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Effects of reduced pesticide use on flora and fauna in agricultural fields

5 Yield and economy

(Jensen, A.-M.M., Rasmussen, C., Rasmussen, S. & Esbjerg, P.)

This chapter is dealing with the yield and economy aspects of reduced pesticide use. Firstly, the relation between the weed vegetation and the yield is described for cereals (section 5.1). Secondly, the yield in sugar beets is described (section 5.2). Thirdly, weed problems and clean-up decisions after three years with use of reduced pesticide dosages (section 5.3) are reviewed. Finally, the profitability of use of reduced dosages is considered (section 5.4).

The main aim of the yield trials (sections 5.1 and 5.2) was to provide a measure for compensating the involved farmers for a possible yield reduction each year, not to measure an accumulated decrease in yields. The aim of the clean-up study (section 5.3) was to reveal weed problems arising after three years with reduced use of herbicides and insecticides seen from the agronomical point of view. However, three years are not enough to reveal long-term consequences for the growing practices.

5.1 Yield and vegetation in cereal fields

(Jensen, A.-M.M.)

5.1.1 Purpose

The aim of this study was to analyse the yield responses of spring barley and winter wheat to reduced use of herbicides and insecticides. The reductions performed were 50 % (half dosage), 75 % (quarter dosage) and in some years a 100 % (non-sprayed) reduction of the normal dosage used in each field and crop. Weed plants compete with crop plants for water, nutrients and light in particularity. Therefore, it is expected that a high density of weeds at reduced dosages is correlated to a decrease in yield. In this study the weed vegetation measured as weed density and species richness was related to the yield and yield quality at reduced pesticide use. A higher density of insects at reduced dosages might also affect the yield, but the occurrence of insects was not measured in this study, so yield changes could not be correlated to the presence of insects, unfortunately.

5.1.2 Methods

5.1.2.1 Field design

Thirty field trials were performed, one in each field of spring barley and winter wheat in each of the three study years in the main study. One field trial in winter wheat was omitted because no differentiation in application of herbicide dosage was made. Each field trial (size: 10m x 40m) was situated in a corner of the field within the plot sprayed with normal dosage at least 30 meters from other plots, hedges, habitat islands etc. and surrounded by a 2.5 m wide buffer zone.

All field trial areas were treated exactly as the surrounding field - sown the same day, sprayed with same dosages and products on the same day etc. (Appendices A.2-A.4). Each field trial consisted of four blocks (replicates) and each block consisted of 3 plots in 1997 and 4 plots in 1998 and 1999. Each plot measured at least 10 m x 2.5 m but they were sometimes longer. The plots within a block were sprayed with different dosages of herbicides and insecticides (Fig. 5.1). The dosages were 1/1: Sprayed with normal dosage of herbicides and insecticides, 1/2: Sprayed with half dosage, 1/4: Sprayed with quarter dosage, 0: Not sprayed. Non-sprayed plots were not included in 1997.

Fig. 5.1.
Design of one field trial. In 1998 and 1999 each field trial contained 16 plots. In 1997, the design consisted of 12 plots, because non-sprayed plots were not present. I to IV are the blocks, 0, 1/1, 1/2 and 1/4 the dosages. The squares in the middle of the plots illustrate the weed investigation areas.

Products and dosages chosen by the farmer as normal dosage were very different from field trial to field trial and not equal recommended dosages (chapter 1 and Appendices A.2-A.4). The farmers chose products and dosages after their experiences and individual needs. The location of a field trial within a field was not totally fixed, so the same plot did not necessarily receive the same level of herbicides and insecticides throughout the three years. Therefore, cumulative effects of reduced dosages could not be expected.

5.1.2.2 Weed observations

In each plot, the weed flora was registered in an area of 0.6 m x 0.4 m (Fig. 5.1). All plants were identified as described in section 2.2.1.6 and counted, giving number of plants per square meter (density) and number of species per 0.24 square meter (species richness). The areas were fixed within a season and were visited in spring (early May) and in summer (late July) (before and after spring sprayings). Care was taken to avoid damaging the weed and crop plants under the investigations.

5.1.2.3 Yield and yield quality measurements

Each plot in each field trial was harvested separately and the yields were measured by the local advisory services. Yield was adjusted to 15 % moisture content and given as tons per hectare. Moreover, the following yield components and quality parameters were measured by the local advisory services: thousand kernel weight, moisture content, content of protein, content of starch, pureness and sorting. Samples from plots sprayed with same dosage within a field trial were pooled before measuring the quality parameters.

5.1.2.4 Treatment intensity index and efficiency

In order to compare dosages of different pesticides, two treatment intensity indexes were calculated: an index for herbicides alone and an accumulated index for herbicides and insecticides together. Herbicides applied to control broad-leaved species were included in the treatment intensity index for herbicides, so products mainly applied to control Elymus repens and Avena fatua were not included. Treatment intensity indexes were calculated for normal dosage in each field trial (Table 1.1) according to Danmarks Jordbrugsforskning & Landbrugets Rådgivningscenter (1997, 1998 and 1999).

