,. .»,-. 3:. $3. . . 94.3.“. . a J 0...? 2..."... , . I .rI a. v»... .v.. .\ i!.-.-. r Irv]. w. :.l .fl.!~tn. -‘ - -§. RA :3». , a: , . .vt,r.ln til if. . Fuct». 1}; a. 14...;.:..q., l . 5 lllv.00. A L a: avvo 01 a” .. .. ta. . 1 n3€.....(5. .. .. .31.: is... .i: . . . . .¢ 1. Enhllt no?! 6.2:; z.... 3.1.... ”.12? ,1...- . .F. J .....~.vro.». :. ‘ :33»: . L a: . : . .... 3|. ya I: r .1. ‘0 L p r 5.67. . ’23,". .5. I . . 3... n . ..‘ :lnli. ‘ A . . to}? \' .. .. Eli“- .- 2 . .11... 7:01 we anANES lllllllllllllllll‘llwill 3 1293 00793 748 This is to certify that the thesis entitled THE EFFECTS OF PLANTING DENSITY AND NEED CONTROL ON THE PARTITIONING OF NITROGEN AND CARBON IN A HYBRID POPLAR PLANTATION presented by Kathleen George Maas has been accepted towards fulfillment of the requirements for M.S. degree in FOY‘CStY‘] Hat SVMM Major professor Date “'18"? 2— 0-7639 MS U is an Affirmative Action/Equal Opportunity Institution LIBRARY Michigan State University K J PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before date due. DATE DUE DATE DUE DATE DUE I MSU Is An Affirmative Amen/Equal Opportunity Institution cMmHJ HJ __ll THE EFFECTS OF PLANTING DENSITY AND WEED CONTROL ON THE PARTITIONING OF NITROGEN AND CARBON IN A HYBRID POPLAR PLANTATION BY Kathleen George Maas A THESIS Submitted to Michigan State University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE Department of Forestry 1992 ABS TRACT THE EFFECTS OF PLANTING DENSITY AND WEED CONTROL ON THE PARTITIONING OF NITROGEN AND CARBON IN A HYBRID POPLAR PLANTATION BY Kathleen George Maas A plantation of P_op_ulg_§ x W c.v. Eugenei clones was established in 1989 to determine the effects weed control and planting density have on community level C and N. A split plot design with random blocking was used. Three planting densities were split on the presence or absence of weeds. Aboveground biomass and N content of trees and weeds was determined by destructive sampling. Equations were developed to estimate tree stand biomass. At the end of the third growing season, cumulative aboveground. biomass was equivalent in, those communities that were fully occupying the site. Nitrogen content on the community level was not influenced by weed control. By the end of the third growing season weed competition did not significantly influence individual tree growth at the high planting density, but the presence of weeds had a significant negative impact on tree growth at the lower planting densities. ACKNOWLEDGEMENTS I’d like to express appreciation for my advisor, Dr. Kurt Pregitzer, who gave me independence in completing this program. My committee members Dr. Donald Dickmann and Dr. Katherine Gross whose additional assistance was most appreciated. And Dr. Carl Ramm whose help was invaluable. A special thanks to Andrew Burton and Dr. Phu Ngyen whose assistance and encouragement helped to make this thesis a success. My parents who have always allowed me to be an equal. And the loggers and sawmill workers in the family who have, unknowingly, put what I'm doing into perspective. iii LIST OF TABLES TABLE OF CONTENTS LIST OF FIGURES Chapter I INTRODUCTION II REVIEW OF LITERATURE III METHODS Experimental Design Site Preparation and Planting Weed Control Field Collection of Weeds Destructive Tree Sampling Standing Tree Measurements Canopy Transmittance Foiliar Nitrogen Concentration Soil Samples Preparation of Dried Plant Material Nitrogen Analysis Data Analysis and Hypothesis Testing Linear Regression Analysis iv Page vi xii 12 12 13 13 17 18 19 20 21 21 22 23 24 26 IV RESULTS INDIVIDUAL TREE PLANT BIOMASS Individual Tree Biomass Tree Stand Biomass Weed Biomass Total Community Biomass LEAF AREA INDEX PLANT NITROGEN CONTENT Individual Tree N Content Tree Stand N Content Weed N Content Total Community N Content SOIL V DISCUSSION AND CONCLUSIONS DISCUSSION CONCLUSIONS LIST OF REFERENCES APPENDIX A 1989 Analysis of Variance APPENDIX B 1991 and Community Analysis of Variance APPENDIX C Poplar Biomass Prediction Equations APPENDIX D 1989 Data APPENDIX E 1990 Data APPENDIX F 1991 Data APPENDIX G Community Values 29 29 41 41 43 46 48 SO 51 51 52 53 53 57 62 62 69 71 76 78 83 114 125 148 Table 10 11 A.1 A.2 A03 LIST OF TABLES Labeling of subplots in the study July 1989 individual tree means (standard deviation) September 1989 individual tree means (standard deviation) 1991 Individual tree means (standard deviation) September 1989 aboveground tree stand means (standard deviation) 1991 Aboveground tree stand means (standard deviation) Aboveground weed biomass and N content means (standard deviation) Cumulative aboveground biomass at the end of year three, means (standard deviation) Page 13 30 32 35 44 45 47 Total community nitrogen content for September 1989 aboveground biomass means (standard deviation) Total aboveground community nitrogen means (standard deviation) in 1991 Soil extractable N and mineralization rates September September September biomass September September 1989 1989 1989 1989 1989 tree height ANOVA tree diameter ANOVA individual tree total individual tree N content community N content vi 54 56 6O 76 76 77 77 1991 Poplar diameter 1991 Poplar total height 1991 Poplar leader length 1991 Poplar standing crop 1991 Poplar standing crop N co Soil mineralization rate 1991 Community N content Cumulative community biomassat of year three 1989 Prediction equations for 1991 Prediction equations for dry weight(kg) 1991 Prediction equations for total dry weight(kg) 1991 Prediction equations for area(cm ) Poplar diameters (cm, at 15cm in July 1989 from destructive Poplar diameters (cm, at 15cm in September 1989 from destruc Total height (m) of poplars in from destructive sampling Total height (m) of poplars in September 1989 from destructiv Individual tree leaf area (m2) from destructive sampling Individual tree leaf area (m2) September 1989 from destructiv Poplar woody biomass (g/tree) from destructive sampling Poplar woody biomass (g/tree) September 1989 from destructiv Total poplar aboveground bioma in July 1989 from destructive vii 78 78 _79 79 ntent 79 80 80 the end 80 poplars 81 poplar woody 81 poplar 82 poplar leaf 82 above the ground) sampling 83 above the ground) tive sampling 83 July 1989 84 e sampling 84 in July 1989 85 in e sampling 85 in July 1989 86 in e sampling 86 ss (g/tree) sampling 87 D.25 D.26 Total poplar aboveground biomass (g/tree) in September 1989 from destructive sampling Poplar total aboveground N content (9 N/tree) in July 1989 from destructive sampling Poplar total aboveground N content (9 N/tree) in September 1989 from destructive sampling Poplar woody N content (g N/tree) in July 1989 from destructive sampling Poplar woody N content (g N/tree) in September 1989 from destructive sampling Total standing tree biomass (g/mz) in September 1989 from prediction equations Leaf area index in September 1989 from prediction equations Aboveground weed biomass (g/mz) in July and September 1989 Aboveground weed N content and September 1989 Weed species (g/mz) at the density in July 1989 Weed species (g/mz) at the density in July 1989 Weed species (g/mz) at the density in July 1989 Weed species (g/mz) at the density in September 1989 Weed species (g/mz) at the density in September 1989 Weed species (g/mz) at the density in September 1989 1989 (g N/mz) in July low planting medium planting high planting low planting medium planting high planting ‘Nitrogen data from weeds sampled in July Nitrogen data from weeds sampled in September 1989 viii 88 88 89 89 90 9O 91 91 92 94 96 98 100 102 104 106 Data from the July 1989 destructive tree sampling Data from the September 1989 destructive tree sampling Aboveground weed biomass (g/mz) in 1990 Aboveground weed N content (9 N/mz) in 1990 Weed species (g/mz) at the low planting density in 1990 Weed species (g/mz) at the medium planting density in 1990 Weed species (g/mz) at the high planting density in 1990 Nitrogen data from weeds sampled in August 1990 Data from the September 1990 destructive tree sampling Prediction equations for total poplar biomass in 1990 Total poplar biomass as determined by prediction equations Poplar diameters (cm) in September 1991 from destructive sampling Poplar total height (m) in September 1991 from destructive sampling 1991 Poplar leader length (m) Individual poplar leaf area (m2) in 1991 from destructive sampling Poplar woody dry weight (g/tree) in 1991 from destructive sampling Poplar total aboveground dry weight (g/tree) in 1991 from destructive sampling Poplar woody N content (9 N/tree) in 1991 from destructive sampling Poplar total aboveground N content (9 N/tree) in 1991 from destructive sampling ix 108 111 114 114 115 117 119 121 123 124 124 125 125 126 126 127 127 128 128 F.13 F.14 F.15 F.16 Leaf area index in September 1991 from prediction equations Standing woody biomass (g/mz) in 1991 from prediction equations Total standing poplar biomass (g/mz) in 1991 from prediction equations Leaf area index in July as determined by canopy transmittance Foliar N concentration (%) in July 1991 Aboveground weed biomass (g/mz) in 1991 Aboveground weed N content (g N/mz) in 1991 Weed species (g/mz) at the low planting density in 1991 Weed species (g/mz) at the medium planting density in 1991 Weed species (g/mz) at the high planting density in 1991 Nitrogen data from weeds sampled in August 1991 Data from the September 1991 destructive tree sampling Soil moisture content (%), August 5-6, 1991 Extractable NH4-N (ug N/g soil), August 5-6, 1991 Extractable N03-N (pg N/g soil), August 5-6, 1991 Mineralization rates (ug N/g soil/day), August 1991 Data used to determine community biomass values Community N content data for September 1989 Community N content data for 1991 129 129 130 130 131 131 132 133 135 137 139 143 146 146 147 147 148 150 151 Figure 10 6.1 LIST OF FIGURES Page LTER site plan at Kellogg Biological Station 14 Diagram of poplar research plots 15 Poplar height in 1991 37 Poplar leader length in 1991 39 Individual tree leaf area in 1991 40 Individual tree woody biomass in 1991 42 Aboveground cumulative community biomass at the end of year three (means with the same letter are not significantly different, Tukey's HSD alpha=0.5) 49 Aboveground nitrogen content in the 1989 plant~ community (means with the same letter are not significantly different, Tukey’s HSD alpha=0.5) 55 Aboveground nitrogen content in the 1991 plant community (means with the same letter are not significantly different, Tukey's HSD alpha=0.5) 58 Soil Mineralization rates in August 1991 61 Aboveground poplar and weed biomass in the low planting density from 1989 to 1991 . 152 Aboveground poplar and weed biomass in the medium planting density from 1989 to 1991 153 Aboveground poplar and weed biomass in the high planting density from 1989 to 1991 154 xi CHAPTER I INTRODUCTION Trees grown under short rotation intensive culture (SRIC) parallel agricultural systems where high productivity and harvestable yields are accomplished by the use of intensive management with a dependence on tillage and chemicals. A present trend in the United States and internationally' is 'toward. low-input, sustainable systems which will eventually mimic natural ecosystems where essential nutrients are more fully utilized and recycled. Rotations of three to ten years under SRIC are achieved through breeding, intensive site preparation, weed control, and fertilizers (Ranney et al. 1987). Management practices to reduce or eliminate competition from weeds utilize herbicides and tillage. This reduction in standing biomass coupled with applied fertilizer increases the possibility of nitrate leaching. Nitrate levels are expected to change under management. Disturbance increases the level of nitrate in the soil solution and concentrations are kept at high levels by fertilization (Vituosek 1983). While present in the soil solution, nitrate is susceptible to leaching and leaching is most likely to occur when the site is not fully occupied (Shepherd 1986). Maximum nitrogen uptake by a community is dependent on the nature of the herbaceous vegetation (Baker et al. 1974). Annual crops are less efficient at nitrogen uptake than perennial plants (White, 1988) . Weed control reduces the ability of an ecosystem to retain nitrogen, increasing the chance of nitrate leaching. Most hardwoods grown in plantations are intolerant of weed competition (Kennedy 1984) necessitating weed control. Without good weed control SRIC with hardwoods is not feasible (Ranney et al. 1987). The competitive inabilities of plantation trees is in part due to breeding. Fast growth rates which require higher allocation of photosynthate to leaf tissue comes at the expense of the root system (Mooney and Gulman 1983). While the trees are partially limited in root growth, decreasing their ability to capture belowground resources, weeds are well adapted to disturbed sites where rapid growth is favored (Grime 1977) and exploitation of belowground resources is required. Resources captured by weeds may further limit the growth of trees in SRIC systems. Previous studies on weed-crop competition have concentrated on the emergence pattern and spatial influence weeds have on agronomic crops (e.g. Beckett et al. 1988, and Monks and Oliver 1988). These studies have yielded a typical result, reduction in the weed population results in an increase in crop productivity as measured by biomass and harvestable yield. The main variables of competition examined are light interception and soil moisture (e.g. Lemieux et al. 1987). Few studies have dealt with how plants sequester and allocate nitrogen under competition. This thesis examines the first three years of growth in a hybrid Populus plantation grown under a short rotation coppice system. The objectives of the study are to understand aboveground partitioning of nitrogen and carbon at the community level. Sub-plots have been established to examine the effect stand density has on community level N and C partitioning and to understand the role of plant competition in the partitioning process. The three null hypotheses of the study are: 1) competition from weeds does not decrease tree standing biomass, height, stem diameter, and tissue nitrogen concentration after three years of growth; 2) the total aboveground nitrogen content and biomass at the community level does not differ among plots where competition has been controlled versus those left untreated; and 3) nitrogen mineralization rates are the same regardless of weed control. This thesis incorporates data from the first three- years of the study. Only a fraction of the presented analysis is used to discuss the hypothesis the rest is included as reference for later use. Data from 1989 and 1990 was collected under the direction of Dr. Kurt Pregitzer and Dr. Katherine Gross. The author collected the data in 1991. CHAPTER II REVIEW OF LITERATURE This review of literature includes studies on trees in SRIC systems as well as agricultural systems. Agricultural studies have generated the most relevant information on weed competition with crOps. Topics of the review include short rotation intensive culture, the effect weeds and crops have on each other as seen in yield, nitrogen content, and in tissue nitrogen concentration. Short rotation intensive culture (SRIC) of hardwoods is aimed at high production through coppice generations on marginal to good agricultural sites with rotations of three to ten years (Ranney et al. 1987). Anderson et al. (1983) has defined short rotation plantations as those that have less than 5,000 trees per hectare with harvesting cycles of six to ten years. In contrast, mini-rotation plantations were defined as having densities of 5,000 or more trees per hectare with harvesting cycles of five years or less. The primary products of SRIC plantations are wood fiber for direct combustion or subsequent conversion to methanol (Moran and Nautiyal 1985). Species used for SRIC in North America include Populus, Salix, Betula, Platanus, Alnus, M We. _J._JaRob'n' 2__£_seudoaca ia. and ___rAce saggharinum (Anderson et al. 1983, Ranney et al. 1987). 