0 ABSTRACT A QUANTITATIVE DESCRIPTION OF OAT GROWTH WITH CEREAL LEAF BEETLE POPULATIONS By John Alfred Jackman The growth of oat plants was studied under various manipu- ‘ lations of nitrogen, water, planting date and cereal leaf beetle density in field experiments. Parameters recorded for oats include: stem density, wet weight, dry weight, plant height, net leaf surface area, head weight, kernel weight and head density. Beetle damage was determined by counting the number of feeding scars. A conceptual model is presented which relates beetle larval instars to leaf classes of stems (defined by the number of leaves/ stem). The two main state parameters used are stem density and net leaf area/stem in each class. Nine leaf classes and an additional head class are used in the model. In the model, as in the field, stems originate by seed germination and tillering. The yield function used relates the time integral of net surface area/ plant (in degree-days > 42°F) to head weight/plant. Exact block diagrams and a FORTRAN simulation are presented for the model which was designed for use in an on-line pest John Alfred Jackman management program. Recommendations are included on the utility and implementation of the model. A QUANTITATIVE DESCRIPTION OF OAT GROWTH WITH CEREAL LEAF BEETLE POPULATIONS By John Alfred Jackman A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Entomology l976 ACKNOWLEDGMENTS The project discussed in this paper was a small part of a larger project designed to develop, screen, and implement control strategies for the cereal leaf beetle. As with any large project, some areas are difficult to define and consequently some overlap in information, needs, and thoughts occurred. Many of these ideas are not original and have been produced by others working on the CLB project. I thank all involved in this project, particularly fellow graduate students. I especially thank Dr. Dean L. Haynes for financial support and constant encouragement throughout this project. The direction of this thesis has been strongly influenced by Dean. His insight has made several significant contributions to the theory and philosophy of this approach. He has always been reliable and inventive in suggesting alternate methods of sampling and problem solving. Drs. S. G. Wellso, R. L. Tummala, and S. N. Stephenson have served admirably in reviewing this thesis and acting as a graduate guidance committee. Dr. Larry Murphy, Department of Agronomy, Kansas State Uni- versity, assisted in designing and initiating my research in l972. He also completed the laboratory tests determining nitrogen content in plant tissue samples. 11 TABLE OF CONTENTS ACKNOWLEDGMENTS . LIST OF TABLES LIST OF FIGURES . LIST OF APPENDICES . INTRODUCTION . LITERATURE REVIEW The Growth of Oats Seeding and Germination . Tillering . Heading and Yield. . The Cereal Leaf Beetle and Host Plants . Plant Modeling. MATERIALS AND METHODS . Gull Lake Fields . Collins Road Fields Plot Descriptions . Leaf Longevity. Stem Samples . Estimates of Stem Growth Using Paint. Wet Weight and Dry Weight . Stem and Head Density . Head Weight and Seed Weight Nitrogen . Soil Moisture Cereal Leaf Beetle Larval Behavior and Orientation on . Host Plants . . . Head Weight and Seed Weight Conversion . RESULTS Analysis of Variance Tests . . Growth Rate of Stems by Leaf Classes iii Page ii Estimates of Stem Growth Using Paint . Relation Between Head Weight and Seed Weight. Yield. . . Nitrogen . . Soil Moisture Cereal Leaf Beetle Larval Behavior and Orientation on . Host Plants DISCUSSION Oat Growth and Cereal Leaf Beetles Description of the Plant Model Desired Outputs . . . Undesired Effects . . . Environmental Inputs--Not Controllable . Overt Inputs--Controllable . Potential State Variables . . Measurements of System Performance Simulation of the System . . Model Interface with the Cereal Leaf Beetle Use of a Model in an On- line Mode Status of the Simulation BIBLIOGRAPHY . APPENDIX iv Table LIST OF TABLES Summary of farming practices at the Department of Entomology Research Fields at Collins Road Time and degree-day changes for painted leaf estimates of oat plant growth at Collins Road in l974 (degree- day estimated from hygrothermograph charts using a planimeter) . . . . . . . . . Mean square values from the analysis of variance tests with significance level (* = .05, ** = .01) and degrees of freedom . . . . . . Painted leaf estimate of growth by leaf class (change in mm2/°D>42/stem) . . . . . . . . Regression constants relating mean time (°D>42°F) and stem growth (change in mm2/°D/stem) by leaf class from the leaf paint data . . . . . Number of larvae on leaves by leaf group at Collins Road in 1974 . . . . . . . . Statistics for this regression of the probit of cumulative first instar feeding equivalents (Y) on time (X) as date, °D>48 and °D>42 (Y?A+Bx) Page 21 32 36 4O 4] SO 67 Figure 10. ll. 12. LIST OF FIGURES Field numbering scheme for Department of Entomology Research Fields on Collins Road, East Lansing . Plot layout for comparing planting dates, nitrogen levels and cereal leaf beetle densities at Gull Lake in l972 (MSU Photo Lab 752702—7) Plot layout of randomized block experiment with three nitrogen levels and four replicates (MSU Photo Lab 752702- 8). . . . . Experimental design with three nitrogen levels and three water levels (MSU Photo Lab 752702— 9) Surface area of stems grouped by the number of leaves on the stems in field 5- 55 at Gull Lake in 1972 (MSU Photo Lab 752702- 26) . A linear relation between head weight and seed weight from individual heads. (Points are from pooled head samples.) (MSU Photo Lab 752702-6) Percent of nitrogen in leaves from nitrogen plots in field 5- 53 at Gull Lake in l972 (MSU Photo Lab 752702- 31) . Dry weight of foliage from nitrogen plots in field 5-53 at Gull Lake in l972 (MSU. Photo Lab 752702- 30) . . Histogram of percent nitrogen in leaves--pooled by position on the stem and in sprayed and unsprayed plots (MSU Photo Lab 752702- 3). . . . . The distribution of larvae on leaves through the season (MSU Photo Lab 752760-8) . . Block diagram of germination used in the model Block diagram of a leaf class by leaves to-date on the stems . . . . . . . . vi Page 20 23 25 26 38 43 45 46 48 51 59 60 Figure Page 13. Block diagram of heading and yield portions of the model . . . 62 14. Block diagram of model with stems as entities grouped by leaves to-date . . . . . . . . . . . . 63 15. Incidence curves for cereal leaf beetle instars and first instar feeding equivalents . . . . . . . 65 l6. A flow diagram of a method for using a model in an on-line mode (MSU Photo Lab 752760-7) . . . . . 69 l7. The density (number/acre) of seeds, heads, and stems in leaf class 4 from the simulation . . . . . . 71 18. The density (number/acre) of stems in leaf classes 1 and 7 from the simulation . . . . . . . . . 72 l9. Net leaf area per stem for selected leaf classes from the simulation . . . . . . . . . . . . . 73 vii Appendix A. Plant Data Summary for Stem Samples from Gull Lake in 1972 (means per stem) (plant length in cm) B. Average Feeding Scars Per Stem in l972 Gull Lake Plots by Date . . . . C. Net Surface Area Per Stem in 1972 Gull Lake Plots by Date . . . . . D. Life Expectancy of Leaves in Degree-Days Above 42°F . E. The Time Spent in Leaf Classes Estimated from Leaf Longevity Data (time in °D>42°F) -. . . . F. Stem and Head Densities from Gull Lake Plots G. 'Wet and Dry weight Measurements from all Plots Studied . H. Net Weight, Plant Weight, Stem and Head Densities from the 1973 and 1974 Plots . . . . . . . 1. Head and Seed Weights from all Plots Studied J. Kernel Weights from all Plots Studied K. Irrometer Readings from Gull Lake in 1972 L. Field Notes on Cereal Leaf Beetle Larval Behavior M. FORTRAN Listing of the Plant Model N. CLB Eggs and Larvae Per Ten Stems in 1972 Gull Lake Plots . . . 0. Seasonal Elytra Lengths of Emerging CLB Adults from the 1972 Gull Lake Plots . . . . P. CLB Pupal Cell Sample Assessment at Gull Lake in 1972 Q. Tetrastichus julis Emergence in 1972 . R. Degree-Day Accumulations for the Areas Studied LIST OF APPENDICES viii Page 86 95 97 99 101 103 108 114 118 131 142 144 147 158 160 162 164 167 INTRODUCTION The cereal leaf beetle (CLB), Oulema melanopus (L.), was introduced into Michigan from Europe. It's identification in the U.S. in 1962 was important because of the beetle's potential as a pest of small grains including wheat, oats, barley, and rye. The CLB rapidly extended its range to the east coast and eastern Canada, while the spread westward and southward has been slower. Several authors have described the biology of this insect (Venturi. 1942, Castro et a1., 1965, Helgesen and Haynes, 1972). The effective control measures developed by entomologists consists primarily of pesticide treatments of infested fields (Ruppel, 1964, Ruppel and Yun, 1965). However, the cereal leaf beetle is a potential pest of vast acreages of cereal grains in the West and midwest; and a pesticide-based control scheme for this pest will have major effects on the environment, particularly with regard to non-target organisms. Alternative control measures are being eXplored and evaluated before this insect has a chance to become a major pest of cereal grains in the U.S. The research described in this thesis is part of an alter- native control scheme, i.e., development of an on-line pest management system. This approach will use biological and weather information to effect the optimal control strategy (Haynes, 1973). Models are probably the most effective method for rapidly l determining optimal control strategies from among various alter- natives. To date, modeling has concentrated primarily on the CLB population (Barr et a1., 1973, Tummala et a1., 1975, Lee et a1., 1976). These models are based on an understanding of the CLB population and were designed to study long-range population changes. More detailed within-generation CLB models are being developed (Tummala et a1., 1976). This project was undertaken to quantitatively describe how small grains grow in a manner that would be relevant to the cereal leaf beetle. At the onset it was not clear what parameters were relevant to plant growth nor to cereal leaf beetles. The parameters ultimately selected for study were chosen because they were believed to be important in describing plants, beetles or the interaction between these two organisms. Plant growth was studied under a wide range of growing conditions, and four main factors were chosen for intensive study: nitrogen fertilization, water, planting date, and cereal leaf beetle density. The first three factors were selected because of the relative importance to plant growth and the facility with which they could be manipulated and monitored during grain pro- duction. Oats (Avena sativa) was the plant selected for concentrated study because it is usually more heavily damaged than wheat in Michigan and, since it is a spring grain, the complexity of host plant vernalization could be ignored. Many supplemental projects and analyses were also performed and will be included in an additional project report (in preparation). That report is valuable in supporting the work in this thesis. It will include winter wheat data similar to the oat data in this thesis. As the field work and the conceptual model of plant growth developed, a more complete mathematical model was initiated. This phase of modeling is still in progress, and this thesis contributes to the modeling effort. LITERATURE REVIEW The Growth of Oats Oats have been a cultivated crop since about 1000 B.C. (Findlay, 1956). Consequently, the varieties now used have long been selected for many agronomic characters including