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Biological Assay of Pumice Soil Fertility

C. T. YOUNGBERG AND C. T. DYRNESS

Reprinted from SOIL SCIENCE SOCIETY OF AMERICA PROCEEDINGSVol. 29, No. 2, March—April 1965. pages 182-187

677 South Segoe Road, Madison, Wisconsin 53711 USA

Biological Assay of Pumice Soil Fertility'

C. T. YOUNGBERG AND C. T. DYRNESS2

ABSTRACT

The fertility of pumice soils is difficult to assess by laboratoryanalysis. A biological assay of grov, th responses yields moremeaningful information. Four pumice soils common in centralOregon Were assayed in the greenhouse using ponderosa pineas an indicator species.

A composite experimental design was used involving addi-tions of N, P, K, Ca, and S. There were no responses to eitherK or Ca. Nitrogen appeared to be the most deficient nutrientelement since it was the only one tested that gave largeresponses when added alone. Combinations of N and P and Nand S gave better responses than N alone. Best growth resultedfrom addition of N, P, and S in combination. The experimentaldesign used was very satisfactory for this type of assay, particu-larly in evaluating various nutrient interactions.

SOILS DEVELOPED on pumice and volcanic ash are verywidespread in central and eastern Oregon and in other

portions of the western United States. Many acres of thesesoils support forest vegetation. Pumice soils are generallycoarse textured, often with a. high proportion of gravelsize particles. In spite of the coarse, gravelly nature ofsome of these soils, there is a relatively large amount ofsurface area exposed due to the porous nature of the par-ticles. This property imparts unique characteristics to thesesoils with regard to moisture and fertility relationships. Italso presents definite problems with regard to analyticalprocedures used in evaluating and characterizing thesesoils (13).

While studying soil-plant relationships on pumice soilsin central Oregon, the authors became aware of the inade-quacy of standard methods of analysis for soil fertilit y . Itseemed that some method that would actuall y test theresponses of plants to certain conditions would be moremeaningful. Observations made on the root developmentof ponderosa pine (Pines ponderosa Laws) in the coarsegravell y horizons of several pumice soils indicated that fieldtrials using broadcast applications of fertilizers would notgive the kind of information that was needed. Some methodwas needed that would give a biological evaluation of theability of each soil horizon or la yer to supply nutrients.A greenhouse study of individual soil horizons appeared tooffer the greatest promise for reaching this objective.

In the past man y of the studies of the influence of nutri-ent elements on the growth of tree seedlings have been ofa single factor nature. All nutrients except one have beenadded at a level that was considered to be optimum, andthe level of a single nutrient was varied in order to deter-

Technical Paper No. 1506. Oregon Agr. Exp. Sta.. OregonState Univ.. Corvallis. Ore. Portions of the material presentedbefore Div . S Soil Science Society of America. St. Louis. Mo..Nov. 29. 1961. Received Apr. 20. 196-1. Approved Nov. 25, 1964.

Professor of Forest Soils. Oregon State University and SoilScientist. Pacific Northwest Forest and Range Exp. Sta.. respec-tively. Statistical analyses were made by the Oregon State Univer-sity Statistical Service. Dr. Lyle A. Calvin in charge.

mine the so called optimum level for that nutrient. Mostof these studies were conducted either in nutrient solutionsor sand cultures. Jenny et al. (5) developed a method forevaluating the fertility status of soils using Romaine lettuceas an indicator plant. Vlaniis et al. (10) have used a modi-fication of this technique to assay the fertility of - wild-land- soils using seedlings of native vegetation indigenousto the soil being tested. Although these approaches havegiven some valuable information with regard to generalfertility status, the experimental designs used have leftunanswered the questions concerning specific interactionsbetween the different nutrient elements.

An experimental design frequently used to define nutri-ent interactions is the factorial. In a complete factorialexperimental design the levels of several nutrient elementscan be varied and studied simultaneously and it is thereforepossible to estimate the effect of varying each nutrient ateach level of the other nutrients. However, to include thedesired number of levels of each nutrient, e.g. three nutri-ents at five levels each, requires a large number of treat-ments and the amount of work involved ma y be prohibitive.

