generalized model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology Manage. 95, 209–228. Landsberg, J.J., Prince, S.D., Jarvis, P.O., McMurtrie, R.E., Luxmoore, R., Medlyn, B.E., 1996. Energy conversion and use in forests: an analysis of forest production in terms of radiation utilisation efficiency (ε). In: Gholz, H.L., Nakane, K., Shimoda, H. (Eds.), The Use Of Remote Sensing in the Modeling of Forest Productivity. Kluwer, Dordrecht, The Netherlands, pp. 273–298. Lawson, T.L., Kang, B.T., 1990. Yield of maize and cowpea in an alley cropping system in relation to available light. Agric. Forest Meteorol. 52, 347–357. Lawson, G.J., Crout, N.M.J., Levy, P.E., Mobbs, D.C., Wallace, J.S., Cannell, M.G.R., Bradley, R.G., 1995. The tree–crop
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interface: representation by coupling of forest and crop process models. Agroforestry Systems 30, 199–221. Linder, S., McMurtrie, R.E., Landsberg, J.H., 1985. Growth of Eucalyptus: a mathematical model applied to Eucalyptus globulus. In: Tigerstedt, P.M.A., Puttonen, P., Koski, V. (Eds.), Crop Physiology of Forest Trees. University of Helsinki, Helsinki, Finland, pp. 117–126. McMurtrie, R.E., Rook, D.A., Keller, F.M., 1990. Modelling the yield of Pinus radiata on a site limited by water and nitrogen. Forest Ecology Manage. 30, 381–413. McMurtrie, R.E., Gholz, H.L., Linder, S., Gower, S., 1994. Climatic factors controlling the productivity of pine stands: a modelbased analysis. Ecological Bull. (Copenhagen) 43, 173–188. Miah, M.G., Garrity, D.P., Aragon, L., 1995. Light availability to the understory annual crops in an agroforestry system. In: Sinoquet, H., Cruz, P. (Eds.), Ecophysiology of Tropical Intercropping. Institut de la Recherche Agronomique, Paris, pp. 99–107. Nygren, P., Campos, A., 1995. Effect of foliage priming on fine root biomass of Erythrina peoppigiana (Fabaceae). In: Sinoquet, H., Cruz, P. (Eds.), Ecophysiology of Tropical Intercropping. Institut de la Recherche Agronomique, Paris, pp. 295–302. Oke, T.R., 1987. Boundary Layer Climates. Methuen, NY. Palmer, J.W., 1977. Diurnal light interception and a computer model of light interception by hedgerow apple orchards. J. Appl. Ecology 9, 341–358. Raison, R.J., Myers, B.T., 1992. The biology of forest growth experiment: linking water and nitrogen availability to the growth of Pinus radiata. Forest Ecology Manage. 52, 279–308. Robinson, N., Stoch, L., 1964. Sky radiation measurement and corrections. J. Appl. Meteorol. 3, 179–181. Ruhigwa, B.A., Gichuru, M.P., Mambani, B., Tariah, N.M., 1992. Root distribution of Acioa barteri, Alchronea cordifolia, Cassia siamea, and Gmelina arborea in an acid Ultisol. Agroforestry Systems 19, 67–78. Russell, G., Jarvis, P.G., Monteith, J.L., 1989. Absorption of radiation by canopies and stand growth. In: Russell, G., Marshall, B., Jarvis, P.G. (Eds.), Plant Canopies: Their Growth, Form, and Function. Cambridge University Press, NY, pp. 21–40. Sanchez, P., 1995. Science in agroforestry. Agroforestry Systems 30, 5–55. Sellers, W.D., 1965. Physical Climatology. University of Chicago Press, Chicago. Soil Survey Staff, 1996. Keys to Soil Taxonomy. 7th Edition, USDA Natural Resources Conservation Service, Pittsburgh, PA. Wang, Y.P., Jarvis, P.G., Taylor, C.M.A., 1991. PAR absorption and its relation to above-ground dry matter production of Sitka spruce. J. Appl. Ecology 28, 547–560. Westoby, M., 1984. The self-thinning rule. Adv. Ecological Res. 14, 167–225. Wilkinson, L., Hill, M., Vang, E., 1992. Systat: Statistics, Version 5.2 Edition, Systat Inc., Evanston, IL.