Efficiency of a treatment is in this chapter defined as the herbicide treatment's ability to reduce the weed density and is calculated as (n₀-n₁)/n₀, where n₀ is the total density of weed plants in spring (before spring spraying) and n₁ is the total weed density 2-3 months after spring spraying.

5.1.2.5 Statistical tests

The following response variables were tested for dosage effects, separately: weed density, species richness, efficiency, yield and the yield quality parameters. Data from spring barley and winter wheat were tested separately, because the crop has a profound effect on weed density and species richness (see sections 2.2.2.1 and 2.2.2.2). The basic experimental unit in the analyses of these variables was the plot (n=220 for spring barley and n=208 for winter wheat).

Before running the analyses, weed density was transformed with the natural logarithm (log_e (y+1)) to achieve a normal distribution and homogeneity of variances. Similarly, the species richness, efficiency, yield and quality parameters were square root, exponential or arc sinus transformed to approach a normal distribution, if necessary.

The statistical test used was analysis of variance with farm, year, dosage and interactions between these as explanatory factors in addition to the block within a field trial. Moreover, in the analysis of weed density after spraying, the weed density before spring spraying was used as a covariate. Similarly, the species richness before spring spraying and the weed density after spraying were used as covariates in the analyses of species richness after spraying. In the analysis of yield, weed density, species richness and efficiency were used as covariates. In addition, the six yield quality parameters were tested for effects of pesticide dosage using mean weed density after spraying, mean species richness after spraying and mean yield per dosage per field trial as covariates and farm, year, dosage and first order interactions between those as explanatory factors. At last, the yield in each field trial was analysed separately. In these analyses the explanatory factors were: dosage, block, weed density after spraying and species richness after spraying.

The number of explanatory factors was reduced during full-scale model calculations using an iterative procedure to remove the variables with p > 0.10 until the model consisted only of variables with p £ 0.10.

Each analyse was run three times; first with the interaction between farm and year and afterwards with the two treatment intensity indexes replacing the farm´ year interaction in the reduced model. This was done to clarify if the variations between field trials could be explained by variations in the treatment intensity indexes.

All analyses were performed using the general linear model (GLM) procedure in SAS (SAS Institute 1999). If a significant effect of dosage was revealed, the differences among dosages were tested by a Tukey-Kramer test for a-posteriori comparisons of least-squares means. Because non-sprayed plots were not present in 1997, the design was unbalanced and thus required modifications in the F-tests by using the Random/Test statement in the GLM procedure.

The proportion of variation explained by a certain factor was calculated as the sum of squares for that particular factor divided with the total sum of squares.

5.1.3 Results

5.1.3.1 Dosage effects on overall weed density, species richness, efficiency and yield

Table 5.1.
Results of tests of effects of reduced dosages on the weed density, species richness, efficiency and yield in spring barley and winter wheat. Grey areas indicate factors not included in the full model. Statistical significance is indicated as follows: +: 0.05£ p<0.10, *: 0.01£ p<0.05, **: 0.001£ p<0.01 and ***: p<0.001.

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Weed density was strongly affected by dosage, where a decrease in dosage resulted in an increase in density of weed plants in both spring barley and winter wheat (Table 5.1 and Fig. 5.2A). The estimated mean weed density in non-sprayed spring barley plots was 177 plants/m², which was 33 % higher than in plots sprayed with quarter dosage (p=0.0001). In winter wheat, the estimated mean weed density in non-sprayed plots was 96 plants/m², which was significantly higher than in plots sprayed with quarter dosage (p=0.020).

In both crops, species richness was influenced by dosage, but the effect varied between farms (Table 5.1 and Fig. 5.2B). The species richness was highest in non-sprayed plots; 6.2 species per 0.24 m² in spring barley and 3.3 species per 0.24 m² in winter wheat.

As expected, the efficiency of the treatments was highly affected by dosage (Table 5.1 and Fig. 5.2C). In spring barley the efficiency was 25 % at quarter dosage, which was significantly lower than the 35 % at half dosage and the 40 % at normal dosage (p=0.043 and p=0.0003, respectively). No significant differences were found between normal and half dosages in spring barley (p=0.46). In winter wheat normal dosage was almost significantly more effective in weed control (46 %) than quarter dosage (28 %) (p=0.053), no significant differences in efficiencies were found between normal and half dosage (31 %) (p=0.16).

Fig. 5.2.
Weed density, species richness, efficiency and yield of spring barley and winter wheat at normal and reduced dosages of pesticides. Each bar represents a mean of 40-60 values. Error bars indicate the 95 % confidence limits.

