Soil erosion-crop productivity relationships for six

Soil erosion-crop productivity relationships for six Alberta soils -

F. J. Larney, R. C. Izaurralde, H. H. Janzen, B. M. Olson, E. D. Solberg, C. W. Lindwall, and M. Nyborg

ABSTRACE Water and wind erosion are major soil degradation forces on the .Great Plains of North America but their effects on soil productivity are not well quantiFed. Six experimentalsites were established in Alberta in 1990-1991 to ascertain the gects of Simulated erosion on soil productivity. Incremental depths of soil (0,5, 10, 15, and 20 cm) were removed with an excavator. Highly si'ijicant relationships were found between the depth of dewfacing and subsequent spring wheat y i e h , showing that simulated erosion drastically reduced soil productivity. Treatment effects at an irrigated site followed the same trend as the dryland sites, illustrating that topsoil loss cannot be ofiet by adequate soil moisture. Our results show that the loss in returns caused by topsoil removal depend on (a) the particular depth increment of topsoil removed by erosion; (6) soil type; and (c) whether the soil is dryland or irrigated.

ind and water erosion lead to a reduction in soil quality and productivity and hence crop yield. However, these effects are difficult to quantify. Topsoil depth is recognized as a major parameter in determining soil quality and productivity. Characterizing topsoil depth-soil productivity relationships is a vital step in assessing the true on-farm costs and benefits of conservation tillage and erosion control programs. If the effect of loss of topsoil (i.e., erosion) on soil productivity could be adequately assessed then figures could be applied to soil erosion costs and the economic benefits of conservation tillage practices. Several approaches may be used to estimate erosion effects on soil productivity (Cassel and Fryrear; Crosson and Stout; Lal; Meyer, Bauer, and Heil; Schertz et al., 1985). Some researchers have compared crop yields on eroded knolls with those on uneroded downslope positions and maintained that differences in productivity were a result of erosion (Battiston et al.; F. J Larney, H. H. Janzen, and B. M . Ohon are soil scientists, and C. W. Lindwall, a tilhge engineer, with the Agriculture Canada Research Station, Lethbridge, Alberta T l J 4Bl. R. C. Izaurralde and M . Nyborg are soil scientists with the Department of Soil Science, University of Alberta, Edmonton, Alberta TGG 2E3. E. D. Solberg is a specialist with the Soil and Crop Management Branch, Alberta Agriculture, Edmonton, Alberta TGH 5T6 This research was supported by the National Soil ConservationProgram/ Canada-Alberta Soil Conservation Initiative. We thank A. W. Curtis, M. E. McCann, Z. Zhang, and B. Hoar for technicalassistance. This paper is Lethbridge Research Station Contribution no. 3879290 J. Soil and Water Cons. 50 (1) 87-91

Langdale et al.). However, this approach has some fundamental drawbacks. The measured yield differences are often due to the effects of erosion plus other confounding factors such as slope, sediment deposition, and soil moisture differences (Daniels et al., 1985; Schertz et al., 1989; Whitman, Hatfield, and Reginato). Also, one has to assume that the productivity of the site was uniform when erosion first occurred (e.g., ancient erosion) and when the site was first cultivated (Daniels et al., 1987). Another technique involves addition of topsoil to a naturally eroded ridgetop or knoll and comparison of subsequent effects on soil productivity with adjacent non-amended areas (Mielke and Schepers; Verity and Anderson). However, this approach has some of the underlying disadvantages of the previous one. A further approach aims at characterizing crop responses to differences in existing topsoil depth and then extrapolating the results to show the yield response to topsoil loss (McDaniel and Hajek). This assumes that the relationship of yield to

Table 1. Characteristicsof six study sites (before topsoil removal)

Site

Great Group*

Parent Material

Ap horizon Texture Organic C depth (cm) 0-7.5 cm 7' 0-15 cm

LD LI TB

Dark Brown Chernozemic Dark Brown Chernozemic Brown Chernozemic

Glaciolacustrine Glaciolacustrine Glacial till

15 10-13 10-15

SCL SCL CL

1.58 1.76 1.40

HS CL JB

Black Chernozemic (Thin) Gray Luvisol Black Chernozemic (Thick)