A simulation model for hedgerow light interception and growth James B. Friday a,∗ , James H. Fownes b,1 a
College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa, 875 Komohana St., Hilo, HI 96720 USA b Department of Natural Resources Conservation, University of Massachusetts, Amherst, MA 01003 USA Received 27 July 2000; received in revised form 29 December 2000; accepted 6 January 2001
Abstract In order to investigate competition for light between trees and crops in an agroforestry system, we wrote a simulation model of light interception and growth by a system of hedgerows and an interplanted crop. To calculate light interception, hedgerows are modeled as long prisms, solar angles and hedgerow shadow lengths are calculated, and light intercepted by the hedgerows and points in the alley is summed. Biomass allocation to leaves and wood and the new hedgerow dimensions are calculated from empirical allometric equations. Hedgerow shoots are modeled as a population undergoing density-dependant mortality. Parameters for the model were developed from an alley cropping experiment of hedgerows of Flemingia macrophylla, a legume shrub with broad leaves, grown alone or intercropped with maize on the island of Kauai, Hawaii. The model was tested with data from field experiments conducted in 1995 and 1996. In 1995, light interception simulated by the model for a point on the floor of the alley tracked measured light interception well over the course of the crop both when hedgerow sizes were input from field measurements and when they were simulated. Hedgerow biomass predicted by the model closely followed that measured in periodic harvests. In 1996, light interception simulated by the model tracked measured light interception well when the model was run with measured hedge dimensions, but the model under predicted hedgerow growth and, thus, over predicted transmission when growth was simulated. Radiation use efficiencies (ε) for the hedgerows over the entire cropping season were calculated by regressing harvest biomass against light interception as calculated by the model. These averaged 0.18 (S.E. 0.005) g above-ground biomass mol−1 photosynthetically active photons for both treatments in 1995 and 0.21 (S.E. 0.008) g mol−1 in 1996. While hedgerow biomass was affected by the presence of the crop, the fact that ε was the same in both treatments indicated that competition was overwhelmingly for light rather than for water or nutrients. © 2001 Elsevier Science B.V. All rights reserved. Keywords: Agroforestry; Alley cropping; Competition; Radiation use efficiency; Flemingia macrophylla
1. Introduction Competition for light from trees often limits growth of crops in agroforestry systems (Sanchez, 1995). Quantifying the severity of competition and separating above-ground competition for light from ∗ Corresponding author. Tel.: +1-808-959-9155; fax: +1-808-959-3101. E-mail addresses: [email protected] (J.B. Friday), [email protected] (J.H. Fownes). 1 Tel.: +1-413-577-0205; fax: +1-413-545-4358.
below-ground competition for water or nutrients is difficult in field experiments, however, simulation models can be used to analyze tree–crop interactions and optimize management of agroforestry systems (Anderson et al., 1993). Models developed for forest growth and crop growth may be modified and combined for use with agroforestry systems (Lawson et al., 1995). Agroforestry systems in particular require unique formulations because they are typically diverse with heterogeneous canopies and incorporate some of the attributes of forest systems and some of crop systems. We wrote a simulation model, HedgeGro,
0168-1923/01/$ – see front matter © 2001 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 8 - 1 9 2 3 ( 0 1 ) 0 0 2 2 0 - 9
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Nomenclature B D ε k L Q R T
biomass (g m−2 ) date of harvest radiation use efficiency (g above-ground biomass mol−1 photosynthetic photons) light extinction coefficient (unitless) leaf area index (m2 m−2 ) photosynthetic photon flux density (mmol m2 s−1 ) replication treatment
which combines principles used in forest growth models (radiation use efficiency, self-thinning of a stand, allometric equations describing biomass partitioning) with principles used in crop models (radiation use efficiency, light interception in a heterogeneous canopy) to model light interception and growth of hedgerows in an alley cropping system. We used the model to assess above- versus below-ground competitive effects of the crops on the trees. 1.1. Forest growth models Forest stand growth may be simulated with a computer model by calculating solar radiation intercepted by the canopy, converting the radiation into biomass by multiplying by a radiation use efficiency (ε), then allocating the new biomass to leaves, stems, and roots (Landsberg, 1986). Some models calculate absorbed radiation by subtracting radiation reflected from the canopy from that intercepted. The biomass allocated to the canopy produces new canopy dimensions, and the cycle starts again with interception of new radiation. Models patterned on this basic procedure have simulated stand growth in eucalyptus (Linder et al., 1985) and pine (McMurtrie et al., 1990; McMurtrie et al., 1994; Landsberg and Waring, 1997). 1.2. Radiation interception Jackson and Palmer (1972) created a model of light interception for a hedgerow system consisting of solid prisms of a given height and width and an infinite length. The model calculated the sun position and calculated light interception based on what fraction of the alley was shaded by the hedgerow and