As usual in Denmark, the yield per hectare was much higher in winter wheat than in spring barley (Fig. 5.2D). There was a significant effect of dosage on yield of spring barley (Table 5.1). Non-sprayed spring barley plots had on average 8 % lower yields compared to sprayed plots (p<0.0001 in all pairwise comparisons). The mean yield at quarter dosage was significantly lower than at half dosage (p=0.043) and normal dosage (p=0.015). No differences in yields were found between plots sprayed with normal and half dosage (p=0.92). The yield in winter wheat was significantly affected by the dosage, but the effect varied between years and farms (Table 5.1). Yields in non-sprayed plots were on average 7 % lower than in plots sprayed with normal dosage (p=0.0002), whereas yield did not vary significantly between normal, half and quarter dosage (p>0.31 in all pairwise comparisons).

Table 5.2.
Percentage increases (+) and decreases (-) in weed density, species richness, efficiency and yield at reduced or zero dosages compared to mean values at normal dosage. Significant difference from normal dosage is indicated as follows: +: 0.05£ p<0.10, *: 0.01£ p<0.05, **: 0.001£ p<0.01 and ***: p<0.001.

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The effects of reduced dosage on weed density, species richness, efficiency and yield are summarised in Table 5.2.

All response variables showed a highly significant effect of the interaction between farm and year (Table 5.1), which corresponds to the variation between individual field trials (included among other things variations in location of the field trial and the treatment intensity index). This interaction explained most of the total variation in most response variables. Furthermore, the dosage effect varied considerably between field trials (Table 5.1).

When the treatment intensity index for herbicides replaced the interaction farm´ year in the reduced models in spring barley, the models were not improved (they showed a higher p-value). Despite this, the treatment intensity index for herbicides had a significant negative effect on weed density and species richness and a positive effect on the efficiency. The yield in spring barley was not significantly affected by the treatment intensity index. In winter wheat models the p-values decreased, when the treatment intensity index for herbicides replaced the farm´ year interaction. Thus, the differences in treatment intensity index for herbicides could explain the variations between field trials. The treatment intensity index for herbicides had a significant negative effect on weed density, species richness and yield and a positive effect on the efficiency. In the case of winter wheat, the result thereby indicates that the higher the treatment intensity index for herbicides the lower the yield at harvest, which is in contrast to the expected results. The yields at normal dosage in both spring barley and winter wheat are illustrated in Fig. 5.3 as a function of the treatment intensity index for herbicides. The figure indicates that no meaningful relationship exists between yield and treatment intensity index. For both crops, all models showed a higher p-value if the accumulated treatment intensity index for herbicides and insecticides replaced the farm´ year interaction.

Fig. 5.3.
Relationship between treatment intensity index for herbicides and mean yield at normal dosage. Each dot represents data from one field trial.

5.1.3.3 Yield quality parameters

Of the six yield quality parameters only moisture content in spring barley grains was significantly affected by dosage (p=0.042): The moisture content was significantly lower at quarter dosage, than at half and normal dosages (Tukey-Kramer tests, p=0.0006 and p=0.003, respectively), and no significant differences in moisture content were found between non-sprayed and sprayed plots (p=0.98, p=0.10 and p=0.20 for pairwise comparisons with quarter, half and normal dosage, respectively). No significant effect of dosage was found in any of the other five quality parameters in neither spring barley nor winter wheat.

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Fig. 5.4.
Yield changes at reduced dosages (0.5, 0.25 and 0) in percent compared to normal dosage (1) shown for all field trials. 0 on the y-axes corresponds to yield at normal dosage.

The total weed densities before and after spring spraying and the dominant weed species varied considerably from field trial to field trial (Appendix E). Yield changes at reduced dosages of pesticides compared to yield at normal dosages are shown in Fig. 5.4 for all field trials in winter wheat and spring barley.

When each field trial was analysed separately, yield was significantly affected by the dosage in only 8 of 29 field trials (Appendix E.2). In six cases, the yield was significantly lower in non-sprayed plots than in sprayed plots. In three field trials, the yield at quarter dosage was significantly lower than at normal dosage. No field trial showed a significantly lower yield at half dosage compared to normal dosage. The simple model explained at least 75 % of the variation in yield in 86 % of the field trials (Appendix E.2).

5.1.4 Discussion

5.1.4.1 Dosage effects on yield

These field trials cover a wide range of weed species and densities (Appendices E.1A and B) and in the majority of cases a yield decrease (Fig. 5.4) at reduced dosages was found. However, the decreases were often small and only statistically significant in 28 % of the field trials. These results are in accordance with Davies et al. (1989) and Salonen (1993b), who found it difficult to show yield response to reduced broad-leaved weed control in winter wheat and spring barley in Scotland and spring barley in Finland, respectively. Also Pallutt (1999) showed that application of quarter of recommended herbicide dosage was enough to prevent yield losses in strong competitive cereal stands in Germany.