5 Successful plantations are dependent on intensive management, which includes improved clones as stock, intensive site preparation, weed control, fertilizer (Ranney et al. 1987), and often irrigation (Anderson et al. 1983) . Weed control is considered critical before canopy closure. Anderson and others (1983) have identified competition from grass as the most detrimental to plantation growth. High yields are produced under SRIC management. Some yields produced under experimental trials have been compiled by Cannell and Smith (1980). Platanus mug produced current annual increments (CAI) of 10-12 tons/ha/year and mean annual increments (MAI) of 14- 16 tons/ha/year (Kormanik et al. 1973). Dutrow (1971) reported. CAI values for’ .2. oc ' e a 's of 12-13 tons/ha/year and MAI values of 16-18 tons/ha/year. Reported, yields for ‘Egpglgg, have been lower. ,ggpglgg Wm produced CAI of 9-10 tons/ha/year and MAI of 12-14 tons/ha/year (Cannell 1980). Populus x eurgmericana produced CAI of 7-8 tons/ha/year and MAI of 9-10 tons/ha/year (Anderson and Zsuffa 1977, Zsuffa et al. 1977). Benefits of weed control to plantation trees include increased survival (Kennedy 1984), increased. height and diameter (Kennedy-1984, Nelson et al. 1981, and Fitzgerald et al. 1975), and early crown closure (Knowe et a1. 1985). The limiting resource is often identified as soil moisture (McLaughlin et al. 1987, Nelson et al. 1981). Although nitrogen has been identified as the most limiting resource in intensively managed forest systems (Shepherd 1986) and in other temperate forest. production systems (Birk and Vituosek 1986) it is not often considered in SRIC research. This may be due to the ability to amend soil with fertilizer. Nitrogen is typically the most heavily applied fertilizer (Groffman et al. 1986). In agronomic crops it is suggested that if light and nutrients (through the application of fertilizer) are adequate then soil moisture is usually the limiting factor (Young et al. 1984). The effect weeds have on crop production is often density dependent. In corn (gee page L.), a low density of quackgrass [Elytrigia repens (L.) Nevski] can reduce corn yields 12 to 16% and high densities can reduce yields 37% (Young et al. 1984). Similar reductions (13 to 39%) in sugar beets (Beta, vulgaris L.) have been shown as well (Schweizer 1981). ‘For tree crops the first year has been identified as the most crucial year for weed control (Fitzgerald et al. 1975) and control is suggested until canopy closure (Dickmann and Stuart 1983). With weed control, survival in loblolly pine (Pings—teed; L.) was 89% by age four as compared to 61% without weed control (Tiarks and Haywood 1986). In the same study a 63% increase in volume was seen with weed control. Knowe et al. (1985) saw a seven fold increase in the first two years of growth in loblolly pine when weeds were controlled. The extent to which the benefits of weed control carry through a rotation has been suggested by several authors. The first three years of tree growth is substantially reduced by weed competition (McLaughlin et al. 1987, Nelson et al. 1981). The fourth and fifth growing seasons, as well, show increased growth (Kennedy 1984) . These early results may not be evident at the end of long rotations. McLauglin et al. (1987) did not see any growth advantage after four years in hybrid Mug receiving weed control. The early growth increase may result in shortening rotations (Knowe et al. 1985, Nelson et al. 1981), but documentation has not yet been published. SRIC may show the greatest benefit of weed control, as measured by merchantable volume, since it is based on rotations of 3-10 years. The effect a crop has on the weed population has not been extensively studied. In one study, velvet leaf (M911 thegphras—ti Medik.) was shown to reduce soybean (QM max L.) yields to 41 and 46% in two consecutive years. At the same time the velvet leaf seed yields were reduced to 58 and 93% by the soybeans (Munger et al. 1987). Ghafar and Watson (1983) increased corn planting density from the normal practice of 66,700 plants/ha to 133,300 plants/ha and reduced the number of yellow nutsedge (m w L.) tubers by 71% In the same study reducing the planting density to 33,300 plants / ha 8 increased tuber increased by 41%. The researchers also found that biomass of yellow nutsedge between corn rows was unaffected by planting density whereas at the higher planting density yellow nutsedge biomass was significantly reduced within the rows. The effect of shading by soybeans on weeds was examined. by Murphy and Gossett (1981). Soybeans were allowed to establish weed free for three weeks to allow for canopy development. Weed green biomass was reduced 85 to 97% when they emerged after the soybeans. At the peak of canopy development only 12% of radiant light reached the ground. In a study of cogongrass [Imperata cylindrica (L.) Beauv.] shading by trees reduced total plant dry weight, leaf’ area and. the number' of (grass rhizomes and leaves (Patterson 1980). As full light was reduced to 56%, dry weight production of cogongrass decreased by 2 to 2.9-fold. A reduction of light to 11% resulted in a further 15 to 30- fold decrease in weed dry weight. Nitrogen recovery from the soil is affected by the type of herbaceous cover. The stress induced by weed competition on trees is also influenced by the weed species. During the course of a rotation the species composition of the weeds present is expected to change. Where SRIC plantations have been established on agricultural land, herbaceous plants are the predominant weeds. Ruderals are well adapted to seasonal disturbances associated with cultivation. Many of these annual weeds 9 utilize the C4 photosynthetic pathway and are thought to have an advantage over C3 annuals in environments where light and temperature levels are high and water is limited (Altieri 1988). Plants with C4 photosynthesis tend to be drought resistant (Baker 1974) . As conditions become more moderate under decreasing cultivation disturbance and as shade from trees increases, C3 annuals have the advantage over C4 annuals. The C4 pathway consumes too much energy to be efficient under moderate conditions (Altieri 1988). The ruderals will be replaced. by competitive perennial herbs which are adapted to relatively productive habitats (Grime 1977). A change in species composition should occur in plantations that do not use tillage as a means of weed control. Nitrogen was found to be the limiting resource in short rotation hardwood stands (Wittwer et al. 1978). Studies examining nitrogen in intensively managed stands generally include fertilizer as part of the treatments, particularly in the planting year. When fertilizer was applied in the planting year of a loblolly pine stand (kept weed free) the trees recovered 46% of the applied nitrogen by the end of the third year. Whereas in a herbaceous plant stand 58% was recovered (Baker et al. 1974). Annual uptake of nitrogen in black cottonwood ngglus trichocarpa Torr_ & Gray and E. trichocarpa x 2. deltoides hybrids ranged from 95 kg N/ha for the former to 276 kg N/ha for the hybrids (Heilman and Stettler 1986). 10 Plant tissue nitrogen concentrations generally decrease under competition and over time. Total leaf nitrogen in Citrus trees was reduced (values not given) by annual weeds and Bermudagrass [gyngggn dactylon (L.) Person] (Jordan and Jordan 1981) . Nitrogen concentration in loblolly pine foliage was found to be 12.5 g/kg in the first season and decreased to 5.2 g/kg in the sixth growing season (Tiarks and Haywood 1986). Kennedy (1984) also documented that the highest tissue concentration was seen in the first growing season and concentrations decreased with each consecutive year. Understory vegetation concentrations were at 1.07% Foliar nitrogen concentrations in hardwood trees averaged 1.63% in weedy plots, 1.78% in mowed plots and 1.94% in disked plots. Heilman (1985) found a difference of nitrogen concentration in black cottonwood leaves depending on position in the crown. Leaves at the top of the leader averaged 2.16% nitrogen. Leaves on the youngest proleptic branches averaged 2.21% and leaves from mid crown averaged 2.14%. Nitrogen concentrations from these three positions were not significantly different. They were, however, significantly different from leaves in the lower half of the crown which averaged 1.75%. Date of sampling also exhibited significant differences in nitrogen concentration for leaves, decreasing from 2.28% on September 5 to 2.05% on September 25 to 1.77% on October 7. McLaughlin et al. (1987) found no significant 11 difference in stem and branch nitrogen concentrations the planting year of Populus hybrids in weed controlled plots that were fertilized or unfertilized. At the end of the second year fertilizer did significantly increase nitrogen concentrations in stem and branch components, 0.87% with fertilizer compared to 0.66% with no fertilizer. Total nitrogen content of leaf litter in fertilized plots was 59 to 103 kg' N/ha and. the nitrogen. content of’ above and belowground portions ranged from 129 to 182 kg N/ha. CHAPTER I I I METHODS e ' a De ' n The study was conducted in southwestern Michigan at the Kellogg Biological Station’s Long Term Ecological Research site. The soil type is Kalamazoo silt loam (fine- loamy, mixed, mesic Typic Hapludalf). The site has a history of agricultural cropping and tillage by moldboard plow. The experimental design is a split plot with random blocking. Three planting densities are split on weed control. Low planting density is at a 2m x 3m spacing (0.17 trees/m2; 1,667 trees/ha); medium planting density at 1m x 2m spacing (0.5 trees/m2; 5,000 trees/ha); and high density is at 0.5m x 1m spacing (2.0 trees/m2; 20,000 trees/ha). The treatments were replicated six times. The area of each density treatment is 50m x 23.2m and each subplot is 25m x 21.6m (Figures 1 and 2). Table 1 shows the treatment notations used in the study. The weed population is naturally occurring, not seeded. 12 13 Table 1 Labeling of subplots in the study Block System* Planting Density Weed Control 1-6 5 1 (Low) 1 (Control) 2 (Medium) 0 (No Control) 3 (High) * There are seven cropping systems in the study as a whole, treatment 5 denotes the poplar plantations. Site Ptepatatgon and PLanttng J._9_8_2 The plots were plowed with a moldboard plow and disked in late .April. Hardwood cuttings of the clone W x egrametigana cv. Eugenei were planted in late April and in early May. Each subplot designated to be free of weeds received an application of herbicide shortly after planting. The tank mixture was: 1.0 qt/A of oxyfluorfen (Goale); 1.5 qt/A of linuron (Lorox 4L6); and 1.5 qt/A of simazine (Princep 4L6). The mixture was sprayed at a rate of 20 gallons/A. All subplots were fertilized in early June with 110 kg N/ha as ammonium nitrate. We ontrol 1182 Blanket herbicide was appl ied as part of the site preparation. Hand removal of weeds was used to keep 'subplots weed free during the growing season. Soil activity l4 fl 3" UI grew: 5-5: BLOCK 5 POPLAR TREATMENT FIGURE 1 LTER site plan at Kellogg Biological Station 15 muo~m noncomou hedmom mo aoumcwo N meUHm m x095 Lo>06 ozomoa 95:03 E .xN ml_ ”mxoOLm to>oo ozomoc 95:03 E .xN Em“ 9:an E .xN _lm can 95:03 E .xN GIN TN Em“ EmN £.9_~ seer and 16 of simazine appeared to injure Eugenei in some blocks, most notably in block three which was partially replanted in 1990. The subplots in block three were partially replanted. L910 Plots were mowed and weeds were hoed through the summer. Mowing is not a favorable method for weed control. In a study of hardwoods it was found that mowing as weed control showed no significant difference in tree yield over plots with no weed control (Kennedy 1984). Competition was seen whether the weeds were allowed to grow (3 to 4 weeks) and mowed or to grow continuously. 12g; Weed control was achieved through the use of herbicide and hand removal. The weed controlled subplots were mowed in mid-May. The weeds were allowed to recover and begin active growth before spraying. A 2% glyphosate (Roundupe) solution was applied using a backpack sprayer the first week of June in the low and medium planting densities. Eugenei sprouts emerging between the rows were avoided, but when accidentally sprayed, the leaves were removed to prevent translocation of glyphosate. Due to limited space between the rows at the high planting density these subplots were not sprayed (except for rhizomatous grass), the weeds were removed by hand. At the end of June the effectiveness of Roundupe was evaluated and it was decided to respray the low and medium plots. Weed control was averaging 40-75% control as determined by remaining herbaceous cover. The low and 17 medium plots were then spot sprayed with 2% Roundup@ solution. Weed control from the second spraying appeared adequate. During the rest of the growing season weeds were periodically removed by hand. FieLd Col;ection of Weeds I982 Weeds were sampled on July 21 and September 15. One quadrat (0.1m x 2.0m) was harvested in each subplot without weed. control. 'The quadrats 'were centered. around trees across the rows. All weeds lying within the quadrat were clipped at the ground line, this included senescent plants (usually winter annuals). Plants were bagged and refrigerated until they could be sorted by species and dried at 60°C for 72 hours. Plants that were not identified were listed as unknown dicots or monocots. 1990 Weeds were sampled on August 8 and 9 within wooden quadrats (0.5m x 2m). Quadrat size was increased from that of 1989 to 1.0m2. One quadrat was randomly placed in each subplot. Plants were bagged and sorted as in 1989. 3.22; Weeds were sampled July 30 through August 1. Two quadrats (0.5 X 2.0m) were randomly placed in each subplot. The placement of the quadrats avoided areas that were previously sampled. The quadrats were again centered around trees across rows to include the maximum number of trees possible. All plants within the quadrats were clipped at Cl Cc H IL) / 1D Dre 0f (be: 18 ground level, this included any Eugenei root suckers present. Weeds were then bagged and refrigerated until they could be sorted by species and dried as in the previous two years. Destructive Tree Sampling Aboveground portions of Eugenei trees were destructively sampled in 1989 and 1991. The trees were cut at 15cm above the ground and separated into components of stem, branches, and leaves. 