how much ground the hedgerow itself occupied. Later modifications of their model included light transmission through the hedgerow canopy based on Beer’s law for clumped canopies (Palmer, 1977; Jackson and Palmer, 1989). In developing the light interception component of the model HedgeGro, we adapted Jackson and Palmer’s (1977) model to include hedgerows shaped as rectangular prisms with hemi-cylindrical tops (Boote and Loomis, 1991) and interception of diffuse radiation based on the fraction of sky visible from the alley (Oke, 1987). We used geometrical shapes and fraction of ground shaded as the simplest method for dealing with a heterogeneous canopy. The leaf area density within the hedgerow canopy is uniform at any one time, although it changes as the hedgerow grows. We added the ability to calculate light interception by a crop grown in the alleys and resulting shading of the hedgerows. Finally, the model calculates the sum of the radiation intercepted over the course of a single day and over a cropping season. 1.3. Radiation use efficiency and competition Radiation use efficiency may be affected by both moisture status and fertility. Drought conditions have been shown to lower ε (Harrington and Fownes, 1995). Fertilization has been shown to increase ε in spruce (Wang et al., 1991) and pine (Gholz et al., 1991; Raison and Myers, 1992), although not in eucalyptus (Linder et al., 1985). Some radiation-driven growth models start with a potential ε and then modify this based on water, temperature, and nutrient availability (Landsberg, 1986). McMurtrie et al. (1994) modeled gross primary productivity in pine stands as a function of ε, modified by factors accounting for incomplete interception of radiation, soil water deficits, water vapor saturation deficits of the air, and low temperature effects. They found that the environmental variables were necessary for the model to make accurate predications of productivity. In contrast, Linder et al. (1985) found that a simple empirical ε was sufficient to model several different stands of Eucalyptus globulus. Crop models such as CERES-Maize (Jones and Kiniry, 1986) also multiply a high potential ε by factors to account for environmental variables. Plants growth may be limited either because of lack of sufficient light, water, and nutrients in the environment or because of competition for these resources
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from other plants. Radiation use efficiency may be used as a tool to assess stress caused by below-ground competition from other plants. In an agroforestry system, if tree growth is limited by competition for nutrients or water from crops, the trees would be expected to have a lower ε than trees grown alone. Radiation use efficiencies of trees grown with and without crops can be compared to determine the severity of competition. Since the calculation of ε explicitly takes the difference in light environments into account, the difference can then be attributed to below-ground competition. In our field experiments, we grew hedgerows with and without interplanted crops. We calculated ε for the hedgerows using the model and compared ε of the sole hedgerow with ε of the alley crop to assess how and if the crops competed with the hedgerow. 1.4. Hedgerow growth The models MPTGro (Fownes and Harrington, 1990) and 3-PG (Landsberg and Waring, 1997) allocate new growth to wood or leaf biomass based on diameter to leaf area allometric equations developed from harvest data. Our field work has shown that the hedgerow canopy changes in leaf area density and in the ratio of leaf biomass to woody biomass as it grows (Friday, 1998). We modeled the hedgerow as a population of shoots undergoing density-dependant mortality (self-thinning) as they grow according to the −0.5 power law (Westoby, 1984). Average shoot size is calculated from the biomass and the number of shoots, and shoot allometry developed from field experiments determines the hedgerow dimensions. Landsberg and Waring (1997) similarly calculate the average stem size of trees in a stand based on a thinning relationship and use the average stem size to calculate the leaf area. New biomass in HedgeGro is calculated by multiplying light intercepted by an empirical ε (Russell et al., 1989). 1.5. Development of model parameters and testing Allometric equations and values for ε used in the model HedgeGro were developed from an alley cropping experiment on the island of Kauai, Hawaii, in 1995. The model was tested against biomass data and independent light interception data from the experiment in 1995 and again in 1996.