It was generally not possible to show significant differences in the yield between plots sprayed with normal, half or quarter dosages, whereas the yield at unsprayed plots decreased with 8 % in spring barley and 7 % in winter wheat. Davies et al. (1989) showed that 1/8 of recommended dosage in some cases gave a yield reduction although it was not significant when a mean of five experiments was considered (Davies & Whiting 1990). In some experiments on clay soil Salonen (1992b) reported a higher yield at reduced herbicide dosage than at recommended dosage. This is also found at both half and quarter dosage in some field trials in this study (Fig. 5.4). Jensen (1986) suggested that recommended dosages of some herbicides could harm the crop, however other herbicides are applied today than in the early eighties, so this might not be the case today, although also modern herbicides in some field trials result in a higher yield at reduced dosages than at recommended dosages (Landbrugets Rådgivningscenter 1999b). Yield decrease in response to no chemical control is lower on clay soils than on sandy and organic soils (Jensen 1985). This could be one of the reasons why only small decreases in yield are found in these field trials on clay soils. From this study, it is clear that dosage can be halved without notable yield decreases within one season.

The yield decrease recorded in non-sprayed plots of spring barley (8 %) and winter wheat (7 %) was almost the same size although winter wheat has a higher competitiveness than spring barley (Rasmussen et al. 1997). Therefore, it was expected that winter wheat would have shown a smaller decrease in yield at reduced dosages. On the other hand experiments performed in winter wheat have shown a yield decrease at 12 % (Davies et al. 1989) or 15 % (Wilson 1986) whereas experiments in spring barley have shown a decrease of 0 %-7 % (Courtney & Johnston 1986, Davies et al. 1989, Salonen 1992b, Salonen 1993a). Therefore, no consistent relation between crop competitiveness and yield response seems to exist. In addition, the competitiveness of crop cultivars is very variable (Valenti & Wicks 1992, Grundy et al. 1993) and confuses the picture even more.

Yield responses to reduced dosages varied from farm to farm and from year to year (Table 5.1 and Fig. 5.4), indicating that there may be differences in the effectiveness of weed or insect control between farms and between years within a farm.

From this study, it must be concluded that no meaningful relationship exists between treatment intensity index and the yield (Fig. 5.3).

5.1.4.2 Weed density and yield

Large yield reductions might be associated with high densities of weeds. However, these field trials showed no significant effect of weed density after spraying on the yields of spring barley and winter wheat.

In the separate analyses, only 14 % of the field trials showed a significant effect of weed density and richness on yield (Appendix E.2), half showing a negative relationship and half a positive relationship. These field trials (showing yield decrease above 4.5 %) were not the ones with the highest weed densities after spraying (Appendix E). One field trial (spring barley at Oremandsgård 1997) had a mean density over all treatments of less than 10 weed plants after spraying, and still showed a significant yield decrease at reduced dosages. In that field trial, the yield reduction might reflect a higher level of herbivorous insects at reduced dosages, although the occurrence of aphids was rather low in the surrounding field (Appendix D).

Many studies, like this, have made it clear that there is a poor correlation between total weed density and yield (Jensen 1991, Salonen 1992b), weed biomass and yield (Salonen 1993a) and weed cover and yield (Fischer et al. 1993). This might be the reason why it has been difficult to show yield response to reduced broad-leaved weed control in winter wheat and spring barley (Davies et al. 1989, Salonen 1993a).

Not all weed species are strong competitors with cereals. Some species have a higher competitive ability than others, measured as the ability to suppress the crop biomass (Wilson 1986, Wilson & Wright 1990, Jensen 1991, Jensen 1996). As suggested by Wilson (1986), yield responses could be influenced more by weed species than by weed densities. Today’s weed control strategy is therefore based on both species and their density (Rasmussen et al. 1997).

In spring barley but not in winter wheat, weed biomass was better correlated to yield loss than the weed density (Jensen 1996). Therefore, a possible difference in responses of density and biomass might not alone explain the reason why no clear correlation between yield and weed density was found in this study (Table 5.1). It can be seen from Appendices E.1A and B that barley field trials with high densities of Brassica napus/Sinapis arvensis, Polygonum aviculare and Trifolium sp. had a large decrease in yield at low dosages. Especially Sinapis arvensis is known as a strong competitor (Scragg 1980). No such species, accounting for major decreases in yield, can easily be found in winter wheat. Among the weed species found in this study, Galium aparine is the most competitive (Wilson & Wright 1987) but the highest yield decreases did not coincide with the presence of Galium aparine. In conclusion, it must be said that in field trials with high densities of weed species with a high competitiveness reduced dosages might have the greatest potential for affecting the yield negatively. In none of these field trials populations of strong competitive grasses as Apera spica-venti, Avena fatua, Bromus sp. or Elymus repens were observed. These species might even in low densities be able to reduce the yield.