1g§2 Two sets of trees were sampled, one on July 20 and one September 11-15. Trees in September were sampled shortly after the terminal bud on the leader had set, but before the majority of leaves began to abscise. Two adjacent trees in each subplot were sampled each time. Diameters were measured after the trees were cut and total height was measured. Individual leaf areas were measured with the Li- cor Li-3100 Area Meter before the leaves were dried. Components were dried at 60-65°C for 72 hours. ;22; Two trees were sampled from each subplot September 3-5 after the terminal bud had set. The sampling was done over a three day period. The sampling was stratified and proportionally allocated. Sampling was based on diameters of permanently marked trees in the middle of each plot (Demaerschalk and Kozak 1974). Two trees per subplot were 91 We an: 19 then randomly selected to fit the sampling scheme with a total of 12 trees per treatment. Edge trees were avoided. Diameters were measured before trees were cut. After felling, total height was measured along with the length of the leader from the previous years terminal bud scale scar to the current apical meristem. Height from the ground to the first live branch was also recorded. Leader leaves were removed and kept separate from lateral branch leaves. Branches were removed, counted, and bagged. The stem was cut and bundled. Individual leaf area was measured with the Li-cor Li-3100 Area Meter. Leaves were dried in a forced air oven at 60°C for 24-72 hours before weighing. Woody components were dried in a kiln at 65°C for one week before weighing. Standing Itee Measurements 1.289 .and 1990 Trees in the center of each subplot were marked for annual monitoring of growth. In September the diameters of these trees were measured at 15cm above the ground with calipers. The number of trees in each subplot were: at the low planting density, 12 trees; at the medium and high planting densities 28 trees in each subplot. ;2g1 An area of 5m X 5m was set in the middle of each plot. All trees within this area were measured for total height (with telescoping pole) and diameter (with calipers) at 15cm above the ground. At the high planting density this area 20 included 50 trees per subplot, at the medium planting density 15 trees per subplot, and at the low density 6 trees per subplot. These trees were measured shortly after the destructive sampling, starting in late September and ending in early November. 5 't e 1221 Canopy transmittance was measured July 11, starting at 1200 hours and ending at 1415 hours. The Sunfleck Ceptometer (model SF-80, Decagon Devices, Inc.) used measured photosynthetically active radiation (PAR, 400- 700nm). The measurements were taken at the height of the weed canopy, about one meter above the ground. Three points in each subplot were randomly chosen and three readings were taken at each point in a 360 degree circle at equal increments. The ceptometer was kept horizontal with the ground. Measurements of total incoming PAR were taken in the open field before and after measuring each block. Leaf area index (LAI, ratio of leaf surface area to unit area of ground) was indirectly estimated by converting canopy transmittance to LAI by using the Beer-Lambert Law (Pierce and Running 1988). The Beer-Lambert Law states: LAI = -ln (Qi/QoI/K. where Qi is canopy transmittance, 00 is total incoming PAR, and K is a light extinction coefficient. The. extinction coefficient used was 0.39 (Raunee 1976). 12: an zIii: 21 Foilia; Nittogen Concentration 122;; Four leaves from two ‘trees in each subplot were collected to asses nitrogen status during the growing season. On July 10, 1991 the 4th, 5th, 6th, and 7th leaves down from the apical meristem on the leader were collected. Leaves were kept on ice in the field, oven dried at 60°C for 24 hours and ground for analysis. W 3.91;. Soil samples were taken to asses available ammonium (NH4+) and. nitrate (NO3'). Soil samples ‘were 'taken. on August 5. One soil core (10cm long X 5cm diameter) was taken randomly beneath the tree's canopy. A total of 12 cores were excavated from each treatment (two per subplot). Loose organic matter on the soil surface was removed prior to taking the cores. The cores were restricted to the Ap horizon. The samples were kept on ice in the field and then refrigerated until they could be processed. The samples were processed within 36 hours. The samples were passed through a 2mm sieve to remove rocks and roots. A subsample was taken to determine soil moisture content and dried in an oven at 95°C until a constant mass was reached. Two Sg field moist subsamples were removed. One subsample was used to determine initial extractable levels of NH4,+ and N03”, and the second sample was incubated to determine Inineralizable nitrogen. The method of sample treatment and We 19; lo! 22 nitrogen analysis follow that of Vituosek et al. (1982) and Zak et al. (1989). Fifty milliliters (50ml) of 2M KCl (1489/1) was added to each subsample, mixed and the sample was allowed to sit for 24 hours. The extracts were then filtered (No. 42 Whatman ashless filters) and refrigerated until they could be analyzed with the Technicon II Analyzer (Technicon 1977b). The second 5g sample was placed in plastic cups with ventilated lids and aerobically incubated for 25 days. The samples were incubated in the dark at 30°C with approximately 85% relative humidity. The samples were kept at field capacity by periodically adding water. At the end of the incubation period the samples were extracted with 2M KCl as outlined above. Ptepatntion of Dried Plant Material L289 and 1990 Dried plant tissues was coarsely ground and then reground through a 20-mesh screen. The three weed species with the highest biomass values in each quadrat were ground separately. The remaining species were combined and ground as a group. 1221 Large samples were subsampled. Branches were subsampled to include a proportional amount (based on weight) of all ages of tissues. The stems were in bundle lengths of 2 to 3 feet long. A section of about an inch long was cut out of the middle of each bundle. These sections were then split into match stick size pieces for 23 grinding. For large diameter stems only a quarter of the sections were kept. Weeds were subsampled when necessary and care was taken to include a proportional amount of all tissue types. Dried plant tissue was ground twice through a 20-mesh screen based on biomass values as in 1989 and 1991. Nittogen Analysis ;989 and 1990 Nitrogen in plant tissue was analyzed using a block digester and the Technicon AutoAnalyzer II. The Kjeldahl procedure tot determine nitrogen is based on a colorimetric method (read at 660nm). Detailed information can be found in the Technicon Manual (1977). Samples of 0.25g were placed in 75ml digestion tubes with two or three boiling chips and one Kjeltab and the catalyst. Nine milliliters (9ml) of concentrated H2804 was added. The mixture was then heated at 380 degrees for 1 to 1-1/2 hours or until the digestion turned clear and the mixture was then allowed to cool for 15-20 minutes. Fifteen milliliters (15ml) of deionized water was added and the mixture allowed to cool for another 20 minutes. The tubes were then brought to volume with deionized water and thoroughly mixed, decanted, and the supernatant poured into sample cups for analysis with the Technicon Auto-Analyzer II. Concentrations were corrected for baseline drift and for tissue moisture content. a: T1: da 31‘ I‘m 24 tag; Ground plant samples were analyzed by combustion with the iNitrogen Analyzer 1500 (series 2, Carlo Erba Instruments). Acetanilide was the standard used to create nitrogen concentration curves. Weights of acetanilide ranging from 0.3mg to 4.0 mg were used in constructing the calibration curves. Samples of the ground plant tissue ranging from 9mg to 14mg were placed in tin cups and folded for analysis. Ground citrus leaves from the National Bureau of Standards were used to check the quality of the analysis. Twenty percent of the samples were replicated. Reproducibility' between. replications.‘wasi good, less than 0.02% difference in N concentration between samples. Weed samples generally had higher variability between replicate samples because all tissue types were ground together. Final nitrogen concentrations were corrected for moisture content in the samples. Data Analysis and Hypothesis Testing Analysis of variance (ANOVA) was performed on the data using procedures for a split plot design using SAS (SAS Institute Inc. 1985). Tukey's studentized range test (HSD) was used to separate significant means. Before analysis of variance was done all data were checked for normality and for homogeneity of variances. The 1991 poplar data showed a significant block effect for most variables. Block three was usually significantly lower than block two. This may have been a result of simizine injury in the pla gro the was mair OCCL dama the {8130' equat destr C.4 trees was C 25 planting year and block three, possibly, being a poorer growing site than the others. Block three was removed from the 1991 data and community totals and analysis of variance was rerun. Herbicide injury was severe enough in that the mainsite ‘was partially replanted in 1990 and replanting occurred in some of the subplots. The severe herbicide damage was the justification for omitting block three from the statistical analysis. It did not appear necessary to remove block three from the 1989 and 1990 data. Leaf area index was determined by applying prediction equations created through linear regressions of the destructive samples taken in 1989 and 1991 (Tables C.1 and IC.4, Appendix C). The leaf area of the permanently marked trees in 1989 and the trees within a 5m x 5m area in 1991 was calculated with the equations. Community biomass was determined by adding weed biomass from all three years to the total tree biomass in 1991. Tree leaf biomass from 1989 and 1990 was added as well. No destructive sampling of trees was done in 1990 in each treatment. The leaf biomass ‘was interpolated from the September 1989 and 1991 values on a subplot basis. Tree biomass was determined by applying the developed prediction equations to standing tree measurements 1991 (Table C.3, Appendix C). Values from 1989 weed data were multiplied by 2 2 an expansion factor to bring them from 0.2m area to 1.0m area equivalent to the 1990 and 1991 weed data. 26 Community nitrogen contents for aboveground biomass were: determined separately for September 1989 and 1991. Total tree nitrogen was combined with weed nitrogen contents. Weed nitrogen contents were presented on g/m2 basis and individual tree values were converted to an area value. It was assumed that unlike tree biomass where carbon has accrued over time in woody tissue that nitrogen is recycled more frequently through litter fall and senescence of roots and ground flora. For this reason biomass was combined over three years, whereas nitrogen contents were analyzed on a year by year basis. i ea e ession Anal sis Linear regression analysis was employed to develop prediction equations to predict total tree biomass and total leaf area in 1989. Analysis from 1989 was done on the July and September destructive harvests (Pregitzer and Gross unpublished). Analysis of variance (ANOVA) was conducted to determine whether or not density and weed control significantly affected tree biomass, leaf area or stem diameter. Diameter-squared was used in all stages of the analysis since scatter plots indicated a quadratic relationship between diameter and leaf area and tree biomass. Planting density did not significantly effect tree biomass or leaf area. In September of 1989, tree density did effect stem diameter. Weeds influenced all three 27 variables both months, except for total weight of trees harvested in July. From the significant effects seen in the ANOVAs it was determined that a single regression equation would be inadequate to predict leaf area or tree weight from stem diameter-squared. A test of the homogeneity of regression coefficients was done. As a result it was deemed necessary to use separate models for July and September harvests. From the July harvest it was also necessary to have separate models to predict tree biomass based on the presence or absence of weeds. In 1991, analysis of variance showed that density and weed control had significant effects on tree diameter, woody biomass, total biomass, and leaf area. Stem diameter still appeared as a quadratic relationship with biomass and leaf area. Accuracy of the prediction equation was improved by adding total tree height as a dependent variable along with diameter-squared. Separate models were developed for each planting density based on the presence or absence of weeds using the NCSS computer program (Hintze 1990). In both years extreme outlying values were removed from the analysis. The outliers were assumed unrepresentative of the sample due to measurement error, incorrect application of treatment, or environmental damage. Removal of observations was avoided as much as possible in 1991 since the maximum number of observations each equation was based on was 12 trees. 28 Equations for predicting total tree biomass in July and September of 1989 are shown in Table C.1, .Appendix C (Pregitzer' and. Gross unpublished). The coefficients of determination (R2) were adjusted for degrees of freedom. The total number of observations (N) is also given. Predicted weight has the units of grams (g) and the predicted leaf area is in centimeters-squared (cmz). Equations were developed for July 1989, but are not applied here since no standing tree measurements were taken. In September, trees in the center of each subplot were measured for diameter at 15cm and these trees were used to determine total tree biomass on an area basis and leaf area index. In 1991 equations to predict woody biomass, total tree biomass, and leaf area are shown in Tables C.2, C.3, and C.4 (Appendix C). The predicted woody and total biomass has the units of kilogram (kg) and the leaf area is expressed in centimeter-squared (cmz). These equations for 1991 include block three. Although there is a significant block effect when block three is present it did contain the lower diameter classes which were present in all blocks when the standing trees were measured. Block three helps to assure that all standing trees fall within the data the prediction 'equations were based on. Equations for both years should be viewed with caution if applied to other sites or growing conditions. CHAPTER IV RESULTS Results are presented here as individual tree variables; plant biomass for individual trees, the stand of trees, weed populations, and the community; leaf area index; plant nitrogen content (follows the same format as biomass); and soil. Analysis of variance tables for some of the measured variables can be found in Appendix A (September 1989 tree harvest) and Appendix B (1991 tree harvest and community). INDIVIDUAL TREE Density and weed control had no significant influence on tree height or diameter in July 1989. Within a planting density weed control did not significantly increase diameter, height, or leaf area (Table 2). By September 1989, density and weed' control appeared to have had a significant effect on tree diameter. Only weed control affected tree height and individual tree leaf area. Tree diameter was significantly lower at each density when weeds were not controlled (Table 3). The low planting density plots with weed control produced trees with the 29 30 clam.mvmm.¢a mmsa.acmm.e anamo.ovefl.o ammo.ocsm.o ammo.ovas.o cum mama.mvmm.am mmmm.~cms.m ammo.ocm~.o «Ama.ovmm.o mAsa.ocmm.o Hum «Amm.mv6m.as mamm.flcom.m ammo.ovma.o ammo.ocos.o ammo.ovmo.o oum mAsm.ncmH.¢H onv.Hcmm.m nmkmo.ocva.o mAmH.oc66.o maed.ovms.o Hum onm.mV~¢.oH ono.mvmm.m anamo.ocma.o mxsa.ocom.o mama.ocns.o onH mxsm.ovso.ma mAHo.~cmm.m nmxmm.ocma.o mams.ocmo.a mmA¢H.ocms.o Hus Awe Low Amzv Asa Azov mmmEOflm mmMEOHm MOH< ufiwflmm kumfimflo HUGOE¢MOHB Houoe >UOOS moon m manna Acofluma>mo ouopcmumv mcoma menu Hosofi>wocH mama >Hsn 31 .mb mos manoeum> some you mcofium>ummno Hwnfisz .mo.oumnmam nmm m.>oxsa .ucmummuwo >Hucoofimacmflm uoc mum Houuma mean ecu nus: menu: a .on Houucoo com: o: no AHV Houusoo pmo3 ma cameo ccouom one can Anaheim .esuumsum .3oHIHc susmcmu suspense mmsuwcmwm cameo amuse H nAHH.ocs~.o ammo.oc¢~.o nAHo.oc¢o.o cum mxma.ocmm.o mA¢H.ocmm.o ammo.ocofl.o Hum nAos.oco~.o nAmo.ova.o nAHo.ovmo.o oum nmAmH.ocmv.o nmAmH.ocsm.o nmxmo.ocoo.o Hum nakem.ocom.o nAo~.ova.o nameo.ocoo.o old nmAmH.ovm¢.o nmAmH.ocsn.o nmxno.ocmo.o and Ice Ace 165 ucmucou ucmucoo acoucoo ucmfiummue z Hmuoe 2 Oman 2 >600: 16.»:005 N manna 32 nAmm.HHvo.oe nao.oavv.ma ammo.ocma.o «Am~.ocmfl.a omma.ovvm.o oum nmAD.HmVs.soH nmAH.mavm.mm nmAmH.ovsm.o mxsm.ocm¢.a nmxmm.ocs¢.a Hum nkm.omvo.om nxv.aavo.aa nAHH.onH.o mAs~.oV~H.H oA-.ov~m.o onm nxm.smc~.moa n16.mmcs.om nmAem.ocsm.o mamm.oc6m.a nmamm.ocm¢.a Hum nxm.mmvo.sm nAH.