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2. The model 2.1. Input The hedgerow system is set-up based on a file containing the basic characteristics of the site. Hedgerow growth can be simulated or interpolated from a table of periodic field measurements containing hedge height, width, leaf area, biomass, and number of shoots per linear meter. When hedgerow growth is to be simulated, another input file consisting of allometric equations for the hedgerow is required. This file includes a radiation use efficiency, the slope and intercept for a self-thinning line relating the hedgerow shoot density to biomass, and coefficients and exponents for equations pertaining to the hedgerow dimensions. If a crop between the hedgerows is simulated, the model calls for input files containing arrays of crop heights and leaf areas for each row of the crop. The model requires a weather file which contains the day of year, the hour, and hourly values for total incident photosynthetic photon flux density and diffuse photosynthetic photon flux density (Q and Qdiff , mmol m−2 s−1 ). Direct beam radiation is calculated as the total radiation less the diffuse radiation. 2.2. Output HedgeGro creates an output file including the hourly photosynthetic photon flux density (Q, mol m−2 h−1 ) incident at the sensor position and hourly Q intercepted by each row of the crop in the alley. The daily summary file includes the daily total photon flux intercepted by the hedgerows (mol m−2 day−1 ), the total incident at the sensor position, and the total intercepted by each row of the crop. 2.3. Calculations of intercepted radiation HedgeGro calculates the solar zenith angle and azimuth at 6 min intervals from the hour angle, solar declination, and the latitude using standard solar geometry equations (Sellers, 1965). To calculate intercepted diffuse radiation, HedgeGro calculates the fraction of the sky visible from each point of interest (crop position, sensor position, or location in the alley) by using the equations for view factors given
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by Oke (1987). Diffuse radiation is assumed to be isotropic, therefore, the diffuse radiation incident at one point is that point’s view factor times the total diffuse radiation. Both direct beam and diffuse light transmission through the hedgerow canopy are calculated with a modification of Beer’s Law to account for clumped canopies (Jackson and Palmer, 1989). Light intercepted by the hedgerow, the crop, or bare soil is calculated as the sum of incident direct and diffuse radiation, less that transmitted through the canopy. 2.4. Hedgerow growth simulation HedgeGro simulates hedgerow growth by converting the radiation intercepted (Qi ) to biomass (B) through a radiation use efficiency (ε) Bn = B + εQi
(1)
The new biomass (Bn ) must be partitioned into wood and leaves. The first step is to calculate the number of shoots in the plot, HedgeGro inverts the classic self-thinning relationship between population density and biomass Number of shoots = aBb
Fig. 1. Flow chart of growth simulation sub-model.
at the Wailua Experiment Station of University of Hawaii, Kapaa, Kauai, Hawaii, longitude 22◦ N, latitude 159◦ W. Elevation at the station is 160 m and annual rainfall averages 2500 mm (Ikawa et al., 1985). The soil is Halii gravelly silty clay and is classed as an anionic acroperox, fine, ferruginous, and isothermic (Soil Survey Staff, 1996). 3.2. Hedgerows
(2)
where a and b are empirically derived constants. In this case, both number of shoots and biomass are divided by the hedgerow drip line area (m2 ), defined as the width of the hedgerow multiplied by the length of the plot. An average shoot biomass is then calculated by dividing the biomass by the number of shoots. Hedge dimensions needed to model light interception are then calculated based on several allometric equations, all of the form Y = aXb . The average shoot biomass is related to an average shoot length, and the average shoot length in turn to the hedgerow height and width. The average shoot biomass also is used to calculate a wood to leaf ratio, which is then used in calculating a leaf area (Fig. 1).
Two treatments, hedgerows with and without an intercrop of maize, were replicated four times in a randomized complete block design. Seedlings of Flemingia macrophylla were outplanted between November 1993 and January 1994. Hedgerows were spaced 5.33 m apart and oriented at an azimuth of 4◦ east of north (orientation was chosen to run basically north–south while following the borders of the available field). Each plot consisted of three parallel hedgerows, with all experimental measurements being taken on the center hedgerow. Trimmings were discarded throughout the experiment to avoid confounding effects on soil fertility. 3.3. 1995 crop
3. Methods 3.1. Site for field experiment Parameters for HedgeGro were developed and the model was tested on an alley cropping experiment
The hedges were cut to a height of 1 m in March 1995, 2 weeks prior to planting the crop. Fertilizer was applied to the alleys between the hedges for both the crop and sole hedge treatments at a rate of 150 kg/ha N, 400 kg/ha P, 200 kg/ha K, and 55.6 kg/ha of granusol, a micro-nutrient mix. For the crop treatment, six rows
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of maize were planted, with the first row 1 m from the center of the hedgerow. 3.4. Meteorological data A micro-meteorological station immediately outside the field recorded weather data on a CR21x datalogger (Campbell Scientific, Inc., Logan, Utah, USA). Hourly measurements were taken of photosynthetic photon flux density (Q, mmol m−2 s−1 ) and diffuse Q with LI190SB quantum sensors (LI-COR Inc., Lincoln, Nebraska, USA). The quantum sensor used to measure diffuse light was outfitted with a homemade shade ring which blocked the direct beam
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radiation (Oke, 1987, p. 368). The shade ring was adjusted weekly to keep it aligned with the solar path and values for diffuse radiation were multiplied by a factor of 1.08 to account for the fraction of the sky blocked by the shade band (Robinson and Stoch, 1964). Daily maximum, minimum, and average temperature were recorded along with daily precipitation, average wind speed, and wind direction. In order to have independent observations with which to test the model, light transmission was measured to a point on the floor of the alley continuously throughout the crop. A line quantum analyzer (LI191SA, LI-COR Inc., Lincoln, Nebraska, USA) which measures the average Q along a 1 m length was
Fig. 2. Hedgerow growth and model predictions compared with measurements in 1995 for: (a) hedgerow shoot biomass; and (b) number of shoots in hedgerow. Error bars indicate standard deviations.