high yield potential and uniformity (Pfahler, 1972). As crops grow, they interact with the soil and environmental factors such as heat, light, moisture, as well as pests. These factors all interact to influence the resultant plant growth which is often only measured in bushels of grain per acre. A somewhat more detailed under- standing of how oats grow is necessary for predicting yield because of the interactions of the factors affecting growth. In oats, as in most annual festucoid grasses, growth con- sists of new leaf emergence and elongation of leaves and stems. Additional stems are also produced by tillering. The final step is the production of an inflorescence or head. The steps or stages of growth in grains have been defined in several ways. The concept of stage is easily incorporated into models for insects or invertebrates. The use of instars as a rough _equiva1ent of age classes is common. The cereal leaf beetle models rely heavily on these concepts (Tummala et a1., 1975, Lee et a1., 1976). Analogous stages are not as clearly defined in most plants. In small grains, the stages have been broken down in two main ways. First, the actual size or stage is arbitrarily determined by the observer. The stages which are frequently con- sidered are seedling, vegetative, shooting, boot, flag leaf, and heading (Coffman et a1., 1961). In addition, the head stage is broken down considerably to define the actual harvest conditions more completely. Bonnett (1937) used a system of growth stages in oats based on visual determination of plant maturity. These stages chronologi- cally were: germination, vegetative, transition, reproductive, and seed stage. More detailed phenological scales for small grains are used, but even with the addition of a considerable number of stages, the stages are somewhat arbitrary at best. The second method is less arbitrary, but has drawbacks in that it is not as easily determined by a single observation. By counting the number of leaves to date on each stem, classes can be clearly defined corresponding to the number of leaves. This is complicated by tillering which often confuses the observer. Problems occur when leaves of the main stem appear to be part of tillers. Late season estimates are not easy, since early season leaves often have senesced. Also, the number of leaves per stem is not exactly determined and is genetically and environmentally influenced as shown in sorghum by Quinby et a1. (1973). Estimation of the number of leaves on a stem can proceed in several ways. Direct counts of this can be made early in the season. Later in the season, the leaves can be counted downward from the flag leaf, at least on the main stems which tend to be more consistent in the leaf number than in tillers for a given variety and location. Green and Goetz (1973) describe a technique to determine the number of leaves/stem late in the season in Agropyron smithii and Bouteloua gracilia. They simply removed the leaf sheaths lower-most first by stripping downward from the base of the blade, and assumed that a single leaf was at each node from the first nodal root upward. Perhaps the best alternative is to record growth throughout the season on individual plants. By recording leaf length on plants several times weekly, estimates of net surface area, the number of leaves/stem, tillering rate, leaf age and longevity, and leaf and stem senescence can be made. Plant phenological events are predictable using degree-days (°D) and other plant parameters. Caprio (1971) predicts lilac bloom by summing °D > 31°F multiplied by a light measurement (langleys) and a constant term. For small grains, °D > 42°F have been used as the growth base (Gage, 1972). The base temperature for computing degree-days for crop growth is usually taken as a constant, but can vary by crop stage as in peas, for example (Balvoll and Bremer, 1965). Another problem occurs when using degree-days since the weather records taken are not the temperature that plants are subjected to in the field. The actual temperature of leaves vary considerably from standard weather measurements (Biebl, 1962). Depending on the crop and weather conditions, the leaf temperature can be either higher or lower than the air temperature. This is critical in modeling crop or insect growth since weather records are often used directly. The relationship between the standard weather temperatures and actual crop temperatures should be corrected. Water is essential to plant growth and photosynthesis. McLaughlin (1917 cited in Coffman et a1., 1961) worked on irri- gation of oats in Europe and produced high yields of 124-161 bu/ acre. The moisture level was maintained to keep the plants growing or to produce an increased second growth. The timing of irrigation substantially influences yield (Harris and Pittman, 1919). Irrigation at the fifth leaf stage gave best yield while delayed irrigation gave progressively lower results. Light is important directly to photosysnthesis, but is usually not limiting in oat production. Wiggans and Frey (1955 cited in Coffman et a1., 1961) found little reduction in oat plant growth with 50% shading. Growth at 75-90% shading produced tall spindly plants. Thus, light can effect oats by changing the growth form of the plant. Wiggans and Frey (1955 cited in Coffman et a1., 1961) stated that head initiation is determined by the length of the dark period. Oats did not head when grown under a 9-12 hour daily photophase, but headed readily when grown under a 15-24 hour daily photophase. No interaction between photoperiod, variety and temperature was observed. The photoperiod effect occurs between the tillering and shooting stages. Thus, the primordial panicle or head is laid down in stems before the shooting stage begins. Seedinggand Germination The main factors affecting germination are temperature and moisture. Therefore, field observations of germination are affected by planting depth, soil moisture, and soil temperature. Oats are best planted about .75 to 1.5 inches deep (Shands and Arny, 1952). Shallow planting produces superior root systems (Hamilton, 1951) and planting over three inches deep can cause poor stands. The number of seeds planted per acre varies considerably. Hildebrand (1965) estimated about 13000 seeds/lb and 32 lbs/bu. At a planting rate of 64 lbs/acre or two bushels, 832,000 seeds/ acre are used. Heavy seed is necessary for good yield production (Findlay, 1956). In fact, in some experiments the sifting out of smaller grains and planting only the remaining heavy kernels in— creased yield. Coffman et a1. (1961) state that seed oats weigh 512 ozs/bu, i.e., 32 lbs, and that seeding rates are about 2.5-3 bu/acre. Grain weighing less than 21 lbs/bu gave reduced yield. Early planting of oats has been generally recommended for a long time (Findlay, 1956, Hildebrand, 1965) but this is not optimal for all weather conditions. In New York it is estimated that a loss of one bu/acre occurs for each day after April 18 that seeding is delayed (Anonymous, 1956). Tillering Tillering is the process of production of additional shoots from an established plant crown. Different varieties of oats vary in their tillering ability. Tillers are important since they allow plants to adapt to a considerable range of densities and environ- mental conditions to produce good yields by increasing head density and leaf density, which relate to total production. Leaf area index (LAI) in pastures has been used as a predictor of dry matter production/day (Loomis and Williams, 1963). Fuess and Tesar (1968) stress the significance of leaf area index in accumulation of plant biomass in alfalfa. To use LAI to predict production, one often assumes that all leaves photosynthesize at the same rate. This is not true since older leaves photosynthesize slower than young leaves (Fuess and Tesar, 1968). Also, some grasses tend to have a critical LAI above which little additional production OCCUT‘S . Headingiand Yield According to the Corn Sales Act of 1921 which applies to all grain, oats are sold by weight (Findlay, 1956). Therefore, yield is expressed as seed weight per land area regardless of the fact that millers usually consider the weight/bu when buying grain. Yield is a function of weight/seed, seeds/head, heads/stem, stems, plant, and plants/land area. These factors are interrelated. The relationship of yield components and stand components in oats has been studied by many authors. Grafius (1956) showed that weight per kernel was independent of the other yield components. Moreover, changes in yield, i.e., weight of grain/plot, were more closely associated with panicles/area than kernels/panicle. erafius then presented two theorems which relate panicles/plant (V) and lO plants/area (U). The relation between these parameters was found to be V = cek'u or dV = KVdu where c and k are constants associated with variety. The second theorem states that U reaches a maximum which is 112 plants/three row ft or at u = 27301:?) ' Jensen (1952) studied similar components of yield which he called seed weight, plant height, culm number (stems/plant), seeds/plant and seeds/ panicle. Grafius (1972) applied the classical ecological competition equations to oats by treating the components of yield as competing populations. Each of three components of yield (heads/area, seeds/ head, and kernel weight), was most competitive with itself. Thus each component contributes some additional yield independent of the other components. The Cereal Leaf Beetle and Host Plants Previous work by Gage (1972) provides an ample review of the literature relating the cereal leaf beetle to its host plants. Several important relationships are included in his work. The re- 2 lation between leaf surface area (A) of oats in mm and leaf length (L) in mm was found to be: A = 52.15 + .034 L2 (1) Also, relations between the plant height, dry weight, and surface area are given. Gage also presents a review of plant growth equations, plant biology and environmental effects on plants, which will not be reiterated here. 11 The number of insects per plant unit is a common statistic in population ecology. For example, Hill et a1. (1943) used puparia/ culm as a population statistic for estimating yield reduction in wheat by the Hessian fly. Merritt and Apple (1969) use CLB larvae/stem on June 7 as a criterion to estimate yield reduction in oats. But the technique is useless if the maximum population density varies in time between years or between fields. Also, the larval densities in their designs were controlled by periodic use of insecticides which probably does not result in continuous damage as an untreated population would. There was no attempt in their work to document the stem density, i.e. stems/acre. Koval (1966) found that two and four larvae/stem reduced yield in oats by 34 and 72% respectively. Wilson et a1. (1964) found that 1.7 larvae/stem reduced yield by 26.4% in oats. Merritt and Apple (1969) show the maximum yield reduction, 48.8%, to occur at 10.4 larvae/stem in oats. They also found an increase in screening loss and a reduction in plant height, kernel weight, kernel number, and straw weight. Kernel number was reduced 40.9%, while kernel weight was reduced only 14.2%. Webster et a1. (1972) working in spring wheat found an average of 25% yield loss due to CLB feeding. Bushels/acre, lOOO kernel weight, kernels/head, and straw length were all reduced because of the CLB, and straw length was the most sensitive to beetle density. Densities were estimated by counting larvae/ten plants on June 11. 