In both spring barley and winter wheat, significantly higher weed densities were found not only in non-sprayed plots but also in plots sprayed with quarter dosage than in plots sprayed with norma1 dosage (Fig. 5.2A). Thus, strongly reduced herbicide dosages did not keep the weed densities at the same level as the normal dosages did as reported from Finland (Salonen 1993a).

After spraying with reduced dosages the surviving weed plants might be weakened and are therefore not able to compete with the crop. This might explain that the yield did not decrease remarkably even when the weed density increased highly at reduced dosage of pesticides.

5.1.4.3 Dosage effects on efficiency

In many short-term experiments with cereals, reduced herbicide dosages have provided adequate control of broad-leaved weeds (e.g. Davies et al. 1989, Davies et al. 1993, Salonen 1993a) without notable yield decreases. The efficiency was as expected increasing with increasing dosage. At normal dosage, the efficiency was on average 49 % in winter wheat and 41 % in spring barley. This is a low efficiency compared to efficiency of recommended dosages, which reach 70 % in 78-91 % of the field trials performed by Salonen (1993a). The yearly variation in herbicide efficiency may be very large. One year Derksen et al. (1995) found a 90 % reduction in weed number, next year the reduction was only 39 % despite the field, the product and the dosage being equal.

The biomass reduction is even higher than the density reduction mentioned here (Salonen 1993a). This means that weed plants have a lower average biomass in sprayed plots than in unsprayed plots. Furthermore, figure 2.12 indicates that the average biomass per plant was higher at reduced dosages than at normal dosages because a plant weighs more in the generative than in the vegetative phase. The long time (2-3 months) between spring sprayings and registration of the weed density after spraying may have influenced the efficiency both negatively and positively. If new plants have germinated within that period, it would be reflected in a lower efficiency, whereas competition through most of the growing season from the cereals might have resulted in dead weed plants reflected in a higher efficiency. Not many seedlings were observed in cereals in July, so the latter might be more likely than the first.

Many other factors might affect the efficiency of the herbicides (e.g. weed composition, the size of the weed, technique used for spraying, the climate around the time of spraying, the competitiveness of the crop (Kudsk & Mathiassen 1991) and water stress (De Ruiter & Meinen 1998)).

5.1.4.4 Dosage effects on yield quality parameters

Statistically significant differences in yield parameters between dosages were only detected in one case. It must be concluded that dosage has little, if any, effect on yield parameters as content of moisture, starch, protein, thousand kernel weight, pureness and sorting. However, Davies and Whiting (1990) have shown that the higher the cover of Stellaria media, the higher the moisture content in the grains at harvest. The effects of weeds on yield quality are proportionately much smaller and can not occur independent of the effects on yield (Whiting et al. 1991), so it might not be very important to focus on yield quality. Other factors varying between farms and years had a much greater influence on the yield quality parameters than dosage.

5.2 Yield in sugar beets

(Esbjerg, P.)

In contrast to the preceding section concerning yields in cereals which also comprise botanical elements, which are a trade off of having mini-plots, this section solely comprises establishment of a background for the landowners yield situations. This is in essence the basis for the payment in a few cases of compensation for losses causes by the lowered dosages.

After the problems with harvesting within mini-plots of sugar beet at Gjorslev estate in the pilot phase (cf. section 1.2.9) the work on yield estimates was changed to a sampling procedure following principles for sampling aiming at estimating effects of variety, fertilization etc. The procedure was selected on the basis of recommendation from "The Foundation for Sugar Beet Research". In the present case the aim was to reveal if the effect of reduced dosages was reflected in the yield levels.

5.2.1 Sampling

In each of the three dosage plots per farm a total of 20 random selected samples were dug up manually.

Each sample consisted of 4 metres of the row at a particular position determined by the random selection procedure. The beet tops were removed in the field by standardized cutting in accordance with instructions from "The Foundation for Sugar Beet Research". This research body also took care of washing, weighing and labelling of samples for subsequent analysis of sugar content. The last part was carried out at the sugar factory in Maribo. The sugar content was only determined as safety measure but it proved to be much less meaningful than the weight due to the in-field type of variation. In addition the prices were estimated according to the type of contract with the sugar factory and the amount and quality of the harvest of the whole field. Therefore the estimated weight yields formed the best background for evaluating whether or not the landowners had losses to be compensated.