Box and his associates (2, 3) have developed a method-ology useful in the experimental determination of responsesurfaces that does not require all combinations of a multi-level factorial to measure interactions. The techniques weredeveloped primarily for use in physical and engineeringsciences, but Hader et al. (4) have given a very thoroughdiscussion of the methods and demonstrated their use inbiological research, i.e., measuring the effects of certainminor elements on the yield of lettuce. Moore et al. (7)have demonstrated this approach in evaluating nutrientinteractions on the growth of lettuce and the accumulationof certain elements in the plant. Kirsch et al. (6) havealso used this experimental design to stud y the interrela-tionships of certain minor elements on the growth andnutrition of tomatoes. These studies were all carried out innutrient solution cultures. It appeared to the authors, how-ever, that the technique could be useful to evaluate thefertility status of soils as well.

It is not the purpose of this paper to go into the theo-retical aspects of the experimental design. For this thereader is referred to the works alread y cited above. Thepurpose of this paper is to demonstrate the usefulness ofthe method for work with soils and trees and to report onthe fertility of four pumice soils from central Oregon.

Essentially the method involves the use of a polynomialmodel to approximate a response surface. The design isknown as .1 central composite design in which the treat-ment combinations are selected to permit estimation of theparameters of the model. A 5 x 5 x 5 complete factorialrequires 125 treatments; however, with the use of this de-sign onl y 15 treatment combinations are required (4). Inorder to obtain a better estimate of the response surfaceeight additional treatment combinations were used for atotal of 23. These eight treatments are an additional2 X 2 X 2 factorial that evaluate the extremes of theresponse surface.

182ti

porn

050

100150200

CI50

100150200

50

255075

1004

C 2 050

100/50200

/50300450600

100150204)

4

YOUNGBERG AND DYRNESS: BIOLOGICAL ASSAY OF PUMICE SOIL FERTILITY 183

Table 1-Amounts and source of nutrients added to Lapine Cland C2 horizon material for ponderosa pine in Experiment 1

Table 3-Observed weights of ponderosa pine seedling topsafter 13 months growth in Lapine Cl. and C2 horizon soil to

which varying amounts of N, P, K, and Ca had been addedHorizon Level no. P K Ca

Nutrient sources

N - NH, NO3P - 1-1 3 PO,Ca - Cad!,K - KCI

Table 2-Soil test data for the CI and C2 horizons of theLapine soil

Horizon pH Avail. Ex clmngeabP K Ca Mg

CEC Total Organic

N matter

pplt1 meq/100g meq/100g

C 1 6.2 3.0

0.16 0. 9 0. 35 4. 85 0.01

0.21

C 2 6. 9 2. 5

0.14 1.1 0.55 4.20 0. 01 0. 18

EXPERIMENT 1

Methods

Dyrness 3 in an attempt to determine some of the reasons forthe lack of root development in the Cl (coarse gravelly sand) andC2 (gravelly sand) horizons of the Lapine series set up a green-house experiment using the central composite design. N, P, andK were the variables for the C1 horizon and N, P, and Ca forthe C2 horizon. Treatment levels and nutrient sources are givenin Table 1.

Pertinent soil data for these two horizons are given in Table 2.Available P was determined using the sodium bicarbonate methodof Olson et al. (8). exchangeable cations by the method of Schol-lenberger and Simon (9) using the flame photometer for deter-mination of the cations, nitrogen by the Kjeldahl method, and pHwith a glass electrode using a 1:1 soil-water paste (1).

Twelve hundred grams of soil were placed in plastic pots andcovered with a thin layer of quartz sand. Twenty-five ponderosapine seeds were sown in each pot. After the seedlings had germi-nated and become well established (about 6 weeks after sowing)the nutrient treatments were applied in solution. Each treatmentwas replicated three times. The pots were irrigated at regular inter-vals with distilled water and the excess water drained into indi-vidual waxed cups so that the leachate could be returned to theappropriate pot. About a month after treatment each pot wasthinned to 12 seedlings. The seedlings were grown for 12 monthsduring which time they had gone through a period of dormancyand a second flush of growth. At the end of the growth periodseedlings were harvested by cutting at the ground line. No attemptwas made to harvest the roots since it is virtually impossible toseparate the roots from the porous pumice gravels. After harvestthe tops were dried in a forced air oven at 65C overnight. Yieldswere calculated on a dry weight per seedling basis.

