PE EIE[R-Rg RESEARCH ON - HJ Andrews Experimental Forest

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Parameter Estimation In order to estimate conductivity (K) and diffusivity (D), both of which are functions of soil water content (0), we used standar d laboratory and computational procedures (Richards 1948, Green and Corey 1971) . The so-called moisture release curve, a plot of ,1i against 0, was also obtained in the laboratory . Curves for K, D, and as functions of 0 are shown in figure 1 . Our Cedar River core samples of the Everett gravelly sandy loam were biased to an unknown degree by the removal of the large stone fraction before the laboratory analysis . These stones constitute perhaps up to 20 per - cent of the volume of the Everett soil series . Because these stones tend to impede the flo w of water in unsaturated soils-the path aroun d them is longer than it would be for smaller obstructions-we believe our estimates of K may be somewhat too large . This decrease in conductivity associated with the presence o f large stones is especially noteworthy if th e soil is highly unsaturated because water strongly held by matric forces flows only along capillary paths around the stones an d not directly through the interstices of aggregations of large stones and cobbles . Since conductivity of water in unsaturate d soils is extremely difficult to measure directly, it has become common practice to estimate this parameter from pore-size distribution data, or equivalently, from the soil moisture release curve. Green and Corey (1971) have reviewed three methods fo r calculating K based on pore-size distribution and found that all give good results whe n compared with measured data . Our curve for K as a function of 0 is based on laboratory measurements of K for the saturated Everett soil and adjusted for unsaturated soils by us e of the Marshall pore-interaction relationship with a matching factor (Marshall 1958) . The shape of the moisture release curve i s also affected by sampling procedures. Removal of large stones clearly biases the result s in the direction of a soil with smaller pores . Accordingly, the correct relationship is some - what to the left of the one determined in the laboratory . This implies that the slope aO i s different from that indicated by our laboratory data and that our estimate of the dif - fusivity D = -K is biased . ao Computational Procedures We used the Remson computer program , which provides an approximation to the solution of (3). As we have already noted, it is possible to calculate at the same time a n approximation to the volume flux of water , v = -D ae, at any depth in the soil. For thi s calculation initial moisture content must b e specified at a number of equally space d points, called nodes, along the vertical soil profile. Our nodes were set at depths of 1, 3 , 5, 7, 9, and 11 cm. Initial moisture content was measured at approximately 5 .5 cm by tensiometer. The lysimeter plate at 11 cm depth provided another point of known moisture content . Because suction at the lysimeter plate was maintained at a constant level, the moisture content at that point coul d be obtained directly from the empirically determined moisture release curve. Estimate s of initial values at other nodes were obtaine d by linear extrapolation . Moisture content at the upper boundary (the soil surface) varie d with incoming precipitation . Results and Discussion Observed flow of water through the lysimeter plate is compared to that predicted by the flow equation in figures 2, 3, and 4 which summarize the outcomes of three field experiments, and the corresponding computer runs . The results follow a consistent pattern . Predicted and observed flows begin, peak, an d subside at about the same time . Maximu m predicted flow is about 25 percent greate r than observed. At lower levels of flow th e correspondence is closer . We conclude that the Richards flow equa - 97
2 10 7100 .160 .220 .280 .340 .400 .460 .520 .580 •640 -70 0 2 10 100 .160 .220 .280 .340 .400 .460 .520 .580 .640 .700 100 0 90 0 t.u I- 60 0 70 0 0 60 0 50 0 U 40 0 30 0 0 20 0 100 0 -10 IQQ .200 .300 400 .500 .600 .70 0 WATER FILLED POROSITY - THETA . (CU . CM . WATER)/(CU . CM . SOIL ) Figure 1 . Soil water diffusivity (top), conductivity (middle), and suction (bottom) a s functions of soil moisture content (0) . Everett gravelly sandy loam . M indicates mea n values used in model . Three samples were used to obtain the moisture-release curve . 98
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PE EIE[R-Rg RESEARC H O N CONIFEROU
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Research on Coniferous Forest Ecosy
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Contents SOME BROADER VIEWS OF BIOM
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Page AQUATIC PROCESS STUDIES 279 St
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Proceedings-Research on Coniferous
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directly, to solution of major natu
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4. Nutritional adaptation to enviro
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where validation studies could be c
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have been developed . Prior to thei
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of gross production and respiration
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Figure 1 . Aerial photo of Findley
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Nutrient levels in stream and lake
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Acknowledgments The work reported i
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inputs into the lakes . Recent stud
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was slightly raised in 1902, the la
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climate, surrounding terrestrial en
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more similar than between the diffe
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The net rate of primary production
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community structure and energy flo
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est adapted organism vacillates bet
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U .S . Analysis of Ecosystems, Inte
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successful . Thus we can see modeli
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of the external quantities of S wou
Page 47 and 48: Figure 2 . The major subsystems of
Page 49 and 50: subsystems as objects . In addition
Page 51 and 52: several models together to form the
Page 53 and 54: Proceedings-Research on Coniferous
Page 55 and 56: The study areas are located at seve
Page 57 and 58: K m Figure 1 . Watershed 2, H . J.
