effects of windbreak strips of willow coppice—modelling and field experiment on barley in denmark

Agriculture, Ecosystems and Environment 93 (2002) 25–32

Effects of windbreak strips of willow coppice—modelling andfield experiment on barley in Denmark

Bente Foereida,∗, Rasmus Brob, Vagn Overgaard Mogensena, John R. Porteraa Department of Agricultural Sciences, Royal Veterinary and Agricultural University, Agrovej 10, DK-2630 Taastrup, Denmark

b Department of Dairy and Food Science, Royal Veterinary and Agricultural University, DK-1958 Frederiksberg, Denmark

Received 12 April 2001; accepted 15 January 2002

Abstract

A combined food and energy (CFE) producing system was designed to produce biomass using short rotation willow coppicein addition to food and fodder crops. Coppice was grown as strips at both ends of a 200 m long field. The effect of the windbreakon microclimate was measured at 11 points.

Results showed that microclimate was modified at a distance up to 4–7 times the windbreak height from the windbreak.Wind speed was more than halved close to the windbreak. Temperature and relative humidity were increased and radiationdecreased. Microclimate was modified also on the exposed side of the windbreak.

A multivariate regression model was made to predict microclimate behind the windbreak from standard agroclimatic data.The accuracy of the predictions obtained was limited by the measurement accuracy of the data.

Barley growth and development were recorded during the season, and the climatic data were used to run the model Siriusto simulate crop growth and development. Anthesis date and crop development were slightly earlier close to the coppice beltdue to elevated temperature. Growth and yield close to the windbreak were reduced. The model showed that the climaticvariables accounting for these effects were temperature and radiation, the effects of the windbreak being somewhat strongerwhen nitrogen is not limiting.© 2002 Elsevier Science B.V. All rights reserved.

Keywords: Windbreak; Microclimate; PLS-modelling; Willow coppice; Barley; Sirius model

1. Introduction

A combined food and energy (CFE) producing sys-tem was described by Kuemmel et al. (1998). The ideaof the CFE system is to grow short rotation coppice(primarily willows) in strips between crops to pro-duce an energy crop in addition to the food crop. Thecoppice is grown as shelterbelts between the crops.The trees act as a source of renewable energy and

∗ Corresponding author. Tel.:+45-35-28-3533;fax: +45-35-28-2175.E-mail address: [email protected] (B. Foereid).

regrow naturally after harvesting (coppicing) every4–5 years. However, an additional goal of the systemis to increase diversity in the agricultural system, andseveral aspects of the system have been studied in-cluding the effect of the willow strips on the spatialdiversity of insects (Langer, 2001). The present studyinvestigates the effects of the windbreak on the mi-croclimate and growth and development of the cropsgrowing between them.

The primary effect of a windbreak is to reduce windspeed. This, in turn, makes the boundary layer aroundthe crop thicker, so that a larger gradient in temper-ature and humidity can persist (McNaugthon, 1988).

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26 B. Foereid et al. / Agriculture, Ecosystems and Environment 93 (2002) 25–32

The physical and aerodynamic processes creatingthe microclimate modifications are reasonably wellunderstood (McNaugthon, 1988; Heisler and Dewalle,1988). In general, a high windbreak will protect a pro-portionally wider area than a short one (Jensen, 1955;Heisler and Dewalle, 1988; McNaugthon, 1988). Itis, therefore, convenient to describe the distance froma windbreak as a number of windbreak heights,h.McNaugthon (1988) divided the zone, leeward of awindbreak, into the quiet zone as a triangular areafrom the top of the windbreak to about 5–8h down-wind, with the wake zone further downwind. Whilefluxes of heat and matter (water vapour and CO2) inthe quiet zone are generally lower than in the open,the reverse can often be true for the wake zone. Thisis because of increased turbulence in the wake zone.The effect of windbreak architecture is not well un-derstood. Apparently the most effective windbreaksare as erect as possible (Heisler and Dewalle, 1988).While most windbreaks have been constructed tomaximise the microclimate modification effect, theprimary objectives in the CFE-system are energyproduction, landscape diversification and biodiversityenhancement. The windbreaks in the CFE-system are,thus, roughly semi-circular or ovoid in profile.