¢mvm.Hm nAma.ocm~.o mAmm.ocoa.H on1m~.ovma.fl oua mam.mmcm.msa mam.emvm.sm mxmm.ocam.o axo~.ccs¢.a mmamm.ocmm.a and Lev Loy Amzc Ase Azov mmeOAm mmoeoflm owns unwwom umumsofio Hucwfiummue Hence >6003 mama m OHQMB Acofluofi>oo unaccoumv mcoofi menu Hosow>wocfl mmma Honsoummm 33 .mo.oumnmao om: m.>mxsa .ucmumuuflo >Hucmowuflcowm uoc mum umvumfl meow may sue: mammz .Hh mfl3 mdnflfihm.) SUMO HOW WCOHUMEOMQO HO Hwflfifiz .on Houucoo Umm3 o: no Adv Honucoo 0mm: ma m Duane ecoomm on» can Asaflnum .asflume-m .3oanac susmcmn meanness moflmflcasm Duane amuse H oAm~.one.o oxss.oc¢m.o 0166.6cmo.o oum nmmmo.ocea.~ onase.ocam.a nmxmm.ocmm.o Hum oAHm.ocme.o 61¢~.ocmm.o camo.ocma.o cum mamm.avm~.m nmmmo.avmm.a onAH~.ovH¢.o Ham onAmo.oVHm.o eoAHm.ovH6.o onAsH.oco~.o onH mAm~.HVH6.m mxmm.ocss.m mAHm.ocmm.o Hid Amy Aoc Ame ucmucou ucmucou ucmucoo ucmfiummue z sauce 2 meme 2 >600: Ae.u:ooc m manna 34 largest diameters (1.92cm), but these were not significantly different from the medium and high density trees. The same trend was seen with individual tree leaf area, with the highest leaf area (0.91m2) found in the low density weed control plots. Mean heights were not significantly different between treatments. At the end of the third growing season, 1991, interactions between density and weed control influenced tree diameter, height, leader length, and individual tree leaf area. Tree height and leader length appeared independent of planting density although a significant interaction with weed control occurred. Tree diameter decreased with increased planting density when weeds were controlled. The low and medium density tree diameters were significantly higher than the high density trees (Table 4). When the weeds were not controlled tree diameter increased with increased planting density. These diameters were not significantly different from one another or from those at high density trees with weed control. Weed control resulted in a 2.2-fold diameter increase in the low density trees; a 1.7-fold increase in medium density trees: and a 1.2-fold increase in high density tree diameter. Tree height decreased with increasing planting density in weed-free plots (Figure 3). Low density tree height was significantly greater than the high density tree mean (Table 4). Tree height, when weeds were present, increased as jplanting density increased. High density trees without weed 35 61mmmvsom vom.oc~m.o onxmm.ocmm.fl onAH6.oV-.v oAm6.ocH~.m oum clawevsoaa oam~.ocmm.o commm.ovmm.a nmxmm.oves.e omms.ocmm.n Hum oxmomcnmo oAm~.oc¢s.o comma.ovos.a ovom.ovmm.m ofism.ovmm.m oum nfisemvmmem nmsm.avmm.m nmxsm.ovmo.m 816m.ovm¢.m clam.ovmm.m Hum oAmNNVmse onAmm.ocom.o 61mH.onH.H 6145.6cem.~ ammo.acm~.m old mammmvmamm 61mm.ocm¢.s ammo.ovea.~ mamm.ovso.m mmAmm.ovm~.e HIH Amy A 25 Rev Rec Leos mmmEOAm m we numcmq unmflmm nmumfimfia Hucmaummus snooz mama smegma Acowuma>mc oumocmumv mamms mmuu Hmsofl>flch Hmma w OHQMB 36 .mo.oumzmam om: m.>mx:B .usmummuflo >Hpcmoflmscmwm no: mum umuuma mamm mnu zpwz mammz .00 mm; manmflum> umm mcowum>ummno mo amnesz .on Houusoo omm3 o: no Adv Houucoo m omma ma ocoomm may one Anmwnlm .Esflcmsim .3oaiav >uwmcmo gcflucmHQ mmflmacmflm meao umuflm H nxmm.avom.¢ 6166.6me.a namm.acmm.m omsmmvomm onm exam.ovem.m okma.ovee.a ammo.ocom.s omamecomafl Hum exam.flvmm.m oxsm.ocmm.a nAem.vam.e oxmmwvass oum blew.mcma.oa n1m6.ovvo.v namm.mcom.as nAHoovmmom Hum ammo.mvm~.o onaom.avmo.~ name.acoo.m oxmmmcmsm oua mmso.o~c-.~¢ mmmv.mvos.aa mmam.macflm.om onmoHcoHee Hid Ame 12 my 12 as Amy ucmucou ucmucoo ucmucoo mmmfiowm ucmaummua z Hence 2 Leon 2 >600: Hmuoe 16.»:665 s manna HEIGHT (METERS) 5.4- 37 6.2- 5.8- 5.0“ 4461 4.2- 3.8‘ 3.44 3.04 2.6J 2.2‘ 1.8- 1.4- 1.0 _/> G—O WEEDS H NO WEEDS l 2 3 PLANTING DENSITY Figure 3 Poplar height in 1991 38 control had a mean height of 4.22m. This approached the height of high density trees with weed control (4.77m). High density mean heights were not significantly different from one another. At the low and medium densities the means of trees with weed control were significantly greater than those at the same density without weed control. A 1.9-fold increase was seen in height at the low density as a result of weed control. Medium density trees showed a 1.5-fold increase and high. density trees. gained only a 1.1-fold increase in height from weed control. Leader length (1991) shows a similar pattern to tree height (Figure 4). When weeds were controlled leader length decreased as planting density increased. Trees at the low and medium densities had significantly more leader growth than the high density trees (Table 4). Trees with weed cover increased leader length as planting density increased. The high density trees without weed control surpassed the leader growth of the high density trees with weed control, although the difference was not a significant (Figure 4). Individual tree leaf area showed a decreasing trend with increased planting density when weeds were controlled (Figure 5). This decrease was significantly different between planting densities. Leaf area at each density in plots without weed control were not significantly different from one another. The individual tree leaf area mean at the high density plots were equal, regardless of weed control. LENGTH (METERS) 39 215 233- 2.1- 1.9% 1.7- 1.5“ 1.3“ 1.1g (19- (I7- 0—0 WEEDS (15 H NO WEEDS i i 3 PLANTING DENSITY Figure 4 Poplar leader length in 1991 LEAF AREA (SQUARE METER) 40 9‘ (fl .0 7‘ .- N N s» s» e .4- .01 L» :3 01 ca (fl (3 (D C) U: c: I I I l I I I I l I —_ H NO WEEDS <>-<-> WEEDS .0 C) PLANTING DENSITY Figure 5 Individual tree leaf area in 1991 41 PLANT BIOMASS Ind;’v;’dua; Tree Biomass Aboveground individual tree biomass and woody biomass was influenced by planting density and weed control, but with no interaction occurring in September 1989. Tree Woody biomass included green leaves and woody components. biomass consisted of stem and branches. Total biomass and woody biomass showed similar patterns across treatments and these closely paralleled tree diameters. Individual trees with the highest total biomass were in the low density weed control plots (176.59; 93.39 woody). Tree biomass in weed control plots decreased as planting density increased. In plots with no weed control, trees at medium and high density had equal biomass values (36.69 and 40.69 total biomass, respectively). Low density trees were slightly larger at 57.09 total tree biomass, but this value was not significantly different from the other two densities (Table 3). At the end of the third growing season an interaction between planting density and weed control was influencing individual tree total biomass and woody biomass. In weed control plots, tree biomass decreased significantly with increased density (Figure 6). At low density, individual trees had a mean total biomass of 44109 (39159 woody). High density trees weighed only 11669 (11079 woody). Biomass in plots without weed control were not significantly different from one another (Table 4, Figure 6). Low and medium GRAMS 42 5000 4500‘ 4000‘ 3500- 3000- 2500- 2000- 1500- 1000- 500- __ H NO WEEDS <>—<> WEEDS LA: I on III N N U-I PLANTING DENSITY Figure 6 Individual tree woody biomass in 1991 43 density trees without weed control were significantly lower than those at the same density with weed control. Trees at the high planting density were not found to be significantly different across weed control treatments. Tgee Stand B; omass Aboveground stand biomass at the end of the first growing season (1989) is shown in Table 5. At the end of the first year, biomass (g/mz) decreased as the planting density decreased. The standing crop (woody biomass per unit area) at the end of the third growing (1991) season was greatest in the high density weed control plots (15529/m2) and the medium density weed control plots had 12259/m2 in biomass (Table 6). Weed control resulted in a 5.8-fold woody biomass increase in the low planting density, a 4.8- fold increase at the medium planting density, and only a 1.6-fold increase at the high density. Without weed control, the high density trees (94Og/m2) were able to produce more biomass than the low planting density (6119/m2) with weed control. In general, the standing crop biomass increased as density increased (Table 6) in 1991. In the weed control plots there was a 2.5-fold increase in biomass from the low to high density plots. With weeds present the increase was 9.0-fold. Total aboveground biomass was similar to the standing crop results. 44 Table 5 September 1989 aboveground tree stand means (standard deviation) Stand Stand Leaf Area Trt1 Biom ss Nitrogen Sontent Index (9/111 ) (ET/111 I 1-1 22.46 (5.24)c2 0.61 (0.20)bc 0.12 (0.03)c 1-0 8.49 (6.01)c 0.14 (0.11)c 0.04 (0.03)c 2-1 76.96 (19.34)bc 1.19 (0.61)b 0.40 (0.10)bc 2-0 24.44 (9.06)c 0.22 (0.17)C 0.13 (0.05)C 3-1 225.26 (101.3)a 4.29 (1.25)a 1.18 (0.53)a 4-0 139.33 (93.11)ab 0.99 (0.27)b 0.73 (0.49)ab II-high) second is l-weed control or O-no control. Means with the same letter are not significantly different, Tukey’s HSD alpha=0.05. 3 1 First digit designates planting density (l-low, 2-medium, 2 .mo.onmnmam cmm m.>mxse .ncmnmnuno annGMOnnnconm no: mnm nmnnma mfimm man nuns mammz N .on Honncoo omm3 o: no any Honucoo omm3 mn ocoomm man one Anonnlm .Esnomeim .3oHTnv Sunmcmo manucmHQ mmnuncmnm unmno nmnnm H 45 AcoHnmn>mo oncocmnmc mamme ocmnm mmnn ocsonmm>oQ< noon 0 OHQMB nanmn.ovmm.o mnem.ocme.n nanos.mvn~.m onomncmmon onnmonvoem cum nien.ovn6.o mnem.ocsm.n 61¢.mncme.mn enmmmvmemn mammmvmmmn nun unmo.ocen.o nasn.oc~¢.o naem.ocmm.m 61mmcomm monmmvmmm onm mnmn.ovmm.o mnmn.ocm¢.n nmAm¢.ncso.m nanomnvmmmn nannmncmmmn nun onmo.ovsn.o nnmo.ocso.o nnmm.ocso.n onsmvmmn misecmon oun nanmo.ovos.o anon.ocmm.o nane.mcmn.s unvoncmns moonmmvnnm nun .ucom snub A s\6c A e\6V 1 9\6c XOUCH XOUQH UCMHCOU mm EOHm OHU HHGOEHMOHB mmhd MONA MOH< NOS 2 Ocmvm Ucmum HMHOB Ofiwficmum 46 Weed Biomass Aboveground weed biomass in July 1989 was not significantly different between planting densities. Weed biomass at the low planting density was 369g/m2 (Table 7). At the medium planting density the biomass was 3429/m2 and at the high planting density weeds were 3639/m2. Weed biomass in September 1989 at the three planting densities was not significantly different from one another. Biomass did decrease with increasing planting density. Weed biomass at the low planting density was 1194g/m2 (Table 7). At the medium planting density weed biomass was 6059/m2 and was 479g/m2 at the high planting density. By August 1990 planting density did have a significant effect on aboveground weed biomass. Weed biomass at the high planting density was significantly lower than the weeds at the medium density. Weed biomass from the low planting density 'was not significantly' different from either the medium or the high densities. The mean biomass for low, medium, and high planting densities was; 2689/m2, 301g/m2, and 14lg/m2. Planting density continued to effect weed biomass in 1991. Weed biomass was not significantly different at the high planting density (889/m2) and at the medium planting density (226g/m2) (Table 7). Weed biomass at the high planting density was significantly lower than the weed biomass at the low planting density which had (4359/m2). 47 Table 7 Aboveground weed biomass and N content means (standard deviation) Month Year Density Bioma s N (Contegt (g/m ) (9 N/I!1) July 1989 Low 369 (332)a1 8.67 (6.30)a July 1989 Medium 342 (159)a 5.82 (2.72)a July 1989 High 363 (110)a 6.40 (2.11)a Sept 1989 Low 1194 (889)a 9.25 (7.99)a Sept 1989 Medium 605 (397)a 7.23 (6.34)a Sept 1989 High 479 (205)a 5.57 (2.68)a August 1990 Low 268 (77)ab 2.79 (1.25)a August 1990 Medium 301 (97)a 3.62 (l.l7)a August 1990 High 141 (52)b 1.92 (0.75)a August 1991 Low 435 (273)a 6.18 (2.73)a August 1991 Medium 226 (51)ab 3.80 (1.01)ab August 1991 High 88 (48)b 1.49 (0.75)b 1 Means with the same letter are not significantly different, Tukey's HSD alpha=0.05. Sample size in each month of 1989 and 1990, N=18 in 1991 N=30. 48 WW Total community biomass is presented here but should be viewed with caution. In 1989 weed biomass was sampled with 2 with. no repetitions within subplots. quadrats of 0.20m Only one quadrat per subplot was sampled. Heterogeneity of weed cover was not accounted for. In projecting the biomass to an area of 1.0m2 the sampling and measurement errors are magnified and these are additive to the errors from the 1990 and 1991 samples. In 1990 and 1991 quadrats of 1.0m2 were used.‘ A quadrat size of 0.20m2 for vegetation sampling is viewed as inadequate by the author and is not recommended. Total community biomass includes weed biomass from 1989, 1990, and 1991, poplar leaf biomass from 1989 and 1990, and 1991 total tree biomass (Table G.1, Appendix G). Planting' density and. weed control did not significantly influence total aboveground community biomass. A significant interaction between density and weed control was present. The only means significantly different from one another were the low density with weed control (7789/m2) and the low density without weed control (21509/m2) communities. The other community values ranged from 14309/m2 to 18529/m2 (Table 8). Figure 7 shows that biomass increases in communities with weed control as planting density increases. The high standard deviation present for the low density community without weed control (1-0) appears to be reflect the high weed biomass values in 1989. These values are probably inflated due to the sampling technique and 49 we. aSR ab ab a memxgzzzzzzzzzzzzzza zZZZZZZZZZZZZ%ZZZZZZZZZZZZ uwwaNwwmmwmwwmzzzzgzzza 21004 1600* 1100— 600‘ amen: mm<30m \ 2~sh :« xuflmcwp onwucm~m 30H wcu um «NE\6» mmwowmm 0003 Gd .0 GHQ—PH. 92 00 O N #00 OM lbw 00.4 N O‘ m OOMOOOMHOOOOOOIOOO‘DOOO O O 0‘ N ¢F.H NN.om mh.mmH w¢.ma mh.mm In H N In [0 O M m In owOOOOOI‘OOOHOOOOOOOQ‘OOOOOO O 00 H \O H OOOOOOOOOOOOOOOHOOOOOOOOOO In N H H COOOO‘OOOO‘O‘OOOOONOOOOOOO O IDID 00 O 00 N In 0 00 00 O mm.mm In GOOOOOOOOOOOOOOOOOOOOCI‘OOO O I‘ H O O H C d‘ OOOQOOOOOOOOOOOOOOOOOO OS mm.va om.how o o mmomumao monazuuom mmmmuaaoo mom osmofiumam moooaou>cm azuoHuHBouosoHU Esoflsmm mumHHmeo Savanna macauum mwaoxo mumHHwOwuu0> omzaaoz mwcflmmuoac mflawnmufiz m>fiumm OOMOflooz muomammc m>amz asumuomumm azowuma>m mwmsmcmwaflo mwumoummum mcmnmu camauu>am “flammabo monooswnom mflamcfizocmm Mahmuwcwo msucmasomo msumm>o mfimsmomsmo muhcoo mwmsmflumcon m~>soo annao fisfipomosmnu manomas> mmumnumm Macedon» mamaoofinmu< Escwnmcsmo Escaoomc awaouwfimflamuuo camounad mm.~mm mzxmauouumu mazusmuwa< o manam manucmuoad om.H~H “ammunmomnu :oaflusna O \D H O OVOCHOOOOOOOOOOOOOOFOOO O In Q In 0 H momu0>< o mmwommm Ln xooam m N mH.Q wanna a mmfiommm mama aasb :« xuflmcmo ocflucmHm 30H 029 um A~E\mv mmwomam 0003 III‘ PC 10.0:00c ma.o manna 93 .cou>mou@¢ masmw 0:» ca manoeuom .mflcfiwufl> mo canon ocmuxm N ou :3ocx #0: ma mfimcmflumcon .0 mo mocmu one .omflmwucmowmfifi >Hnmnoum whoa mucoam muons H mm.omm wh.mm mo.mbH mm.mHH mN.MNOH mm.HHm HMUOB xOOHm 000 [‘0 M m I!) Q‘ P! 00 00000000000000 0 V 00 00000000000000 Ln OONOOOOOMOOOOO O 00 H 00000000000000 00000000000000 00000000000000 OOOOQ‘OOOOHOOOO V‘ O newuomumm moficoum> mpooflo :3ocxso savanna: aaflaouaua madam“ asafiOMHuB macawofimuo anomxmuoe mfioma mwumaamum asnucmo>um Bosoaom meowufi> owumumm wumnwm mwumumm adammouoom xmesm mamom xmfism aflomoooosmmm mfiswnom 00wc0>uos waafiucmuom omusmmum maafiusmuom momum>< mmflommm \O LO Q‘ m N xoodm 16.0cooc ma.o manna mmflommm mmoa >~=o CM >uflmcmp Oswucoam EzfiUmE mcu um «NE\UV mmwommm 0003 ON .0 QHQQB 94 mo.o mm.o o o o o o omomumao monazuuom oo.o o mm.o o o o o mmmmumsoo mom m~.e mm.m oo.mH o o o o accumumam moooaouanm no.5 om.m m¢.m~ mm.o oa.o mh.w mm.m BflhOameOUOfiOHG azowcmm -.o o om.H o o o o «undeadmo savanna m¢.o o o o o om.