12 Losses ranged from 9.5% to 74.6% depending on year and cultivar with a larval density range of 2.8 to 20.3/ten plants. Gallun et a1. (1967) found a reduction in kernel weight and kernel number (kernels/head) on wheat damaged by the cereal leaf beetle. The resulting yield loss was as high as 23%. They found no difference in protein content, pearling index, mill yield and alkaline water retention capacity. Yellow traps were preferred by CLB adults over green traps (Wilson and Shade, 1967). This seems curious since yellow leaves presumedly would be deficient in nitrogen, i.e., protein, but this might also affect oviposition site preference. Eggs are generally laid on the upper leaf (Wellso and Cress, 1973), while adult CLB feeding takes place on the leaf below. The feeding of individual CLB larvae has been quantitatively studied by Wilson and Shade (1964a), Gage (1972), and Wellso (1973). The quantity of foliage needed for larval development by instars was determined for several hosts and is presented as first instar feeding equivalents. One first instar feeding equivalent is the quantity of food necessary for a first instar CLB larva to develop to the second instar (Gage, 1972). Shade and Wilson (1967) suggest that leaf vein spacing is critical to CLB larval survival. Measurements of distance between leaf veins in unfavorable hosts is less than the width of first instar mouth parts. Also, the larvae orient perpendicularly to the leaf length during feeding on unfavorable host plants. 13 The percent survival and developmental time by instar were used as criteria by Wilson and Shade (1966) to rank superiority of host plants. They rated all the small grains as good or superior along with reed canarygrass. Roebuck and Brown (1923) defoliated wheat by stripping leaves (either half or totally) after heading occurred and found that yield was generally inversely related to damage. Their results could be explained by relating the yield directly to the time integral of leaf area. The only apparent exception to this relation can be explained by differential leaf size (since the flag leaf is often smaller than lower leaves) in two equivalent percent damage tests. Plant Modeling Modeling in biology is dependent on several factors and the first is the objective of the modeling effort. Models are designed fbr a purpose and understandably to fulfill these needs a variety of models are necessary. For instance, a model designed to explain a detailed chemical process would be very different from one designed to economically manage the growth of a crop. There is a hierarchy of biological understanding from biochemical, to cellular, to leaves, to stems, to plants, to field, to regions, etc. This hierarchy is incomplete, but does show the progression from lower levels of organization to higher levels. Miles et a1. (1973) define three levels of modeling: (1) physiological models; (2) "individual element models which combine into a single model describing the actions and interactions occurring 14 within the bounds of the specifically defined ecosystems;" (3) farmstead management simulator. Giese et a1. (1975) present a good outline of the problem and concepts of on-line pest management. The use of weather data and plant models are an essential step in this process. An early attempt at plant modeling with the cereal leaf beetle (Barr et a1., 1973 and Lee et a1., 1976) is based on data from Gage (1972) of a single season of research and available literature. This model consists of four linear differential equa- tions which predict growth rates from plant states which are: dry weight of foliage, surface area of the top three leaves, head weight, and surface area of the head. This model has several drawbacks. It is linear and addi- , tional factors are included by multiple regression only. Random elements are not easily incorporated. It lends no biological insight into timing or mechanisms. There is no way to include plant density other than change in surface area. The leaf surface area measure in the model is the top three leaves, which may be logical from a beetle standpoint, but does not improve our understanding of plant growth. A plant population model would seem to have benefits, since the relation between stem density and damage could be handled. Inter- action effects between stems could be accounted for in such a model. Also, the model would be easy to understand and interface with insect models since an average or typical stem would be well defined in the model. Physical description of the plant would make the model 15 biologically meaningful and allow for interfacing with an herbivore which has preferential feeding habits. Models of the relation between crop yields and weather have been reviewed amply by Baier (1973). Available models are primarily on a macroscopic scale relating yield to temperature, rainfall, or evapotranspiration at various plant growth stages. Several plant models for other crops are being developed throughout the country, for example, on cotton, soybeans, corn, and alfalfa are well developed. These models use leaf surface area per land area as a standard state parameter. Growth equations used are generally multiple regression equations predicting rates from the present surface area. They incorporate the basic photosynthetic concepts in that growth is dependent on light, water, temperature, fertilization, and leaf area. The concept of a carbohydrate storage system in the plant is used. Models like this are justified for individual plants (soybeans) or crop canopies when plant entities are indeterminant (alfalfa). For corn and small grains, population models which treat plants or stems as individuals could be developed. Miles et a1. (1973) have simulated alfalfa growth with a model (SIMED) consisting of ten basic plant processes with associated rates. "Each of the ten rates of the plant system has been expressed as a maximum rate times a series of dimensionless multipliers." This idea is borrowed from models by Forrester (1961), Waggoner et a1. (1972), and Loewer et a1. (1973). The alfalfa model needs environ- mental inputs of air temperature, soil temperature, atmospheric moisture, and solar radiation. 16 Southern corn leaf blight models (EPIDEM and EPIMAY) are well developed (Waggoner and Horsfall, 1969, Waggoner et a1., 1972). These models use on-line weather data to predict the extent and degree of infestation of this disease. Colwell and Suits (1975) present a model for the growth and yield of wheat. The model uses the plant responses to environ- mental phenomena to predict the rates of photosynthesis and respi- ration. One state variable in the model is the leaf area index projected into the vertical and horizontal planes.’ Yield was then predicted from the summation of the horizontal projected leaf area index through time. Photosynthesis is modeled in moles of fixed COZ/m2 as a function of the incident light. This growth model was coupled to a model which predicted reflectance from the crop canopy and thus observable to a remote sensing system. The general form of the growth equations in all of these models is photosynthesis less respiration. Photosynthesis at any time is limited by available light, moisture and C02. A common equation used is the standard logistic equation with the maximum set at a limit. The simulation of plant-pest interaction has not progressed much. Miles et a1. (1974) have outlined this problem separating the interactions into physical and behavioral. The physical inter- actions include: (1) feeding or loss of plant mass; (2) competition with weeds for light, water, and nutrients; (3) disease transmission and toxin injection; (4) degradation of crop quality; and (5) pol- lination. Behavioral modifications stated include: (1) migration; and (2) oviposition site selection. 17 Some of the problems of simulation have been pointed out by Miles et a1. (1974). For example, feeding must be subtracted after plant growth occurred in each time step. However, some problems of interfacing are not even considered. There was no reference to diurnal changes in behavioral patterns or differences between plants and pests relative to degree—day bases. MATERIALS AND METHODS Gull Lake Fields The Gull Lake research area includes sections 4, 5, 8, and 9 of Ross Township, Kalamazoo County, Michigan. The traditional field numbering system (Casagrande, 1975) has been a two-number code: the section number followed by a field number, e.g. 5-55. The fields were numbered roughly clockwise from the northwest corner field of each section. The recent crop sequence in the three main research locations within the region are summarized by Gage (1974). In 1972-74, oats at the Gull Lake Farm were planted at the rate of two bushels of seed/acre. The herbicide, MCP, was used at 3/8 lb/acre in 1972 and 1973 in oats. In 1974, weed control in oats consisted of .4 pt/acre of 2,40 ester in all plots except mixed alfalfa and oats. In 1972, the insecticide, ThiodanR, was ap- plied to cause low CLB density plots in fields numbered 9-12, 9-13, 5-53, and 5-54 at a rate of two lbs/acre on May 8 and June 2. No other insecticide treatments were applied in grain in the years of study. In 1972, all oats were fertilized with 200 lbs/acre of 6-24-24. All oats were top dressed with 100 lbs/acre of 45% urea, except the nitrogen plots in fields 5-53, 5-54, 9-12, and 9-13, which were treated at rates of O, 50, and 100 lbs of actual urea/ acre. The nitrogen was applied to the plots on April 28 (Section 5) and May 1 (Section 9). l8 19 In 1973, oats were top dressed with 100 lbs/acre of 45% urea, except the O, 50, and 100 lbs/acre plots in 9-17 and 8-11 (on May 15). In 1974, oats were top dressed by a commercial operation with 28% Liquid Gold fertilizer at 100 lbs/acre on June 3. In 1972, early oats (Garry) were planted on April 12. Normal age oats (Garry) were planted on April 28 and late oats (all Rodney except 5-55 which was Garry) were planted on May 13. In 1973, normal age oats were planted on April 26 and late oats on May 15. Oats were harvested on August 16, 1972 and August 14, 1973. Collins Road Fields The Michigan State University Department of Entomology Experimental plots on campus at East Lansing were also used for this study. These fields are located adjacent to Collins Road on south campus and comprise about 34 acres. A map of the area with field labels is included (Figure l). A breakdown of the acreage by field and a complete summary of cropping practices since 1970 is reported in Table 1. Plot Descriptions The small fields at Gull Lake and Collins Road were used as a major source of data. In addition, smaller plots were used in selected fields to study effects of controlling planting date, CLB density, nitrogen, and water. It was too cumbersome to test levels of all these parameters in a single design. However, by using several plot designs, differences between levels and interactions between variables were tested. .Aommcu mmsma ma enmp .m. cmnouuov mcwmcmg “mam .coom mcwp_ou co mupmwu cocmmmmm amoposoucm we ucmsucmamo com wemcum acmcmnszc npmwd .P mgamwd 20 e , : 2 o \ n RT? m — m.. m N l _ E dfll 3 2 C m a 2 L 23%: : _.1|l_ 21 lotoaology Research Yarn Colllna Road mm Acres mo 1911 1912 1913 197:. 