Many studies have considered the effects of wind-breaks on final crop yield (Baldwin, 1988; Kort, 1988),but predicting the effect is difficult. Several modelsexist to predict crop growth from climatic data (Porter,1984; Jamieson et al., 1998). To predict growth be-hind a windbreak requires a model that can predictclimatic modifications behind the windbreak also. Themodels described so far (Mayus, 1999; van Noordwijkand Lusiana, 1999) considered competition for water,radiation and nutrients, but not effects of temperature.

The purpose of the present study was to adapt ex-isting models to model the effects of the windbreakon both the microclimate and on the crop, and usethe models to increase the knowledge of the effect onshort rotation coppice willows as windbreak.

2. Materials and methods

The experiments were performed at Höjbakkegård,20 km west of Copenhagen (Latitude 55◦40′N, Longi-tude 12◦18′E; 28 m above sea level) during the 1999growing season, June being very wet, and July and

August were warm and relatively dry. Spring barleywas sown on April 24th, after a grass-clover crop. Thebarley was managed organically and organic manureequal to 60 kg N ha−1 was added. Willows were intheir fourth year of growth, about 5 m high, the densestrip being about 10 m wide at the base, with a roundedshape.

Wind speed, temperature and humidity in soil andair were measured at 11 points placed symmetricallyabout the middle of a 200 m long field of spring barleywith a willow coppice strip at each end. The micro-climatic parameters were recorded at crop height,except wind speed, which was recorded at 2 m. Soiltemperature was measured 10 cm below the soil sur-face. Radiation was only measured at the centre andat both ends, and calculated at other points (Goudri-aan and van Laar, 1994). Microclimate variables weremeasured every 10 min, hourly averages being stored.All sensors used were calibrated under standardconditions.

The following formula was used to estimate windspeed behind shelter from standard agroclimatic mea-surements of wind speed:

u = au0 + bu0(1 − sinϕ) + c (1)

whereϕ is the angle between incoming wind and thewindbreak,u the wind speed behind shelter,u0 thereference wind speed anda, b and c are regressioncoefficients. This formula can account for differentwind directions, but only as long as the pointu is onthe sheltered side of the windbreak. The data for windspeed and direction were from 4 days at the end of Junewith predominantly southwesterly wind. Regressionsbetween open wind speed (data from the agroclimaticstation (Jensen, 1996, 2000)) and wind speed behindthe shelter were made for each point on the leeside ofthe windbreak for every hour.

In order to make a model that would predict allmicroclimatic variables (including wind speed), amultivariate regression model (Martens and Næs,1989; Esbensen et al., 1994) was made for each ofthe spatial points between the windbreaks. The totaldata set from the whole season was divided into acalibration data-set (to make the model) and a test set(to test the model).

Plant growth was measured by sampling plantsevery 1–2 week at the same 11 points as the climatemeasurements were made. The aboveground part of

B. Foereid et al. / Agriculture, Ecosystems and Environment 93 (2002) 25–32 27

a 10 cm row was sampled, the plant material wasweighed for fresh weight, dried for 24 h at 80◦C, anddry weight was determined. Leaf area index was alsodetermined on the sampled plants using a LI-3100area meter. For two of the sampling sites, total nitro-gen content in the plant samples was determined bygrounding the dried plant material and then measuringnitrogen content in a mass spectrometer (Europa Sci-entific, 20–20) coupled to an ANCA-SL sample prepa-ration module (Europa Scientific, Crewe, UK). Date ofear emergence was determined for five plants at eachof the 11 points where climate data were available.

The Sirius model (Jamieson et al., 1998) was usedto analyse plant growth and development. As it wasdeveloped originally for wheat, it was parameterisedfor barley using the plant growth data from the mid-dle of the field. The other ten points were used to

Fig. 1. Averages of hourly measurements of wind speed from 1st May to 13th July 1999 at 2 m height as a function of distance from thewestern windbreak for different wind directions.

validate the model. The microclimatic measurementswere used to drive the model for each of the 11points.