Glacial till Glacial till Glacial till

10-13 15-18 30-33

CL CL L

2.97 3.47 4.00

*Dark Brown Chernozemic = Typic Haploboroll; Brown Chernozemic = Aridic Haploboroll; Black Chernozemic (Thin) = Udic Haploboroll; Gray Luvisol = Typic Cryoboralf; Black Chernozemic (Thick) = Typic Cryoboroll. JANUARY-FEBRUARY 1995

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Copyright © 1995 Soil and Water Conservation Society. All rights reserved. Journal of Soil and Water Conservation 50(1):87-91 www.swcs.org

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differences in existing topsoil depth is a reasonable approximation of the yieldtopsoil loss relationship. For example, it assumes a location with 20 cm of topsoil would yield the same as an area in the same field with only 15 cm of topsoil, if the first location suffered the loss of 5 cm of topsoil through erosion. This approach thereby infers that each incremental depth of topsoil has equal productivity. We chose the scalping or desurfacing approach, whereby incremental depths of topsoil are mechanically removed to simulate erosion and subsequent effects on soil productivity are monitored (Eck; Ives and Shaykewich; Mbagwu, Lal, and Scott; Smith and Shaykewich; Tanaka and h e ) . Levels of amendments needed to restore productivity may also be studied (Dormaar, Lindwall, and Kozub; Massee). We recognize that effects of desurfacing are different from those of natural soil erosion processes. Natural wind erosion is a sorting process involving preferential removal of aggregates of certain sizes over a period of time. With natural water erosion, soil removal is very uneven due to rilling and gullying. In contrast, desurfacing is a onetime removal of soil to a uniform depth. Despite these shortcomings, this approach can overcome the confounding aspects of landscape position and inherent topsoil depth variability. In Alberta, there is a lack of information on erosion-productivity relationships for major soil types. Various models such as PI (Productivity Index) and EPIC (Erosion Productivity Impact Calculator) can estimate long-term effects of erosion on soil productivity (Kiniry, Scrivner, and Keener; Williams, Renard, and Dyke) but they have not been validated by actual experiments for northern climates like Alberta. We therefore initiated field studies at multiple locations, with the objective of assessing the effects of simulated erosion on soil productivity for a representative range of Alberta soils. In this paper we present data from the first growing season

and discuss the initial impact of simulated erosion on crop performance.

3000

+

RL= 0.941

0 3m

2500

x

lY----l

+

y =2520.218 . 7 ~ 5. 02x2

IHS I

I

I

I

I

I

I

t

I

JBI

y =1121-47.5~-t0.74x2

t

It2= 0.918

0

3000

I

I

I

-

-

-

- y =2665-45%-2.05'

500

R2= 0.968 I

0

0

5 10 is Depth of Cut, m

20

0

I

I

5 10 I5 Depth of Cut, cm

I

20

Figure 1. Depth of topsoil removal and spring wheat yield at six simulated erosion sites in Alberta: LD, LI, and TB (1990); HS, CL, and JB (1991) water during the growing season to ensure that root zone soil moisture was not a limiting factor. Growing season precipitation (May-August) was 182 mm (7 in) at LD and LI, and 179 mm (7 in) at TB in 1990, and 272 mm (10.7 in) at HS, and 274 mm (10.8 in) at JB and CL in 1991. Ponding of water was not a problem on the deeper cuts. Six (LD, LI, TB, HS) or two (CL, JB) 5-m row lengths were hand-harvested at maturity in late August-early September. Statistical analysis was performed on grain yield data using the General Linear Models Procedure and regression analysis (SAS).

Results and discussion Plant density was not affected by depth of desurfacing (data not presented). Sub-

J O U R N A L O F S O I L A N D WATER CONSERVATION

sequent differences in plant performance were therefore a result of treatment effects rather than plant population effects. The relationship between depth of topsoil removal and grain yield for the six sites is shown in Table 2. Topsoil removal had a significant effect at all six sites, most noticeably at LI where all five treatments were significantly different from each other. Polynomial equations were used to define the yield-depth of topsoil removal function as follows: y = a - bx + cx2 where y = grain yield and x = topsoil depth removed (Figure 1). The b and c coefficients represent the slope of the relationships. These equations show that there are diminishing marginal returns with incremental loss of topsoil, i.e., top-