19151- 1 2.4 Alfalfa Alfalfa Alfalfa Alfalfa Wheat Alfalfa 10-6-73 9-17-74 lonla 255211 2 2.4 fallov Wheat Oats Wheat Oats ‘beat 9-70 5-12-72 9-16-72 4-27-74 9-19-74 3 2.4 Wheat Oats fallow Wheat Wheat Wheat 4-20-71 10-14-72 10-12-73 10-12-74 4 2.4 Oats fallow Wheat Oats Wheat Oats 9-15-71 5-6-73 9-22-73 5 4.2 fallow fallcv Nursery Nursery Nursery Nursery 0 2.0 Alfalfa Alfalfa Wheat Wheat Oats Wheat Stubbla Stubble 9-16-71 9-28-72 4-26-74 10-12-74 7 1.0 Alfalfa Alfalfa Wheat Wheat Oats Wheat Stubble Stubblc 9-16-71 9-28-72 4-26-74 9-19—74 0 1.5 fallow fallow Oats Wheat Wheat Oats 5-12-72 9-28-72 9-23-73 9 1.0 Vegetables Cucuzbera Cucu:bers Vegetables Vegetables Vegetables 20 0.25 Cucuzbers Cucuabers Cucumbers Cucumbers Cucumbers Cucuabers 11 1.0 Cucumbers Cucuabera Cucumbers ?egetables Vegetables Vegetables 12 1.4 Fallow Fallow Wheat Alfalfa Alfalfa Alfalfa 9-15-71 8-21-72 8-21-72 0-21-72 Saranac Saransg Saraaag 13 1.3 Fallow Fallow Wheat Wheat Oats Wheat 9-15-71 9-16-72 4-26-74 9-19-74 14 2.5 Fallow fallow Wheat Wheat Wheat Wheat 9-15-71 10-14-72 10—12°73 10-12-74 15 2.5 fallow Fallow Wheat Oats Wheat Oats 9-15-71 5-4-73 9-22-73 16 1.7 fallow Fallow Wheat Alfalfa Alfalfa Alfalfa 9-15-71 8-21-72 8-21-72 8-21-72 Saranac §aranac Saraqgg 17 4.0 fallow Fallow Fallow Wheat Wheat Wheat 10-11-72 10-6-73 9-23—74 .lonla 12212 1970 1971 1972 1973 1974 1975 2:212 ' "'_' ' "' ' "" Alfalfa 5.40 5.40 2.40 5.50 3.10 5.50 Wheat 2.40 2.40 14.80 17.10 17.70 15.60 Oats 2.40 2.40 3.90 4.90 6.70 6.40 Nursery 0 0 4.20 4.20 4.20 4.20 fallow 2l.50 21.50 6.40 0 0 0 20201 33.95 33.95 33.95 33.95 33.95 33.95 All wheat planted was Certified Genesee except where stated. .lhe 1975 Wheat seed was a year frcn Ccrtlflcd Cenesee. A11 oats towed was Certified lentland 64. Table 1. Summary of farming practices at the Department of Entomology Research Fields at Collins Road (Jim Crago 10/15/74). 22 In 1972, three nitrogen levels and three beetle densities were manipulated in field number 9-13. This design included three planting dates of cats (Figure 2). The nitrogen levels were 0, 50, and 100 lbs/acre applied as urea. Beetle density was reduced in low (L) density plots by two insecticide (Thiodam:)) treatments. The medium (M) density was uncontrolled and resulted directly from the beetle movement and field selection. The high density (H) in plots was attained by sweeping up beetles in adjacent fields and confining them in cages for a few days. Adult oviposition in the caged condition caused an increase in feeding damage and egg density. The larvae swept up with the adults also contributed to the density. Beetles were collected on May 26 and June 6 and placed in all high density oat plots of the first two planting dates, and on June 13, in the high density plots of all three oat ages. Three water levels were maintained in field 8-10 (oats) at Gull Lake in 1972 in adjacent plots 20 feet on each side. These plots were placed at the top of a hill to ensure that water levels could be manipulated effectively without excess horizontal water flow. The high water level plot was irrigated by using a garden sprinkler until the soil was saturated on May 25 and June 27. The drought condition was maintained by covering the entire plot and , plants with plastic (4 mil clear) during each rain from May 16 to July 3. The remaining plot received prevailing rain and was the control for water level. Beetle density was not manipulated in the experiment. 23 PLANTINGS HDMgER EARLY (E) MIDDLE (M) LATE (L) (E15 255:) DEMQVTR 1 O MEDIUM 2 0 HIGH 3 0 Low 4 50 MEDIUM 5 50 HIGH 6 50 Low 7 100 MEDIUM 3 100 HIGH 9 100 Low 20' 10’ 10’ Figure 2. Plot layout for comparing planting dates, nitrogen levels, and cereal leaf beetle densities in oats at Gull Lake in 1972. 24 A randomized block designed was set up in field 5-53 at Gull Lake in 1972 with three nitrogen levels and four blocks (Figure 3). Nitrogen was applied on April 28, 1972 as urea at O, 50, and 100 lbs of nitrogen/acre. These plots were used to study nitrogen effects in undamaged plants because the beetles were controlled by Thiodan® treatment. Also in field 5-53, an unsprayed portion was compared to a sprayed portion independent of nitrogen level. In 1973, three nitrogen levels were studied in two ages of oats in field 9—17. In field 8-11 at Gull Lake, three water levels were maintained in plots with three nitrogen levels (Figure 4) to study the interaction between these two variables. At Collins Road in 1973, two planting dates of oats were studied. Two beetle densities were compared in field 4, since sprayed and unsprayed portions were studied. Leaf Longevity Oat plants selected early in the season (shortly after emergence) were tagged and marked with stakes. On each observation day the length of each leaf was recorded to the nearest .5 cm. Observations were made about twice weekly in l972, weekly in 1973, and daily in 1974. By recording the leaf length and position, each leaf was related to the previoUs length recorded. As tillers initiated data for them was recorded with the main stem data to facilitate future analyses about the entire plant. It was necessary to record the data often to associate the new growth with the older leaves. 25 NITROGEN PLOTS AT GULL LAK E-BAILEY FARM 1972 NITROGEN (L88) 0 50 100 100 50 50 100 100 50 50 100 PLOT # BLOCK 4 3 2 PLOT # 1 BLOCK 4 3 BLOCK 3 ‘ 3 2 2 1 1 BLOCK 3 3 BLOCK 2 3 2 2 l 1 BLOCK 2 3 BLOCK 1 3 2 2 1 1 BLOCK 1 3 2 WHEAT 1 5-54 OATS 5-53 Figure 3. Plot layout of randomized block experiment with three nitrogen levels and four blocks. OAT PLOTS AT GULL LAKE 1973 FIELD 8 - 11 NITROGEN LEVELS (LBSJ 0 so 100 on 501 1001 ON SON 10111 (e— 25’ H8 Levels I rrigated Normal Drought Figure 4. Experimental design with three nitrogen levels and three water levels. 27 When measuring the leaves other factors were recorded includ- ing the number of eggs, larvae, feeding scars per leaf and a visual estimate of the condition of the leaf. Senescent leaves which had dried were not measured. Ten plants per field were measured in fields 5-53 and 5-55 in 1972 and in fields 5-58, 5-59, 5-61, and 5-62 in 1973. Five plants per plot were measured in 1973, in fields 9-17 and 8-11 at Gull Lake. Thirty plants were measured in field 2 in 1974 at Collins Road and beetle density was manipulated on 20 plants by adding larvae at two density levels. The leaf longevity technique provided a good data base to estimate a variety of plant parameters and growth statistics. The time of emergence in °D > 42°F for each leaf was esti- mated by averaging the time that the leaf was first observed and the preceeding sample time. The time spent in each leaf class was then estimated by subtracting the emergence time for each leaf from the emergence time of the succeeding leaf. Life expectancy of individual leaves was calculated by subtracting the emergence time from the final time that a leaf was green. Again, as in the last case, an average time between sample dates before and after an event was used to calculate an estimate of when the event actually occurred. Three surface area statistics were computed (in mmZ/plant): total or cumulative surface area, net or current surface area, and senesced or dead surface area. All of these are functions of time and were estimated for each leaf class on a per stem basis. On a 28 particular date the current area was estimated by computing area per leaf by using each recorded leaf length and Equation 1 (p. 9). The area per leaf was then summed to compute area per stem. Total area per stem was calculated by using the maximum size of all leaves to date and summing the area per leaf as above. Dead leaf surface area was calculated directly by using the maximum leaf length acquired by all leaves which had dried. Dead leaf area per stem could also be found simply by subtraction of the net leaf area per stem from the total area per stem. All surface area measures were placed in leaf classes simply by including the stems in the classes corresponding to the number of leaves to date on the stem. The leaves that subtended the tillers were included with the initial stem. Instantaneous rates were estimated using a difference equation. Thus, for net surface area: dNSA A NSA NSA(t2) - NSA(t1) ( ) _......_: = 2 dt A t t2 - t] where t] and t2 were times in °D > 42°F such that t2 > t]. The time integral of the net surface area/stem calculated numerically using the trapezoidal approximation (Manetsch and Park, 1973). Thus, the area under the net surface area curve was calcu- lated by the following formula. 29 t t NSA + NSA f NSAdt Z Z ( ) (3) . _ 2 t . - t. to 1 - to [1+1] 1 NSA = Net surface area/stem at time t. t. = °D > 42 at sample date i. t = °D > 42 at planting. t = °D > 42 at harvest. (For all t. sample times where j = 1, 2, . . . , n = Number of sample J dates.) Stem densities were computed by adding the number of stems in each leaf class and using the number of stems per two linear row foot as measured throughout the season. The presence of a stem was determined by the presence of any green leaf. Tillering rate per plant was estimated by the change in the observed number of tillers per plant divided by the time change. Mortality of stems per plant was computed by counting the number of stems that had died, i.e., all leaves had dried, and dividing by the total plants sampled. Percent mortality of stems was computed for a time period by dividing stems dying by the total emerged stems, times 100. Stem Samples Individual stems were randomly selected once per week through- out the growing season and the length and position of all leaves were recorded. Maximum width was measured for all leaves which ‘were green. The number of feeding scars per leaf was recorded, as 30 well as the number of CLB eggs and larvae when present on the stems. Total plant length was recorded by extending the leaves and measur- ing the maximum length. Dry weight of the stems was also recorded, by cutting the stems at the soil surface and holding the stems in a 110°C drying oven for 48 hours. Stems were collected from the plots in fields 8-10 and 9-13 at Gull Lake in l972. Fields 4 and 15 at Collins Road were sampled by this method in 1973, as was field 2 in 1974. This procedure produced data for estimating damage by the number of feeding scars. Estimates of net surface area were computed from length of green leaves as described for the leaf longevity data. Estimates of Stem Growth Using_Paint This study estimated the growth rate of stems as defined by the change in net surface area of foliage per unit time. Time was measured in D° > 42°F. Leaf growth in oats occurs primarily from the meristematic region at the leaf base. Individual leaves were marked at the initiation of the observation period by a small dab of paint at each leaf axil. After a growth period of about a day, the initial and final leaf lengths were measured as the distance from the paint to the leaf tip and the axil to the leaf tip, respectively. Leaf area was predicted from the leaf lengths using Equation 1 (p. 9). The growth or change in area was found by subtracting the initial area from the final area. .The number of leaves per stem to date, leaf class, was also recorded. The observations were repeated 31 several times through the 1974 season in oats, field 2, at Collins Road (Table 2). Wet Weight and Dry Weight Wet weight of foliage was collected by clipping the above ground foliage from two linear row feet. Foliage was placed in a closed plastic bag and returned to the laboratory for weighing on the following day. The larvae and eggs were counted and removed from the foliage. All foliage was then placed in paper bags and dryed at 110°C in an oven for 48 hours. The foliage was removed and weighed after the foliage cooled to ambient temperature. Stem and Head Density Either stems or heads were counted in two linear foot samples which were selected randomly in the field or plot. Stems included all main stems and additional tillers which were not dry and deteriorated. Heads were any visible exserted inflorescence. Head Weight and Seed Weight Heads was collected by clipping the stem directly below the inflorescence. The heads were weighed air dry (or oven dry for comparison). Individual heads, and 100 pooled head samples, were weighed. Head samples were thrashed mechanically to separate seeds and the seed weight was recorded. Kernel weights were determined by counting all kernels, or 1000 kernels per sample, weighing them, and computing the 1000 kernel weight estimates. 