3. Results

The windbreak markedly reduced wind speed asshown in Fig. 1. Wind speed close to the leeside ofthe windbreak was, on average, less than half that inthe middle of the field. There was also a fairly strongeffect of the windbreak on the exposed side. Airtemperature was slightly increased close to the wind-break. Temperatures were increased during the day,but during the night there was often a decrease closeto the windbreak. Soil temperature was also generallyincreased close to the windbreak. Vapour pressure was


higher close to the windbreak, an effect that did notdepend on wind direction in a consistent manner. Soilmoisture was lower close to the windbreak, at least onthe western side of the windbreak where topographydid not change a lot. Water content in the soil wasnever limiting for crop growth. The points closest tothe windbreak received about 10% less radiation thanthose in the centre, the eastern ones received slightlyless than the western ones.

Fig. 2. Comparison of measured and predicted values of wind speed and temperature (error bars are RMSE).

Wind speed in the experimental field was comparedto simultaneous wind speed as measured by the agro-climatological station over four days at the end ofJune under predominantly southwesterly winds. Theregressions using Eq. (1) gave good predictions faraway from the windbreak; relationships were weakerclose to the willows.

The multivariate model could reproduce variationover time. However, root mean square error (RMSE)


Fig. 3. Simulated and measured nitrogen uptake by the barley crop over time 5 and 65 m from the western windbreak (with S.E.,n = 3).

of the prediction was large compared to the actualdifference between points (Fig. 2). Similar results wereobserved for relative humidity and also for radiation.The model could reproduce the spatial pattern for all

Fig. 4. Simulated crop biomass at anthesis and at maturity with and without N-limitation as a function of distance from the westernwindbreak.

the microclimatic variables as the bias was of similarmagnitude for all the spatial points.

The crop growth curves at the edges of thefield differed significantly from those in the centre.


(P < 0.05). Ear emergence was 2–3 days earlier(P < 0.05) close to the eastern windbreak than in themiddle. The differences were, in general, rather smalland only significant close to the windbreak.

The Sirius model showed good agreement withobserved data. The model predicted too fast a growthin the beginning, then leaf area developed to reacha maximum somewhat higher than predicted, andsenescence occurred earlier than predicted. RMSEvalues also decreased late in the season.

Crop N at the beginning of the season was higherthan predicted (Fig. 3). Later in the season there wasgood correspondence between measured and observedN-contents. Both the observed and the modelled re-sults showed higher levels of N close to the windbreak(5 m). Simulations of N-content in the soil also in-dicated slightly higher values close to the windbreaklate in the season.

By successively exchanging each of the climate pa-rameters in the climate file for the point closest to thewindbreak (5 m) with those from the centre (100 m),it was found that a lower maximum temperature andhigher radiation both contributed to increased growth.Minimum temperature, relative humidity and windspeed all had little effect on growth.

The simulated curves of biomass at anthesis andbiomass at maturity had similar shapes (Fig. 4), indi-cating that the shelter had the same effect on growthearly and late in the season. Growth was alwaysslightly reduced close to the windbreak. Harvest indexclose to the windbreak also did not differ significantlyfrom that in the middle of the field. When the modelwas run without N-limitation (Fig. 4), the growthdepression close to the windbreak was somewhatlarger, and the harvest index slightly lower close tothe windbreak.

4. Discussion

Wind speed was reduced; the ratiou/u0 was foundto be 0.37 at the point closest to the windbreak. At35 m from the windbreaku/u0 reached 0.86 and didnot increase further. This seems to indicate that theequipment measured significantly lower values thanthe reference, in particular it had a higher 0-threshold.

The ratiou/u0 has been measured by several authorsto values between 0.4 and 1.0 (Mulheran and Bradley,

1977; Brenner et al., 1995a; Zhang et al., 1995). Thisrange is supported by the data presented here. Brenneret al. (1995a) also found that wind speed reduction wassomewhat smaller at high than at low wind speeds.Zhang et al. (1995) found thatu/u0 was extremelyvariable, but slowly decreased with wind speed to athreshold after whichu/u0 did not change with in-creasing wind speed. It was also found that wherewind reduction was significant,u/u0 was extremelyvariable. In the present study, no decrease inu/u0 withincreasingu0 was observed. Day temperature was in-creased by proximity to the windbreak, and night tem-perature decreased. The modification in microclimateextended to only about 20–35 m, or about 4–7 wind-break heights, as predicted by McNaugthon (1988).