~ o muofluum mHmeo o o o o o o o mundawowuum> omzaaoz mo.o o m¢.o o o o o mmcfimmuosc mwafinmuflz o o o o o o o m>flumm OOMUMUm: o o o o o o o muomammc m>amz o o o o o o o asumuomuma Esowumm>m o o o o o o o mflmcmcmwafio mflumoummum o o o o o o o mammmu mfimwuuaam oH.m ms.mm o mm.¢a o o o mammmzuo moanoocflnom 5H.Hn o o o oo.sma o o mflamcfismcmm mflumufimao No.6 6 mH.o o o o o maucmaaomm maummmo o o o o o o o mamamonsmo unacou o o o o o o o Hmwmcowumson mn>coo mH.bmH om.oo~ o mo.mnm om.oo~ mm.~m mm.mom Hanan Bfiwflomocwsu o o o o o o o mwumoas> mounnumm o o o o o o o msmfiamnu mammopflnmu< me.mo¢ o o o oo.o~v~ mm.o o ascfinmccmo anamooda oH.o o o oo.o o o o mflHoMflfimmsmuua memounsd mh.mw om.mm om.¢ma o mm.mm o om.mHm mzxmamouuwu manucmumfid ha.o o oo.a o o o o manao manucmunad mm.mm om.mmm mm.o¢ o mm.mm o m¢.wd “ammunmomnu Godwuznd mmwu0>< o m 6 m m H mmwommm mmwomam xoon mmmd mash :H >uwmcmo mswusmam aswpma 02» um A~a\mv mmwommm 6003 ON.D wHQMB “0.0200c om.o 0~nmfi 95 .couamouma mssmm on» :w wauwauom .0wcflmufi> Mo sumo: ocmuxm on :3ocx #0: ma mfimcmflumcon .0 mo mason one .omwuflucmpflmflfi hanmnoum mum: mascam muone N H om.va mm.mmm m¢.mmm ow.©wwN om.¢h m¢.w¢v HMUOB xOOHm o o o o o o o msfluooumm moficoum> mo.o o oH.o o o o o muooflo asocxco Ho.o o o o o no.0 o Savanna: EsflHOMMHB mm.m o oH.¢H o o o o mammmu snaflouwue HH.o 0.0 o o o o o mHMCwUMHMO EzomeHMB mm.aa o om.mo o o o o wwvmfi mflHMHHmum mm.o o o H.v o o o annucmoxum Baccaom o o o o o o o meowufl> Mahmumm o o o o o o o flumnmm mwumumm o o o o o o o oaawmoumow xmasm o o o o o o o ‘ oumom xmasm o o o o o o o aflomoooosmmm aficflnom No.0 o o o o oa.o o moflmm>uoc caawucmuom o o o o o o o mmusmmum waaflucmuom 0mmum>< 6 m 4 m m H mmflommm mmwommm xoon Ac.ucooc o~.o wanna cacp >F:h cw >ummcwp ccfluco~o new: 0cu up ~NE\®~ m0w00Qm U003 am .0 QHQMB 96 o o o o o o o mmomu0ao momasuuom o o o o o o o omm0umaoo com o o o o o o o msmoflu0am moomaoumsm va.m o mm.o o~.H mm.m mm.m o asuoHuflEouonoflp savanna o o o o o o o mundawmmo savanna o o o o o o o muofiuum mflamxo o o o o o o o mumHHfiofluu0> omsaaoz o o o o o o o m0cwmmuomc mflawnmuwz mm.ma om.mm o o o o o m>flumm omoofiumz ~m.o o o om.m o o o anomammc m>amz vo.o o o o mm.o o o asu0u0mu0m fisofiu0m>m o o o o o o o mfimc0smwafl0 mfiumoummum m~.~H mm.mh o o o o o 0:000“ mamwuumam o o o o o o o fiHMMmsuo monoocfinom mo.o o o os.n o o o mfiamcfismcmm nwumuflmfio mm.m o o o ms.a~ o o mzucmasomw maumdmo mm.o o oo.m o ma.o o o mfimc0omcmo anacou -.o o o o mm.H o o Hmflmcmflumcon «assoc mv.ooa o om.bma 0H.¢0H mH.NbH oo.mNm o BSQHM Enfifiomocmnu o o o o o o o mfiummaz> m0umnumm o o o o o o o unmeamzu mammoownmu< mm.o om.o o o o o om.m escflnmscmo ass>009< o o o o o o o awaouwwmfia0uum camouna< hm.¢NH mo.HNN Ob.wa oo.th m¢.HH o 0N.HNN max0Hu0Hu0u manucmumfid om.m o om.ON o N.o o o manam mssucmumfid wm.mN on.m o om.o mh.¢w mo.o mH.mm flammucmomnu :onvflnd mmmum>< 0 m a n m H mmaowdm 00HO0Qm xoon mmma mash cw hufimc0p mswucman swan 0:» an Ama\mv m0fio0mm p003 HN.Q manna A0.u:00c H~.o menus 97 .soummouod mss0m man :H >Hnmshom .chHmuH> mo cuno: os0ux0 N on czocx #0: 0H mHmc0Humcon .0 no 0mcmu 0:9 .U0HuHus0onHs >Hnmnoua 0H03 mu:MHQ 00028 H om.mo¢ mw.mHN oo.Nm¢ om.¢mN oo.oem mm.nmN Hmuoe xoon o o o o o o o msHuomu0Q moHsou0> o o o o o o o muooHo c3osxca mo.H o o o o OH.6 o sonunmn ssHHOHHue mm.o o oo.m o o o o 020000 asHHOHHue no.0 o o o o o o~.o 0HmsHoHuuo Esomxmuwe mm.m w.m om.mm o~.o o o o oHoma MHMMHHmum o o o o o o o Eszusoo>um szcmHom mm.o o o oo.m o o o mHoHuH> 0Hu0u0m o o o o o o o Humnmu mHumumm o o o o o o o 0HHOmou000 x0fiam o o o o o o o mu0om xmfism o o o o o o o 0Homomoosmmm MHQHnom o o o o o o o oon0>Moc mHHHpc0uom o o o o o o o amusmmum mHHHuswuom 0mmum>< m m a m m H mmHomom m0Ho0mm xOOHm 16.»:ooc Hm.o oHnme mmmH 00QE0uQ0m :H >uHmc0U mcHucmHQ 30H 02b um «NE\me 00HU0Q0 0002 NW .0 QHQQB 98 co N O H 00 OOQONONOOOOOOOOOOFOOO 0‘ C O C N t‘ o 0‘ m N om.H vm.¢mv Nb.vm o mo.¢mH O \OOOOOOONOOOMOOOOOOOOOOOOOO O m m0omu0Ho MOMHsuuom mmm0umaoo mom msmoHu0EM moomHoumnm EnuonHaouonoHo EsoHsmm oumHHHQmo 8:0Hsmm muoHuum mHmeo mumHHHUHuu0> omsHHoz m0chmuo>s mHHHnmqu m>Huom oomoHo0= ouo0Ho0c 0>Hmz asumuouu0m EsoHu0Q>m mHmc0cmHHHo mHumoummum mummmu MHOHHHNHM HHmmmsuo ooHnoochom mHHmcwamcmm «HumuHmHo mauc0Hsom0 mzumahu mHmsmpmcmo anacou mHms0Huwson nuasou Eanm azHooaoc0£U mHuomHs> m0umnumm msmHHmnu mHonoHnmu< ov.HH ascHnmcsmo Ezcmooad mo.mmmm MHHouHHmHa0uum meouna< o mo.omH msmeuouumu manusmumad o o manHm manusmuma< o¢.m mm.mm Humaunmownu :oHHusn< o O Q N O l‘ l‘ V‘ O In m C O In \D O Q' P! O OQOOOOO‘OOOQOOOOOOOOOO¢OOO N In 0 H .moHH H In C [x O .mmH m OOOOQ‘OFOOOOOOOOOOOOI‘OCO OOOOOOOOOOOOOOOOOOOOO O Q In H N o o o w. o o o o o o o o o o o o o o o o o o o o o m. COOOOOOfi'OOOO0000000000000O .mNm o mww om.m 0mmu0>¢ m0Ho0Qm m H moHommm \O m e M xoon mmmH H0Qfi0um0m cH huHmc0p ocwucmHm 30H 02» um A~a\mv m0Ho0Qm p003 NN.D manna 10.0200c mm.o 0ans 99 .couzmoumd 00:00 0:» :H >Hu0shom .chHmnH> mo sumo: psmux0 on CBocx no: 0H mHmc0Humson .0 no 0mcmu 0:8 .00HMHuc0pHmHE >Hnmnoum 0H03 mucmHm 00058 N H mm.momH mm.omm om.mHm o¢.Nho ON.MNom om.¢hm HMHOB xoon V N l‘ OOOOOHOOOONOOO O O M H CO OOOOOOOOOOOOOO OOOOOOOOOONOOO O 0 00000000000000 0 H 00 [x 0 00000000000000 OOOOOOOOOOMOOO In m V'OOOOOOOOOQOOO O In H O mcHuomhmm moHcou0> muooHc czocxco EspHHn>s asHHomHuB mc0m0u EDHHOHHMB 0HmcH0Hmmo Esomxmuma 0H00E mHumHH0um Ennusmoxum fiscmHom mHUHuH> 0Humu0m Hu0nmu 0Humu0m mHH0mou000 x0fism mumom x0fiam mHomomooawmm MHCHnom 00Hm0>uoc mHHHuc0uom amus0mum MHHHucmuom 0mmu0>¢ 00H00Qm xUOHm 16.0coov -.a mHnme m0Ho0mm mm .0 GHDMB 100 0000H0Ho momquuom 000000800 mom 0:00Hu030 0000Houanm aauoHMHaouocoHp EsoHcmm 0H0HHH900 asoHcmm muoHuum mHmeo mumHHHoHuu0> omzHHoz 00sHmmu0>s mHHHnmqu 0>Humm 0000H00= 0900Hm0: 0>Hmz asumuomu0m aonn0Q>3 mHms0s0HHH0 0Humoummum 020900 mHoHuuaHm HHmmmsuo moHnooanom mHHmcHsocmm mHumuHmHa maus0H5000 0:00Q>0 mHmc000200 0u>s00 mHms0Humson 00>:00 aanm asHoomoc0n0 mHnmde> 00umnumm 0c0HHmsu mHonanmud EscHnoccmo azsaoom< mHHouHHmHB0uu0 MHmounE< .Hmn msx0Huouu0u 0::us0u034 manHm manucmuma< Hummunmomau coHHusnc O OOFOOOOOOOOOOOQOOO N tn 0 O <' H ID V Q C O (x O (x H m N .mmH O 10 MN OH M O O OOOO‘OOOVOOOOOOOOOOOHOOO I Q' hm.N¢ H mH.o o mm.NH mo.me m No.0mN mo.o ov.¢ 0 V’ o Q H m o O ("'1 HO O N O 1010 OHOOOHLDOOONOOOOOOOOOOO‘OOO O OONOFOOQ‘OOOOOOOOOOOOOOIDOOO [\ [x .ONHH O OOBOOOOOOOOOOOOOOOOOOOO‘COO H 05 [x I!) Ch M om.va o mo.¢ om.HN .mON O OONOOOOWOOOOOOOOOOOOOOHCOO OOOHOOOOOOOMOOOO0000000000 O [D <‘ 000u0>¢ 00Ho0nm 00H00Qm \0 LO Q' m N H xOOHm mmmH u0na0um0m CH NuHms00 mcHusmHa a5H00a 0:» an A~E\mv 00Ho0m0 0003 MN.D 0HQMB 101 .couamoum< 05:00 0:» :H >Hu0fiuom .mHsHmHH> mo :uuo: 0c0ux0 N on :3ocx #0: 0H mHmc0Humcon .0 mo 00:0“ 0:9 .00HMHus0pHmHa >Hnmnoum 0003 mucmHQ 000:9 H m¢.OOMH ¢.mmm mo.mmm mN.NmN om.NNm mh.hhm HQHOB xOOHm O NQ‘ H NQ 000000000MH000 00000000000000 0000000000Q000 O N \O In 000000000H0000 0 O N N 000000000000000 00000000000000 00000000050000 6') H mcHHm0u0Q 00HCOH0> muooHu asocxca asoHunsa azHHouHua 0:090“ EsHHOHHHB 0H0CH0Humo Baomxmuma 0H00E mHumHH0um E::u:00>um ascmHom mHUHuH> 0H00u0m Hu0nmu 0H00u0m 0HH0mou0om x0asm 00000 x0asm 0Homomop=0mm chHnom 00Hm0>uos mHHHuc0uom 009:0000 0HHHus0uom 0mmu0>¢ m0Ho0mm xOOHm 16.0:000 m~.o 0Hnma m0H00Qm 102 00.0 0 0 o 0 0m.o 0 000000Ho 000Hs00o0 0 0 0 0 0 0 0 000000E00 000 o o 0 o 0 o 0 0:0000050 0000Ho0>:0 om.v¢H om.>bm 0m.~mm 00.00H mm.00 m~.H0 00.0HH Ea0oHuHso0o:000 EsoHc00 0 o 0 0 0 0 0 000HHH000 EsoHc00 0 0 0 0 0 0 0 000H000 mHHOxo 0 0 o 0 0 o 0 000HHH0H000> omsHHoz 0 0 0 0 0 0 0 00:Hm000>: 0HHH000HS mm.m mm.~m 0 o o o 0 0>H000 om0oH00z o o o 0 o o 0 0000Hm0: 0>H0z No.0 0 0 0 mH.0 0 0 8000000000 aaoH000>I «0.6 o o o o mm.e o 000:0:00H00 0Humoumm0m 0 o 0 0 0 0 0 000000 000000>Hm 0 0 0 0 0 0 0 HHOM0000 0oH:0o:H:om oo.n mo.n o 00.0H o o o 00Hmc0zmcmm 000000mHo «0.0H o o o 00.HHH o o 0:0:0H5000 0900000 0 o o o o o o 0H0c000c00 000000 0 o 0 o o o 0 H00000H00co: 000000 0N.bHH 0 0 00.000 0N.0 0n.hm 0 EfiQH0 55H0omocwnu 0 o 0 0 0 0 0 0H00OH=> 00000000 0 0 0 0 o 0 o 0:0HH0:0 00000000000 00.0 0 0 0 0 0 0m.0 EscHn0cc0o anchoo0< 0H.mH 0 0 0 0 0 00.Hm 0HHOMHH0HE0000 0H0000E¢ m0.m> 0 0 0 00.0N 0H.0HH 0m.mmN 05x0Hmo0000 05:0:000fid mm.0 0 0 mm.m 0 0 0 mdnH0 00:0:00034 mm.¢m 0.mH 0 0 00.Hm 00.0Hm m0.~mH H0000:0o0:0 :oHH00:< 0m000>0 0 m w m N H 00H0000 00H000m xoon mmmH 000300000 :0 >0H0c00 0:00:0H0 3:000a 0:0 00 :~a\0v 00Ho000 0003 vN.D 0H308 103 .0o0>0000< 00000 0:0 00 >HO0E0om .0H0H00H> no :0000 000000 00 03000 000 0H 0H000H000o: .0 00 00000 0:8 .00H0H0000H0HE >Hn0no00 0003 0000H0 000:9 N H 0.0Nm 0.00m 0m.0m0 0N.wNN 00.000 0H.Nb0 H0008 xoon NH.0 0 0 0 0 05.0 0 00H000000 00H0o00> 0 0 o 0 0 0 0 0000H0 0300000 6 o o o o o o 0:0H0000 0:0H0000e 00.0H o o~.mm o o o m~.s 000000 ssH00000a «0.0 0 o 0 o 0 mm.v 0H00000000 000000009 0 0 0 0 0 0 0 0HO0E 0H00HH00m o 0 o o o 0 0 0000000>00 0000Hom 0 0 0 0 0 0 0 0HOHOH> 0H0000m 0 0 0 0 0 0 0 H00n0u 0H0000m No.0 0 0 0 0 o 0H.0 0HH0000000 xwfifim vm.H 0 o o 0 00.0 0 00000 00000 0 0 o o o o o 000000000000 0H0Hnom o 0 0 0 0 0 o 00H00>0o0 0HH0000000 o o o o o o 6 00000000 0HH0000000 0m000>< 0 m e m m H 00H000m 0000000 x0on 00.00000 ¢~.o 0H000 104 Table 0.25 Nitrogen data from weeds sampled in July 1989 Blk Trt Species WeigBt N Conc N Cogt (9/m ) (%) (9 N/m) 1 1-0 Abutilon theophrasti 121.90 1.66 2.02 1 1-0 Amaranthus retroflexus 282.95 1.64 4.63 1 1-0 Chenopodium album 85.10 2.39 2.04 1 1-0 Other Species 21.70 2.14 0.46 1 2-0 Abutilon theophrasti 18.45 1.57 0.29 1 2-0 Amaranthus retroflexus 219.30 1.29 2.82 1 2-0 Chenopodium album 205.35 1.71 3.51 1 2-0 Other Species 5.35 1.85 0.10 1 3-0 Abutilon theophrasti 69.15 1.32 0.91 1 3-0 Amaranthus retroflexus 221.20 1.29 2.86 1 3-0 Apocynum cannabinum 3.20 1.51 0.05 1 3-0 Other Species 0.20 2.60 0.005 2 1-0 Amaranthus retroflexus 467.50 1.60 7.46 2 1-0 Ambrosia artemisiifolia 541.35 2.10 11.35 2 1-0 Chenopodium album 9.80 1.98 0.19 2 1-0 Other Species 4.60 1.83 0.08 2 2-0 Chenopodium album 62.25 2.37 1.48 2 2-0 Other Species 1.10 2.68 0.03 2 2-0 Oxalis stricta 2.80 1.47 0.04 2 2-0 Panicum dichotomiflorum 8.75 2.15 0.19 2 3-0 Chenopodium album 525.00 1.85 9.72 2 3-0 Other Species 0.05 1.62 0.001 2 3-0 Panicum dichotomiflorum 8.85 1.69 0.15 2 3-0 Trifolium hybridum 6.10 2.41 0.15 3 1-0 Abutilon theophrasti 17.90 1.04 0.19 3 1-0 Panicum dichotomiflorum 100.75 1.24 1.24 3 2-0 Chenopodium album 200.20 1.55 3.11 3 2-0 Other Species 83.85 1.67 1.41 3 3-0 Abutilon theophrasti 64.75 2.33 1.51 3 3-0 Chenopodium album 172.15 1.66 2.86 3 3-0 Cyperus esculentus 21.75 1.12 0.25 3 3-0 Other Species 15.65 1.78 0.28 4 1-0 Abutilon theophrasti 32.95 1.88 0.52 4 1-0 Amaranthus retroflexus 88.05 1.97 1.73 4 1-0 Chenopodium album 28.90 1.66 0.48 4 1-0 Other Species 27.95 1.89 0.53 105 Table 0.25 (cont’d) Blk Trt Species Weight N Conc N Cogt (9/111 ) (’6) (9 Wm ) 4 3-0 Amaranthus retroflexus 275.00 1.21 3.32 4 3-0 Chenopodium album 164.10 1.51 2.47 4 3-0 Other Species 7.45 1.26 0.09 5 1-0 Mirabilis nyctaginea 0.20 2.52 0.005 5 1-0 Other Species 0.15 1.44 0.002 5 1-0 Robinia psuedoacacia 18.25 4.12 0.75 5 1-0 Stellaria media 14.35 0.83 0.12 5 2-0 Abutilon theophrasti 46.25 1.51 0.70 5 2-0 Amaranthus retroflexus 184.90 1.69 3.12 5 2-0 Other Species 58.90 2.14 1.26 5 2-0 Stellaria media 69.90 1.41 0.98 5 3-0 Amaranthus albus 20.80 1.92 0.40 5 3-0 Chenopodium album 137.50 2.77 3.81 5 3-0 Other Species 33.30 2.77 0.92 5 3-0 Stellaria media 28.30 1.22 0.34 6 1-0 Amaranthus albus 80.85 2.46 1.99 6 1-0 Chenopodium album 53.75 4.55 2.44 6 1-0 Digitaria sanguinalis 161.15 2.32 3.74 6 1-0 Other Species 54.50 2.32 1.26 6 2-0 Abutilon theophrasti 232.60 1.75 4.08 6 2-0 Amaranthus retroflexus 58.60 1.53 0.98 6 2-0 Chenopodium album 200.20 2.04 4.08 6 2-0 Other Species 49.90 1.98 0.99 6 3-0 Elytrigia repens 73.55 2.55 1.87 6 3-0 Amaranthus retroflexus 221.65 1.91 4.24 6 3-0 Medicago sativa 99.30 1.86 1.85 6 3-0 Other Species 11.80 2.95 0.35 106 Table D.26 Nitrogen data from weeds sampled in September 1989 Blk Trt Species Weight N Conc N Coat (g/m ) (5%) (9 Wm ) 1 1-0 Abutilon theophrasti 95.95 0.70 0.67 1 1-0 Amaranthus retroflexus 186.65 0.87 1.63 1 1-0 Other species 26.50 2.16 0.57 1 1-0 Panicum dichotomiflorum 65.70 1.27 0.83 1 2-0 Amaranthus retroflexus 331.20 1.05 3.46 1 2-0 Chenopodium album 30.65 1.28 0.39 1 2-0 Panicum dichotomiflorum 2.15 1.38 0.03 1 2-0 Taraxacum officinale 13.75 2.29 0.31 1 3-0 Abutilon theophrasti 152.05 0.84 1.28 1 3-0 Amaranthus retroflexus 299.30 1.23 3.68 1 3-0 Other species 103.05 1.61 1.66 1 3-0 Panicum dichotomiflorum 117.70 1.52 1.79 2 1-0 Ambrosia artemisiifolia 2969.05 0.78 23.13 2 1-0 Apocynum cannabinum 11.40 1.37 0.16 2 1-0 Other species 9.75 0.40 0.04 2 1-0 Panicum dichotomiflorum 35.00 0.69 0.24 2 2-0 Amaranthus retroflexus 209.20 0.90 1.89 2 2-0 Apocynum cannabinum 77.70 1.28 0.99 2 2-0 Chenopodium album 18.40 1.17 0.22 2 2-0 Panicum dichotomiflorum 17.50 0.80 0.14 2 3-0 Abutilon theophrasti 310.70 0.78 2.43 2 3-0 Amaranthus retroflexus 118.15 1.01 1.19 2 3-0 Other species 50.00 1.24 0.62 2 3-0 Panicum dichotomiflorum 61.25 1.01 0.62 3 1-0 Chenopodium album 195.40 0.69 1.34 3 1-0 Panicum dichotomiflorum 477.00 0.64 3.03 3 2-0 Amaranthus retroflexus 164.90 1.04 1.71 3 2-0 Other species 34.95 1.21 0.42 3 2-0 Panicum dichotomiflorum 70.10 1.38 0.97 3 2-0 Trifolium repens 22.30 1.63 0.36 3 3-0 Abutilon theophrasti 31.00 0.81 0.25 3 3-0 Cyperus esculentus 111.85 0.59 0.66 3 3-0 Other species 25.00 1.44 0.36 3 3-0 Panicum dichotomiflorum 60.35 1.36 0.82 107 Table 0.26 (cont’d) Blk Trt Species Weig t N Conc (9/In ) (35) 4 1-0 Chenopodium album 70.95 1.15 4 1-0 Other species 28.25 1.28 4 1—0 Panicum dichotomiflorum 38.40 1.15 4 1-0 Setaria faberi 781.00 0.42 4 2-0 Amaranthus retroflexus 39.15 0.94 4 2-0 Chenopodium album 200.55 0.55 4 2-0 Other species 11.00 1.47 4 2-0 Panicum dichotomiflorum 84.95 1.44 4 3-0 Chenopodium album 666.00 1.21 4 3-0 Digitaria sanguinalis 18.55 1.04 4 3-0 Panicum dichotomiflorum 106.35 1.44 5 1-0 Abutilon theophrasti 669.50 0.74 5 2-0 Amaranthus retroflexus 791.70 0.81 5 2-0 Panicum dichotomiflorum 140.90 0.85 5 2-0 Trifolium repens 62.80 2.22 5 3-0 Panicum dichotomiflorum 252.20 1.13 5 3-0 Trifolium repens 98.20 1.86 6 1-0 Abutilon theophrasti 325.65 0.76 6 1-0 Chenopodium album 1163.20 0.98 6 1-0 Digitaria sanguinalis 14.50 1.26 6 2-0 Ambrosia artemisiifolih 1120.15 1.62 6 2-0 Digitaria sanguinalis 186.30 1.32 6 3-0 Abutilon theophrasti 15.60 0.80 6 3-0 Panidum dichotomiflorum 277.50 1.24 108 00000000 0000 0>000000000 @000 >000 000 0000 0000 hN.O 0HQMB 06.6 06.6 06.6 «6.6 «0.0 60.6 «0.0 ««.6 60.6 0 0:0 « «0.6 06.6 60.6 «6.6 ««.« 0«.« m«.m «0.6 00.6 « 6-0 « 00.6 «6.6 00.6 06.6 00.60 «0.« 0«.0 00.6 ««.6 0 6-0 « 00.6 00.6 60.6 ««.6 «v.0« «0.0 60.«0 00.6 00.6 « 0u« « 60.6 06.6 «0.6 6«.6 00.6« m«.0 06.00 00.6 00.6 0 «a« « ««.6 06.6 ««.6 00.6 06.00 60.0 «0.«0 ««.6 00.6 « 6u« « m«.6 06.6 0«.6 «0.6 00.00 «0.0 m«.0 6«.6 «0.6 0 6.« « 666.6 6 666.6 066.6 66.60 00.6 06.6 ««.6 m«.6 « 0u« « «0.6 66.6 00.6 00.6 6«.«0 00.0 ¢«.«0 00.6 m«.6 0 «u« « 0«.6 06.6 ««.6 00.6 «0.00 60.0 «0.0 ««.6 00.6 « 6u« « ««.6 06.6 ««.6 00.6 m«.0« 6¢.« m«.40 60.6 60.6 0 6n« « ««.6 «6.6 0«.6 60.6 00.0 «6.« 00.0 60.6 60.6 « 0:0 « m«.6 06.6 ««.6 «0.6 «0.«0 «0.« m«.0 0«.6 0«.6 0 0-0 « 00.6 60.6 «0.6 6«.6 0«.0« m«.60 «0.6« 66.0 60.6 « 6-0 « «0.6 «6.6 m«.6 00.6 «m.«« ««.m 6«.00 60.6 «6.0 0 6:0 « «0.6 06.6 «0.6 0«.6 ««.«« 00.