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installed in one plot of each treatment running north to south, parallel to the hedgerows. The sensors were 1.67 m from the center line of the hedgerow, which in the alley crop was at the base of the second row of maize. A third line quantum analyzer was placed above the crop canopy to record incident radiation. Percent light transmitted to the sensor was calculated by dividing the Q of the below canopy sensor by the Q of the above canopy sensor. Light transmission in each subplot was measured for 2 weeks prior to the harvest of that subplot. Moving the sensors after each harvest served to average out spatial variability along the hedge.
3.5. Harvest procedure In each main plot, harvest subplots 2 m long were randomly selected from the middle hedgerow. The first cut was made 3 weeks from the date of the maize planting (4 weeks from the time the hedgerows were trimmed). Subsequent subplots were harvested every 2 weeks until the final crop harvest, for a total of eight harvests. At each harvest, hedgerow height, width, fresh shoot biomass, and number of shoots were measured. Hedges were cut at 1 m height. In the alley cropping plots, maize height and total above-ground fresh
Fig. 3. Hedgerow growth and model predictions compared with measurements in 1996 for: (a) hedgerow shoot biomass; and (b) number of shoots in hedgerow. Error bars indicate standard deviations.
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Fig. 4. Leaf area index (L) for hedgerows and alley crop in 1995. L for hedgerows is calculated as m2 leaf area m−2 ground actually covered by the canopy of the hedgerows.
biomass for each row were recorded in the field. Subsamples of both maize plants and hedgerow shoots were taken for determination of biomass, leaf area, average shoot length, and wet to dry ratios. Leaf area was determined for green leaves with a LI-COR LI-3100 Leaf Area Meter.
3.6. 1996 crop A second maize crop was planted in 1996, 5 weeks after the hedges had been cut back to 1 m in height This resulted in hedgerows which were considerably larger relative to the crop in 1996 than they had been
Fig. 5. Leaf area index (L) for hedgerows and alley crop in 1996.
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in 1995. Plots were harvested every 4 weeks in 1996 and were 4 m long rather than 2 m. 3.7. Calculation of results and model parameters The constants for the allometric equations were all derived from the field experiments (Friday, 1998). Only the data from 1995 were used so that the 1996 data would be completely independent for model validation. Separate allometric equations relating average shoot length to hedgerow width were used for
the alley crop and the sole hedge treatment. Specific leaf area is kept constant at 0.0225 m2 g−1 . The hedgerow light extinction coefficient k was calculated as 0.9 for the Flemingia hedgerows based on a separate set of instantaneous measures of light transmission with the line quantum analyzers on a sunny day and leaf area based on a harvest The model follows the CERES model in using a k of 0.65 for maize (Jones and Kiniry, 1986). Because the hedgerows were not harvested at the time the crop was planted in 1996, biomass and leaf
Fig. 6. Transmittance of light to a sensor on the floor of the alley: (a) percent transmittance on a sunny day; (b) total light incident on the same day; (c) percent transmittance on an overcast day.
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area were estimated from the hedgerow height based on allometric relationships developed from the 1995 data for the start of the 1996 simulations. In testing for differences in hedgerow growth, hedgerow biomass and leaf area were log-transformed to homogenize variances. An analysis of variance was done for each year using the model Y = T + R + TR(error) + D + DR(error) +DT + DTR(error)
(3)
where Y = ln of biomass or leaf area, T = treatment,
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R = replication, and D = harvest date. The split block model was used instead of the split plot because both biomass and leaf area are not randomly distributed but increase throughout the growing season. Hedgerow leaf area indices were calculated as leaf area divided by the total ground area occupied by the hedgerow, which increased as the hedgerows grew. Radiation use efficiency (ε) was calculated by regressing the light intercepted by the hedgerows against the biomass harvested. The model was run to calculate cumulative intercepted radiation for each plot based on field measurements of hedgerow dimensions.
Fig. 7. Measurements and model simulations of percent light transmitted to sensor on the floor of the alley over the entire cropping season for 1995 in: (a) sole hedgerows; and (b) alley crop.