5.2.2 Yields estimated

The results are presented in Table 5.3. It appears that significant yield losses are very few and with one exception only occur at quarter dosage. In summary in 1997 Nordfeld lost 12 % of the yields at half and 14 % at quarter dosage but part of this loss may have been caused by troubles with the new equipment for mechanical hoeing under slippery conditions at sloping terrain. (During the two next seasons this problem was counteracted by computerised steering). In 1998 Lekkende lost 25 % at quarter dosage and in 1999 no significant losses were found, except in quarter dosage at Nøbøllegård where spots of weeds, mainly common couch Elymus repens, were known as problematic at that particular area. However, it would have been disturbing for the project to permit the solving of the problem by use of full dosage of Glyphosate in stubble before growing beets.

Table 5.3.
Yields estimated in sugar beets. It is important to notice that during the pilot phase at Gjorslev 1996 the dosage plots were all treated with the particular dosage applied as broad swath. In addition the yields at different dosages were estimated by producing mini-plots: During the subsequent years the dosage reductions were obtained by treating only bands over the rows and for yield estimations random samples were used. Every yield marked * is significantly lower than the corresponding yield of the normal dosage plot shown in the same line (the same farm and the same year).

5.3 Clean-up decisions

(Jensen, A.-M.M.)

5.3.1 Purpose

In this study, effects on the weed vegetation by use of reduced dosages of herbicides and insecticides during three years were emphasised.

The objective was threefold: 1) To spot major weed problems after three years with reduced pesticide use. 2) To estimate economic compensations, so the farmers could bring the areas sprayed with reduced dosages in the same state as areas sprayed with normal dosage with regard to weed populations. 3) To estimate compensations for future yield decrease as a result of accumulated weed populations.

5.3.2 Method

In July 1999, observations during field walks were made by an agricultural adviser from the local advisory service, a botanical investigator and the farmer in each of the three fields used in the main study on each of the five farms. Each of the 15 fields was observed for about an hour. Weed species with a higher density or abundance in plots sprayed with reduced dosages compared to plots sprayed with normal dosage were spotted and the area in which they were present was estimated. Most species occurred in spots within the estimated area of the plot. The possibilities for reduction of these populations as well as a price estimated for the future control strategy were discussed. In addition, economic compensations for presumable yield decrease in 1999 and 2000 were estimated.

5.3.3 Results

Different weed species were observed in the different fields (Table 5.4). In total, 19 weed species increased in densities in plots sprayed with reduced dosages, 12 of these species were spotted in more than one of the 15 fields. Of these species, eleven were broad-leaved and one was a grass: quackgrass (Elymus repens). The perennial Cirsium arvense was the species observed in most fields, although it was present in small areas compared to annual species as Galium aparine and Sinapis arvensis.

No clear differences in species with increased density and the area they covered were observed between half dosage and quarter dosage.

Table 5.4.
Weed species with increased abundance or density within plots sprayed with reduced dosages. The estimated area of the 6 ha-plot(s), where the species was present, is given in percentage. Prices estimated for cleaning the fields from these weed species are given in Table 5.8.

Elymus repens was the only species that caused heavy yield decreases after three years with reduced dosages (Table 5.5).

Table 5.5.
Estimated yield decrease in 1999 and 2000.

5.3.4 Discussion

Many weed species appeared in increased densities, but only the high density of Elymus repens caused heavy yield reductions in some areas. Therefore, in this study, reduced dosages of glyphosate (compound used to control Elymus repens) have economic consequences already after few years. Most broad-leaved weed species increased in densities without causing remarkable yield decrease after three years with reduced use of pesticides. The reason why broad-leaved species did not cause major yield reductions might be that the weed infestation at the beginning of the main study was very low, which are also found in other experiments running more than two years (Erviö et al. 1991). Thus, the accumulation of the broad-leaved weed population during three years has probably not yet reached a level, where it reduces the yield remarkably. Further increased densities of the broad-leaved species mentioned in Table 5.4 may result in yield decreases at reduced dosages over a period longer than three years.

Three other studies controlling broad-leaved weed species with reduced dosages of herbicides during some years have shown that: 1) Recommended dosage applied one year out of three was as effective in controlling broad-leaved species as half dosage in three years (Skorda et al. 1995). 2) Half of recommended dosage each year or recommended dosage two of three years maintain the weed density at a stable level (Jensen 1991). 3) No difference in the broad-leaved weed density or the yield was found between the following three treatments with reduced pesticide application over three years in three places: spraying in year three, spraying in years two and three or spraying in all three years (Courtney & Johnston 1986). Thus in regard to the yield and the control of the weed species, use of reduced dosages of herbicides might be performed as reduced dosages every year as well as no spraying one year followed by spraying with normal dosage the next year. However, this might not be the case, where weed plants with high competitiveness are present in high densities, then half dosage might be preferred each year to keep the yield decrease low over the years (Landbrugets Rådgivningscenter 2000b). No experiments have studied the effects on the weed and animal diversity of the latter senario, which is very important before an evaluation of the different strategies can be made.