Results and DiscussionThe yield data for the Cl and C2 horizons are presented

in Table 3. Statistical analysis of the data is presented inTable 4. Both the linear and quadratic effects of N and Pare statistically significant as is the N times P interaction.The lack of visual seedling response to K and Ca is con-firmed by the low, nonsignificant F values for the two ele-ments. Regression coefficients were also calculated accord-ing to the procedure outlined by Hader et al. (4). Theseregression coefficients were then used to derive prediction

Dyrness. C. T. 1960. Soil-vegetation relationships within thePonderosa pine type in the central Oregon pumice region. Unpub-lished Ph.D. thesis. Oregon State University, Corvallis, Oreg.

Treatment level Average seedling top weight

Cl C2 CI C2

N, P, K, N, P 2 Ca, 0.40 0.45

14, P 3 K, N, P, Ca, 0.18 0.19

N 3 P 3 K 3 N5 P, Ca, 0. 47 O. 52N 3 P,K 3 N, P, Ca, 0.34 0.34

N, P, K 3 N3 P, Ca, 0.38 0.43

N 3 P 3 K, N, P, Ca, 0.41 0.51

N 3 P 3 K, N, P3 Ca5 0.40 0.43

N 2 P2 K2 N2 P. Ca2 0.36 0.37

N 4 P 2 K 2 N4 P 2 Ca2 0.40 0.43

N 2 P, K2 N2 P, Ca, 0.30 0.42

N, P, K, N4 P, Cat 0. 53 0. 55

1,1 2 P2 K, N2 P 2 Ca, 0. 31 0. 35

N4 P2 K 4 N4 P 2 Ca, 0.45 0.44

N2 P, K, N2 P 4 Cat 0. 30 U. 37

N, P, K, N, P, Ca, 0.49 0.70N, P, K, N, P, Ca, 0.20 0.17N 5 P, K, N5 P, Ca, 0. 35 0. 37N2 P5 K, N, P5 Ca, 0.13 0.15

N, P5 K, N5 P5 Ca, 0.60 0, 58N, P, K, NIP, Ca, 0. 14 0. 15N5 P, K, N5 P, Ca, 0. 33 0. 33

N I PS K, NI P, Ca, 0. 15 0. 16N, P, K, N, P, Ca, 0.61 0.50

Table 4-Analysis of variance and prediction equations forLapine Cl and C2 horizon, Experiment 1

Source Degrees offreedom

Cl horizon C2 horizon

Meansquares

F values Meansquares

F values

Replications 2 0. 0006 0. 29 0.0086 2. 32

N 1 0. 8402 400. 11" O. 8372 226. 27"

P 1 0.0841 40.05" 0.124H 33. 74"

K(C1) Ca(C2) 1 0. 0029 1. 37 0. 0052 1.40

N x P 1 O. 1401 66. 70" 0. 0808 21.83"

N x K(C1) / 0. 0008 0. 36 0.0011 O. 31N x Ca(C2)

P x K(C11 1 0. 0023 1. 07 0.0001 0.1)3P x Ca(C2)

N , 1 0.0368 17.53** 0.1020 27.77"

P 2 1 0. 0094 4.49* 0. 0489 13.21"

K t (C liCa 2 (C2) 1 0.0012 0. 60 0. 0006 0.17

Total regression 10 1.0080 480. 00" 1. 1793 318.73"

Lack-of-fit 13 0.0026 1.24 0.0104 2.81*

Error 44 0.0021 12.0037

Prediction Equation

To solve equations the following coded levels are substituted for the treatmentlevels.