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Biomass measurements were independent since separate subplots were harvested at each interval, but since the hedges continued growing each harvest was greater than the preceding ones. The intercepted radiation calculated was cumulative for each replication. There is, therefore, some autocorrelation in the measurements of ε, although less so than in forestry experiments where the same trees are repeatedly measured (Russell et al., 1989). Using a general linear model with treatment and year as categorical variables and intercepted radiation as a covariate, we tested for differences among the slopes of the regressions by the F-tests for the interactions of treatment by radiation and year by radiation (Wilkinson et al., 1992).
actions were significant in each year (P = 0.001 in 1995 and P = 0.004 in 1996). Leaf area indices for the hedgerows in the alley cropping treatment also decreased relative to those in the sole hedgerow plots as the maize canopy developed (Figs. 4 and 5). The 1995 maize crop was P deficient in some plots and additional P was applied in 1996. Precipitation was also greater and more evenly distributed in 1996. During a dry spell in 1995, there were 9 weeks in a row during the season where the daily average precipitation was less than 3 mm, while in 1996, only 3 weeks in a row had average daily precipitation of less than 3 mm. Average daily rainfall in 1996 was 1.4 times that of 1995. 4.2. Partial validation for 1995 season
4. Results 4.1. Hedgerow and crop growth The maize alley crop clearly competed with the hedgerows. Hedgerow biomass was greater in the sole hedgerow plots than in the alley cropping plots after 13 weeks after the initial cut (11 weeks after the crop was planted) in 1995 and after 24 weeks after the initial cut (9 weeks after the crop was planted) in 1996 (Figs. 2a and 3a). Treatment by harvest inter-
HedgeGro accurately predicts the light incident at a given point in the alley over the course of a day. Fig. 6a shows the percentage of the total light transmitted through or past the hedgerows and crop and incident on the sensor for a clear day, June 24. The sensor was in the shade of the hedgerow until 10:00, then emerged into the sun. In the sole hedge plot, the shadow of the hedge actually became darker as the sun rose in the morning since the light passed through more of the hedgerow canopy. Cloudiness at midday
Fig. 8. Radiation use efficiency of hedgerows in 1995. Regression line is for all points.
J.B. Friday, J.H. Fownes / Agricultural and Forest Meteorology 108 (2001) 29–43
decreased the percentage of light incident at the sensor because much of the diffuse radiation, which is distributed evenly over the sky, was blocked by the hedgerows. Finally, the sensor was again in the shadow of the hedgerow after 16:00. The sensor in the alley cropped plot showed relatively little light transmitted through the mature maize canopy. The model successfully predicted all these trends. Predictions of the total light incident at the sensor on the same day closely follow the measured light (Fig. 6b). The percentage of light incident at the sensor varied little over the course of an overcast day, May 12 (Fig. 6c).
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Over the entire growing season, HedgeGro predicted the day to day variation in the average daily percent of incident light transmitted to the sensor in the alley when hedge sizes were read in from data tables (Fig. 7). Sensor calibration problems probably caused the spurious measurements of >100% transmittance in the first week. Percent transmittance declined sharply under the maize in the alley crop for the first 6 weeks, as predicted by HedgeGro (Fig. 7). The predictions of transmittance at the end of the crop were high probably because HedgeGro does not account for light interception by stalks, dead leaves, and ears.
Fig. 9. Measurements and model simulations of percent light transmitted to sensor on the floor of the alley over the entire cropping season for 1996 in: (a) sole hedgerows; and (b) alley crop.
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4.2.1. Radiation use efficiency The hedgerow biomass at each harvest was linearly related to the accumulated intercepted radiation as calculated by the model (r 2 = 0.95, P < 0.001, Fig. 8). There was no significant difference between the slopes of the lines for the alley crop and the sole hedge treatment. The average of the two slopes gave a value of ε of 0.176 g biomass mol−1 photons, and this value was used in subsequent calculations. When the hedgerow growth was simulated, the model tracked the day to day fluctuations in the transmittance to the sensor in the alley but consistently predicted greater transmittance than when it was run using measured hedgerow dimensions (Fig. 7). The model drastically under predicted growth if the simulation was started at the time of the initial cut, therefore, simulations were only started after the first 2-week growth interval. The difference between the predictions of the two modes of the model increased with time. HedgeGro predicted the hedgerow biomass within one standard deviation for each harvest interval except for the last harvests (Fig. 2a). The increasing hedgerow biomass drives the shoot thinning process, and HedgeGro predicted the number of shoots in the harvest plots to within one standard deviation (Fig. 2b). The model correctly predicted that the hedgerows in the alley crop will be smaller and have more shoots per linear meter than the sole hedgerows.