Eq. (1) gave relatively poor predictions close to thewindbreak. This makes the use of this formula rela-tively limited, because wind speed far away from thewindbreak is anyway similar to the reference windspeed. Eq. (1) cannot be directly compared to themultivariate model because the regression data (r2 andRMSE) for the multivariate model are based on manydata from other weather conditions. However, the or-der of magnitude of these data indicates that the mul-tivariate model is at least as good as Eq. (1). There areother advantages of the multivariate model comparedto simple regression equation: it can be used directlyfor all wind directions, and predicts all microclimaticvariables. The measurements needed are generallyavailable from any agroclimatological station, butrecalibration is needed for each new windbreak.

The multivariate model predicted spatial variationaccurately, but with a bias. However, the error of pre-diction was as large or larger than the spatial variation.Interestingly, for each time-point, the error was aboutthe same for each spatial point. This indicated thatthe problem of the model might be errors in the in-dependent variables. When making the model, it wasassumed that only the dependent variables had mea-surement errors (Martens and Næs, 1989). However, inthis case the measurement errors were almost as largefor the dependent variable since both rely on sensors ofsimilar accuracy. The accuracy obtained here can prob-ably not be improved without more accurate sensors.

The Sirius model predicted growth reasonablyaccurately, but the timing and extent of leaf devel-opment may be a problem. However, final yield maybe more correctly predicted than the exact timing of


development. The tendency to better N-supply closeto the windbreak was probably caused by faster min-eralisation at the higher temperature observed closeto the windbreak.

Growth of barley was slightly decreased by proxim-ity to the windbreak, particularly on the side that wasshaded in the evening. This was probably because theincreased maximum temperature close to the wind-break increased development rate so that there was lesstime for photosynthesis (Grace, 1988). The model re-produced these observations. According to the model,the microclimatic variables that accounted for this ef-fect were mainly radiation and maximum temperature.However, only the effect of wind speed on evapotran-spiration was modelled. Any possible direct effects ofwind on particularly young plants were excluded. Asthe model also predicted a growth depression closeto the windbreak, this rules out the possibility thatthe observed growth depression is only an edge effect(Chaney et al., 1999; Sparkes et al., 1998). Baldwin(1988) noted that vegetative growth was positively af-fected by shelter. Brenner et al. (1995b) found thatfor millet, high temperature in the lee of a windbreakincreased vegetative growth, but shortened the periodfor grain filling so that harvest index was lower be-hind the shelter. The simulated curves for biomassat anthesis and biomass at maturity had rather simi-lar shapes, and harvest index did not change signifi-cantly. This indicated that under these conditions, theeffect of proximity to the windbreak was about thesame both early and late in the season. However, inthe simulations there was a tendency for the nega-tive effect of shelter on growth and harvest index tobe more pronounced when nitrogen was not limiting.This was probably because the better N-supply closeto the windbreak counteracted the growth-depressingeffect when N was limiting.

As the overall effect of the microclimatic changeswas rather small, consideration of the effect of mod-ified microclimate should not be of major concernwhen designing temperate agroforestry systems.

Acknowledgements

The authors wish to thank Anne-Lise Pedersenfor help with assembling equipment for microcli-mate measurements. This work formed part of an

EC supported research project: Evaluation of CFEsystems for more efficient land use and environmen-tally benign sustainable production (Contract number:FAIR-CT96-1449). The content of this paper doesnot represent the views of the Commission or itsservices and in no way anticipate the Commission’sfuture policy in this area. Support from the DanishAgricultural and Veterinary Research Council is alsoacknowledged. Dr. Peter Jamieson is acknowledgedfor commenting on the manuscript. Dr. Svend ErikJensen is acknowledged for supplying standard agro-climatic data and for commenting on this manuscript.

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effects of windbreak strips of willow coppice—modelling and field experiment on barley in denmark

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