Treatment level: 1 2 3 4 5Coded level: -2 -1 0 1 2

Cl horizon:Yield = .406 - .076 N - .024 P - .004 K • .019 NP .001 NK

- . 002 PK - . 017 N 2 - . 009 P 2 - . 003 K2

C2 horizon:

Yield = .483 .076 N - . 029 P - .006 Ca • .014 NP - .002 NCa- . 001 PCa - . 028 N 2 - . 002 Cat

•• Significant at / °,3 probability level. • Significant at 55; probability level.

equations. Equations for the yield of seedlings tops (dryweight in grams) as a function of treatment levels of N,P, and K in the case of the Cl horizon and N, P, and Cafor the C2 horizon are presented in Table 4. These equa-tions also describe the response surfaces for the yield. Allregression coefficients, even those which were not signifi-cant, were used in calculating the response surface. Thispractice is recommended by Box (3), who pointed out thatthe elimination of nonsignificant regression coefficients re-sults in the replacement of an unbiased estimate of smallest

0 80K = 50 P Pm

e kANEW,

ArPM r r

ti

020 To->:

060

040

O

184 SOIL SCIENCE SOCIETY PROCEEDINGS 1965

50 100 150 200

P ppm

Fig. 1-Response surface showing yield of ponderosa pine (dryweight seedling tops) at various treatment level combinationsof N and P and 50 ppm K for Lapine Cl horizon.

variance by an estimate (zero) which has neither of thesequalities.

A response surface obtained by solving the C1 horizonprediction equation for N and P at the middle level of Kis shown in Fig. 1. As might be expected, a similar N x Presponse surface plotted for the C2 horizon has an almostidentical appearance. This graph shows the interactionwhich existed between N and P. At the lower rates of Nthe application of P resulted in a decrease in seedlinggrowth. Conversely at high rates of N application a pro-nounced stimulatory effect of P is readily apparent. Theresponse surface also indicates that the seedling growthwould most probably have been increased by the applica-tion of still larger quantities of N and P. Even at thehighest levels (200 ppm) the yield surface had not yetleveled off and was continuing in an upward direction.

Differences among treatments with respect to the criteriaother than seedling top weight were very apparent through-out the course of the experiment. For example, seedlingsgrowing in soil to which no N had been added exhibitedextremely sparse foliage having a pronounced chloroticappearance. The most vigorous seedlings, as denoted bytheir dark green foliage, were those growing in soils receiv-ing additions of N and P. Height growth also varied mark-edly among treatments. Nevertheless, the determination oftop weights appears to offer a most rapid and sensitivemeasure of the response of ponderosa pine seedlings tovariation in soil fertility.

EXPERIMENT 2Methods

The results of the experiment with the Lapine Cl and C2horizons indicated the need for more detailed investigation Of thenature of the N N P interaction. The possibility of a sulfur defi-ciency was also suggested from preliminary studies. The need formore complete information on the fertility status of the wholeLapine profile and several other pumice soils was also apparent.Accordingly. experiments similar to those used on the Lapine Cland C2 horizons were set up using the A. Cl. and C2 of theLapine series and the A and C horizons of the Shanahan. Steiger.and Newberry' series. The Lapine and Shanahan series have devel-oped on the Mazama pumice shower. The Shanahan lacks the coarse

' Proposed series name.

Table 5-Treatment levels for N, P, and S used for the Lapine,Shanahan, Steiger, and Newberry soils-Experiment 2

Level no.PPm

1 0100 100 25

3 200 zoo 504 300 300 755 400 400 100

gravelly C horizons typical of the Lapine series. The Steiger serieshas developed on the z\Iazama pumice flow and the Newberryseries on the pumice fall from Newberry crater. The Mazamapumice which is about 7,600 years old, is dacitic (12) and theNewberry pumice which is about 2,000 years old. is ryholitic (11).The Lapine Cl and C2 horizons and the Newberry A and Chorizons are dominantly pumice gravel. All four series are Regosols.

The nutrient levels of the Lapine A horizon, particularly P andtotal N. are somewhat higher than those shown for the Lapine Cland C2 horizons in Table 2. The fertility status of the Shanahan,Steiger, and Newberry soils is comparable to that of the Lapine.

The procedures outlined for Experiment 1 were also followedfor the subsequent experiments. However, since the optimum levelsof N and P had not been reached in the earlier experiment, thelevels of these two nutrients were increased as shown in Table 5.Nutrient sources were the same as in the earlier experiment.Sulfur was added as calcium sulfate (CaS0_,•21-L0).