88

I

I

y = f28P93.&r 1.48~:

Materials and methods Six sites (five dryland, one irrigated) representing the major soil groupings in Alberta were chosen. Four sites were located near Lethbridge in southern Alberta, where wind erosion is a major problem, and two near Edmonton in central Alberta, where water erosion is common. In spring 1990, two sites were established at the Agriculture Canada Research Station at Lethbridge (49" 43' N, 112" 48' W): one on dryland (LD) and one on irrigated land (LI). A third site was established in spring 1990 at Taber (TB) about 50 km east of Lethbridge. In 1991, a site was established at Hill Spring (HS), about 70 km southwest of Lethbridge, and two sites about 20 km east of Edmonton (53" 34' N, 113" 33' W) at Cooking Lake (CL) and Josephburg (JB). Table 1 shows soil types and surface textures for the six sites. Each site had quite uniform Ap horizon depth and level topography. All sites were under cultivation for about 80 years in rotations typical of their agroecological region: wheat-fallow at LD and TB; continuous cereals/specialty crops at LI; continuous cereals/oilseeds at HS and JB; and continuous foragedcereals at CL. Five treatments, or cuts, [12 x 10 m (40 x 33 ft) in area, with four randomized replications] were established at each site by carefully removing 0, 5, 10, 15 or 20 cm (0, 2,4, 6, 8 in) of topsoil using a specialized excavator with a grading bucket. The study plots were 3 x 10 m (10 x 33 ft) [the remaining 9 x 10 m (30 x 33 ft) area on each cut was used for an amendment study]. The depth of the Ap horizon varied with site (Table 1). At LD, LI, TB, and HS there was a thin Bt horizon [2-7 cm (0.8-2.8 in) thick] so that the Cca horizon was exposed on some of the 20 cm (8 in) cuts. At CL desurfacing to 15 (6 in) and 20 cm exposed the Bt horizon. The depth to the Ck horizon was about 85 cm (33 in) at CL. A 30-33-cm (12-13 in) deep Ap horizon at JB prevented the exposure of the Bt horizon which extended to 63 cm (25 in) depth with a BC horizon to 100 cm (39 in) depth. Seedbeds were prepared with one pass of a powered rotary cultivator, as the desurfaced plots were quite dry and compact. All sites were seeded to spring wheat (Giticum aestivum L., cv. Lancer at LD, LI, TB and HS; cv. Roblin at CL and JB) in May using recommended seeding rates. The LI site received 17.5 cm (7 in) of

I

LD '

0

5

10

15

50

25

0

100

75

Relative Yield, % Figure 2. Spring wheat yield (relative to non-eroded 0-cm cut) with removal of successive 1-cm increments of topsoil at six study sites (data generated from equations in Figure 1) soil close to the surface has more value, in terms of its effect on yield, than do deeper increments of topsoil. This is in contrast with the effect on soil productivity portrayed when linear forms are used to describe yield-topsoil depth relationships (Christensen and McElyea). Even though all six sites had significant linear relationships (only the LI site had a significant second order polynomial) we feel justified in using polynomial equations to describe the yield-topsoil removal

relationships. The linear form is a naive representation of the yield-soil depth relationship and has limited value in economic analysis of soil erosion, while the polynomial form is theoretically satisfactory and useful in economic analyses (Christensen and McElyea). The JB (thick Black soil) site was an anomaly in this study, having a negative c coefficient. The equation indicates that superficial increments of topsoil were worth less than deeper increments with

Table 2. Grain yield and its standard deviation with topsoil removal treatments at LD, LI, and TB (1990) and HS, CL, and JB (1991) cut Grain yield, kg/ha 0 cm 5 cm 10 cm 15 cm 20 cm LSD 0.05