4.3. Validation for 1996 season HedgeGro also closely predicted the magnitude and daily fluctuations in light incident on the sensor between the hedgerows in 1996 when the hedgerow dimensions were read in from data files (Fig. 9a). Predictions for light transmitted through the maize crop were also generally accurate when hedgerow size data was read in from tables, with the exception that the model over predicted transmittance late in the maize crop, probably due to not taking stover, ears, and dead leaves into account (Fig. 9b). When hedgerow growth was simulated, however, the model over predicted the light to the alley (Fig. 9). Correspondingly, it also under predicted the biomass in both the alley cropping treatment and in the sole hedge treatment (Fig. 3a). 4.3.1. Radiation use efficiency Biomass growth was linearly related to radiation intercepted (r 2 = 0.96, P < 0.001, Fig. 10). Radiation use efficiency was significantly greater in 1996 than in 1995 (0.21 versus 0.18 g above-ground biomass mol−1 photosynthetic photons, P = 0.012). There was no significant difference between treatments, although the alley crop hedgerows had a lower ε both in 1995 and in 1996.
Fig. 10. Radiation use efficiency of hedgerows in 1996. Regression line is for all points.
J.B. Friday, J.H. Fownes / Agricultural and Forest Meteorology 108 (2001) 29–43
5. Conclusions 5.1. Light interception and growth predictions HedgeGro accurately predicted the light interception on the floor of the alley between the hedgerows and, thus, by inference light intercepted by the hedgerows and crops. We did not attempt any more direct measurements of light interception by the plants, since such measurements would have necessitated a large array of sensors and detailed models for interpolation. Some agroforestry experiments (Lawson and Kang, 1990; Howard et al., 1995; Miah et al., 1995) have only measured light transmission on a few single days over the cropping season. The effect of day to day variability in sky conditions makes the accuracy of such measurements suspect. Howard et al. (1995) found that the fraction of light intercepted by trees in a hedgerow–maize intercrop as measured by above and below canopy ceptometers was 10–20% greater when the sky was clear than when it was overcast, and in this study transmittance to the alley floor varied by 10–20% over the course of a few days (Fig. 7). Two or three single day measurements in a heterogeneous canopy system are not likely to give a good estimate of crop light interception. The smaller biomass of the hedgerows in the alley crop indicates that the crop competed significantly with the hedgerows. The differences in hedgerow growth, however, may be explained solely on the basis of differences in radiation intercepted. In the model, the hedgerows in the alley cropping treatment were shaded by the maize and so received less light and grew less. HedgeGro correctly predicted these differences (Figs. 2a and 3a). The difference in number of shoots between the two treatments was correctly predicted by the model in 1995 (Fig. 2b) but over predicted in 1996 (Fig. 3b), indicating that a different self-thinning line (Eq. (2)) may be needed. Data from hedgerow harvests for 1996 (Friday, 1998), which were not used to create the model, indicate that the self-thinning line in 1996 may have had a steeper slope or higher intercept. 5.2. Radiation use efficiency The increase in ε in 1996 accounts for over half the difference between the model predictions of biomass
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and the average measured values. If the model is run with ε set at 0.207 g biomass mol−1 photons, the average of the two treatments in 1996, instead of 0.176 g mol−1 , final hedgerow biomass in the sole hedge treatment is predicted to be 882 g m−2 instead of 735 g m−2 , in comparison with a measured value of 1015 g m2 . Although ε for the hedgerows was less in the alley crop in both years, the differences were not significant. Had the differences in ε been significant, the difference would have been an indication that the crop competed with the hedgerows below-ground. The competitive effect of the crop on the hedgerows in this experiment, therefore, is significant, as shown from the biomass growth data, but overwhelmingly above-ground rather than below-ground. In this experiment the maize crop was almost as tall as the hedgerows, so crop competition for light would be expected to affect hedgerow growth. In other cases, such as with tall hedgerows and low stature crops such as rice or vegetables, or with full grown trees grown as widely spaced windbreaks with many rows of crops between, the effect of the crop on the hedgerows may be negligible. The higher ε in 1996 may be attributed to improved nutrient or moisture status. Hedgerows presumably benefited from the additional P application in 1996 and may also have benefited from the more evenly distributed rainfall. The radiation use efficiency of the Flemingia in this experiment was relatively low compared with other tropical fast-growing trees (Corlett et al., 1992; Harrington and Fownes, 1995) and willow cuttings grown in Scotland (Cannell et al., 1987) (Table 1). Coppicing trees, including cutting hedgerows, may result in root dieback (Fownes and Anderson, 1991; Nygren and Campos, 1995), and much of the biomass produced by the hedgerows may have been root re-growth, which was not measured in this study. The shoot to root ratio as different species grow back after coppicing is variable (Fownes and Anderson, 1991; Ruhigwa et al., 1992) and Flemingia may allocate a relatively large amount of biomass below-ground. Fownes and Harrington (1995), however, did not find any difference in ε between planted and coppiced trees in their study. Also not measured in this study were litterfall and biomass increment of the 1 m tall stumps, although these are probably small relative to the overall biomass.