« 00.00 00.6 00.6 « 0:« 0 00.6 00.6 00.6 m«.6 60.«« 00.60 m«.0« 06.0 06.0 0 0n« 0 ««.6 «6.6 6«.6 00.6 0«.0« 6«.0 00.0 60.6 06.0 « 6.« 0 «0.6 «6.6 «0.6 00.6 06.«0 00.0 60.« 00.6 00.6 0 6.« 0 «0.6 06.6 ««.6 «0.6 mm.«0 m«.« ¢«.m 00.6 00.6 « «u« 0 ««.6 «6.6 6«.6 «0.6 ««.«0 00.« 00.0 00.6 ««.6 0 0:« 0 ««.6 «6.6 00.6 60.6 00.«0 00.« 0«.0 0«.6 «0.6 « 6.« 0 «0.6 06.6 «0.6 06.6 66.0 mv.« 00.0 00.6 «0.6 0 6.« 0 00.6 00.6 «0.6 ¢«.6 06.0« «0.0 0«.00 00.6 00.6 « «-0 0 00.6 «6.6 00.6 0«.6 00.00 00.0 00.«0 «0.6 ««.6 0 0:0 0 00.6 «6.6 «0.6 «6.6 ««.« 0«.« 00.0 «0.6 00.6 « 6:0 0 0«.6 «6.6 ««.6 ««.6 0«.«0 00.« ««.0 «0.6 ««.6 0 6-0 0 000 000 000 A 00 0:00:60 0:00:60 0:00:60 0 00 000 03 000 03 000 03 0000 000 00000 000 000 2 00060 2 00663 2 0000 0000 00060 00663 0000 0006 000000 109 00.0:600 00.6 00000 0«.6 06.6 ««.6 60.6 00.00 66.« 00.0 00.6 «0.6 0 0-0 0 6«.6 06.6 00.6 00.6 00.00 00.0 00.00 «0.6 00.6 « 6-« 0 «0.6 «6.6 60.6 06.6 00.0 00.« ««.0 00.6 60.6 0 6-0 0 ««.6 «6.6 00.6 06.6 00.0 «0.0 00.0 60.6 00.6 0 0-0 0 0«.6 06.6 6«.6 «0.6 60.60 «0.0 06.0 00.6 00.6 0 0-0 0 0«.6 06.6 0«.6 00.6 «0.00 00.0 00.0 60.6 00.6 0 6-0 0 00.6 00.6 00.6 00.6 «0.00 00.0 06.00 00.6 «0.0 0 6-0 0 0«.6 06.6 ««.6 00.6 00.0 00.« 06.0 00.6 00.6 0 0-« 0 «0.0 00.6 00.6 60.6 00.0« 00.00 0«.00 «0.0 «0.0 0 0-« 0 00.6 «6.6 00.6 00.6 00.00 60.0 00.0 00.6 00.6 0 6-« 0 00.6 «6.6 00.6 06.6 00.0 «0.0 00.0 00.6 «0.6 0 6-« 0 60.6 6 60.6 00.6 00.«0 00.« 00.0 00.6 00.6 0 0-0 0 00.6 06.6 00.6 00.6 00.00 06.0 00.60 60.6 «0.6 0 0-« 0 ««.6 06.6 00.6 00.6 00.00 00.0 60.00 00.6 00.6 « 6-« 0 60.6 06.6 06.6 06.6 00.0 00.0 0«.0 «0.6 00.6 0 6-0 0 60.6 «6.6 00.6 06.6 00.0 00.0 60.0 00.6 00.0 0 0-0 0 00.6 06.6 60.6 00.6 00.00 00.0 00.60 00.6 «0.6 0 0-0 0 00.6 06.6 «0.6 06.6 00.0 00.0 00.0 «0.6 60.6 0 6-0 0 06.6 06.6 06.6 06.6 60.0 00.0 00.« 00.6 00.6 0 6-0 0 «0.6 06.6 00.6 00.6 0«.60 00.0 00.00 00.6 00.6 0 0-« « 60.6 06.6 0«.6 «0.6 «0.00 06.« 00.0 00.6 00.6 0 0-0 « 00.6 «6.6 «0.6 06.6 00.0 0«.0 0«.0 00.6 60.6 « 6-« « ««.6 06.6 00.6 00.6 0«.00 «0.0 «0.00 60.6 00.6 0 6-« « 0«.6 06.6 6«.6 «0.6 «0.60 «0.0 60.0 «0.6 00.6 « 0-0 « 00.6 «0.6 «0.6 00.6 ««.«0 00.0 00.00 «6.0 00.6 0 0-0 « 60.6 06.6 06.6 06.6 «0.0 06.« 00.0 00.6 60.6 0 6-0 « 00.6 06.6 «0.6 06.6 «0.0 00.0 00.0 00.6 «0.6 0 6-0 « 00.6 06.6 60.6 00.6 00.00 00.0 00.60 «0.6 «6.0 0 0-0 « 000 000 000 0 :0 0:00:60 0:00:60 0:00:60 0 00 000 03 00v 03 000 03 0:00 020 00000 000 000 z 00060 2 00663 2 0000 0000 00060 00663 0000 :00: 0:000: 110 Ac.u:oov um.a mHnma Hm.o mH.o o>.o m~.o no.5m mm.m. Hm.mH Ho.H oo.H m Hnm o o>.o oH.o Hm.o mm.o mm.o~ om.m mo.¢H «m.o nm.o H Hum m o¢.o no.o mm.o «H.o Hm.mH o¢.m mm.oH mn.o mm.o m cum m 5H.o No.0 «H.o mo.o mo.m ¢m.~ ¢H.m Ho.o m>.o H cum o ¢¢.o mo.o mm.o mH.o HN.HH m¢.m m>.m mn.o no.0 m Hum o mm.o «H.o H>.o m~.o om.wm Hm.m mm.>H mm.o mm.o H Hum m o~.o no.0 oH.o mH.o m~.HH mH.¢ ho.b H>.o bu.o m cum 0 mH.o ~o.o mH.o mo.o ~¢.m mm.~ «h.m mo.o mm.o H cum o oh.o oH.o om.o m~.o mm.- Ho.o vo.mH om.o mm.o m HuH m mm.o oH.o mm.o m¢.o mm.o~ Ho.m mm.¢H mm.o mm.o H HuH o om.o oH.o om.o ¢~.o mm.o~ no.m mm.nH om.o mm.o m ouH m hw.o HH.o mm.o H~.o m.mm m~.m Hm.mH mm.o mm.o H ouH m m~.o No.0 m~.o oH.o mm.» mo.~ mo.m om.o nw.o m Hum m m¢.o oo.o 0«.0 oH.o mm.¢H m~.m vm.HH mo.o mm.o H Hum m om.o vo.o o~.o HH.o mo.mH hH.¢ Hm.m mo.o mm.o m cum m om.o mo.o om.o ¢~.o ~>.o~ mo.m no.5H mm.o pm.o H cum m mH.o Ho.o mH.o mo.o oo.m mH.H mm.m om.o n¢.o m Hum m Hay Am. Amy A av ucmucou ucmucoo ucmucoo a H< Hwy as Amy as Amy us Haov Hay *mmua Hue me z Hmuoa z >oooa z mama mama Hmuoa acooz Mama amHo usonm 111 ««.m NN.H NN.¢ N.NmN o.NHH N.o¢H mN.H em.H NN.N H HuH N om.o mo.o mN.o N.mm H.mH N.oH NH.o NH.H oo.H N ouH N NH.o mH.o «o.o N.mH H.N m.N No.o HN.o NN.o H ouH N hm.o mo.o NN.o o.mH o.oH m.m HH.o NN.o eo.o N Hum N mo.N Nm.o NH.N m.mNH N.Nm N.NN NN.o m¢.H mN.H H Hum N NH.o Ho.o oH.o N.o H.e N.N mo.o Nm.o om.o N ouN N NN.o NH.o om.o N.m> N.HN m.m¢ mN.o pm.H NN.H H can N mm.o oH.o om.o e.mN o.oH m.m NH.o oN.o oN.o N HuN N mm.H mN.o NN.H m.mo N.NN N.HN mm.o «N.H NN.H H HnN N HH.o No.o mo.o m.m ¢.m m.« No.0 Nh.o am.o N ouN N em.o mH.o Ne.o N.No N.oN o.NN oN.o NN.H mN.H H ouN N NN.N oo.o NH.N o.oNH N.No N.Nm HN.o N¢.H mo.H N HuH N mN.N mm.o NH.N «.NNH 0.5m «.mo mm.o NN.H «o.H H HuH N Nn.o No.o oN.o m.NN H.mH m.NH mH.o oH.H «m.o N ouH N NN.o mo.o mN.o H.NN N.NH N.NH mH.o NH.H em.o H ouH N HN.N mN.H wm.H N.NNH N.mN N.HoH No.0 Nm.H Hm.H N Hum H no.N m¢.o hm.H N.HHH N.Hm o.mm No.0 NN.H mm.H H Hun H N¢.o mH.o NN.o o.NN o.mH o.NN NH.o m¢.H mm.o N cum H «N.o «N.o om.o H.mm «.HN N.NN mN.o oN.H oN.H H cum H «H.H NH.o um.o N.NN N.mN o.NH mN.o Nm.o mo.H N HuN H m¢.H NN.o NH.H N.mo N.NN m.NN «N.o NN.H NN.H H HuN H om.o 0N.o mm.o N.No N.NN N.NN NN.o N¢.H NN.H N onN H NN.H NN.o Ho.H o.om N.Hq N.¢¢ 0«.0 NH.H m¢.H H o:N H mN.N me.o Hm.N N.NmH N.NN N.NN oN.o Ho.H NN.H N HuH H mN.o No.o HN.o N.NH N.m m.N No.0 mm.o No.0 H HuH H op.o wH.o Hm.o N.NN o.HN N.mN m¢.o mm.o HN.H N ouH H oe.o No.o NN.o N.HN «.mH N.mH mH.o oo.H Nm.o H onH H Amy Hmv Amy H av ucmucoo ucmucoo ucoucoo Amy»: Amy»: Hmvuz m um Hay Aaov *mmue any me z Hmuoa z moooz z ummg Hmuoe mama acooz mama uanmm aaHa Ucflamawm mun» m>fiuosuummu mama umnfimuamm map scum mama mN.Q QHDMB 112 Nm.o NH.o om.o N.Nm N.NN N.NN NN.o oN.H NH.H H ouN m NN.o NH.o oN.o N.NN N.oN N.NH HN.o NN.o NN.o N HuN m NN.N oN.o NH.N H.NNH N.HN N.HN mm.o NN.H NN.H H HuN m om.o No.o oN.o N.NN N.NN N.NN NN.o oH.H No.H N onN m NH.o NH.o o N.NH N.N m.m No.o NN.o No.o H onN m NN.N oH.H NN.N N.NNN N.NoH o.NNH NN.H NN.H NN.N N HuH m HN.N mm.o NN.N N.NNH N.HN N.NN Nm.o NN.H HN.H H HuH m NN.o NN.o Nm.o N.NN o.mN N.NN oH.o NN.H NH.H N ouH m NN.N NN.o NN.N N.NNH H.oN N.NHH No.H NN.H NN.H H ouH m NN.o oH.o mm.o N.NN N.NH N.HH NH.o HN.o NN.o N HuN N NN.N oN.o NH.N N.NNH N.NN N.Hm NN.o NN.H NN.H H HnN N NN.o No.0 NN.o N.NN H.NH N.NH NH.o NN.o NN.o N ouN N o o o o N.o N.N oH.o NN.o Ne.o H ouN N HN.N NH.o NH.N N.HN o.Nm N.NH Nw.o NN.H NN.H N HuN N NN.N NN.H NN.m N.NNN N.NmH N.HNH NN.H NN.H Nm.N H HuN N HN.o No.o NN.o N.HN N.oH N.oH NH.N oN.o No.0 N ouN N NN.o No.o NN.o N.NN N.NH H.HH NH.N NN.o HN.o H cuN N No.m NN.H Nm.N H.mNN o.NN H.NNH No.H oN.H NN.N N HuH N mo.N om.o NH.N m.oNH N.NN N.NN NN.o NN.H HN.H H HuH N HN.o NN.o No.o N.NN H.NN H.NN NN.o NN.o NN.H N ouH N NN.o oH.o NN.o N.NN o.NH N.NH NH.o mm.o NN.o H ouH N Nm.N HN.o NN.H N.NHH N.Nm H.Ho mm.o NN.H HN.H N HuN N oN.N NN.o NN.H N.HHH N.Nm H.Nm NN.o NN.H Hm.H H HaN N o o o o o o NH.o HN.o NN.o N ouN N NN.o Nc.o NN.o N.NN N.NH N.HH NH.o NN.o NN.o H onN N NN.H NN.o NN.H N.NN H.NN N.oN NN.o NN.H NN.H N HuN N NN.N Nm.o NN.N NNH N.NN H.oN NN.o NN.N NN.H H HuN N No.H NN.o NN.o N.Ho N.NN N.NN NN.o HN.N NH.H N ouN N mN.o mo.o NH.o H.NH N.N N.N No.o NN.o mo.o H ouN N How Amy Amy A av ucmucoo ucmucoo ucmucou vaua Amvuz Hwy»: N “a Hay Haov *mmua uua me z Hmuoa z Noooz z ummq Hmuoe mama acooz Mama usonm aNHo Ac.u:oov NN.o mHnma 113 NN.N NN.o NN.H N.NHH N.NN N.NN NN.o NN.H HN.H N HuN N NN.N om.o NN.N N.NNH N.HN N.NN NN.H NN.H NN.H H HuN N NN.o NH.N oN.o N.NN H.NN N.NN oN.o NN.H NH.H N ouN N oN.o No.o NN.o N.NN N.HH N.N NH.N HN.H NN.o H ouN N HN.N NN.o NN.H N.NNH N.NN N.NN NN.o NN.H NN.H N HuN N NN.N oN.o NN.N N.NNH N.NN N.NN NN.o NN.H NN.H H HIN N HN.N No.o NN.o N.NH N.NH N.N NH.N oa.o NN.o N onN N NH.N No.o NH.N N.HN N.N N.N No.o NN.o NN.o H ouN N NN.N NN.o NN.N N.NNH N.NN N.NN NN.o NN.H NN.H N HuH N HN.N NH.H NN.N N.NNN N.NoH N.NNH NN.H NN.H HN.N H HIH N NN.H NN.o NN.o N.NN N.NN N.NN NN.o NN.H NN.H N ouH N NN.o NH.N NN.o N.NN H.NN N.NN NN.o NN.H HN.H H ouH N NN.H NN.o NH.H N.NN N.NN N.NN NN.o NN.H NN.H N HnN N NN.H oN.o NN.H N.NN N.NN N.NN NN.o NN.H NN.H H HnN N NN.o NH.N NN.o N.NN N.HN N.NN NN.o NN.H NH.H N ouN N ANN Amy Amy A av ucmucoo ucmucoo pcmucoo Amy»: Amvuz Hmvpz N Na 12V Aeov Nmous ans me z HNuoa 2 >000: z NNNA HNuoa mama Noooz Nqu ucmNmm ENNo AN.ucoov NN.o oHnNa APPENDIX E APPENDIX E 1990 Data Table B.1 Aboveground weed biomass (g/mz) in 1990 Planting Density Block 1 2 3 1 256.26 184.61 181.12 2 193.72 368.40 162.74 3 236.84 352.29 189.41 4 237.62 298.52 145.17 5 416.83 187.36 46.87 6 265.60 417.74 122.15 Average 267.81 301.49 141.24 Table E.2 Aboveground weed N content (9 N/mz) in 1990 Planting Density Block 1 2 3 1 2.15 3.10 2 2.01 5.71 2.25 3 2.97 1.95 4 1.97 3.17 1.56 5 4.93 3.20 0.84 6 2.88 3.02 1.78 Average 2.79 3.62 1.92 114 115 o o o o o o o mumaaflmmo azoflcmm o o o Hoo.o o o o NaoNuum mNHNxo o o o o o o o moaccw msuofiamz o o o o o o o N>NuNm omNoHNoz Hoo.o o o Noo.o o o o chHzmsH omNoNomz Noo.o 0 «6.6 o o o o muonN>th N>Hmz No.o o o o o o NN.o ssoNchuH> asNNNnmq o o o o o o o NHoHuumm mosuomq o o o o o o o mwscmu mzocsh NN.NH o NN.NH No.o No.NN o o snumuouumn aaoNummax o o o o o o o mmowwuum commoflum ow.NN HN.NN o o o ~m.mm o mammou NNUNHU>HM o o o o o o o Nammmsno acanoosflsom ¢C.MN mo.wnH 50.0 mo.o o o o mflamcwfimnmm maumufimwo o o o o o o o mausmazomm mahmaho 00.5ma oa.ooa Hm.m¢n No.5mm na.mma mn.~m vu.nam mfimcmflwcmo m~>cou om.~ om.H 5N.ma o o o o Hmwmcmwhmcon mn>coo mm.o 0N.H o o mo.o o o annam azfiooaosmno o¢.o o Hm.~ o o o o wmoNomam mmamumo o o o o o o o mwuwmas> mmumnumm NN.o o o o NN.N c o momNuzm mNHmmHomm 55.5 o o o o NN.NN o asswnmccmo asc>ooa¢ oN.o o o o o o HN.N NHsuoo mNamsu:< oN.o N5.o o o o NN.N o NNHouNNmNsouuN NNmouns< Noo.o o o o o 0 No.0 asflaommaafia mmaawno< oH.o o Na.o .o om.o o mo.o «ammusmomnu :oHNusnd mkum>< N m N m m a mmfiowmm mmfiomam xoon omma :N huwmsmc mswucmHm 30H man an A~fi\mv mmwommm ummz n.m manna .cou>mou0< mscmm map 0N >Humfiuom .mficflmuw> mo :uuo: ccmuxm ou c3osx #0: ma mNmsmNumcon .0 mo macaw was .Umwuflucmuwmfim wanmnoum mums mucmam mumse a m.mmN mm.wH¢ Nw.5mm vm.mnm Nh.m0H 0N.mmm H0808 £OOHm 116 msfluvmumm mafisoum> muouflo ssosxca mmcmumum aafiaouwua asoHunag ssHHoNHua mammmu Esaaomaua mamcflowuuo asomxmuma mNoma mflumaamum Numnmu mfiumumm mN0NNN> Mahmumm nonmav mfiumuom mammNuo xmasm NHHmmoumom xmasm mumom xmazm mwomomoosmma mfisanom muomu NHHNucmuom mowmm>uoc NHANucmuom mousmoum maawusouom mmomumao momazuuom acmoflumamusm x mzasmom mzaz>ao>coo Ezsomhaom mmmmumaoo mom Manna ommucmam asuoauwaoponoNc azoflcmm 0 00.0 0 0 m5.0m .H NN.H r-l 000000000000000000000Ln0 Q H N no fiOOOOOOOOOfiOOOOOOWOOOWO w co 0 O H N V O O l‘ O (x H O OMOOOOOOOOOOOOQ‘OOOOOOOO O N OOOOOOOOOOOOOOO®NOONO C mm.d m0.m V 0‘ OOOOOOOOOOOOOOOOOOWOOOO OOOOOOOOOOOOOOOOONOOOOO N O H \O O‘OOOOOOOOOOOOOOOO O H \0 w \0 N m0mum>¢ mmwummm \O ID V m N H mmfiommm xoon 16.»:ooe N.m mHnNs 117 Ho.o 5o.o o o o o o muNHHNQNo aaoNcmm No.0 0H.0 0 H0.0 0 0 0 macahum madmxo o o o o o o o moNucH mnuoNHmz o o o o o o o N>Numm ommoNNmz Hoo.o o o 5oo.o o o o chHsmsH owmoNomz o o o o o o o NHOHMN>MNQ m>amz 0 0 0 0 0 0 0 asoficwauw> esfinfimma HN.Nm 0 0 0 0N.00~ 0 0 macauumm cospomq 55.0 0 0 0m.0 an.m Hm.0 0 mflscmu unocah m00.0 0 0 no.0 0 0 0 azumuounmm aaofluoaam No.o o o o o NN.o o mmooHuum coummHum 0 0 0 o 0 o o mammmu «Hofiuu5Hm o 0 o 0 o o o Nammmzuo moHnoosflnom No.H NN.N o NH.H NN.H o o mNHchsocNm NNuNquNo N5.o o o 5N.N o o o msucstomm msuwm5o 00.0ma n.0ma m¢.05m HN.00H H.vva mo mfimcmumcmo Muhcoo wN.mN 0 o .0 0 0 NmNmsmNumcon Nuance no.0 0 0 00.0 HH.0 0 0 fiznam Bawflomocmno 0 0 0 0 o 0 0 mmoNoQO mmamumo NH.o o o m5.o o o o mNuNmHS> mmumnumm 0 0 o 0 0 0 0 womNu5m mmwamaom< NN.H o o No.o NN.oH o o ascHnmccmo anamooa< 0 0 0 0 0 0 0 mazuoo mwawnucc ~0.H m0.0 5N.a 5N.0 0 mm.m H5 aflflouwwmwfimuum mwmounad Noo.o o o o o No.0 0 asNHommHHNa NNHHNnoa NN.0 5m.0 0 05.0 0 00.0 H 0 Hummunmomnu :onuznd mmmum>¢ 0 m N m m a mmflommm mmfiommm omma :N 5me200 mswusmam aafluma man an ¢.m QHQMB Amfi\mv mmwomam Ummz .couhmouvd mscwm may :N adamauom .NNCNUHN> mo :uuo: Usmuxm ou :3osx #0: ma mNmsmNumcon .0 mo mmsmu was .omwufiusmcsflmfls Manmnoum mum3 musmflm mamas N 118 N5.5HN NN.5NH NN.NNN NN.NNN NN.NNN HN.NNH Hmuos xoon NN.N NN.N o NN.N o NN.H o chuomumm NoNcoum> NN.N NN.5 o 5o.o o o NN.NH muooHN asocxca 5N.NN o NN.NN o o HN.NNH N5.HH mmcmumua asNHouNus NN.H o o o o NN.NH o sonunaz asHHoNHus NN.H NN.5 NN.N o o o o mcmnmu azHNomNua NH.N No.0 NH.N NN.N NN.N Ho.o NN.N mHchoNuuo anomxmume o o o o o o o NNnma NHNNHHmuN 0 0 0 0 0 0 0 Numnmm Mahmumm 0 0 0 0 0 0 o mNcNuN> mwumumm 0 0 0 o 0 0 0 nonmaw mflumumm NN.N NN.NN o o o o o mammHuo stsm o o o o o o o NHHmmoumoN xmasm NN.o NN.N o o o NN.H o mumoo xmasm 0 0 0 0 0 0 0 mfiomomoozmmm mwswnom 0 0 0 0 0 0 0 muomu maafiusmuom NN.NH NN.NN o o HN.N NN.NN o monw>uoc NHHNucmuom NN.o o NN.N o o HN.N o mmucmoum NHHNucmuom o o o o o o o mmomumao nowazuuom o 0 . o o o o H .v . N o o MCMOHHmEmHn—m X mfiHfinwONm 0 o o o o 0 0 maaz>ao>coo ascooaaom 0 0 o 0 0 0 o mmmmumaoo mom 0 0 0 0 0 0 0 Hanna omnucnam N5.N NN.N o NH.HH NN.NH 5N.N NN.N asuoHuNaouonoNc anoNcNm momum>¢ N m N m N N mmwowmm mmflommm xoon Aflsucoov ¢.m manna 119 0 0 0 0 0 0 0 oumaafimmo asoflsmm 0~.0 00.0 0 0 0 HH.H 0 muofluum mwamxo 0N.0 0 o 0 mm.0 0 0 NUN0CN mauoNHmz NH.H HN.N o o o o o N>Numm oomoNomz o o o o o o o chHsmsH omNoNNmz o 0 o 0 0 0 0 NNOHHN>MNQ N>HNS 0 0 o 0 0 0 0 asoflcfimuw> aswcwmmq 0 0 0 0 0 0 0 maofluumm mozuomq No.0 0 0 5m.0 0 0 o mwacmu wsossb NN.NN o o oo.NN H5.NoH o o asumuouuma azoNuma>= 0 0 0 0 0 0 0 mmowfluum :oummwum NH.N o o o o o HN.N mammmu NNmHuuaHm 0 0 0 0 0 0 o Nammmsuo magnoocflnom NN.N NN.N o H5.oH o o o NNHNcHsocmm NHuNuNmNo 0 0 0 0 0 0 0 mausmazomm msumm5o 05.NN mm.m N.ma NN.N 5m.0m no.0 NN.NN mwmsmvmcmo anacoo NN.N 5N.NN o o o o NH.N HmchmNumcon Nu>cou No.0 0 0 0 NN.0 0 0 fianam anaconosmso 0 0 0 0 0 0 0 mmoNoQO NQHNHNU No.0 0 0 N~.0 0 0 0 mNuN0H3> mmumnumm 0 0 0 0 0 0 0 momwuhm mmwamaomc NN.N o o o NH.N o N5.N sacHnmccmo a::>oon¢ 0 0 0 0 0 0 0 wasuoo mwewnuc< NN.N o o NN.N o NH.N NH.HH NNHouNHmNamuuN NHmounsm 0 0 0 0 o o 0 Edwaommaawa mmaafisoc N5.o NN.N o No.0 o HN.N HN.N Nummusmomnu :oHNusn4 momum>¢ N m N m m a wwwommm mmwomam xooam m.w manna oNNH cN NuchmN chucmHm gmNs mg» uN ANaxwe mmHommm Now: 120 .sou5mouom mscmm on» :N haumeuom .oficfimuw> mo sumo: acouxw ou ssocx uo: mN mflmcmwuoson .0 mo mmcmu one .UmNuNucocmem >Hnmnoum mum: mucwaa mmmsa H NN.NNH 5N.NN 5H.NNH HN.NNH NN.NNH NH.HNH Hmuoe xoon oN.o NN.N o o o NN.N o chummuma woNcouo> NN.N NN.N o o NN.N HN.N NN.H muooNN caocxco oN.o NN.H o NN.N o o o omcmumum asHHoNNus NN.NH o o o o Nm.5 NN.NN asoNun5: asNHouNus N5.oH o NN.NH o o o N.NN mcmnmu ssHNouHus NN.N NN.NN o NN.N o o NN.H mHchoNuuo ssomxmuma 0 0 0 0 0 0 0 cwowa mwuoaamum 0 0 0 0 0 0 0 Numnou owumumm o o o o o o o mNNNuH> NHuNuwm Ho.o No.o o o o o o NUNNHN NNuNumm N5.H 0 o o 0 NN.0N 0 msnmwuo xmasm o o o o o o o NHHmmoumoN xmasm NH.H o o o o NN.N NN.N muwom xmaam o 0 0 0 o 0 0 Naomomoosmmm mNanom ~00.0 0 0 No.0 0 0 0 muomu oaawucmuom 5N.HN o NH.N NN.NN NN.NN NN.NNH o Nonm>uoc NHHNucmuom NN.H o NN.HH o o o o mmucmouu NHHNucmuom 0 0 0 0 0 0 0 ooomumao nomazuuom OH . o O o o 0 H0 . o o MEMOflHmBMHflm X mfidfiflom No.0 0 o 0 0 No.0 0 msaz>ao>soo 35:005Hom Noo.o o o o o o No.6 Nmmmumsoo mom o o o o o o o uoNNe ommucmHm NN.N NN.N o NN.NH NN.N NH.H 5m.o azuoHuNaouosoNc ssoNcmm mvmum>< N m N m m N mmwommm mwfiowmm xoon AN.ucoov N.m «Hams 121 Table E.6 Nitrogen data from weeds sampled in August 1990 Blk Trt Species Weight N Conc N Con (g/m ) (%) (9 N/m ) 1 1-0 Conyza canadensis 213.24 0.85 1.81 1 1-0 Panicum dichotomiflorum 26.44 0.96 0.26 1 1-0 Other species 8.91 0.94 0.08 1 1-0 Taraxacum officinale 7.67 * * 1 2-0 Conyza canadensis 140.09 * * 1 2-0 Other species 16.78 * * 1 2-0 Unknown dicots 15.98 * * 1 2-0 Trifolium pratense 11.76 * * 1 3-0 Trifolium hybridum 73.06 1.81 1.32 1 3-0 Trifolium repens 52.30 1.99 1.04 1 3-0 Conyza canadensis 28.45 1.20 0.34 1 3-0 Other species 27.31 1.46 0.40 2 1-0 Conyza canadensis 82.39 0.97 0.80 2 1-0 Elytrigia repens 55.52 0.79 0.44 2 1-0 Apocynum cannabinum 46.63 1.17 0.55 2 1-0 Other species 9.18 2.38 0.22 2 2-0 Trifolium pratense 152.91 2.01 3.08 2 2-0 COnyza canadensis 144.18 1.30 1.88 2 2-0 Potentilla norvegica 42.98 0.88 0.38 2 2-0 Other species 28.33 1.34 0.38 2 3-0 Potentilla norvegica 125.54 1.35 1.70 2 3-0 Other species 17.95 1.80 0.32 2 3-0 Rumex crispus 10.42 1.06 0.11 2 3-0 Conyza canadensis 8.83 1.33 0.12 3 1-0 Conyza canadensis 153.13 * * 3 1-0 Hypericum perforatum 58.06 * * 3 1-0 Panicum dichotomiflorum 18.86 * * 3 1-0 Other species 6.79 * * 3 2-0 Lactuca serriola 200.46 0.70 1.41 3 2-0 Conyza canadensis 108.21 1.00 1.08 3 2-0 Other species 24.20 1.22 0.30 3 2-0 Panicum dichotomiflorum 19.42 0.96 0.19 3 3-0 Hypericum perforatum 106.71 1.06 1.13 3 3-0 Potentilla norvegica 38.99 0.81 0.32 3 3-0 Conyza canadensis 30.57 1.16 0.35 3 3-0 Other species 13.14 1.14 0.15 122 Table B.6 (cont'd) Blk Trt Species Weight N Conc N Con (g/m ) (’6) (9 Wm ) 4 1-0 Conyza canadensis 227.64 0.83 1.89 4 1-0 Plantago major 9.34 0.79 0.07 4 1-0 Setaria viridis 0.41 0.86 0.004 4 1-0 Other species 0.23 1.54 0.004 4 2-0 Conyza canadensis 188.03 1.09 2.06 4 2-0 Conyza canadensis 90.42 1.00 0.90 4 2-0 Panicum dichotomiflorum 11.13 1.00 0.11 4 2-0 Other species 8.94 1.09 0.10 4 3-0 Potentilla norvegica 82.58 0.92 0.76 4 3-0 Hypericum perforatum 28.00 1.25 0.35 4 3-0 Other species 19.99 1.39 0.28 4 3—0 Panicum dichotomiflorum 14.60 1.18 0.17 5 1-0 Conyza canadensis 345.31 1.13 3.91 5 1-0 Trifolium repens 30.75 1.98 0.61 5 1-0 Other species 21.55 0.93 0.20 5 1-0 Hypericum perforatum 19.22 1.11 0.21 5 2-0 Conyza canadensis 150.33 1.52 2.29 5 2-0 Trifolium pratense 30.74 2.64 0.81 5 2-0 Potentilla argentea 4.49 1.61 0.07 5 2-0 Other species 1.80 1.72 0.03 5 3-0 Conyza canadensis 19.64 1.73 0.34 5 3-0 Trifolium pratense 12.03 2.53 0.30 5 3-0 Potentilla argentea 11.08 1.29 0.14 5 3-0 Other species 4.12 1.26 0.05 6 1-0 Digitaria sanguinalis 138.06 0.98 1.35 6 1-0 Conyza canadensis 100.30 1.23 1.24 6 1-0 Elytrigia repens 21.31 0.96 0.20 6 1-0 Other species 5.93 1.55 0.09 6 2-0 Conyza bonariensis 290.91 0.54 1.57 6 2-0 Rumex crispus 49.66 0.67 0.33 6 2-0 Other species 42.62 1.74 0.74 6 2-0 Potentilla norvegica 34.55 1.08 0.37 6 3-0 Taraxacum officinale 48.26 1.69 0.82 6 3-0 Conyza bonariensis 36.27 0.89 0.32 6 3-0 Other species 28.09 1.77 0.50 6 3-0 Conyza canadensis 9.53 1.57 0.15 1 Formerly in the genus Agropyron. 