LD

LI

TB

HS

CL

JB

1205a 1061a 397b 154bc 59c 269

2507a 1588b 809c 369d 159e 193

1146a 877ab 650bc 698bc 417c 303

1522a 1100a 627b 33913 289b 455

2585a 1767b 1340b 615c 424c 594

2653a 2357ab 2159b 1335c 993c 408

176 95 238 194 79

122 156 176 268 200

221 379 364 92 164

559 405 347 161 102

255 480 409 308 497

Standard deviation, kg/ha Ocm 317 5cm 106 1Ocm 151 15cm 32 20cm 29

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respect to grain yield. The JB site had 3033 cm (12-13 in) of topsoil, the deepest A horizon of the six sites in this study (Table 1). The yield-simulated erosion relationship suggests there was still enough Ap horizon material present to mitigate the effect of the removing 20 cm (8 in) of topsoil, unlike the other five sites. At the other sites removal of 20 cm of topsoil exposed the B or even the C horizon. T h e effects of desurfacing are more drastic where nutrient fertility is concentrated in the top few centimeters and subsoil horizons are edaphically unfavorable (Lal). The LD and LI sites had high levels of calcium carbonate in their B and C horizons, which may have contributed to the poor crop performance on the deeper cuts at these sites by binding phosphorus and making it unavailable for plant uptake. In contrast, the effects of scalping were less drastic on soils with deep surface soil and more favorable subsoil conditions like the JB site. The application of water did not compensate for the loss of topsoil. Yields on the 0-cm cut at LI in 1990 were over twice those of the 0-cm cut at LD and TB. This is to be expected when comparing irrigated and dryland management systems. However, the yield dropped off rapidly at LI when topsoil was removed. In fact, the TB site outyielded the LI site on the 15- and 20-cm ( 6 and 8 in) cuts. Various figures are suggested for the value of topsoil lost to erosion. Our study shows that since productivity loss is curvilinear the value of the soil lost depends on which particular increment is removed by erosion. It also depends on soil type and whether the soil is dryland or irrigated. Because the polynomial form of the yieldtopsoil removal function provided such good fits (R’ values of 0.918-0.999, Figure 1) we used these equations to generate yields for each centimeter increment of topsoil loss between 0 and 20 cm (8 in)(Figure 2). Since the sites were cropped in two different years and there were some climatic differences, relative yields (i.e., yields expressed as a percentage of that on the 0-cm cut at each site) are shown. Loss of topsoil had the greatest effect on productivity at the LI site. Relative yields were reduced more at this site with respect to the non-scalped soil to 16 cm (6 in), than those at any other site. At 1620 cm (6-8 in) of topsoil removal the LD site had the lowest relative yield. The LD and HS sites were almost identical in their incremental yield reductions to a depth of 8 cm (3 in). Below this depth they diverged with the HS site showing less relative yield reduction than LD. Artificial

ern Alberta, where rainfall is limited. We have also treated sub-plots [3 x 10 m (1033 ft)] at these six sites with an optimum rate of N and P fertilizer, reapplication of 4 cm (2 in) of topsoil and feedlot manure in order t o assess the value of these amendments on eroded soils.

0 1

I

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1

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5

Conclusions

I0

I5

0

I

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I

I

1

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1

2

3

4

5

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8

9

Yield Loss, 96 of non-scalpedyield Figure 3. Spring wheat yield loss due to removal of successive 1-cm increments of topsoil at six study sites (data generated from equations in Figure 1)

erosion affected grain yields on the TB and JB sites to a lesser degree than the other four sites. The JB site was the least affected of all sites to a depth of 17 cm (7 in) of topsoil removal. These trends are further exemplified by the depth of topsoil removal required to halve the yield of the non-scalped plots (Figure 2). The sites may be split into two broad groups: LI, LD, HS, and CL, where removal of 7-9 cm (3-4 in) of topsoil halved yield; and TB and JB, where removal of 16-17 cm (6-7 in) of topsoil was necessary to halve yields. Figure 3 shows the relative yield loss associated with the removal of each centimeter of topsoil. The reverse trend on the JB site compared with the other five is evident. Generally, the greatest differences between soils occurred in the 0-5-cm (2 in) increment. The differences declined with depth of topsoil removal and yield losses per centimeter were most similar in the 10-15-cm (4-6 in) increment. Below 15cm depth, differences were greater again, mainly due to the trend at the JB site. Removing the surfice centimeter of soil reduced spring wheat yield by 8.5% [213 kg ha-'(3.2 bu a d ] at LI, 7.4% [113 kg ha-' (1.7 bu ac')] at HS, 7.1% [86 kg ha-' (1.3 bu ac-l)]at LD, 6.3% [163 kg ha-' (2.4 bu 90