32 Table 2. Time and degree-day changes for painted leaf estimates of oat plant growth at Collins Road in 1974 (degree-days estimated from hygrothermograph charts using a planimeter). Degree- Number Initial Time Final Time 5132;5d (EggéF) ngfis 4:00 p.m. 24 May 2:00 p.m. 29 May 4.92 54.08 17 10:30 a.m. 7 June 2:00 p.m. 11 June 4.15 131.18 5 2:10 p.m. 11 June 1:45 p.m. 12 June .98 16.73 17 2:15 p.m. 12 June 4:15 p.m 13 June 1.08 21.45 25 3:45 p.m. 13 June 4:00 p.m. 18 June 5.01 72.58 19 4:45 p.m 18 June 3:30 p.m 20 June 1.95 56.13 17 4:15 p.m. 20 June 4:00 p.m. 21 June .99 28.76 12 5:00 p.m. 24 June 1:30 p.m. 25 June .85 16.89 1 3:00 p.m. 25 June 4:30 p.m. 26 June 1.06 24.73 3 33 Nitrogen Percent nitrogen in the foliage was estimated through the season using the total Kjeldahl method (Taras et a1., 1971) on the foliage collected for dry weight samples taken from the plots in 5-53 at Gull Lake in 1972. Combined leaf samples were also analyzed for the irrigated, control, and drought plots in field 8-10 once in 1972. One set of samples was processed by leaf class to find where in the plants the nitrogen was located. Leaf classes were determined from the flag leaf downward; thus, flag leaves were A pooled together, second leaves were pooled, etc. These samples were collected at Gull Lake on July 5, 1972. This procedure was ‘used for insecticide treated and untreated oats on that date. Soil Moisture Irrometers were set up in several plots at Gull Lake in 1972 at various depths to estimate the soil water potential under different conditions. In the irrigated, normal, and drought plots, 18-inch irrometers were used (field 8-10). In field 9-13, l8-inch irrometers were placed in plots OM and 0L to test the gradient across the plots. Also, in OM 24-inch and 36-inch irrometers were used to study the soil moisture profile at this location. Irrometers were read throughout the season about once per week. The diurnal change in irrometer readings was determined on July 7, 1972 by taking readings at 815, 1000, 1430, and 1615 hours. At 1200 hours irrigation was initiated in field 8-13, and this caused a noticeable change in irrometer readings. 34 Cereal Leaf Beetle Larval Behavior and Orientation on Host Plants Larval feeding patterns and rates, orientation, and movements, were studied since this may affect plant growth and yield. Two techniques were used to study CLB larvae: watching larvae for extended time periods, and direct measurements of larval location on oat plants. Three 4th instar larvae were watched with head capsule widths of 1.10 mm on June 14, 1.08 mm on June 20, and 1.08 mm on August 8. In the direct measurement study, larvae were recorded as small (S) and large (L). Larval position (distance from axil) and leaf sizes and number were recorded. Data were recorded from 13 larvae on June 14, 22 on June 18, 20 on June 27, and 6 on July 2. Head Weight and Seed Weight Conversion One hundred oat heads were selected throughout the Gull Lake Farm in 1972. These heads were intentionally selected from as wide a range of environmental conditions and size classes as possible in order to show as much variation as was possible. Each head and the corresponding seed was weighed. RESULTS Analysis of Variance Tests Analyses of variance were used to screen the data from all plots. With these analyses I attempted to find which factors, i.e. water, nitrogen, crop age, and CLB density, affected which plant measurements. The effect due to time was removed in the analyses by treating each sample date as a block. Sample dates, in general, A were highly significant which, of course, means that the plant measurements are functions of time. The data analyzed is in Appendices A-J. The means were used for the analyses and only complete blocks were included. Deviations from this approach are indicated in the data tables and ANOVA results in Table 3. Growth Rate of Stems by Leaf Classes Surface area statistics were calculated from the leaf longevity data from field 5-55 in 1972. The two data sets graphed (Figure 5) for each leaf class were the total area to date (TSA) and the dead area to date (TSS) per stem. The area between the two is the net surface area (NSA) which represents the photo- synthetic tissue. The lines in Figure 5 are freehand fit by using stepwise linear approximations. The equations used in the model to fit the lines are ramp and unit functions as explained in Manetsch 35 36 Table 3. Mean square values from the analysis of variance tests with significance level ( s - .05. " - .01 ) and degrees of freedom. SOURCE OF VARIATION Yr. Field Oates’ Blocks Nitrogen Water Age Clb NxW NxA ch AxC NxAxC BxN DxN Error Stems/2 linger row feet 72 8-10 32.62 108.70 4.24 ea 5 es 2 10 72 5-53 402.93 33.36 8.83 3.36 12.02 " 7 * 3 2 6 77 72 9-12 0E 393.13 19.41 1.51 41.31 14.41 " 5 2 2 * 4 40 72 9-12 0N 542.07 36.16 80.23 84.10 34.31 ee 5 2 2 A 40 72 9-12 0L 502.59 285.56 .86 14.84 37.27 " 4 " 2 2 4 32 72 DE 8 ON 69.13 52.68 2635.3 36.47 2.89 60.84 45.27 64.57 73.87 5 2 " l 2 2 4 2 4 85 72 DE 4 0L 241.13 153.32 6.52 8.46 136.09 10.75 5.16 27.22 36.38 " 4 ' 2 l ' 2 4 2 4 68 73 8-11 715.19 186.54 179.04 22.43 34.39 as 4 ea 2 e 2 A 32 73 9-17 439.71 148.33 134.43 29.20 94.79 ' 3 2 1 2 15 Dry weight/2 lingr row fag 72 5-53 1743.5 21.17 331.32 43.81 21.83 " 4 3 " 2 8 42 Wet weight of foliage/2 linear row feet 72 5-53 33697. 217.13 10824. 672.05 741.30 " 8 3 ft 2 6 88 73 8-11 74726. 9832.5 599.11 116.32 1018.0 ee ee 2 4 24 73 9-17 79478. 7346.1 7360.9 14.39 1177.1 " 2 ' 2 * l 2 10 Yr. Field Oates Blocks Nitrogen Water Age Clb NxW NxA Nxc Axc NxAxC BxN DxN Error 051 weight7stea 72 9-12 OE 7.24 03 .28 .04 .. 7 2 z s '05: 72 9-12 ON 2.82 01 .01 .03 .06 " 5 2 2 4 40 72 9-12 0L 4 31 Ol .02 .07 .03 ee 5 2 2 4 40 72 DE 8 ON .27 .01 1.25 .12 .01 .07 .33 .05 .15 3 2 *' l 2 2 4 2 4 51 72 OE 8 OL 7‘4; .15 3.70 .03 .17 .06 .10 .07 .11 2 " 1 2 2 4 2 4 72 8-10 2.85 1.08 .35 " 7 2 1‘ Life expectancy of leaves 73 8-11 648095. 284965. 7913.4 52551. 13043. ee 7 es 2 2 *9 56 73 9-17 32094. 166185. 13757. 181455. 9175.3 ea 7 es 2 1 " 2 35 Time spent in leaf classes 73 8-11 772085. 279475. 14167. 57382. ee 2 es 2 2 4 280218 73 9-17 447835. 18247. 540.02 35653. 25305. *‘ 7 2 l 2 35 Plant height 72 5-53 1380.4 1.03 3.65 2 31 " 5 3 2 ° 5 22: Table 3 (cont'd.). 37 SOURCE OF VARIATION Yr. Field Dates Blocks Nitrogen Water Age Clb NxW NxA NxC AxC NxAxC BxN DxN Error !££_!!£I££!Ljfllflyflfl!!! 72 9-12 0E 3374.8 56.41 20.04 72.52 35.47 to 7 2 2 4 56 72 9-12 ON 4967.9 12.23 33.89 256.55 78.59 ee 5 2 2 9 4 72 9-12 0L 6621.3 461.94 186.71 104.55 143.14 0' 5 0 2 2 4 48 72 Of 8 0L 2216.0 29.80 16222. 10.95 66.91 68.76 70.41 691.09 e 3 2 fl 1 2 2 2 4 51 72 8-10 922.88 50.15 77.25 ee 7 2 14 Dry weight7head 72 9-12 Of .3427 .0362 .1723 .0253 .0316 '* 2 2 * 2 4 16 72 9-12 ON .6495 .0221 .0001 .0098 .0265 " 3 2 2 4 24 72 9-12 0L .2200 .0009 0189 .0269 0188 " l 2 2 4 8 72 DE 3 ON .6351 .0066 2.2612 0440 .0389 .0055 .1423 .0278 .0459 " 2 2 " 1 2 2 4 2 4 34 72 ON 6 0L .1482 .0132 2.4492 .0227 .0246 .0229 .0081 .0507 .0296 ' l 2 " 1 2 2 4 2 4 17 72 8-10 .23 .09 .O4 2 2 a O 1 weight of pooled head samglgg 72 9-12 .0062 .4290 .0162 .0133 .0274 2 " 2 2 4 15 72 5-53 .0148 .2011 .0160 3 .0 6 73 8-11 740.01 839.85 1388.5 2 2 4 73 9-17 2027.7 4836.5 254.4 2 t 1 2 Yr. Field Oates Blocks Nitrogen Water Age Clb NxW NxA NxC AxC NxAxC BxN Ogu Error Kernel weight 73 8-11 2.23 1.63 1.52 73 9-17 1.38 17.07 .8: 2 s 1 2 Heads/2 linear row foot 72 9-12 71.4; 337.10 1.90 34.50 14.53 72 553 3.07 9.59 2 2 4 16 3 2 3.42 6 Feeding scars/stem 72 9'12 OE 43:87. 2388.; llgagsé 2671.: 4209.“ 72 -1 . 56 9 20" 7314; 3445.; 11455. 1315.: 1220.4 72 9-12 OL 15 4. ‘0 .2 3 255.3; 4294.; 337.62 288.69 56 72 GE 6 0L 43296. 1769.; 122855i 63824é 1430.0 2734.9 32355. 2418.3 4576.1 72 8-10 154905. ‘“ 2 4 51 ea 5 2099'; 9193.7 10 38 FIELD 5‘55 0 TOTAL SURFACE AREA A DEAD SURFACE AREA LC-I °°T LC-2 Q 30 20 A 10 2 U E N 00 E E 00 v 40 4 g 30 -< 20 1M 10 U E 23 so N 70 IO 50 40 so 20 10 ’0’ LC'9 0 so» 1 .5 70’ a .0» got 40» ° w» 20* cl 4 460 A 060+120C A ne‘oolzooo‘ ‘24?)on °D>42 Figure 5. Surface area of stems grouped by the number of leaves on the stems in field 5-55 at Gull Lake in l972. 39 and Park (1972). The lines represent the state values and the rates were estimated by differentiating the equations. Other more general equations were unsatisfactory in approxi- mating the growth rates directly because some negative growth rates resulted. This could easily be explained due to the small sample size, e.g., 10 plants which resulted in only a few stems in a leaf class at any time. The negative growth rates occurred when stems changed classes (by adding a leaf) but the resulting average area decreased. Estimates of Stem Growth Using Paint The leaf paint data (Table 4) were analyzed to find gener- alized growth equations for each leaf class. Stems which changed leaf class by new leaf emergence during a sample period were not included in the analyses. The linear equations which relate growth to time were presented in Table 5. The negative slopes probably represent the fact that tillers were generally slower growing and these were included later in the season within a leaf class. Due to the class changes between initial and final measurements, the first and last leaf classes were not well represented in the data. This was corrected by fitting a line relating the known slopes and intercepts to leaf class, assuming equal lihear distances between leaf classes, and then extrapolating to find the slopes and intercept for leaf classes 1 and 9. The resulting equations did not fit the data well and were not con— sidered further. 40 Table 4. Painsed leaf estimates of growth by leaf class (change in mm / D > 42/stem). Mean L E A F c L A s s °0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 391.5 9.57 22.92 17.02 14.68 16.48 18.42 723 2.51 6.41 6.52 778 2.13 2.37 .99 13.03 16.26 13.70 1.81 1.11 8.32 18.29 16.34 1.42 8.63 14.55 2.68 12.22 796 1.19 7.86 5.50 14.27 22.48 65 1.84 32 16.73 20.01 2.80 15.72 19.69 11.51 13.35 22.31 867 1.69 2.62 14.17 34.18 11.59 1.62 930 .53 1.12 .35 7.70 7.62 1.42 11.24 4.45 1.38 5.11 10.68 976 .71 6.89 10.59 6.31 8.39 16.52 5.36 4.63 1.29 6.71 1.97 1057.5 7.25 1079 2.61 41 Table 5. Regression constantszrslating mean time (°D>42°F) and stem growth (change 1n mm / D/stem) by leaf class from the leaf paint data. Leaf Class Intercept Slope r2 n 2 7.38 -.007 .36 10 3 26.14 -.028 .84** 14 4 35.21 -.034 .47* 12 5 12.08 .004 .002 6 6 36.25 -.286 .58* 7 7 56.78 -.052 .51** 12 8 95.29 -.094 .91** 8 ** slope #0, P>.OS slope f0, P>.Ol 42 Relation Between Head Weight and Seed Weight Using linear regression, the relation between head weight (X) in grams and seed weight (Y) in grams for individual heads was: Y = .775 X + .066 (4) with coefficient of determination (r2) of .91. This line was graphed (Figure 6) with points from pooled head samples collected in 1972 to show the correspondence of the relation between pooled and single head samples. Using the 1972 leaf longevity data from oat fields 5-53 and 5-55, head and seed weights were put on a plant basis. This means that the variables were head weight (H) per plant and seed weight (S) per plant in grams. The equation on a plant basis was: S = .749 H + .103 (5) for both fields. The corresponding r2 value was .97 with sample size of 19. lisfl Several equations were used to predict head weight from surface area measures with the 1972 leaf longevity data. This can be done grossly on a field basis, but more detailed information available from the leaf longevity study in 1972 was used. Two types of area measurements were used in regressions to predict head weight. One measure was the maximum area of leaves and the other was the time integral of net surface area (NSAT). The NSAT values 43 L40 P OATS Y-.066 +.775x "30 ' r'-.91 1.20 - name I. l 0 1.00 .90 .80 .70 .60 .50 .40 .30 .20 . l0 SEED WEIGHT/HEAD (GRAMS) l l l j .20 .60 [oo 1 1.40 1.80 HEAD WEIGHT (GRAMS) Figure 6. A linear relation between head weight and seed weight from individual heads (points are from pooled head samples). 