Page 59 and 60: An alternative way of considering i
Page 61 and 62: Snowmelt A flow chart of the snow a
Page 63 and 64: d Gs Gr = (1 - Ki) d t By integrati
Page 65 and 66: Calibration of Parameter s In gener
Page 67 and 68: model being developed under the Con
Page 69 and 70: Usually, we are interested in the o
Page 71 and 72: LINEAR Y~(T) 2nd ORDER Y2 (T) 3rd O
Page 73 and 74: the watershed. The hydrologic model
Page 77 and 78: considered as part of another food
Page 79 and 80: PRIMARY PRRODUCTIO N ■ FOLIAGE CO
Page 81 and 82: Graham, S. A. 1952. Forest entomolo
Page 83 and 84: ful in regions with relatively unif
Page 85 and 86: epresents the basic linkages betwee
Page 87 and 88: Cleary and Waring 1969, Reed 1971,
Page 89 and 90: vation that species such as Brewer
Page 91 and 92: Table 3.-Predicted plant response i
Page 93 and 94: Walker, Reed, Scott, and Webb are c
Page 95 and 96: Water and Nutrien t Movement Throug
Page 97: Here v is the volume of water cross
Page 101 and 102: .0500 .040 0 z .030 0 E L.) 0 .020
Page 105 and 106: ment of the flux of ions through th
Page 107 and 108: Table 2 .-Forest floor composition
Page 109 and 110: Table 5 .-Monthly amounts of litter
Page 111 and 112: Figure 2 illustrates how CO 2 produ
Page 113 and 114: Ballard, T. M. 1968 . Carbon dioxid
Page 115 and 116: 2. How effectively are these chemic
Page 117 and 118: Table 2 .-Nutrient budget for disso
Page 119 and 120: Figure 1 . Water content of the sur
Page 121 and 122: 0.12_ _30 rn z 0 Q z w 0 z 0 0 z Q
Page 123 and 124: _3 0 . Outflow Concentration _ __ R
Page 125 and 126: 0.10_ 0.08 _ Pea k 0.04_ Concentrat
Page 127 and 128: 8J Calciu m 0 I I I I 0.25 0.50 0.7
Page 129 and 130: water is dominant because flowing w
Page 133 and 134: Table 1.-Characteristics of study p
Page 135 and 136: Z w 2 w J w 3 0 Table 2. Average to
Page 137 and 138: of the nitrogen was not determined.
Page 139 and 140: Table 6. Total kg per hectare per y
Page 141 and 142: through litterfall . More amounts o
Page 145 and 146: Figure 3. Two additional carabiners
Page 147 and 148: 1 1 Figure 11 . The climber places
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Figure 16. The spar in use. The sus
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in our example) and the running tot
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Dashed lines are dead branches . Th
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Table 1.-Transpiration rates, mean
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this case the slopes of activity-ti
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solve equation 2 for Tm since the f
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ing methods . Every point in the sa
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Patterns in Point Displacemen t Mea
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trees indicates that the coordinate
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data; there is no obvious explanati
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where C is the percentage cover by
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Table 1.-Epiphyte biomass on the tr
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NZ. 4 50 100 150 EPIPHYTE IMPORTANC
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Table 4.-Biomass estimates (kg) for
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watershed 10 (C . T. Dyrness, perso
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Table 1 .-Some population character
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Table 2 .-Annual litter fall in Col
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Table 4. Biomass and growth increme
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Table 6.-Annual turnover from certa
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Kiil, A. D. 1968. Weight of the fue
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condition differ) ; the turnover ra
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proportionally about the same for e
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Bird Studies The forest birds were
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Further Studies The data provided f
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Terrestrial Process Studies 209
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from theses. The principal processe
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Table 1 .-Saturating light intensit
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at least 0 .06 percent CO 2 . Howev
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Pharis et al. 1967). Again Helms (1
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Effects of Leaf Temperature an d Le
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Literature Cited Baule, H., and C.
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Lopushinsky, W . 1969. Stomatal clo
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Von Bertalanffy (1969) calls nonsum
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which may be of importance in model
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The first three terms of equation 1
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P = F+ R where F = net assimilation
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This function is asymptotic to zero
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The important interaction between l
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(3 = H/AE=yo$/De (3 ) where y is th
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0.4 0.2 v 0 0 w IX -0.2 I- cr -0.4
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Table L-Diurnal energy budget compo
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4 8 10 12 14 16 18 20 22 24 TIME, H
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1970. Evapotranspiration an d meteo
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may bias the results . Meteorologic
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7.4 ppm . The lysimeters at Coshoct
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Acknowledgments The work reported i
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extracted was determined by the wei
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I - 5 -l o -1 5 HPV 1 10 . 0 I . 6
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Table 1 .- Tukey's w Multiple Compa
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studies in conifers-a review . In J
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permeable to both CO 2 and water va
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insolation (1 cal cm 2 min-1 ) and
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Aquatic Process Studies 279
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stream environments (Krygier and Ha
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S, - 4ydrolo9i c S2 = I¢rr¢strIa
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ingestion variation between individ
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contribute to detrital compartment
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volume measurement, realizing that
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fer of the indicated carbon-14 trac
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18L LAKE WATER LIGH T 50m1 HOURLY D
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a function of time and space, (b) c
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Table 1.-Suggested criteria for jud
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Table 4.-Average C, N, and P conten
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during 1963 to 1967 and from Lake S
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greater than 7 .2:1 (16:1 by atoms)
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2 .0 1 .0 0 Si P-N N-Si P-Si P-N-Si
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detectable increase in concentratio
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in lakes . J. Ecol . 29 : 280-329 .
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Woodey 1970 ; Thorne, Reeves, and M
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targets are insonified several time
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This program will automatically cal
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The FOREST SERVICE et ; U :' S D pa
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