Results and DiscussionYield data for the Lapine horizons are given in Table 6.

Similar data for the A and C horizons of the Shanahan,Steiger, and Newberry soils are presented in Table 7. Thesedata were subjected to analysis of variance and regressioncoefficients were calculated in the same manner as inExperiment 1.

The prediction equations for the Lapine horizons are asfollows:

Table 6-Observed weights of ponderosa pine seedling topsafter 12 months growth on Lapine A, C1, and C2 horizons

to which varying amounts of N, P, and S hadbeen added-Experiment 2

Treatmentlevel

Average seedling top weightA Cl C2

N 3 P3S3 0.82 0.71 0.36N, P3S3 0. 25 0. 14 O. 15

P3S3 0.83 0. 81 0. 54N 3 P 1 Ss 0.71 0.53 0. 30

N 2 P 5 S3 0.82 0. 7 ., 249N 3 P3S, 0.54 0.41 0.33N 3 PaS5 0.80 0.67 0. 55N, P. S. 0.75 0.522 0.35

N4 P. S2 0. 93 0. 7' 0.56N 3 P, S2 0.64 0. 6 , 0.53N. P ., S. 0. 91 0. 69 0. 37N, P. S4 O. 70 0. 45 0. 51

N 4 P 2 S4 0. 78 0. 6, 0.33N, P 4 85 0.81 0.610 0.50N 4 P: 0. 91 0. 86 0.63N 1 P, Ss 0. :32 0. 16 O. 14

N5 P, 0.47 0.41 0.29N, P5 S, 0. 30 O. 1 , 0. 14Ns P 5 S, 0. 66 0. 33 0. 38

N 3 P I S5 0. 34 0. 15 0. 14

N 5 PISS 1.00 O. 45 0. 34

N i P 5 S5 0. 26 0. 14 0. 14

N 5 P. Ss 1. 10 O. 7 ,-, 0.64

•

YOUNGBERG AND DYRNESS: BIOLOGICAL ASSAY OF PUMICE SOIL FERTILITY 185

A horizonYield = .823 + .121N + .015P + .049S + .012NP

.027NS + .002PS - .053N 2 .003P2 - .018S2

Cl horizonYield = .720 + .107N + .037P + .021S + .011NP

.011NS .007PS - .52N2 - .007P2 - .034S2

C2 horizonYield = .574 + .65N + .026P + .022S + .012NP

.01ONS + .007PS - .038N 2 - .014S2.

Using these prediction equations theoretical yields werecalculated. Response surfaces were then plotted as follows:

for the A horizonP and S at the middle level of N (Fig. 2);

for the Cl horizonP and S at the middle level of N (Fig. 3);N and S at the middle level of P (Fig. 4); andN and Pat the middle level of S (Fig. 5).

Analysis of variance showed that the lack of tit termwas significant for all three horizons (Table 8). This indi-cates to some degree the failure of the equation to predictyields. However, the lack-of-fit mean square and F valueswere very small as compared to the regression mean squareand F values. The predicted and actual values were in closeenough agreement to conclude that the prediction equationsfor these three horizons are satisfactory for showing trendsand relative magnitude of responses. The significance ofthe linear, interaction and quadratic effects for the Lapinesoil horizons is given in Table 9.

The analysis of variance for the Shanahan, Newberry,and Steiger soils revealed that the lack-of-fit terms werenot significant. For these soils the predicted value and

Table 7-Observed weights of ponderosa pine seedling topsafter 12 months growth on Shanahan, Newberry, and Steiger

A and C horizons to which varying amounts of N, P,and S had been added-Experiment 2

Treatmentlevel

Average seedling top weight

Shanahan Newberry SteigerA A A

gN, P,S 3 0. 76 0.91 0.76 0.44 1. 00 1.06N 4 P,S, O. 23 0.17 0. 22 O. 12 0. 18 0. 14N3 P B S, O. 95 0.79 0.99 0.48 0.97 1.33N 3 P t S, 0.70 0.82 0.60 0.27 0.46 0. 69N 3 P, S, 0.72 1.02 0.91 0.45 0.81 1. 13N,P,S, O. 54 0.4E 0.48 0.32 0.50 0.556N, P, 5, 0.71 0.09 0. 76 0.42 0.80 1.16