44 were computed using trapezoidal approximations as explained earlier and equations were tested by stem as well as by plant. For the analyses on a per stem basis, unheaded stems were omitted. How- ever, for the total plant analysis, area and NSAT included the values from the unheaded tillers. Photosynthesis of individual leaves contributes in different proportions to head weight, but this was not testable due to sample size. The analyses performed assumed equal weights of area and NSAT between leaf classes. The best equation was: .0071 NSAT + .52 Head weight (gr/plant) (n = 19. r2 = .64). (6) Yield (seed weight/acre) was calculated with equations 5 and 6 thus, relating plant density (plants/acre) to yield. Bushels/ acre were calculated with the same equations and assuming 32 lbs/bu and 453.6 gr/lb to give the following equation: bu = 1.8945 X (head weight/plant) X (plants/acre) acre + .26598 X (plants/acre). (7) Nitrogen Percent nitrogen and dry weight throughout the season from fertilized plots are graphed in Figures 7 and 8. In oat plots the nitrogen content was not different, but the dry weight was in- creased by higher nitrogen fertilizer levels. % NITROGEN IN LEAVES BY WEIGHT 45 GULL LAKE -1972 WHEAT so . , OATS W ”000‘ ! . LOW NITROGEN 40 ~ ' o O :0 - ' 0 U o . 0 0 2D ’ ‘ o 7 0 . 2 . I 2 I 1 . g 0 IO . . I l I . . A 0.0 . . L O WHEAT 5 0 , OATS umuu 11171100511 ‘ nemuu 111111005111 0 ' 4.0 " o ' o 0 3.0 > . ' 3 7 2 3 o . o. ’ 2.0 1 ’ ' t o f . ' O ‘ . O 0 3 . 10 I o O . | z 5 A A on A L O WHEAT 5 OATS mu 111111005111 “OT 3 ° HIGH mmooen 0 o I 40 - . l 0 g . . D . 0 w . . . : ° - z ' o 20" o o ' . : . . o . ID' 5 o ' o A A A A A A A o A 4 A A A A A A A .00 1000 1200 1400 1600 1000 000 000 1000 1200 1400 1600 1000 2000 2200 2400 °D>42 Figure 7. Percent of nitrogen in leaves from nitrogen plots in field 5-53 at Gull Lake in 1972 (MSU Photo Lab 752702-31). ' W WEIGHT/2 LINEAR FEETIGR.) 46 GULL LAKE - 1972 WHEAT OATS L“ NITROGEN LO' NITROGEN WHEAT OATS noun 1117mm uemuu NITROGEN 5 9 ‘5 v C... O O. . "°1 WHEAT oars . HIGH mm 0 HIGH NITROGEN 3 8 8 :3 '°' 0 . ‘ALAJA o AA‘LAAA‘ 10040000000010001200140010001000 anmoooooonoomomoonoonoozoooitoo 'D>42 Figure 8. Dry weight of foliage from nitrogen plots in field 5-53 at Gull Lake in 1972 (MSU Photo Lab 752702-30). 47 In general, the upper leaves had more nitrogen than lower leaves (Figure 9). This is important to the CLB because the location of feeding on the plant affects the nitrogen content in their diet. Leaves from plants grown with less moisture had higher nitrogen content than normal or irrigated plants, indicating an inverse relation between water and resulting nitrogen. These samples were reported as percent of nitrogen in leaves by weight of leaves and do not indicate total nitrogen utilization on a land area basis. The sprayed i.e., low CLB density, plants had more nitrogen than the unsprayed, i.e., damaged, plants. This indicates that as beetles fed the percent nitrogen in the diet decreased or that feeding occurred on high nitrogen portions which caused the leaf samples to be reduced in percent nitrogen. No evidence was found that nitrogen affected either plant height or stem density in plots in field 5-53 at Gull Lake in 1972. Soil Moisture Soil moisture fluctuates most rapidly at the soil surface (Appendix K). At 36 inches the soil moisture is very constant and high. The soil moisture at shallower depths fluctuates rapidly in response to rain. As shown in Appendix K, soil moisture can change diurnally but these responses are small. The noticeable changes in field 8-13 are due to artificial irrigation and could be used to estimate the soil response to rainfall. “UNSPRAYED OATS JULY 5,1972 Eonouen‘r MSPRAYED OATS JULY 5,1972 MNORMAL -WHEAT JUNE 9,1972 WIRRIGATED 48 ALL 0000000000000 ............................. .......................................... OOOOOOOOOOOOOOOOOOOOO s\\\\\\\\\\\\\\\‘ "\\‘ N7 .................................................. 'U c ........ ...................................................... OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO .LHOIBM A8 SBAV31 NI NBOOHLIN °/o LEAF GROUP -pooled by position on the stem and in Figure 9. Histogram of percent nitrogen in leaves- sprayed and unsprayed plots. 49 Cereal Leaf Beetle Larval BehaVior and Orientation on Host Plants The field notes (Appendix L) from watching individual larvae were used to evaluate feeding and migration. The feeding speed during the feeding periods was 0.17 cm/min between two leaf veins. However, for the entire observation time the feeding rate was calculated as total feeding length/total time observed, which was .03 cm/min. Larval migration speed was found to be 1.79 cm/min while walking. The overall migration rate, however, was much less (0.11 cm/min). Clearly, large larvae are capable of considerable migration. They are also able to change leaves or plants without moving to the soil surface simply by walking onto overlapping leaves since this was observed for one larva. It seems that large larvae could migrate considerable distances and find desirable food even at low food densities. Direct meaSurements of larval locations by leaf group were summarized by counting leaves from the bottom of the stem (Table 6) and top leaf downward (Figure 10). Both summaries were completed because tillers vary in leaf number. The temporal shift in leaf group using the bottom count shows primarily a change in leaf group available to the larvae. The summary from the top leaf downward indicates that the larvae are on the upper leaves. Forty-four percent of the larvae occurred on the top leaves, 41% on the second leaves and 14% on the third leaves. This means that the approach of using the top three leaves as a standard plant measure may be 50 Table 6. The number of larvae on leaves by leaf group in field 4 at Collins Road in 1974 ' LEAF GROUP 3 4 5 6 7 8 9 TOTAL l4 June Main stem 1 3 6 1 ll lst Tiller l 1 2nd Tiller l . 1 TOTAL 1 2 3 6 1 13 18 Jugg Main stem 3 ll 6 20 lst Tiller l l 2 2nd Tiller . 0 TOTAL 22 27 June Main stem 3 l 10 4 18 lst Tiller l 1 2nd Tiller 1 1 TOTAL 20 2 July Main stem 2 3 5 lst Tiller 0 2nd Tiller l 1 TOTAL. 1 2 3 6 51 .commwm mg“ zmsocgu mm>mwp co mm>cm_ mo cowuznwsumwu 05H .o_ mczm_u mm>m<4 Qm>mmmmo mo hzmomma ¢Nm_ .N 33, km 0:3. m. mcaw E 0:3, on Om ow ox. Om mm 9. On 0N on On mm 7 fm Fth l a Em ~ 11 Em m L838. m 0.. nVN n c mum ".0 m. n c 52 justified. This was used by Gage (1972) without proof as a standard plant measure. However, this measure is not useful if the top three leaves are insufficient to predict yield or if larvae defoliate upper leaves and sequentially damage lower leaves significantly. The fact that larvae feed on upper leaves indicates that feeding is not randomly distributed throughout all green leaves. This was probably due to a positive phototropic response. A response of this type would keep the larvae on newer leaves which were also greater in nitrogen content. DISCUSSION Oat Growth and Cereal Leaf Beetles As an oat plant grows, several processes are occurring. After emergence of a primary stem, additional leaves are subsequently added to the top of the stem. The individual leaves grow succes- sively with stem elongation occurring almost exclusively on the uppermost leaf. Each new leaf on a stem reaches a size about equal to or larger than the size of the preceding leaf. In general this is true except for the flag leaf and for damaged or stressed plants. As new leaves emerge, old leaves are also dying both occur at specific rates governed by the genotype and environment. This process of leaf senescence occurs first with the lower leaves, which have existed longest. Thus, as a growing season progresses, the number of leaves existing on a stem is a net result of the rates of these two processes. The process of tillering is also occurring during the previously described growth process. The addition of a new stem and the emergence of new leaves on the stem adds complexity to the dynamies of plant growth. In some oat plants it even becomes difficult to distinguish between tillers and main stems. Heads are produced on the main stem of oats but are not always produced on the tillers. The number of leaves on a stem before heading is entirely predetermined for a stem and varies 53 54 with the photoperiod and variety. The tillers also produce fewer leaves than the main stems. Thus, the resulting plant presents a complex array of leaves and stems. This array certainly is strongly influenced by the environmental conditions in which the plant has been grown. In this sense, the plant acts as an integrator of the environment. Since each successive plant part is influenced by the history of the plant up to that time, measurements of suc- cessive parts are well correlated. The CLB interacts with the plant by feeding on leaves. This immediate effect removes surface area which is lost as potential photosynthetic tissue from feeding time to the end of a normal leaf age. However, more subtle interactions occur, such as inter- actions with feeding and environmental factors. For instance, a feeding scar opens a leaf and causes increased water loss and a disease introduction site. The feeding damage can also cause the leaf to senesce earlier than it normally would, thus causing addi- tional loss of potential photosynthesis. Heavy damage can also cause reduction in tillering or actual stem mortality. The nature of the damage is thus complex in itself. The temporal synchrony between the beetle and the plant can change the relative significance of equal damage. For instance, the damage on early leaves influences every stage after the damage. Damage later in the growing season consequently has fewer future stages to influence. This is confounded since early photosynthesis contributes mostly to plant establishment which allows later photo- synthesis to contribute more directly to yield components. 