123 Table E.7 Data from the September 1990 detructive tree sampling Blk Trt Diam Height Woody Leaf Total (C!!!) (In) Wt (g) Wt (g) Wt (9) 1 2-0* 3.5 3.23 570 102 672 1 2-1* 4.8 3.9 1381 189 1570 1 3-0 2.25 2.79 200 38 238 1 3-1 4.08 4.09 1008 142 1150 2 2-0* 3.46 2.81 552 107 659 2 2-1* 4.86 3.76 1412 237 1649 2 3-0 3.35 3.5 483 74 557 2 3-1 3.31 3.41 515 73 588 3 2-0* 3.66 3.5 706 159 865 3 2-1* 6.34 4.31 2342 412 2754 3 3-0 1.68 2.25 97 22 119 3 3-1 2.87 3.03 368 61 429 4 2-0* 4.04 3.3 719 120 839 4 2-1* 5.54 3.43 1787 290 2077 4 3-0 2.85 3.4 364 55 419 4 3-1 3.58 3.33 600 81 681 5 2-0* 3.45 3.44 545 143 688 5 2-1* 5.45 4.19 1234 346 1580 5 3-0 2.84 2.91 342 79 421 5 3-1 3.6 3.52 693 85 778 6 2-0* 3.24 3.07 508 82 590 6 2-1* 5.1 4.74 1662 217 1879 6 3-0 3.23 4.09 538 168 706 6 3-1 3.61 3.72 643 102 745 These trees were actually removed from the extra ’2x1m planting’, not from the treatment plots. See Figure 2, page 15. The trees from the no weed control plots were not used in the regression analysis. These representative trees at the medium density were not linear when combined with trees from 1989 and 1991. 124 Table E.8 Prediction equations for total poplar biomass in 1990 Treatment1 Equation3 R2 N Weed Contro -189.837 + 84.313 (diam2) 0.957 83 SE of Coeff [50.506] [1.978] No Weed Control 55.942 + 46.040 (diam2) 0.747 70 SE of Coeff [29.942] [3.252] g All densities are combined into one equation. Predicted biomass (g), diameter (cm) at 15 cm above the ground. Data used for anlaysis was a compilation from destructive tree sampling in Sept 1989, Sept 1990 (from weed control plots only) and Sept 1991. 4 Standard error of the coefficient. Table E.9 Total Poplar biomass as predicted from regression equations Treatment BlOCk 1-1 1-0 2-1 2-0 3-1 3-0 1 277 21 773 141 1674 439 2 356 32 642 116 1155 541 4 268 34 722 94 968 474 5 256 64 642 146 708 573 6 355 35 615 108 1172 404 Average 302 37 679 121 1135 486 APPENDIX F APPENDIX F 1991 Data Table F.1 Poplar diameters (cm) in September 1991 Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 7.34 3.29 6.36 3.33 4.77 3.04 2 7.52 2.16 5.52 3.30 4.42 4.18 4 6.88 2.42 6.47 2.86 3.00 2.36 5 6.46 4.92 5.78 3.60 4.25 3.10 6 7.95 3.64 5.31 3.85 3.34 3.38 Average 7.23 3.29 5.89 3.39 3.96 3.21 * Diameter at 15cm above the ground, from destructive sampling Table F.2 Poplar total height (m) in September 1991 from destructive sampling Treatment BlOCK 1-1 1-0 2-1 2-0 3-1 3-0 1 5.48 2.94 5.78 3.61 5.56 3.88 2 5.74 2.17 5.00 3.58 4.54 5.08 4 5.22 2.38 5.47 3.27 4.02 3.82 5 5.66 4.04 5.58 3.80 4.93 3.69 6 6.26 3.17 5.62 3.70 4.78 4.64 Average 5.67 2.94 5.49 3.59 4.77 4.22 126 Table F.3 1991 Poplar leader length (m) Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 2.15 1.06 1.84 1.30 1.47 1.40 2 2.14 0.87 1.72 1.48 1.34 1.99 4 2.24 1.12 2.22 1.34 1.38 1.50 5 2.08 1.34 2.22 1.69 1.72 1.78 6 2.11 1.29 2.17 1.47 0.92 1.76 Average 2.14 1.14 2.03 1.46 1.37 1.69 Table F.4 Individual poplar leaf area (m2) in 1991 from destructive sampling Treatment BlOCk 1-1 1-0 2-1 2-0 3-1 3-0 1 4.42 0.60 2.39 0.45 0.80 0.34 2 5.04 0.39 1.47 0.68 0.67 1.00 4 4.83 0.61 1.99 0.65 0.54 0.20 5 2.82 1.54 5.50 1.01 0.86 0.48 6 5.03 1.66 1.55 0.92 0.29 0.59 Average 4.43 0.96 2.58 0.74 0.58 0.52 Poplar woody dry weight (g/tree) in 1991 from destructive sampling 127 Table F.5 Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 3985 486 2656 566 1431 494 2 4386 214 1984 616 1270 1021 4 3902 286 3380 432 634 332 5 2408 668 2244 1134 1526 534 6 4893 738 2044 738 677 653 Average 3915 479 2462 697 1107 607 Table F.6 Poplar total aboveground dry weight (g/tree) in 1991 from destructive sampling Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 4422 552 2900 619 1519 532 2 4938 255 2149 692 1321 1118 4 4465 344 3609 502 663 353 5 2736 834 2451 1242 1624 585 6 5488 906 2234 802 705 710 Average 4410 578 2669 771 1166 660 128 Table F.7 Poplar woody N content (g N/tree) in 1991 from destructive sampling Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 22.13 3.11 7.90 3.24 7.24 2.80 2 39.88 1.30 10.10 3.74 18.31 5.34 4 21.53 1.72 15.98 3.65 3.19 2.10 5 12.46 4.43 11.71 7.05 5.99 2.85 6 58.06 4.42 11.83 4.09 4.24 3.51 Average 30.81 3.00 11.50 4.35 7.79 3.32 Table F.8 G Poplar total aboveground N content (9 N/tree) in 1991 from destructive sampling Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 31.95 3.90 13.35 4.49 9.78 3.71 2 50.60 2.14 13.76 5.32 19.42 7.63 4 34.74 3.01 20.51 5.34 3.65 2.63 5 21.09 7.89 16.64 9.26 8.39 4.15 6 72.69 14.47 16.48 5.49 4.95 4.90 Average 42.22 6.28 16.15 5.98 9.24 4.60 129 Table F.9 Leaf Area Index in September 1991 from prediction equations Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 0.63 0.09 1.01 0.28 0.76 0.70 2 0.80 0.20 0.69 0.32 0.54 0.92 4 0.67 0.19 0.96 0.26 0.54 0.74 5 0.60 0.19 0.84 0.50 0.44 0.98 6 0.78 0.18 0.89 0.34 0.76 0.79 Average 0.70 0.17 0.88 0.34 0.61 0.82 Table F.10 Standing tree woody biomass (g/mz) in 1991 from prediction equations Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 544.2 31.8 1436.7 193.7 2027.4 821.8 2 720.7 83.0 936.7 227.6 1567.0 1021.2 4 586.8 139.6 1267.9 198.6 1338.4 866.1 5 509.0 138.7 1266.8 399.9 1109.0 1082.3 6 695.1 130.2 1218.3 258.4 1718.9 909.5 Average 611.2 104.7 1225.3 255.6 1552.1 940.2 130 Table F.11 Total standing poplar biomass (g/mz) in 1991 from prediction equations Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 643.3 37.8 1560.2 220.0 2161.8 897.9 2 840.9 100.0 1021.3 258.1 1661.3 1117.9 4 690.9 168.8 1378.3 225.5 1413.4 946.6 5 603.9 167.6 1377.1 452.4 1165.3 1185.2 6 812.2 157.3 1357.2 292.9 1826.8 994.4 Average 718.2 126.3 1338.8 289.8 1645.7 1028.4 Table F.12 Leaf Area Index in July as determined by canopy transmittance Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 0.26 0.05 1.70 0.26 1.89 1.29 2 0.28 0.05 1.37 0.35 1.47 0.98 4 0.60 0.08 1.24 0.29 1.88 1.19 5 0.20 0.10 1.40 0.63 1.38 1.38 6 0.39 0.05 1.54 0.26 1.74 2.45 Average 0.35 0.07 1.45 0.42 1.67 1.46 Foliar N concentration (%) in July 1991 131 Table F.13 Treatment BlOCk 1-1 1-0 2-1 2-0 3-1 3-0 1 2.88 2.07 3.24 2.39 3.18 3.11 2 3.14 2.59 2.99 2.87 3.14 3.12 4 3.16 2.38 3.18 3.18 2.98 3.29 5 3.29 2.86 2.98 2.94 3.32 3.56 6 3.03 2.92 6.31 2.92 3.43 2.93 Average 3.10 2.57 3.12 2.86 3.21 3.19 Table F.14 Abovground weed biomass (g/mz) in 1991 Planting Density Block 1 2 3 1 253.48 154.68 99.87 2 361.63 223.11 64.50 4 313.12 235.04 167.16 5 368.58 _255.88 52.14 6 880.42 286.08 56.90 Average 435.45 226.16 88.11 132 Table F.15 Aboveground weed N content (g N/mz) in 1991 Planting Density Block 1 2 3 1 3 60 2.48 1.26 2 6.13 3.07 1.36 4 5.12 6.36 2.82 5 5.24 5.00 0.96 6 10.78 4.06 1.06 Average 6.18 3.80 1.49 133 0 o o 0 o o 0 mwaommzvcflsv mammfloosmnuumm NN.o o NN.N oN.o o NH.N NN.o asuoHNNsouonoHN asoNcmm NN.N No.0 NN.N No.6 0 NH.N NN.N muoNuum NNHNxo o o o o o o o , N>Nuam ooNoHnmz HN.o o N5.o o o NN.N o NHoNuumm mozuowq NH.N o o o o NH.N NN.o mNscmu msocsn HN.NN HN.NN o No.NNN NN.NN o o asumuomumm azoNume5m HH.o o o o No.o o HN.o msmomNuum coummNum NN.NN o NN.NH NN.NN o NN.NN NN.NNH masccm coumNNum NN.N o o o o NN.NN o Hmcmemu NNmNuuaHm NH.o o o o o o N5.o moNocN chmsmHm NN.N NH.H No.6 NN.N o o o NNHNchmcam NNuNuHmNo No.6 o NN.o o o o o muoumo msosmo o o o o o o o NpNHOEan mNH5u000 0 0 0 0 0 0 0 msucmazomw msumaao HN.NN Noo.o NNo.o NN.N NN.NHH NH.N o mchmumcmo Nthoo NN.N o 6 No.0 6 o o mquHa> astuNo NN.N o o o o o NN.N mmcm>um astuNo 5N.HN o oo.oNN o o o o mmoNommm NeHmuNo o o o o o C o mcmuflc mfififihmo NN.NNH NN.N55 NH.NN o NN.N NH.N NN.NN msmoHNm umumm 0 o 0 0 0 0 o moawuhm mmwmmaom< NN.NN o o o HN.NN oo.N5H NN.H asanmcho ascsoom< ma.0 0 0 0 0m.0 05.0 No.0 cwaouflflmfiamuum camounad HN.N o o o o o NN.NN asNHoumHHHa NNHHNnoN NN.H HN.N NH.H NH.H No.6 NH.H o Nummuneomsu :oHNusn< mmmum>¢ N N N N N H mmNommm mmwommm goon Hmma :N auwmcmu vcfiucmaa 30H 02» um A~E\mv mmflommm 0003 0H.h NHQMB 134 .souamou04 mason map :N hauosuom H NN.0mm 0m.00m NH.mHm 05.0Nm N0.HNn 0N.mmm mommm>¢ xOOHm No.0 No.0 0 0 0 0 o mammmcu ssommnum> mm.0 0 mm.0 0H.0 0 mm.0 m0.H muoowb :3ocxcb HN.N 0 00.0 mm.0 0 ~0.~ 00.0H mmcmmmu ESNHOHHHB HN.N o o o o NN.NN o mmcmumue ssNNomNus NN.N o o o o NN.N o asoNunms esNHoNNNe mm.5a mm.Na mn.5m mm.ma 0m.w 00.5 mm.0m OHMCNONMHO Esomxmume NN.N o NN.H NN.N NN.NH o o mNHNuosm: omNoNNom o o o o o o o NNHoNNcNeNum omNNNHom No.6 o o NN.o o o o Numnmu NNuNumm 0N.0 o 0 mw.~ o 0 o nonmao Mahmumm m5.m 0 N0.0H 0~.N 0 0N.0 0m.m caawmoumom xmfism o o 0 o o o 0 muoHuNuHsfi mmom 5m.a o 00.5 0 o o o mNomomoomzmQ NNanom 0 0 0 0 0 0 0 msmofluou mssm 0 o 0 o 0 o o NCNNCN0HN> macsum 00.0 0 0 mm.0 0 0 0 msfluoumm macsum 0 0 0 0 0 o 0 muomu NHHNucmuom o o o o o 0 o amusmvum NHHNucmuom 0N.N o NN.N o o o o osmoNumsmusm x msasmom 0 o 0 0 0 0 0 BSONGN>H>mcmm ascom5aom 0m.0 0 0 mH.m 0 0 0 macaw mom am.o o o o 0 o NN.H mmsmumum sumacm 0 o 0 0 0 o 0 Hanna ommucmam mowum>¢. 0 m N m m N mmwommm mmfiomam goofim 10.»:000 NH.N «Hams 135 N5.o 5N.N o o o o o NNHoumschsv mammNoocmnuuNm NN.N NN.N Ho.o o o No.o NN.N ssuoHuNsouonoNN ssoNcNe 5N.o NH.N NN.H o No.6 o o muoNuum mNHNxo NN.N Nm.w 0 om.ma 0 0 0 N>Numm oONONcmz NH.N o NN.N o NN.N NN.N o NHoNuumm weapon; HH.H o NN.N NN.N o o NN.N mNscmu msocan NN.NN o o NN.N NN.NNN o o asumuomumm ssoHumesm NN.NH NN.HN o o o o o mcmemu NNmNuu5Hm NH.N o NN.N NN.N o om.NH NN.N mwmomfiuum coummNum HN.NH NN.NH NN.NH NN.NH o NN.NN o Nassau couoNNum o o o o o o o .NoNocN chmsmHm Ho.o No.o o No.o o o o mNHchsvcmm NNuNuNNNo o o o o o o o MHOHMO mDOSMQ 0 0 0 o 0 0 o mumumson mfiaxuomo NN.N o o o NH.N o e msucmHsomm msume>o NN.NN No.oN N5.N NN.NHH NN.NNH NN.NN NN.N mchmcmcmo NNscoo 55.NN o NN.NN HH.NN o o o muNmHa> astuNo NH.N o o o o o NN.N mmcm>uN asHmuNo o o o o o o o mmoNowdm NQHNuNo o O o o o o o mcmufic mflflflHMU NH.NN NH.NHH NN.N o o NH.NH 55.N5 szoHNd “meme 0 0 0 0 0 0 0 NONNM>m mmwamaom< NN.N NN.N o HN.N NN.NN NN.N NN.NH asanNcho ascNOoQN 5N.o oH.o NN.N o o NN.N No.o NNHoNNNmNsmuuN NNmounaa NN.N o o o o o NN.N asNHommHHNs NNHHNnoN NN.N No.o o NN.H HH.N N5.o NH.N Nummuneomsu :oHNuan mowum>< o m N m m N mmwommm mmflommm xoon Hmma :N huflmsmo mcwncmaa sswnms on» no 5H.h QHQwB A~a\mv mmwomam 0003 136 .cou50ou04 mzsmm 0:» CN adumsuom a 00.0mm mm.mm~ N0.mm~ Nm.mmm 5m.mma 00.de 000h0>< xOOHm 0 0 0 0 0 0 0 mammmnu ssommnum> ««.0 NN.0 0H.0 0m.0 0«.0 0 NN.0 muoowv c3osxcb N5.N oH.o NN.oN NN.N o NN.N N5.NH mmcmmmu ssNHouNus NN.N o o NN.N o NN.H o «Nemumue asNHouNue NN.0 NN.N o 0 0 o o savaun5: ssfiaoufiua 0N.0H m5.wa NN.5N 0H.mm N5.0 00.0 N5.HN OHMCHOwumO BflOMXMHMB NN.NH NN.N HN.NN NN.5 NN.NN o o mNHNuoam: omNNNHom HH.N o o o o o NN.o NNHoNNcNeNum ONNNNHom No.6 No.0 6 NH.o o o o Numnmu NNuNumw 0 0 0 0 0 0 0 moamam Mahmumm 0N.m 00.0 m00.0 0 0 mm.Nm Nm.H maammoumoo xmasm NN.o o o o o o NN.H muoHuNuHsa mmom 0 o o o 0 0 0 mwomooocmsmm aficdnom No.0 0 HN.0 o 0 o o mCNONumu mama 0 o 0 0 o 0 0 NCNNCN0MN> wasnum o o o o 0 o o msfiuoumm mzczum 00.0 0 0 0N.0 mN.m mm.m 0 muOOH MHHHusmuom 5N.0 o H0.N o o o o mmucmmum maawucwuom 0 o 0 0 0 0 0 ocooflumsmusm x msazmom 0 0 0 o o 0 0 asONGN>H5msmm ascom5aom N5.H 0 0 mm.0 0 0 No.0 macaw mom 0 o o 0 o 0 0 mucoumum samacm o o o o o o 0 Hanna ommusmam momum>< N N N N N H mmNomam mmfiowqm xooam AN.ucoov NH.N «Hams 0 0 o 0 0 o 0 mNaoumschsv mammfioocmnuumm NH.N o NN.N o o No.0 NN.N sauoHuNsouonoNo ssoNcmm HH.0 no.0 0 0 0 0 0 muONuum mNmeO NN.H mm.m 0 0 0 0 0 N>Numm ovcoflcmz 0 0 0 0 0 0 0 mHoNuumm monuoma NN.N o NN.N 5N.H o o NN.N mNscmu maocsn NN.NN o o No.NNH NN.NN o o sensuouume asoNuma5: 5H.o o No.H o o o o msmovNuum commoNum NN.N o 5m.m o NH.N o o Nassau coumoNum NN.N 0N.NN o o o o o Hmcmmmu NflmNuu5Hm 0 0 0 0 0 o 0 NONUGN mcwmamam Noo.o No.6 6 o o o o mHHchsmcmm NNuNuNNNo Ho.o o 5o.o o o o o muoumo msosuo NN.N o o NN.N o o NN.N NumumsoHN NNH5uomo Hoo.o o o o HN.N o o msucmHaomm maumdxo NN.N o NN.N NN.H NN.N 5N.NH NN.N mchmNNcNo NNNcoo ~00.0 0 0 No.0 0 0 0 mummaz> szfimuwu 0 0 o 0 o o 0 mmcm>uo asfimuwo 0 0 o 0 0 0 0 omoflommm NQHNHNO NN.N o o o o o NN.N manna: mssuumo NN.N NN.N o NN.NH o o NH.N msmoaNe uwumc NN.N o o NN.N o o o NONNumm mNNemHoma NN.HN o NH.NN o NN.NN NN.NN NN.HN aaanNccmo anamoom< NN.N o NN.H o o o NN.N NNHouNHmNsmuuN NNmounsN 0 0 0 0 0 0 0 saflaommaaws mmHHN:O< 5H.o NH.o Ho.o NN.N o No.6 NN.o Numaunnomnu :oHNuzn4 mmmum>< N N N N N H mmNomem mmfiommm xoon md.m OHQMB amma :N hauchmo mswucmam now: may um A~a\0v mmflomnm 0003 138 .souamoumd mscmo 0:» GM 5Hu0suom H 00.00 NH.Nm No.00a wn.NmH 00.N0 00.00 Ommum>< XOOam N00.0 0 0 No.0 0 0 0 mammmsu ssommnum> mm.0 H0.0 00.0 00.0 N.0 N5.H Hm.0 quOwU c30chD 00.N 0 m0.~ 0 0 NN.NN NH.0 mmcmmmu ssfiaowwus NN.H 0 05.0 NN.N 0 0 HN.N mmcmumue ssNHouNus N00.0 N0.0 0 0 0 0 0 ssoNun>n esfiaomfiue 00.