The yield decrease at reduced dosages is in a short term of minor economic and quantitative importance whereas the demand for a harvest without problems and the long-term aspects are very important. Especially, a build-up of seed reserves in the soil is a strong concern to farmers. No significant differences between pesticide dosages were found in the seed rain after three years (section 2.3) or in the germinating weed density after two years (Fig. 2.8). Also Salonen (1992a) could not detect statistically increases in the number of weed seeds in the soil seed bank after continuous use of on third of recommended herbicide dosages for three years. This indicates that dosage differences in the soil seed bank and the seed rain are small in comparison with the differences caused by farms, crops, land-use history, the great weed community variations within fields etc. However this qualitative clean-up study seems to indicate that an increased density of weeds may cause more seeds in the seed bank. Three years study is not enough to detect severe consequences of use of reduced dosages from the agronomical point of view - more years are needed. The extent of changes in weed population dynamics as a result of low pesticide dosages usually shows only after three to ten years, and can therefore be safely determined only in long-term trials (Pallutt 1999). Few long-term trials with reduced herbicide dosages have been performed yet (Jones et al. 1997, Pallutt 1999) both showing increased weed densities at reduced dosages either as weed seeds in the topsoil (Jones et al. 1997) or as infestations of weed species with strong competitiveness (Pallutt 1999).

The results are not based on a scientific documentation of increase in density but reflect species that mainly were spotted due to their height or the farmers' worries. These species are, anyway, weed species with a high competitiveness and therefore species that may cause economic problems over a longer period with reduced dosages of herbicides. Because this study was mainly qualitative, it could not detect the quantitative differences in weed density between half and quarter dosages as found in the main study (chapter 2).

It is a problem that the field walks did not take place during the late summers of 1996, 1997 and 1998. It is thus not possible to conclude whether or not the weed densities have accumulated over the three years. The differences in weed vegetation between normal dosage and reduced dosages might have been noticeable after one year only, as the main study indicates (Fig. 2.8), even though the total weed density has increased in all dosages during the three years.

5.4 Profitability analysis

(Rasmussen, C. & Rasmussen, S.)

5.4.1 Purpose

This section presents and discusses the results of the profitability analysis of reducing dosages of herbicides and insecticides. The aim of the study was to estimate the profitability consequences in crop production when dosages of herbicides and insecticides are reduced. The objective was: 1) to estimate the impact on short-term profitability and 2) to give an example of long-term profitability effects of a dosage reduction.

5.4.2 Method

A spreadsheet budgeting model was developed for the three crops: winter wheat, spring barley and sugar beet, calculating profit for each of the three crops in three different pesticide scenarios. It is assumed that farmers are interested in maximizing net returns or profitability per hectare. Profit is the total value of the product less the total factor cost, given fixed product and factor prices. Profit is calculated by aggregating the net returns for each season, and one season is defined as one year.

Total value of the product includes for wheat and barley both grain and straw value, but for sugar beet the total value includes only beet value, which depends on the sugar content (%). It is assumed that reduced pesticide dosages do not affect the straw production. Sugar beet prices depend on sugar content meaning that a varying content of sugar may contribute to differences in the profits calculated in the three scenarios (see section 5.4.3 for results).

Total factor costs are divided into two separate measures categorised as costs I and costs II. The costs I category includes costs of seeds, NPK fertilisers, additives and all pesticides. The costs II category includes the costs of labour and machinery, both of which are calculated using machine pool standard prices. All product and factor prices are standard prices stated by Landbrugets Rådgivningscenter (1998, 1999a and 2000a) and Danmarks Jordbrugsforskning & Landbrugets Rådgivningscenter (1998, 1999 and 2000). Developments in product and factor prices are important causes of differences in profit from one year to another. Price developments are stated in the literature above.

The model accounts for the following input factors: NPK fertilisers, herbicides, insecticides, fungicides, additives and growth regulating additives. Theoretically the output produced varies with the dosage of these input factors. Please note that only the dosages of herbicides and insecticides vary between the three scenarios. Furthermore it is important to note that the other input factors are not necessarily added in the same dosages on each farm. Apart from the variation in input factors, the treatments of the crops also varies between the five farms. Because of the variation in input factors, dosages and treatments the reference scenarios (labelled scenario A) are not identical for the five farms. Even though the reference scenarios are not identical, it seems probable that the change in profit is related to the reduction in the dosages of herbicides and insecticides. All other input factors are kept constant on each farm with the exception of sugar beet production where mechanical weed control also varies between the scenarios.

5.4.3 Results

Three scenarios differentiated by the dosage of insecticides and herbicides are considered in the model. Scenario A corresponds to normal dosage. Scenario A is not necessarily the optimal dosage that maximizes profit but serves as a reference scenario.