55 when viewing or sampling damage in a field, the damage is not visible if the leaves have already senesced. Thus, if damage occurred on the first two leaves and damage was estimated after the first 2 leaves senesced, then no damage would be visible but the effect would remain. ‘Now, by viewing an entire field of oats, we can visualize describing it as a population of stems and leaves. This adds an additional degree of complexity to the oat and CLB interactions. This is done by describing all the processes of leaf growth, emergence, senescence, and tillering as population phenomena- CLB‘s also occur as populations and can be described in this manner as well with growth and feeding functions. The population of beetles also interacts with the same four major damage possibi- lities. The temporal synchrony with the population also effects the actual damage that occurs. The distribution between leaves, between stems, and between plants can be described as dynamic functions. A description of dynamic plant growth and CLB growth can be as complex as desired. Thus, a functional model must be a compro- mist between complexity that we know exists and what is necessary or practical to accomplish. A model should be viewed as a dynamic entity which is continually updated and corrected. Description of the Plant Model The system model consists of a single oat field which is to be used in conjunction with the CLB model to evaluate the plant growth responses and to predict yield. The model was also designed 56 to explore and recommend appropriate control measures for the mini- mization of damage due to CLB populations. The overall cereal leaf beetle ecosystem was functionally related by Haynes et al. (1974). The biological components included in this model were the grain plants and the cereal leaf beetles. The parasites of the CLB were not included here since there is no evidence that parasitized larvae feed differently than non-parasitized. The soil and soil organisms were lumped into a single nutrient pool. It was assumed that the soil and associated organisms had no other significant effects on the plants except to provide nutrients and water. If these other factors are found to be significant they will need to be incorporated in the model at a later date. At present the system includes only biological aspects without economic considerations. An outline of the plant system follows. Desired Outputs 1. Grain production 2. Straw production Undesired Effects 1. Environmental contamination due to pesticides and herbicides 2. Fertilizer runoff causing pollution and waste of nutrients Environmental Inputs--Not Controllable 1. Heather parameters a. Rainfall b. Solar radiation c. Temperature 0'1th 1. 2. 57 Nutrients from soil (N,P,K,etc.) Overt Inputs--Controllable Fertilizer rates Planting dates Spatial pattern of planting Variety of crop Irrigation of crop Potential State Variables Plant state measurements a Surface area of leaves b Biomass--wet or dry weights c Density of stems d. Head weight e. Density of heads f Plant height 9 Crop age C a b ereal Leaf Beetle . Age of population . Population density Measurements of System Performance Levels of desired outputs and undesired effects Compatibility with good farming practices This approach stresses biological understanding and the crux of the model includes biological components for plants with appropriate interface ability to CLB models. The present CLB model is based on populations of various life stages, and the plant is modeled similarly. This allows for compatibility and assures that both models are operating on similar levels. 58 The time increment used to produce the model was l°D > 42°F. Germination and tillering in the model were related as in Figure 11. The input to the germination stage was a single pulse of seeds. The output from the stages was a time delayed distribution which described the variation in plant emergence from seeds. This distribution was estimated from the leaf longevity data. The magnitude of the input pulse used was estimated from actual plant density counts and the mortality rate was set at zero. The mortality function was included in the figure for completeness (to be used if the input pulse was seed density rather than plant density). The tillering function was estimated from the leaf longevity data and the output rate was added to the rate of stem production from the germination stage. The tillering output and the germi- nation output are nearly distinct because of the time differences in the processes. Each leaf stage was modeled as in Figure 12. The two major divisions were the stem density by stage and the leaf surface area by stem. The stem density in each leaf class was computed by integrating the input minus the output from the leaf stage function. The input rate for the first stage was defined from Figure 11. The leaf stage function was a time delay function as used for germi- nation. The mean time and the distribution of the output were estimated with the leaf longevity data. The output for each stage was corrected for stem mortality and head production before the rate was used into the following stage. 59 mogm ”Em: Em: 0.— Al ME». :52 .pmuoe mg“ cw uwma co_pmc_sgmm mo Eagmmwu xuo_m .pp mg:m_u 20:02:”. 02.5.3: 20:02:“. 536.592 HzEmzoo zo_.5m _ Em _ o 55m 2223215 . mew + a Emmp xn uwaaogm mm_uwpcm mm msmpm ’ ‘ \r < [O‘NSA loflflfifl 350‘ g a! a! 10.30:: _ o o u _ 3.50.00. A... 8 3.. 3.3» :3 8 2.2. uto<\:. can... .853. 9 5.5.3. o 8.8. u H 133 I (I: 1 532.00 IBIS-.3 :8..- .u! 4 ow :8..- 0‘2. 0 O 5:035 , :0- !hgs :00 U 8:39. Fol-8.1 u 1.33. F lac-.1 >51! 2 «I: u. 3.: an... 3.. . IS. n. In».\ cl. 5. 54.: O 2.. u./ h ..... .5 a. Al. F QI/ _ @w I. ..... T n UCUQ\ Clor- vaso. .00: I cl:- OIOC \ _ 3:. I 'Irlu 8.8!... 2:3...» 3:85. 30.53. 3338.. 3.3:... I. > .x. I I. S O. HOS—h . II o. H O H I... g O 3.5 . 345 V Bi: m: .I-I: Etc-“hp 35“..» :1 .18.... 50:“..3 5.8.8 . . 3 inc-3 00.1.3533:- 3 00.50.05... A A 20.3 peace we Emgmmwn xuopm .cp mgammu nouum 64 and Park (1973). The main subroutine used was the distributed delay which allows for dynamic storage in a stage. Integrating around the delay gives the number in a stage or, in this case, a leaf class. Cascading the germination delay with leaf class delays and a head delay made up the stem density portion of the model. The time increment used in updating the simulation was one degree- day which was suggested by Tummala et a1. (1975). Model Interface with the Cereal Leaf Beetle The modeling procedures used were general enough to include several types of interactions between the cereal leaf beetle and oats. Four effects of the beetle on the plant response had been hypothesized: (l) removal of net surface area due to feeding; (2) decrease in longevity of individual leaves; (3) increase in mortality of stems; and (4) reduction in growth due to an inter- action effect between damage and moisture stress. These four potential interactions interface with the model at the bold arrows in Figure 12. The primary interaction of feeding was included in the model. The CLB interface assumes random feeding on all net surface area. Therefore, a constant loss per net leaf area was used regardless of size or age class. This is reasonable since the net leaf area and the larvae occur at the top of the stems. The cereal leaf beetle population data described by Fulton (1975) was used to model a CLB interface with the plant model. These data were used to find a single population of first instar feeding equivalent (FIE) as in Figure 15, using Wellso's (1973) 65 com. H09. Mu .1... ICON. mu .1... VOOm. Nu M . moo¢1 ms. 3 1 N m. Ioomx I: .1. 300». com. .macmpm>w=cm mcwummm scams. umgwm new mgmumcw OFHmmn mom, Pmmcmu so. m0>g=0 mucwuwucm .mp mgamw. ow¢ A m> 42°. This time scale puts the beetle population on the same time scale as plant growth and did not seem to result in a loss in predictibility. The rate of feeding was computed by calculating the differ- ence between two points on the line for each time increment in the model. Use of a Model in an On-line Mode A model can be easily designed which gives a consistent output for set inputs and runs non-stop through a set time period. However, to use a model such as this one for plants or beetle popu- lations in an on-line fashion for short term predictions, it is necessary that the model be updated continuously. Two general solutions to this problem are available. (1) Choose a model which is not dependent on historical phenomena. A model of this type has no internal memory and all responses are based on stimuli with no recognition of the past. Models of this type are generally referred to as static linear models. The equa- tions involved would be a set of multiple regression equations which could be reduced to a single matrix equation, i.e., 67 Table 7. Statistics for the regression of the probit of cumulative first instar feeding equivalents (Y) 0" time (X) as date, 00 > 48 and 00 > 42 (Y=A+BX). Date OD>48 oD>42 Eisléf’ 59E 5. 9. A. E. A. .9 2RG 67 2 -11.50 .0980 1.460 .0045 .7132 .0035 ZRG 68 13 -23.56 .1744 -1.358 .0085 ~2.734 .0066 ZCC 68 5 ~42.47 .2892 —4.841 .0142 -7.393 .0109 2R0 59 11 -20.54._ .1513 -2.508 , .0100 -3.353 .0071 2cc 69 9° -19.99 .1414 -l.766 .0080 -2.797 .0060 216 70 6 -18.37 .1466 - .2550 .0070 — .8100 .0054 ZRG 70 5 -19.81 .1549 - .5495 .0073 -1.165 .0057 200 70 5 -24.59 .1811 -2.010 .0084 ~2.777 .0066 ZTG 71 5 -22.10 .1737 - .3512 .0094 -1.090 .0072 2RG 71 4 -26.23 .1966 -l.2600 .0100 ~2.101 .0077 286 71 3 -23.41 .1767 - .5364 .0085 ~l.428 .0066 2A6 72 5 -21.74 .1653 -1.103 .0092' -l.847 .0070 286 72 6 -13.06 .1117_ .5364 .0062' .0562 .0047 2CD 72 1 -21 29 .1512 -4.656 .0103 -4.834 .0073 2E6 73 4 -32 00 .2215 -2.729 .0091 -4.434 .0073 2LG 73 2 ~38.48 .2616 -3.870 .0107 -5.884 .0086 ”codes from Fulton (1975) 68 I11) = A0) '50:) (9) by simply sensing the state of the system, the outcome is completely determined. (2) Use a more complicated dynamic model with a corrector capability. This allows historical events to influence predictions as well as non-linearities and interactions to be included in the model. A general outline- of how this would occur (Figure 16) is similar to a feedback control loop. Using a loop of this type, the system can be updated or corrected based on the actual state of the system found by direct observation. The corrector algorithm may be rather complicated to account for non-linearities, etc. How- ever, the corrections can be completed in practice by use of a covariance matrix. Status of the Simulation Initially the model structure was chosen to satisfy the following criteria: 1. It should represent the phenological events of the plant; 2. It should provide the variation of the net surface are of oats through the season; 3. The net surface area of oats and CLB damage should reflect the actual synchrony of the two organisms; 4. Net leaf surface area should be related to yield; 69 .0005 mcwpuco cm :. _muos a mcwm: Low conums a mo Emgmmwv 3o_w < .o_ 023mm. zzh~mom4< mwhdpm zonhummmou mo mommm mhmmmmo _ 5... mhbmzu zouhummxou @AI 25...... .35.. + 70 5. Yield quantities should be in realistic ranges of O—lOO r bu/acre depending on environmental conditions and CLB levels; 6. Beetle damage should reduce yield at moderate and high densities. The structure of the model presented is general enough to be applicable to many cereal crops. Specific relationships were not available and hence in the initial simulation studies, repre- sentation based upon the best guesses were used. The initial values used in the model are presented in Appendix M1 and the FORTRAN simulation model is presented in Appendix M2. The equations and constants used in the model are documented earlier in the thesis, in the appendices or in the FORTRAN program as "comment cards." The initial simulation runs of the model were qualitatively evaluated against an intuitive understanding of the system. This process of qualitatively evaluating model responses was completed before quantitative evaluation can be justified. The process of developing growth equations and evaluating constants was in itself informative in pointing out weak points in the data collected, the equations selected and the model itself. The output from the simulation is given in Figures 17, 18, and 19. The stem density/acre and surface area/stem were plotted for selected leaf classes. The densities for the leaf classes that are not shown are intermediate between those leaf classes that were plotted. The stem density changes through time in a leaf class closely relates to the observations in the field. The group of 71 On .:0wum—:Ewm map 202% c mmm_o mmmp cw mEmum ucm mvmm: .mvmmm mo Amgum\.wnsacv xuwmcmu one 32+. 022.244.... mmhuq moN¢Aoo 3 ON m. o. m h @930 Dawn. 2. mZMkm 4 _ mm<40 ham; 2_ mimkm c .A. 6.35.. ((1 I 38017/ BSGWON 1901-:— 72 .cowum_:swm mgu son» A new _ mmmmmpu mam. cw msmum mo flwgum\.wnszcv xuwmcwu 02H .m. mgzmw. 