ac-I)] at CL, 4.2% [48 kg ha-' (0.7 bu ac-I)] at TB, and 1.8% [48 kg ha-' (0.7 bu ac-I)] at JB. Wheat yield reductions per millimeter of topsoil loss have been roughly estimated at 8 kg ha-' (0.12 bu ac-I) (National Soil Erosion-Soil Productivity Research Planning Committee). Our results are in general agreement with this estimate. Using the equations in Figure 1 and substituting 0.1 for x we calculated yield reductions of 9 kg ha-' (0.13 bu ac-') at LD, 21 kg ha-' (0.31 bu ac-') at LI, 5 kg ha-' (0.07 bu ac-') at TB, 12 kg ha-' (0.18 bu ac-I) at HS, 16 kg ha-' (0.24 bu ac-') at CL, and 5 kg ha-' (0.07 bu a d ) at JB. Averaging the six sites gives a value of 11 kg ha-' (0.16 bu ac-I) per millimeter of topsoil loss. Loss of productivity on eroded soils may be caused by the lack of soil physical, chemical, and microbial conditions associated with topsoil (Carlson et al.; National Soil Erosion-Soil Productivity Research Planning Committee). These properties will be examined in the future to further explain the reasons for loss of productivity. Some soil physical properties that may be affected by topsoil removal are surface texture, soil water storage, effective root zone, and soil temperature. These parameters are likely to be especially important in semi-arid areas like south-

J O U R N A L OF S O I L A N D W A T E R C O N S E R V A T I O N

REFERENCES CITED Battiston, L.A., R.A. McBride, M H. Miller, and M.J. Brklacich. 1985. Soil erosion-productivity research in southern Ontario. In: Erosion and Soil Productivity. ASAE Publ. 8-85, American Society of Agricultural Engineers, St. Joseph, Mich. pp. 28-38. Carlson, C.W., D.L. Grunes, J. Alessi, and G.A. Reichman. 1961. Corn growth on Gardena surface and subsoil as affected by applications of fertilizer and manure. Soil Science Society of America Proceedings 25: 44-47. Cassel, D.K., and D.W. Fryrear. 1990. Evaluation of productivity changes due to accelerated soil erosion. In: W.E. Larson, G.R. Foster, R.R. Allmaras, and C.M. Smith (eds). Proceedings of Soil Erosion and Productivity Workshop. Publ. by Univ. of Minnesota, St. Paul, Minn. pp. 41-54. Christensen, L.A., and D.E. McElyea. 1988. Toward a general method of estimating productivity-soil depth response relationships. Journal of Soil and Water Conservation 43: 199-202. Crosson, P., and A.T. Stout. 1983. Productivity effects of cropland erosion in the United States. Resources For The Future, Washington, D.C. Daniels, R.B., J.W. Gilliam, D.K. Cassel, and L.A. Nelson. 1985. Soil erosion class and landscape position in the North Carolina Piedmont. Soil Science Society of America Journal 49: 99 1-995. Daniels, R.B., J.W. Gilliam, D.K. Cassel, and L.A. Nelson. 1987. Quantifying the effects of past soil erosion on present soil productivity. Journal of Soil and Water Conservation 42: 183-187. Dormaar, J.F., C.W. Lindwall, and G.C. Kozub. 1986. Restoring productivity to an artificially eroded Dark Brown Chernozemic soil under dryland conditions. Canadian Journal of Soil Science 66: 273-285. Eck, H. V. 1987. Characteristics of exposed subsoil:


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In this study, substantial yield reductions followed the removal of topsoil showing that the relationship between simulated erosion and soil productivity was curvilinear. The removal of the surface centimeter of topsoil exerted the greatest yield effect on the Dark Brown irrigated soil, followed by the thin Black, the Dark Brown dryland soil, the Gray Luvisol, the Brown, and lastly the thick Black soil. The value of topsoil depends on which particular depth increment of topsoil is being removed by erosion; soil type; and whether the soil is dryland or irrigated. Irrigation, without added fertilizer or manure, did not prove to be a 'quick fix' for an artificially eroded soil. Wheat yield reductions of 2-8% are possible with the loss of the surface centimeter of topsoil. These results are from the first growing season after artificial erosion. Continuing studies at these sites will determine long-term costs of erosion on soil productivity.