N 2 P 2 52 0. 38 0. 55 O. 48 0. 24 O. 61 0. 78N 4 P 2 S2 0.94 0. 91 0. 79 0.43 0. 75 1. 32N 2 P4 5 2 0. 55 0.59 0.45 0.24 0.73 0.96N4 P 4 5 2 1.10 1. 03 1. 02 0. 52 1. 08 I. 091,1 2 P 2 5, 0.62 0.48 0.41 0. 25 0. 64 O. 82N, P 2 S, 0. 90 0. 98 0. 83 O. 44 0. 76 1. 20N 2 1,4 54 0.70 0.61 0.58 0.25 0.76 0.84N4 P., 5 4 O. 87 1. 03 1. 04 0. 44 0. 81 1. 32N, P, S, O. 24 n. 17 0. 20 0. 13 0. 13 0. 15N, P, S t 0.50 0. 36 0. 62 0. 25 0.40 0.47N, P, 5, O. 24 11. 17 0. 25 O. 12 0.17 0. 14N, P, S, 0. 62 0. 39 0. 57 0. 34 0. 53 0. 54

N I Pi 5, 0.21 0.18 0.20 0.13 0.13 0.16N5 P, S5 O. 90 O. SI 0. 77 0. 32 O. 49 0. 73N, P, S5 0. 21 O. 10 0. 24 0. 12 0. 15 0. 14N, P, 5, I.24 0. 92 1.10 0.53 0.84 1.30

observed values for yield are in close agreement. The sta-tistical significance of the linear, interaction and quadraticeffects for these three soils is presented in Table 10.

The yield data presented in Tables 6 and 7 and thesummaries of statistical significance in Tables 9 and 10,show that significant increases in seedling dry weight pro-duction resulted from additions of N, P, or S. Also indi-cated were significant N X P, N X S and NXPXS interac-tions. The most striking response was noted in a doublingof seedling dry weight on the Shanahan A and C horizonsand the Steiger C horizon with the addition of N, P, andS at the highest levels as compared to adding only N andP at the highest levels. Also of interest is the comparisonof the influence of P at low N levels with the addition ofK or S in Lapine C horizon materials (Figs. 1 and 5).With the addition of K (no S added) P had a depressingeffect on seedling growth at low levels of N (Fig. 1). Onthe other hand, with additions of S, P increased seedlinggrowth even without added N. These kinds of nutrientinteractions are only observable with an adequate experi-mental design which allows several variables to be investi-gated simultaneously.

Table 8-Summary of analysis of variance for Lapinesoil-Experiment 2

dt Mean square

TotalReplication

68

A horizon

O. 0017 O. 05Regression 9 1. 0388 313. 58••Lack-of- fit 13 0. 0355 10. 71•*Error 44 0. 0033

Cl horizon

Total 68Replication 0. 0001 O. 11Regression 9 0. 7509 621. 11••Lack-of-fit 13 0. 0283 23.42**Error 44 0. 0012

C2 horizonTotal 68Replication 0. 0006 1. 03Regression 9 0.4281 713. 53••Lack-of-fit 13 0. 0231 41. 85••Error 44 0. 0006

*• Significant at the 1 e level of probability.

Table 9-Regression coefficients and statistical significance oflinear, interaction and quadratic effects for the

Lapine soil horizons

Effects Horizon

A Cl C2Mean O. 823 0.720 0.374Linear 0.121.* 0.107** 0.063**Linear O. 015** 0.037** 0. 020"*Linear 0.049** 0.021** 0. 022_••Interaction N a P 0. 012•• 0.011 • * 0. 012**Interaction N a 5 O. 027** 0.012 • * 0.010**Interaction P x S -0.002 0.007** 0. 0070*Quadratic N' -0.053** -0.052** -0.038**Quadratic 0. 003 -0.007* -0. 025**Quadratic s2 -O. 018** -0.034** -0.014••

•* Significant at 1°.; probability level. • Significant at probability level.