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Table 1 Radiation use efficiencies (ε) of coppiced treesa Species
ε
Location
Source
Flemingia macrophylla Acacia auriculiformis Eucalyptus camaldulensis Gliricidia sepium Leucaena diversifolia Salix viminalis Leucaena leucocephala
0.40 0.87 0.81 0.65 0.37 0.99 0.80
Hawaii Hawaii Hawaii Hawaii Hawaii Scotland India
This study Harrington and Fownes Harrington and Fownes Harrington and Fownes Harrington and Fownes Cannell et al. (1987) Corlett et al. (1992)
(1995) (1995) (1995) (1995)
a g above-ground biomass MJ−1 total intercepted radiation, assuming a conversion ratio of 2.1 mol photons MJ−1 for data for this study (Oke, 1987; Landsberg et al., 1996)
Absorbed radiation, defined as intercepted radiation minus radiation reflected from the canopy, may be less than intercepted radiation by about 10% (Boote and Loomis, 1991; Demetriades-Shah et al., 1992). Estimates of ε based on absorbed radiation will, thus, be greater than estimates based on intercepted radiation, The empirical extinction coefficient k in this study included the effect of light transmitted through the leaves but did not account for light reflected by the canopy. Radiation use efficiencies for woody plants tend to be lower than those for herbaceous crops because of respiration by woody tissue and may be lower for legumes because of the energy cost of maintaining N-fixing bacteria (Russell et al., 1989). The Flemingia in this study was observed to nodulate in the field.
fruitful discussions, R. de la Peña for the use of his laboratory facilities, and T. Giambelluca, J. Silva, G. Tsuji, and R. Yost for comments on the manuscript. This research was partly supported by USDA CSRS Special Grant in Tropical and Subtropical Agriculture No. 90-34135-5341 and partly by the US AID Soil Management Collaborative Research Support Program (TropSoils). We thank Pioneer Hi-Bred International Inc. for supplying maize seed free of charge and on short notice. This paper is College of Tropical Agriculture and Human Resources Journal Series No. 4530.
5.3. Simulating hedgerow growth
Anderson, L.S., Muetzelfeldt, R.I., Sinclair, F.L., 1993. An integrated research strategy for modelling and experimentation in agroforestry. Commonwealth Forestry Rev. 72, 166–174. Boote, K.J., Loomis, R.S., 1991. The prediction of canopy assimilation. In: Modeling Crop Photosynthesis — From Biochemistry to Canopy. CSSA Special Publication No. 19, Crop Science Society of America, Madison, WI, pp. 109–140. Cannell, M.G.R., Milne, R., Sheppard, L.J., Unsworth, M.H., 1987. Radiation interception and productivity of willow. J. Appl. Ecology 24, 261–278. Corlett, J.E., Black, C.R., Ong, C.K., Monteith, J.L., 1992. Above- and below-ground interactions in a leucaena/millet alley cropping system. Part II. Light interception and dry matter production. Agric. Forest Meteorol. 60, 73–91. Demetriades-Shah, T.H., Fuchs, M., Kanemasu, E.T., Flitcroft, I., 1992. A note of caution concerning the relationship between cumulated intercepted solar radiation and crop growth. Agric. Forest Meteorol. 58, 193–207. Friday, J.B., 1998. Competition for light between Flemingia macrophylla and Zea mays in an agroforestry system. PhD dissertation, Dept. of Agronomy and Soil Science, Univ. of Hawaii, Honolulu, HI.
The use of an empirical radiation use efficiency limits the ability of the model to predict growth under conditions where environmental variables such as temperature, water, or nutrient status are different than in the original experiment (Demetriades-Shah et al., 1992). HedgeGro could be linked with water or nutrient models to calculate a maximum potential ε and modify growth based on nutrient and water availability (Landsberg, 1986; McMurtrie et al., 1994).
Acknowledgements We thank J. Ornellas and the staff of the Kauai Branch Station for assistance in field work, J. Brewbaker, R. Ogoshi, J. Ooka, and M. Willanison for
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