at exposure and 23 years later. Agronomy Journal 79: 1067-1073. Ives, R.M., and C.F. Shaykewich. 1987. Effect of simulated soil erosion on wheat yields on the humid Canadian prairie. Journal of Soil and Water Conservation 42: 205-208. Kiniry, L.N., C.L. Scrivner, and M.E. Keener. 1983. A soil productivity index based upon predicted water depletion and root growth. Research Bulletin 105 1, University of Missouri, Columbia, Mo. 26 pp. Lal, R. 1988. Monitoring soil erosion’s impact on crop productivity. In: R. Lal (ed) Soil Erosion Research Methods. Soil and Water Conservation Society, Ankeny, Iowa. pp. 187-200. Langdale, G.W., H.P. Denton, A.W. White, J.W. Gilliam, and W.W. Frye. 1985. Effects of soil erosion on crop productivity of southern soils. In: Follett, R.F., and B.A. Stewart (eds). Soil Erosion and Crop Productivity. American Society of Agronomy, Madison, Wisc. pp. 25 1-270. Massee, T.W. 1990. Simulated erosion and fertilizer effects on winter wheat cropping intermountain dryland area. Soil Science Society of America Journal 54: 1720-1725. Mbagwu, J.S.C., R. Lal, and T.W. Scott. 1984. Effects of desurfacing of Alfisols and Ultisols in southern Nigeria: I. Crop performance. Soil Science Society of America Journal 48: 828-833. McDaniel, T.A., and B.F. Hajek. 1985. Soil erosion effects on crop productivity and soil properties in Alabama. In: Erosion and Soil Productivity. ASAE Publ. 8-85. America Society of Agricultural Engineers, St. Joseph, Mich. pp. 48-58. Meyer, L.D., A. Bauer, and R.D. Heil. 1985. Experimental approaches for quantifying the effect of soil erosion on productivity. In: R.F. Follett and B.A. Stewart (eds) Soil Erosion and Crop Productivity. American Society of Agronomy, Madison, Wisc. pp. 213-234. Mielke, L.N., and J.S. Schepers. 1986. Plant response to topsoil thickness on an eroded loess soil. Journal of Soil and Water Conservation 4 1: 59-63. National Soil Erosion-Soil Productivity Research Planning Committee. 1981. Soil erosion effects on soil productivity: a research perspective. Journal of Soil and Water Conservation 36: 82-90. SAS. 1985. SAS User’s Guide: Statistics. Version 5 edition, SAS Inst. Inc., Cary, N.C. Schertz, D.L., W.C. Moldenhauer, D.P. Franzmeier, and H.R. Sinclair. 1985. Field evaluation of the effect of soil erosion on crop productivity. In: Erosion and Soil Productivity. ASAE Publ. 8-85. American Society of Agricultural Engineers, St. Joseph, Mich. pp. 9-17. Schertz, D.L., W.C. Moldenhauer, S.J. Livingston, G.A. Weesies, and E.A. Hintz. 1989. Effect of past soil erosion on crop productivity in Indiana. Journal of Soil and Water Conservation 44: 605-608. Smith, E.G., and C.F. Shaykewich. 1990. The economics of soil erosion and conservation on six soil groupings in Manitoba. Canadian Journal of Agricultural Economics 38: 2 15-23 1. Tanaka, D.L., and J.K. Aase. 1989. Influence of topsoil removal and fertilizer application on spring wheat yields. Soil Science Society of America Journal 53: 228-232. Verity, G. E. and D. W. Anderson. 1990. Soil erosion effects on soil quality and yield. Canadian Journal of Soil Science 70: 471-484. Whitman, C.E., J.L. Hatfield, and R.J. Reginato. 1985. Effect of slope position on the microclimate, growth and yield of barley. Agronomy Journal 77: 663-669. Williams, J.R., K.G. Renard, and P.T. Dyke. 1983. EPIC a new method for assessing erosion’s effect on soil productivity. Journal of Soil and Water Conservation 38: 381-383.

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