Table 10-Regression coefficients and statistical significance oflinear, interaction and quadratic effects for the

Shanahan, Newberry, and Steiger soils

Effects Shanahan Newberry SteigerA C A C A

Mean 0.802 0. 882 0. 758 0. 397 0. 869 1.158Linear N 0.156** 0.138** 0.160•• 0.071** 0. 116* • O. 186*•Linear P 0.022** 0.021 0 * 0. 041 0 * 0.021** 0.049** 0.1146**Linear S 0.045** 0.060** 0. 0420 * 0.014*" 0.025** 0.069**Interaction N a p 0. 013** O. 004* . 0. 008** 0.010 • * 0. 015** 0. 050**Interaction NOS 0.029** 0.029** 0. 021 0 * 0.007** 0.010** 0.032•*Interaction P o S 0. 006** 0. 002 0.012** 0. 003* 0. 003 O. 013**Quadratic N , -0. 036 0 * -0.094** -0.036** -0.023** -0.055** -11.084**Quadratic P2 -0.008* 0.015** 0. 002 -0.009** -0.040** A. 039**Quadratic S , -0.027•• -0.043** -0.033** O. 007** -0.035** -0.053**.• Significant at 1", level of probability. Significant at 57,, level of probability.

PROCEEDINGS 1965

The evaluation of the fertility status of pumice soils by-chemical analysis alone is of doubtful value. A biologicalassay using greenhouse pot studies of the different pumicehorizons and layers gives much more meaningful informa-tion. The experimental design used in this study has dis-tinct advantages over many in current use. One of the mainadvantages is the fact that nutrient interactions are readilydiscerned.

0 25 50 75 100S ppm

Fig. 4—Response surface showing yield of ponderosa pine (dryweight of seedling tops) at various treatment level combina-tions of N and S at 200 ppm P for Lapine Cl horizon.

0 100 200 300 400

P ppm

Fig. 5—Response surface showing yield of ponderosa pine (dryweight of seedling tops) at various treatment level combina-tions of N and P at 50 ppm S for Lapine Cl horizon.

186 SOIL SCIENCE SOCIETY

CONCLUSIONS

Greenhouse studies with four pumice soils from centralOregon have shown that ponderosa pine seedlings respondto additions of N, P, and S; Ca and K did not give anyresponse. Nitrogen was apparently the most deficient ele-ment since it is the only one that caused large growthresponses when added alone. However, the greatest re-sponses resulted from additions of N and P, N and S orall three in combination, indicating strong interactions.

0 100 200 300 400P ppm

Fig. 2—Response surface showing yield of ponderosa pine (dryweight of seedling tops) at various treatment level combina-tions of P and S at 200 ppm N for Lapine A horizon.

O 100 200 300 400P ppm

Fig. 3—Response surface showing yield of ponderosa pine (dryweight of seedling tops) at various treatment level combina-tions of P and S at 200 ppm N for Lapine Cl horizon.

YOUNGBERG AND DYRNESS: BIOLOGICAL ASSAY OF PUMICE SOIL FERTILITY 187

LITERATURE CITED

Alban, L. A.. .ind Kellogg, Mildred. 1959. Methods of soilanalysis used in the 0. S. U. Soil Testing Laboratory. Ore.Agr. Exp. Sta. Misc. Paper 65.Box. G. E. P.. and Wilson, K. B. 1951. On the experimentalattainment of optimum conditions. J. Roy. Statist. Soc., SeriesB XIII, No. I. . 1954. The exploration and exploitation ofresponse surfaces. Biometrics, 10:16-60.Hader, R. J., Harward. M. E., Mason, D. D.. and Moore.D. P. 195'. An investigation of some relationships betweencopper, iron, and mol ybdenum in the growth and nutrition oflettuce: I. Experimental design and statistical methods forcharacterizing the response surface. Soil Sci. Soc. Amer. Proc.21:59-64.Jenny. H.. Vlamis, J.. and Martin. W. E. 1950. Greenhouseassay of fertility of California soils. Hilgardia 20(1):1-8.Kirsch. R. K.. Harward. M. E., and Peterson. R. G. 1960.Interrelationships among iron, manganese. and molybdenum inthe growth and nutrition of tomatoes grown in culture solu-tion. Plant Soil XII (3):259-275.

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