« N0.0 0H.N 00.N 0.0 N~.0 mm.m GHMCHONMMO Esomxmuma NH.0 0 NN.0 0 0 NN.0 0 mNHNuosm: cachHom N5.H NN.N NN.N 0 0 0 NN.N NNHomNchNuv omchNom 0 0 0 0 0 0 0 Numnmm Mahmumm 0 000.0 0 0 0 0 0 nonmam afiumumm 00.0 0 00.0 5N.0 0.0 50.m 00.0 MAHOmOUGOM xmfism 0 0 0 0 0 0 0 NHONMNHHSE mmom 0 0 0 0 0 0 0 Naomomovosmm mfiswnom No.0 NN.0 0 o o o 0 mcmoNNNu menu No.0 0 No.0 oH.o o o o NcmNcNouN> museum 0 0 0 0 0 0 0 mcfiuoumm macsum m~.0 mm.0 00.0 0 0 0 Nm.0 muomu maawucmuom 0 0 0 0 0 0 0 mmucmmum waawusmuom 0 0 0 0 0 0 0 NQNONumsmusm x maHsQom m00.0 No.0 0 0 0 0 0 a50N20>H>mst ascov5aom 0 0 0 0 0 0 0 macaw 00m 0 0 0 0 0 0 0 mmcmumum asmasm HH.0 o o o o o NN.N uoNNs ammucmHm m0mum>< N N N N N H mmNomem mmwomam xoon 10.00000 NH.N «Hams 139 Table F.19 Nitrogen data from weeds sampled in August 1991 Blk Trt Tree Species Weig t N conc N con (g/m ) (35) (9 Wm ) 1 1-0 1 Erigeron annuus 154.56 1.14 1.76 1 1-0 1 Other species 50.07 1.77 0.89 1 1-0 1 Aster pilosus 44.00 1.42 0.62 1 1-0 1 Achillea millefolium 31.66 1.07 0.34 1 1-0 2 Erigeron annuus 106.42 1.02 1.09 1 1-0 2 Other species 52.92 1.84 0.97 1 1-0 2 Aster pilosus 35.15 1.77 0.62 1 1-0 2 Trifolium repens 32.18 2.77 0.89 1 2-0 1 Other species 41.04 1.48 0.61 1 2-0 1 Taraxacum officinale 29.13 2.12 0.62 1 2-0 1 Trifolium repens 25.45 2.55 0.65 1 2-0 1 Apocynum cannabinum 24.81 1.27 0.32 1 2-0 2 Aster pilosus 128.33 1.39 1.79 1 2-0 2 Other species 27.17 1.24 0.34 1 2-0 2 Poa annua 19.09 1.65 0.32 1 2-0 2 Taraxacum officinale 14.35 2.30 0.33 1 3-0 1 Apocynum canabinnum 56.81 1.72 p 0.98 1 3-0 1 Aster pilosus 10.28 1.48 0.15 1 3-0 1 Other species 1.67 2.24 0.04 1 3-0 1 Taraxacum officianle 1.25 2.34 0.03 1 3-0 2 Other species 46.16 2.08 0.96 1 3-0 2 Apocynum cannabinum 45.58 * * 1 3-0 2 Aster pilosus 20.38 * * 1 3-0 2 Dactylis glomerata 17.61 2.08 0.36 2 1-0 1 Apocynum cannabinum 350.00 1.61 5.63 2 1-0 1 Other species 13.60 2.11 0.29 2 1-0 1 Erigeron annuus 11.65 1.14 0.13 2 1-0 1 Taraxacum officinale 9.85 2.27 0.22 2 1-0 2 Trifolium pratense 112.96 2.11 2.39 2 1-0 2 Erigeron annuus 107.44 1.46 1.57 2 1-0 2 Other species 74.62 1.80 1.34 2 1-0 2 Elytrigia repens1 43.14 1.56 0.68 2 2-0 1 Erigeron annuus 91.87 1.48 1.36 2 2-0 1 Rumex acetosella 67.12 0.97 0.65 2 2-0 1 Conyza canadensis 43.89 1.80 0.79 2 2-0 1 Other species 36.20 1.98 0.72 140 Table F.19 (cont’d) Blk Trt Tree Species Weig t N conc N co t (g/m ) (3‘) (9 N/m ) 2 2-0 2 Rumex acetosella 42.66 1.21 0.51 2 2-0 2 Conyza canadensis 41.41 1.97 0.82 2 2-0 2 Other species 40.80 2.01 0.82 2 2-0 2 Aster pilosus 28.27 1.65 0.47 2 3-0 1 Trifolium repens 33.99 3.16 1.07 2 3-0 1 Conyza canadensis 23.97 1.70 0.41 2 3-0 1 Reumex acetosella 5.71 1.46 0.08 2 3-0 1 Other species 1.58 2.70 0.04 2 3-0 2 Apocynum cannabinum 48.88 1.54 0.75 2 3-0 2 Conyza canadensis 5.97 2.30 0.14 2 3-0 2 Trifolium repens 4.91 3.19 0.16 2 3-0 2 Other species 3.98 1.70 0.07 3 1-0 1 Conyza canadensis 175.91 1.32 2.32 3 1-0 1 Apocynum cannabinum 40.85 0.95 0.39 3 1-0 1 Taraxacum officinale 1.80 1.54 0.03 3 1-0 1 Other species 0.06 0.71 0.000 3 1-0 2 Hypericum perforatum 131.18 1.22 1.60 3 1-0 2 Conyza canadensis 55.32 1.30 0.72 3 1-0 2 Other species 27.21 1.12 0.30 3 1-0 2 Solidago nemoralis 21.24 1.35 0.29 3 2-0 1 Hypericum perforatum 700.00 1.91 13.37 3 2-0 1 Apocynum cannabinum 58.59 1.33 0.78 3 2-0 1 Potentilla recta 6.50 1.46 0.09 3 2-0 1 Other species 0.30 0.89 0.003 3 2-0 2 Conyza conadensis 271.12 1.28 3.47 3 2-0 2 Solidago nemoralis 50.44 1.32 0.66 3 2-0 2 Hypericum perforatum 26.49 1.26 0.33 3 2-0 2 Other species 6.44 1.28 0.08 3 3-0 1 Hypericum perforatum 135.04 1.78 2.40 3 3-0 1 Apocynum cannabinum 16.22 1.49 0.24 3 3-0 1 Conyza canadensis 6.88 1.72 0.12 3 3-0 1 Other species 2.70 2.18 0.06 3 3-0 2 Hypericum perforatum 56.63 1.35 0.76 3 3-0 2 Apocynum cannabinum 42.86 0.87 0.37 3 3-0 2 Erigeron annuus 4.25 0.79 0.03 3 3-0 2 Other species 0.19 1.67 0.003 141 Table F.19 (cont’d) Blk Trt Tree Species Weig t N conc N cogt (Q/m ) (2;) (9 Wm ) 4 1-0 1 Hypericum perforatum 241.65 1.60 3.88 4 1-0 1 Taraxacum officinale 27.07 2.12 0.57 4 1-0 1 Other species 8.01 1.81 0.14 4 1-0 1 Rumex acetosella 4.51 1.74 0.08 4 1-0 2 Hypericum perforatum 262.48 1.74 4.56 4 1-0 2 Erigeron annuus 59.76 0.87 0.52 4 1-0 2 Other species 16.97 2.19 0.37 4 1-0 2 Setaria glauca 5.78 1.94 0.11 4 2-0 1 Taraxacum officinale 56.95 2.25 1.28 4 2-0 1 Cirsium vulgare 55.40 1.38 0.76 4 2-0 1 Other species 16.71 2.30 0.38 4 2-0 1 Hypericum perforatum 4.63 2.01 0.09 4 2-0 2 Conyza canadensis 220.57 1.85 4.09 4 2-0 2 Other species 55.19 1.74 0.96 4 2-0 2 Medicago sativa 31.71 2.65 0.84 4 2-0 2 Erigeron annuus 28.91 1.13 0.33 4 3-0 1 Hypericum perforatum 264.46 1.65 4.36 4 3-0 1 Trifolium pratense 12.67 2.82 0.36 4 3-0 1 Other species 11.64 1.87 0.22 4 3-0 1 Aster pilosus 6.80 1.50 0.10 4 3-0 2 Aster pilosus 17.77 1.43 0.25 4 3-0 2 Other species ' 8.08 2.07 0.17 4 3-0 2 Hypericum perforatum 7.61 1.19 0.09 4 3-0 2 Asclepias syriaca 5.29 1.41 0.07 5 1-0 1 Catalpa speciosa 500.00 1.21 6.03 5 1-0 1 Other species 74.98 2.12 1.59 5 1-0 1 Taraxacum officinale 31.33 2.20 0.69 5 1-0 1 Erigeron annuus 29.15 1.06 0.31 5 1-0 2 Aster pilosus 48.65 1.28 0.62 5 1-0 2 Taraxacum officinale 43.42 2.34 1.02 5 1-0 2 Trifolium repens 4.89 2.56 0.12 5 1-0 2 Other species 4.73 1.85 0.09 5 2-0 1 Cirsium vulgare 195.48 1.61 3.15 5 2-0 1 Other species 18.61 1.61 0.30 5 2-0 1 Trifolium repens 14.82 2.62 0.39 5 2-0 1 Taraxacum officinale 9.01 2.74 0.25 142 Table F.19 (cont’d) Blk Trt Tree Species Weig t N conc N con (9/111 ) (’6) (9 Wm ) 5 2-0 2 Solidago nemoralis 104.95 1.67 1.76 5 2-0 2 Trifolium repens 65.75 2.66 1.74 5 2-0 2 Other species 57.27 1.89 1.08 5 2-0 2 Taraxacum officinale 45.88 2.90 1.33 5 3-0 1 Apocynum cannabinum 44.38 1.86 0.82 5 3-0 1 Erigeron annuus 19.94 1.41 0.28 5 3-0 1 Other species 11.71 2.12 0.25 5 3-0 1 Conyza canadensis 9.67 1.90 0.18 5 3-0 2 Solidago graminifolia 8.90 1.96 0.17 5 3-0 2 Other species 5.83 1.92 0.11 5 3-0 2 Taraxacum officinale 1.99 2.17 0.04 5 3-0 2 Trifolium repens 1.85 2.71 0.05 6 1-0 1 Aster pilosus 809.35 1.03 8.34 6 1-0 1 Hypericum perforatum 164.02 0.94 1.54 6 1-0 1 Taraxacum officinale 9.36 1.68 0.16 6 1-0 1 Other species 1.06 1.57 0.02 6 1-0 2 Aster pilosus 750.00 1.47 11.02 6 1-0 2 Taraxacum officinale 20.60 1.84 0.38 6 1-0 2 Abutilon theophrasti 4.18 1.94 0.08 6 1-0 2 Other species 2.28 1.85 0.04 6 2-0 1 Aster pilosus 159.17 1.42 2.26 6 2-0 1 Other species 52.20 1.50 0.78 6 2-0 1 Conyza canadensis 39.90 2.00 0.80 6 2-0 1 Taraxacum officinale 35.91 2.22 0.80 6 2-0 2 Elytrigia repens1 183.81 1.05 1.93 6 2-0 2 Aster pilosus 71.16 1.49 1.06 6 2-0 2 Medicago sativa 17.68 2.85 0.50 6 2-0 2 Other species 12.33 * * 6 3-0 1 Elytrigia repens1 66.99 1.71 1.14 6 3-0 1 Medicago sativa 18.57 1.91 0.36 6 3-0 1 Taraxacum officinale 4.16 1.97 0.08 6 3-0 1 Other species 3.52 2.18 0.08 6 3-0 2 Taraxacum officinale 13.47 2.42 ' 0.33 6 3-0 2 Aster pilosus 5.98 1.88 0.11 6 3-0 2 Oxalis stricta 0.67 1.57 0.01 6 3-0 2 Other species 0.43 2.73 0.01 1 Formerly in the genus Agropyron. 143 NN.NN HN.NN 5N.HH NN.NNNN NNNN NN.5NN NN.N NN.N 55.5 NNH H H H NN.N NN.N NN.N N5.NNN 5NN N5.N5 H5.o NH.N NN.N NNH 7 H H NN.N N5.N NH.H NN.NNN NNN NN.NN NN.N N5.N NN.N NNH 7 H H NN.NH NN.5 5N.N 5N.NNHN H5oN 5N.NNH NH.H NH.N NN.N NNH H N N HH.N N5.N NN.H 5N.NNoH HNN 5N.5N NN.N H5.N NN.N NNH H N N NN.N NN.N HN.N NH.NNN NNN NH.HN NN.o NN.N NN.N HNH 7 N N HN.H NN.H NN.N NN.NNH N5H NN.NH NH.N N5.N NH.N oNH 7 N N NH.NH NH.NH NN.N NN.N05N NNNN NN.NNN NN.N NN.N NN.N NHH H N N NH.NH NN.HH NN.N No.5NHN NNoN NN.HNH NN.H NN.N NN.N NHH H N N HN.NH NN.N NN.N HH.NNoH NNN HH.NNH NH.H NN.N NN.N 5HH 7 N N NN.N NN.5 NN.H NN.NoNH NHNH NN.NN NN.N HN.N 5N.N NHH 7 N N 5N.NN NN.NH NN.HH NN.NNNN NNNN NN.HNN 5N.N NN.N HN.5 NHH H H N NN.5H NN.HH NN.N NN.N5HN NNNH NN.NHN N5.H N5.N HN.N NHH H H N NN.NH NN.N NN.N 5N.NNN NH5 5N.HNN NN.N NN.N 5N.N NHH 7 H N NN.N 5N.N NN.N N5.NH5 NNN N5.NN NN.N NN.N 5N.N NHH 7 H N HN.N NN.N NH.N NH.NNN 5HN NH.5 50.0 NN.N HN.N HHH H N N NN.N NN.N NN.H NN.NNN 5NN NN.NN HN.N 5N.N NN.N oHH H N N NN.N NN.N NN.H 5N.NNN 55N 5N.NN 0N.o NN.N NN.N NoH 7 N N NN.N NN.N HN.H NN.NN5 NN5 NN.NN NN.N 5N.N NN.N NoH 7 N N NN.NH NN.NH N5.N NH.NNNN NHNN NH.5NN HN.N NN.N 55.N 50H H N N N5.NH NH.NH NN.N NN.NHNH NNNH NN.NNH NH.H NH.N NN.N NoH H N N NN.N NH.N NN.H HN.HNN NNN HN.NN NN.N NN.N NN.N NoH 7 N N NN.N NN.N NN.H NN.NNoH NNN NN.HN NN.H NN.N NN.N NoH 7 N N NN.NoH NN.5N NN.NH 5H.5oNN N.HNNN 5N.NNN N5.N NH.N NN.N NoH H H N NN.NN NN.NN NN.NH NN.NNNN NNNN No.NNN NN.N NN.N NN.5 NoH H H N NN.N NN.N NN.H NN.NNN HHN NN.NN N5.N NN.N N5.N HoH 7 H N N5.NN NN.N NN.N NH.5HNH NNoH NH.NNN 5N.N NN.N NN.N 00H 7 H N Amvueoo locucoo Avcucoo 10003 10003 locus A N50 lac .aoc *mmua a: me z HNuos z 50003 2 NNN; Hmuos 50003 “NNN NNNNN mama uszo: aaNo onwamamm mmuu 0>Nuoauummc amma umnawummm 0:» scum mumo 0N.m wanna 144 NN.N NH.N NN.0 N5.NNN HNN N5.NH NH.0 NN.N NN.N NNH HuN N N0.N NN.H 00.H 0N.NNN 00N 0N.NN 0N.0 NH.N NN.N NNH 0uN N NN.0 NN.0 NH.0 5N.N0 05 50.5 50.0 0N.H HH.H NNH 0-N N NN.0 NN.0 NN.0 5N.HN 0N 5N.NH NH.0 HN.H NN.H HNH HuH N 5N.0N NN.NN 00.5 N5.NNNN 0NHN N5.N0N NN.N H5.N NN.N 0NH HuH N 00.0 NN.0 5N.0 HN.HHH 50 HN.NH NH.0 5N.H 00.H 0NH 0uH N HN.0 NN.0 No.0 NN.NN NN NN.H N0.0 00.0 NN.0 NNH 0uH N NN.N 0N.N N0.H 0N.NN5 5N5 0N.NN NN.0 HN.N 05.N 5NH HuN N 0N.NN eNN.NN 5H.H HH.NNNH N00H HH.NN HN.0 NN.N NH.N NNH HnN N N5.N NN.N 5N.N HH.HNHH NN0H HH.NNH 5N.H NN.N 5N.N NNH 0uN N NN.N NN.N NN.H NN.N50H 0N0H NN.NN N5.0 NH.N 00.N NNH 0uN N NH.NH 05.HH NN.N NN.5NNN NNNN NN.NNH NN.H NN.N 00.N NNH HuN N NN.HH NN.N N0.N 0N.HN5H NHNH 0N.5NH NN.H 0N.N NH.N NNH HnN N HN.N 0N.N HN.0 N0.NNN NNN 00.NN NN.0 0N.N 0H.N HNH 0uN N NN.N NH.N NN.N NN.NN5 NNN NN.NN 05.0 NN.N HN.N 0NH 0sN N NN.NN HN.NN NN.0H NN.N0HN NNNN NN.NHN N5.N HN.N N0.5 0NH HuH N N5.NN NN.NN NN.0H NN.055N NNHN NN.5NN NN.N NH.N 00.5 NNH HuH N NN.N N0.H NN.H NN.NNN NNN NN.NN NN.0 NN.N N5.N 5NH 0uH N N0.H N5.0 HN.0 NN.HNH 50H NN.NH 5H.0 05.H 0N.H NNH 0uH N HN.N 00.5 HN.H NN.NoNH 0NNH NN.NN NN.0 5N.N NN.N NNH HnN H NN.HH NN.5 N5.N N5.NNNH NHNH N5.NHH 00.H NN.N 00.N NNH HuN H N0.N 5N.N NN.0 NN.50N 5NN NN.0N NN.0 N5.N 00.N NNH 0uN H 0N.N NN.N NN.0 NN.NNN HNN NN.NN. NN.0 H0.N 00.N NNH 0uN H NN.NH NN.0H NN.N NN.NNNN NNHN NN.NNN NN.N 00.N H5.N HNH HuN H HN.0 NN.N NN.N H5.N5NN 5NHN H5.NNH 0N.N 5N.N H0.N 0NH HuN H NN.N NN.N NH.H NN.NN5 05N NN.5N HN.0 NN.N NN.N NNH 0uN H HN.N N0.N 5N.H NN.HHN NNN NN.0N NN.0 NN.N NN.N NNH 0uN H NN.0N NN.0N 00.5 0N.NN0N NHNN N.NNN NH.N H0.N N0.N 5NH HnH H 1000000 1000000 1000000 10003 10003 10003 .Nsc Hay 1000 50005 was me 2 H0009 z 50002 2 0000 H0009 50003 0000 0000 0000 000000 00H0 10.00000 0N.N 0HnNs 145 00.0 NN.0 H0.0 50.50HH 050a 50.00 N0.0 00.N H0.N H5H Him N 00.0 00.0 0 00.00H 00H 0 0 0H.m 00.H 05H Him N 00.H 5N.N 0N.0 NH.0NN omm NH.0 00.0 00.0 00.H 00H olm N 05.0 N0.N 00.0 5N.00N NNN 5N.0m 00.0 0H.N 55.N 00H 0Im N 0N.0N HN.HN 00.5 00.NO0N 000N 00.000 H0.N 00.0 05.0 50H Him N 00.NH N5.0H H0.H 00.0000 N000 00.HOH 0N.H 00.N 0H.0 00H HIN N 00.5 00.N N0.N 00.0N5 ~00 00.0HH 0H.H 05.0 00.0 00H 0IN N 00.0 N0.N 0N.0 NN.00N 0N0 NN.0N 00.0 N0.N 00.N NOH 0IN N 50.00 00.00 HH.0H 50.0005 0500 50.000 No.5 Nm.0 N0.0 00H HIH N HN.5H HN.0H 00.5 0N.000H 0NNH 0N.05N N0.N 0H.N 00.0 00H HIH N 05.H 00.0 00.0 NN.00H 00H NN.0m 0N.0 05.H 00.H HOH old N 5N.N H0.N N5.N 00.00N ANN 00.05 N5.0 00.N 00.N 00H 0IH N 0N.0 00.N 0N.0 00.0H0 00N 00.00 5H.0 00.N 00.N 00H Him 0 05.H 50JH 0H.0 N0.HHO N00 00.5 NH.0 0N.N 00.N 00H Ham 0 0N.H 00.H NH.0 H0.5NN NNN H0.0 00.0 HN.0 00.N 50H 0Im m NN.N 0N.N 00.0 00.550 5N0 0.0m 0N.0 00.N 50.0 00H 0:0 0 m0.0 00.N 50.H 00.000 H50 00.00 00.0 N0.N N0.N 00H Ham 0 1000000 1000000 1000000 10003 10003 10003 ANec 100 1000 50000 009 0H0 z Hmuoa 2 50003 2 “000 Hmuoe 50003 0000 00H< «000 unmflmm ENNQ 10.00000 0N.0 0H000 146 Table F.21 Soil moisture content (%), August 5-6, 1991 Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 7.34 8.89 8.42 8.04 21.46 16.06 2 12.74 11.97 8.68 9.94 10.29 11.17 4 11.83 11.40 10.71 13.37 11.38 7.84 5 12.45 13.44 12.91 12.51 7.07 7.69 6 14.54 12.56 11.68 18.82 11.04 16.30 Average 12.10 13.17 11.10 13.39 12.82 14.07 Table F.22 Extractable NH4-N (pg N/g soil), August 5-6, 1991 Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 0.84 1.99 1.02 1.75 1.50 2.09 2 1.94 2.53 0.63 3.34 1.92 2.17 4 1.82 2.39 1.64 3 32 1 66 2.26 5 2.29 3.15 3.04 3.06 1 31 2.49 6 2.42 3.02 2.21 4.49 3.78 4.66 Average 2.22 2.87 1.90 3.30 2.17 3.39 147 Table F.23 Extractable NO3—N (ug N/g soil), August 5-6, 1991 Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 0.72 5.19 2.10 4.12 8.16 10.82 2 1.40 1.49 5.38 0.68 0.56 5.80 4 2.83 7.10 0.97 1.23 0.51 3.75 5 1.74 0.71 1.13 4.00 0.87 3.80 6 1.79 2.15 0.83 3.13 0.97 2.39 Average 1.85 1.67 1.05 1.92 0.98 1.38 Table F.24 Mineralization rates (pg N/g soil/day), August 5-6, 1991 Treatment Block 1-1 1-0 2-1 2-0 3-1 3-0 1 0.12 0.27 0.14 0.26 0.49 1.28 2 0.50 0.33 0.31 0.45 0.29 0.43 4 0.12 0.54 0.12 0.64 0.16 0.26 5 0.04 0.58 0.17 0.69 0.13 0.48 6 0.38 0.47 0.28 0.61 0.29 0.48 Average 0.23 0.44 0.20 0.53 0.27 0.59 APPENDIX G 148 0000 H.000 000 5.5HN N.0N N.000H H.N 0IN 0 000H 0.000 NNN N.50H 0.0m .N.000 0.5 010 0 HNHH 0.000 000 0.000 0.00 0.0mm 0.0 olm N 05HH H.00H 00m N.00m 0.00 0.NNO 0.0 0IN m 550 5.NOH omm 0.NOH 0.Nm 0.55m 0.5H 0:0 H H00 NHO 0.m0 N.0H HIH 0 N00 N00 0.Nm 0.0H HIH 0 005 H00 0.00 0.NH HIH N 000 HNO 0.00 N.0H HIH N ~00 0N0 N.HN 0.5 HIH H 0000 N.000 50H 0.00m 0.0H N.000H 5.N 0IH 0 0NOH 0.00m 00H 0.0HN 0.5H 0.000 0.0 01H 0 0NOH H.NHm 00H 0.500 0.0 0.0H0 H.N 01H N 0000 0.H00 00H 5.00H N.0 0.0000 0.0 0IH m 000 0.000 00 0.000 H.5 0.N5m H.N 0IH H E\0 E\0 E\0 B\0 E\0 E\0 s\0 aha xoon mm Eon m 003 m 009 m 003 m >000 m 003 m >004 H0009 HO0H «HO0H 000H 000H 000H 000H mmsz> mmmEoHn >uHcsasoo 0cHEu0u00 on 000: 0000 H.U OHQMB mmch> wuHssfisoo U XHszmm< 149 .000HH00 0:0 muc0comeoo 00003 .H00H :H mm0fioHn cczouv0>on0 H0uoe « 30.»:oov H.0 mHnma 0N00 000H 0.00 0.m0H Him 0 00mH 00HH 0.HOH N.00 Him 0 m00H mHNH 0.00 0.00 Him N 000H HO0H 0.00 0.00 Him 0 00N0 00H0 0.00H 0.00H Him H 000H 0.00 N00 0.00H 0.00 H.m00 0.00 0im 0 mbhH H.00 00HH 0.0N 0.00 N.00m 0.00 0im 0 0000 0.00H 0N0 0.0NH N.0m 0.000 0.0H 0im N 0m0H 0.N0 0H0 0.00H 0.0HH H.0N0 0.0m 0im 0 0NOH 0.00 000 H.HOH 0.00 H.000 N.0m 0im H mNNH 000H N.0m 0.00 Hi0 0 00NH hbmH 0.00 0.00 Hi0 0 0HOH 0bmH N.00 0.00 Hi0 N 000H HO0H 0.00 0.0H Hi0 0 0NOH 00H 0.00 0.NH Hi0 H E\0 a\0 E\0 E\0 B\0 B\0 E\0 pus xoon mm son m 003 m 0u9 m 003 m >00H 0 003 0 >004 H0u09 HO0H HO0H 000H 000H 000H 000H 150 Table G.2 Community N content data for September 1989 Poplai Weeds Total Block Treatment g N/m g N/m2 9 N/m2 1 1-0 0.09 3.71 3.80 2 1-0 0.06 23.56 23.62 3 1-0 0.04 4.37 4.41 4 1-0 0.11 4.91 5.02 5 1-0 0.36 4.92 5.28 6 1-0 0.15 14.00 14.15 1 1-1 0.31 0.31 2 1-1 0.46 0.46 3 1-1 0.92 0.92 4 1-1 0.65 0.65 5 1-1 0.68 0.68 6 1-1 0.65 0.65 1 2-0 0.52 4.20 4.72 2 2-0 0.19 3.24 3.43 3 2-0 0.33 3.47 3.80 4 2-0 0.16 2.86 3.02 5 2-0 0.005 8.98 8.98 6 2-0 0.12 20.65 20.76 1 2-1 0.65 0.65 2 2-1 0.56 0.56 3 2-1 1.44 1.44 4 2-1 2.28 2.28 5 2-1 0.89 0.89 6 2-1 1.35 1.35 1 3-0 1.22 8.40 9.62 2 3-0 0.90 4.87 5.77 3 3-0 0.86 2.09 2.95 4 3-0 0.56 9.80 10.36 5 3-0 1.36 4.68 6.04' 6 3-0 1.04 3.58 4.62 1 3-1 5.24 5.24 2 3-1 3.02 3.02 3 3-1 4.84 4.84 4 3-1 3.64 3.64 5 3-1 2.88 2.88 6 3-1 6.12 6.12 151 Table 6.3 Community N content data for 1991 Poplag Weeds Total Block Treatment 9 N/m g N/m2 9 N/m2 1 1-0 0.66 3.60 4.26 2 1-0 0.36 6.13 6.49 4 1-0 0.51 5.12 5.63 5 1-0 1.34 5.24 6.58 6 1-0 2.46 10.79 13.25 1 1-1 5.43 5.43 2 1-1 8.60 8.60 4 1-1 5.90 5.90 5 1-1 3.58 3.58 6 1-1 12.36 12.36 1 2-0 2.24 2.48 4.72 2 2-0 2.66 3.07 5.73 4 2-0 2.67 4.37 7.04 5 2-0 4.63 5.00 9.63 6 2-0 2.74 4.06 6.80 1 2-1 6.68 6.68 2 2-1 6.88 6.88 4 2-1 10.26 10.26 5 2-1 8.32 8.32 6 2-1 8.24 8.24 1 3-0 7.42 4.06 11.48 2 3-0 15.26 1.36 16.62 4 3-0 5.26 2.81 8.07 5 3—0 8.30 0.96 9.26 6 3-0 9.80 1.06 10.86 1 3-1 19.56 19.56 2 3-1 38.84 38.84 4 3-1 7.30 7.30 5 3-1 16.78 16.78 6 3-1 9.90 9.90 152 HmaH 0» 000H 9000 aufimcoc 0cHuc0Hm 3oH 0:» :H 000aoHn 0003 0:0 u0Hmom ucaoum0>on< H.o 0usmHm m .00. omn— 000. 1000 .. .a I? ,8. tr -000 [000 [000— r 1000— r00N. [000— momma 59E; «Smog I -82 080; 2:; 05%.. 0.0 L 568 00H—>3 MIN 0000 HBLEW BHVHOS 03d SWVHO 153 Ham. on mam. sou“ auHmcmo 0cHuc0HQ ESH00E 0:0 :H 000EoHn 0003 0:0 u0HQon ccsou00>on< 0.0 00:0Hm m .00. 600. A... lr/ 00003 #30102, 15000 I maumz, It; @3000 OIO mama; MIN mmmp r000 [00¢ [000 1000 :000— i000— T003 1000— [000. 10000 0000 HELEW Bavnos 83d swvao 154 HmmH on 000H 3000 qumcoo ocHuc0H0 00H: 0:» :H 000EoHn 0003 0:0 00H0o0 canoum0>on< m.o ousmHh —00— 000— 000— L h b {000 100v V .600 .660 .. Hooo. 1000— 100?— room— mouuz. 50:2; mfiaom I 68. Ill mam—u; It; 03000 AVIO 10000 mama; MIN 0000 HBlBW EHVHOS 83d SWVHO 70000