Compared to the dosage used in the reference scenario (A), scenario ½ is characterised by a 50 % and scenario ¼ by a 75 % percent reduction in the dosage of herbicides and insecticides.

Results of the economic analysis are presented in Table 5.6. In scenario A, the average profit for the five farms is calculated for each of the crops winter wheat, spring barley and sugar beet. Note that results for scenario ½ and ¼ are shown as both the absolute and the relative change in profit compared to the reference scenario.

More detailed results are presented in Table 5.7 showing the figures from Table 5.6 broken into product value, costs I and costs II. Detailed results for each farm are presented in Appendices F.1-F.5.

Table 5.6.
Calculated profit in current prices (DKK per Hectare) and changes in relation to A at scenarios ½ and ¼.

Table 5.7.
Change in product value, costs I, costs II and profit with a ½ and ¼ dosage of insecticides and herbicides in the period 1997-1999. Results are presented in DKK per hectare in current prices.

For winter wheat table 5.6 shows a marginal positive change in the calculated profit in both scenario ½ and ¼. From table 5.7 it appears that the reduction in costs I due to reduced dosage of herbicides and insecticides is greater than the loss in product value causing profits to increase.

Table 5.6 also shows a marginal positive change in the calculated profit for spring barley in both scenario ½ and ¼. However, an exception appears in the scenario ¼ 98/99 where the change in profit is negative due to a decreased product value caused by a decreased yield (see Table 5.2 for estimated yields).

It is difficult to derive a clear trend in the change of sugar beet profit from the tables. As explained earlier there are several factors contributing to the change in profit for sugar beets. First of all the sugar content significantly affects beet prices and secondly additional mechanical weed control is required in scenario ½ and ¼ thus increasing costs (costs II). The varying sugar content in the three scenarios results in varying prices which seems to be the main reason for the absence of a clear trend.

In general it appears from the above results that a 50% or a 75% reduction of the herbicide- and insecticide dosages has a very limited effect on the profitability at farm level primarily because the reduced costs of pesticides compensate for the decrease in product value (if any occurs). It is, however, uncertain whether this result can be maintained on a long-term basis. This question is considered in section 5.4.4 along with the questions of increased production risk, long-term weed accumulation (see section 5.3 for discussion) and possible adjustment capacity costs. These adverse effects of a reduction in pesticide dosages have not been taken into account in the present section.

5.4.4 Discussion

After the 1999 production season the clean-up costs were estimated (see section 5.3). Clean-up costs refer to the costs of returning the given plot of land to the pre-experiment state. Thus, these costs provide no indication of the development in profit the following years if production is continued using reduced pesticide dosage. However, it is probable that a long-term reduction in pesticide dosages will lead to an accumulation of weed seeds on the given plot of land. Given limitations in chemical weed- and insect-control, variation in production yield is likely to increase thereby increasing the production risk. Furthermore it may be necessary to adjust the capacity in terms of new weed control machinery or perhaps adjust the treatment of the crops to the new conditions. Consequently, adjustment costs would arise.

Even though the clean-up costs do not correspond perfectly with the costs arising from increased production risk and adjustment costs, we can interpret the clean-up costs as an example of the present value of these unpredictable long-term costs. The clean-up costs are estimated after three seasons of experimental production using reduced dosages of pesticide. It cannot be excluded that clean-up costs will increase in the future if production with a reduced pesticide dosage is continued. As an example, the clean-up costs after three years are shown in Table 5.8. The clean-up costs are stated for the land farmed with a seventy-five-percentage reduction in pesticide dosages.

Using a real interest rate of four percent the average cost per hectare per year in an infinite time horizon is also calculated in Table 5.8. This example shows that if long-term effects are taken into consideration they would probably account for an average extra cost between 50 and 78 DKK per hectare per year. Taking the average long-term costs per year per hectare into account when calculating the short-term profit it appears that the positive effect in the ½ and ¼ scenarios is markedly reduced.

Table 5.8
Clean-up costs interpreted as long run effects of a reduction in pesticide uses (DKK per hectare).

In an overall assessment of the profitability consequences of reduced pesticide dosages this example is meant to illustrate that long-term effects could influence the final result significantly. Furthermore the example illustrates that the results presented in Tables 5.6 and 5.7 should not be considered as final results and therefore should not be used as basis for long-term conclusions.

5.4.5 Conclusion

The economic analysis has shown that a reduction in pesticide dosages does not have any critical short-term effect on the profit which farmers can obtain growing winter wheat, spring barley and sugar beet, nor does a reduction in pesticide dosages calls for immediate choice of alternative crops. A pesticide dosage reduction may require that farmers have to adjust for new growing conditions. These adjustments combined with the increased production risk are important long-term effects that have not been taken into consideration in the short-term assessment. Long-term effects may contribute extra costs thus being a cause of decreasing annual profits.

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