50.1. 023.2415 cur... uoNvAoo on 8 ON A... o. m o . N o I — n . W . 8 c o 3 8 . . N x . av . O M. . . 3 . . . n I 4 0—0 . . O . . c. a: mo 42 from January 1 and the plant growth occurs in °D > 42 after planting. When this was not taken into consideration, the beetles 75 were eliminating all leaf surface and it was becoming a negative quantity. The solution selected to eliminate this problem was to stop all feeding before plant growth had started by a conditional statement in the simulation. Unusual values of beetle density or planting date may cause the problem to reoccur. An error diagnostic in the simulation points out when this occurs. Certain assumptions have to be made in parameterizing the model based upon their relative importance. For example, no feed- back effect of feeding by CLB's on the changes in the leaf area growth rates was assumed. Also no effect of available nitrogen on the tillering rate or change in leaf area was assumed. The tillering function used in the model did not include the environmental factors, the stem density and stem age. For example, the tillering function does not produce additional tillers at low seed densities or fewer tillers at high seed densities which is a well-known phenomenon. The tillering rate represented in the model is valid for seed densities close to the standard seeding rate of 2 bu/acre. The equations which compute the rates of surface area production and senescence are linear approximations of time (in °D) based on one field and do not reflect changes in the environment nor the plant state. Thus, a rate is a function of time and is not altered for changes in the state. This means that each growth rate occurs at a set rate even after changes in plant state. For instance if a plant has been fed upon by the CLB, no Change occurs in the rate of growth which results in the next time step. 76 Furthermore, it is not Clear from the field data that CLB's really affect the rate and not just the state but it seems logical that plant growth rates should be state dependent. Specific tests of more subtle interactions between CLB's and oats, as well as rate functions, should be completed if these are to be incorporated in the model. Individual stems in the model contribute equally to final head weight since all leaf area is integrated through time to predict head weight. This is reasonable on a plant basis since all photosynthesis is important to the plant. It is true that photo- synthesis in late leaves contributes more directly to head weight but photosynthesis in early leaves contributes to plant estab- lishment and tillering which is also critical to plant growth at a later time. A considerable modification of the model would be necessary to allow for apportioning the energy accumulated to various leaves, stems, and heads. This would really be changing the model level from a stem population model to a leaf population model. It is tempting to change the model level in a similar manner as the CLB interface is incorporated. With the stem model, as presented, it is not reasonable to account for the preference of CLB larvae for upper leaves. All stems have upper leaves and the preference for these leaves is accounted for since leaf area is expressed as leaf area/stem. The leaf population modeling approach would allow for a preference between leaves by CLB's. However, this level of complexity is not obviously needed for pest management purposes. 77 The present model simulates a single field well. The model can be used to screen temporal synchrony between the beetle and the plant and to estimate the feeding that a field can sustain. The model was not designed to include all the variables that are present between fields, e.g. soil conditions, nutrients, microclimate, topography. This again is asking more than the model was designed for. However, adjustments in the equations and corrections fOr starting points in the model would make the model functional for this purpose. In practical use of this model in an on-line pest management scheme, early season plant samples might be an ideal method of estimating the factors necessary for initiating the model. Plant samples like two linear row foot of foliage can be used to estimate the stage of oat growth both stem density and net leaf area. In addition, if the samples are timed after the CLB egg input has ended, they can be used to estimate the CLB density by egg, larvae, and damage counts. Thus, a single sampling procedure can be used to initialize models early in the season and still have time to make management recommendations. BIBLIOGRAPHY 78 BIBLIOGRAPHY Anonymous. 1956. Cornell recommends for field crops. New York State College of Agr. Cornell Univ. Baier, w. 1973. Crop-weather analysis model: review and model development. J. App. Meteorology. 12(6): 937-47. Balvoll, G. and A. H. Bremer. 1965. Vermesum og plateavl i samband med vekst og utvikling av ymse grpnsakvokstrar. (The heat- unit system and plant production in connection with growth and development of different vegetables.) Meldinger Norges Landbrukshdgskole. 44: 1-18 (seen as abstract). Barr, R. O., P. C. Cota, S. H. Gage, D. L. Haynes, A. N. Kharkar, H. E. Koenig, K. Y. Lee, H. G. Ruesink, and R. L. Tummala. 1973. 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Madison, Misc. 650 pp. Colwell, J. E. and G. H. Suits. 1975. Yield prediction by analysis of multispectral scanner data. Nat. Aeronautics and Space Admin. NASA CR-ERIM lO9600-17-F. Houston, Texas. 73 pp. 79 80 Findlay, W. M. 1956. Oats: their cultivation and use from ancient times to the present day. Oliver and Boyd. Ltd. Edinburgh, England. 207 pp. Forrester, J. W. 1961. Industrial Dynamics. Mass. Institute Tech. and J. Wiley and Sons, Inc. Frey, K. J. and S. C. Wiggans. 1957. Tillering studies in oats I. Tillering characteristics of oat varieties. Agron. J. 49: 48-50. Fuess, F. W. and M. B. Tesar. 1968. Photosynthetic efficiency, yields, and leaf loss in alfalfa. Crop Sci. 8: 159-63. Fulton, W. C. 1975. Monitoring cereal leaf beetle larval popu- lations. M.S. Thesis, Michigan State University. 108 pp. Gage, S. H. 1972. The cereal leaf beetle, Oulema melanopgs (L.), and its interaction with two primary hosts: winter wheat and spring oats. M.S. Thesis, Michigan State University. 105 pp. Gage, S. H. 1974. Ecological investigations on the cereal leaf beetle Oulema melanopus (L.), and the principle larval parasite, Tetrastichus julis (Walker). Ph.D. Thesis, Michigan State University. 172 pp. Gallun, R. L., R. T. Everly, and W. T. Yamazaki. 1967. Yield and milling quality of monon wheat damaged by feeding of cereal leaf beetle. J. Econ. Entomol. 60: 356-9. Giese, R. L., R. M. Peart, and R. T. Huber. 1975. Pest management, a pilot project exemplifies new ways of dealing with agri- cultural pests. Science. 187: 1045-52. Grafius, J. E. 1956. The relationship of stand to panicles per plant and per unit area in oats. Agr. J. 48: 460-62. Grafius, J. E. 1972. Competition for environmental resources by component characters. Crop Sci. 12: 354-56. Green, C. E. and H. Goetz. 1973. Morophological variation in three ecotypes of Agropyron smithii Rydb. and Bouteloua gracilis (H.B.K.). Lag. Ex. Steud. Agr. Exp. Sta. Bul. 491. N. Oak. 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A discrete component approach to the management of the cereal leaf beetle eco-system. Environ. Entomol. 4(2): 175-86. 83 Tummala, R. L. 1976. An age-dependent simulation model of an insect population. (in preparation) Venturi, F. 1942. La Lema melanopa L. (Coleopera, Chrysomelidae). Redia. 28: 11-88. Waggoner, P. E. and J. G. Horsfall. 1969. EPIDEM: A simulator of plant disease written for a computer. Conn. Agr. Exp. Sta. Bull. 698. New Haven. 80 pp. Waggoner, P. E., J. G. Horsfall, and R. J. Lukens. 1972. EPIMAY, a simulator of southern corn leaf blight. Conn. Agr. Exp. Sta. Bull. New Haven. Webster, J. A., D. H. Smith, Jr., and C. Lee. 1972. Reduction in yield of spring wheat caused by cereal leaf beetles. J. Econ. Entomol. 65(3): 832-35. Wellso, S. G. 1973. Cereal leaf beetle: larval feeding, orien- tation, development and survival on four small-grain cultivars in the laboratory. Ann. Entomol. Soc. Amer. 66: 1201-1208. Wellso, S. G. and C. E. Cress. 1973. Intraspecific competition of the cereal leaf beetle reduced through_spatial separation of eggs and feeding. Environ. Entomol. 2(5): 791-92. Wiggans, S. C. and K. J. Frey. 1955. Photoperiodism in oats. Ia. Acad. Sci. Proc. 62: 125-30. Wiggans, S. C. and K. J. Frey. 1957. Tillering studies in oats II. Effects of photoperiod and date of planting. Agron. J. 49: 215-17. Wilson, M. C. and R. E. Shade. 1964. The influence of various gramineae on weight gains of post-diapause adults of the cereal leaf beetle. Oulema melanopa (Coleoptera: Chysomelidae). Ann. Entomol. Soc. Amer. 57: 659-61. Wilson, M. C., H. H. Toba, H. F. Hodges, and R. K. Stivers. 1964. Seed treatments, granular applications and foliar sprays to control the cereal leaf beetle. Purdue Univ. Agr. Exp. Sta., Res. Prog. Rep. 96. 8 pp. Wilson, M. C. and R. E. Shade. 1966. Survival and development of larvae of the cereal leaf beetle, Oulema melanopa (Coleoptera: Chysomelidae). on various species of gramineae. Ann. Entomol. Soc. 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APPENDICES 85 APPENDIX A PLANT DATA SUMMARY FOR STEM SAMPLES FROM GULL LAKE IN 1972 (MEANS PER STEM) (PLANT LENGTH IN CM). 86 0 .0 0 00 0 00 0 .0 0 0 00 0 m0 0 .0. 0 0o. 0 00. 0 0.. 0 00 00. 0 - 0. .00. 0 0 0 0 0 0. 0 0. 00 0 m0 0 0.0 0 00. 0 00. 0 0.. 000 0 - 0. .00. 0 0 0 0. 0 0. 0 0. 0 0. 00 0 00 o mvN O 00— 0 On— a $0— 0 60— '8 O 1 O— O~\~ o O O - 0 CN 0 o~ O - no 0 a 0 000 0 00. 0 00. 0 00. 0 0.. 0.0 0 m 0. 00.. 0 0. 0 0. 0 00 0 .0 0.. 0 0. 00 0 Now O v0- 0 :— o x was N 2 u o. 2: o o o m— o o— o v— o 2 mm .6 mm 0 000 0 00. 0 00. 0 00. 0 00. 000 0 0 . 0. 0... 0 .0 0 0. 0.. 0. 0.0 .0 00 0.00 «0 o oo— c.0— 3. n.: m2 ”.2 ow- o; ~.—o~ 1 O— o: o ow n ON o._ a— o.— n— 2 06 a 0.0 0.. 0.0 0.. 0 0. 00. 0.0 00 000 0.0 0 0. 0.. 0 0 0.. 00 0, 0 . . 0. 0.. 0. 0. 0.00 00 O ~ :~ as a: ~.o g— 00. o- ~o— n6 2— nos p.m: m or axe o; m~ ~ — o~ O.— QN N.— m. 00— b.~ cw . . . 0.0 000 0 .. 00. 0.0. 00. 0.0 .0 00. 0.0 - 0. 0000 . . 0. 0 . 00 0 . 00 0.. .. 0.0 .. 00 0 000 00 0.0. 000 0.0. 000 0 0. 00. 0.0. 00. ..0. 0.. 00. 0..00 0 0. 0000 0. 00 .._ 00 0.. 00 0.. 00 0.. 0. 00 _.0 00 . . 0... 000 0.0. 00. 0.0. 00. 0.0. 0.. 0.0. 00. 00. 0.0. 0 0. 0000 0 00 ... 0. 0 0 00 0.0 00 0.. .0. .0. 0.00 00 0.2 fix a... 02 0.2 3. 0.: .2 v o. 0: 3m «.02 u o. 23 o o o; 2 n.~ o~ n.~ a. 0..- _~ o.~ 0~ 3 0.: on . 0.0 0.0 0.. 00. 0,0. 00. 0.0. 00. 0.0. .0. 0.0 0.. 0.0 0.0. 0 0. 0.00 0 . .0 0.. .. 0.. 0. ... 0. 0.. 00 0.0 .0 00 0.00 00 _ 0.0 0.0 0.0 0.0 0.0. .0. 0... 00. 0.0. .0. ... 00 000 0..0 m 0. 0.0 0 0 0.. .0 0.0 00 0.0 00 0.0 0. 0.. 00 0.0 00 0. 0.0. 00 0.0 00. 0 0 00. 0.0 0.0 0.0 00. 0.0. .0. 0... 00. 0.0 00 .00 0 0. m 0. 000 0.. 00 0 . 00 0.0 00 0.. 0. 0.. .0 00 0.00 00 ad 8. n6 0: —.0 we. _d— 8— —.o no. 33 v 9 u c— :0 o. : _._ R m.~ 9.. o.~ On ~.. en en 0.: cm . . . 0.. 00. 0.0 00. .10 0.. 0.0 00. ..0 .0. 000 0.0. - 0. .00 0 . 0. 0 0 00 0 0 00 0 0 .0 . _ .0 00 0 0. 00 n m x o a ~n_ VA :— «A N: s-m :— :N 7: m 0. o~\m o.~ mm _.N _v m.— o~ #4 ON 9.. c; an . , . 0.0 00. 0.0 00. 0.0 00. 0.. 00. 000 0.0. 0 0. 0000 0 . 0. 0 0 00 0 . .0 0.. .0 00 0 0 00 v.n 3 0.0 a: a.“ On— v.0 co «2 n.' m O~ 23 ~.~ z 0.. - m4 ON «N o.~ ow 111-11-111111 1111.-- . - 11 - 0.0 00 0.0 00. 0.0 00 00. 0.0 m 00 0.00 10.11. .0, 1m 1 ._, b-1101 M 0 1h 1111.1 .... . 59.3 :30 0 300 1. 11-1 . II. 01|1 .011 1 1|. -- 23011 I0I .3. . 0...... .01 IF 1.0 1.1 1.1 0. .0 _- .1. 101-.. .. I..11I.1 -. . so... 2:0 e 3.0 ...:. .0. 0.0.. 02. ... 0002.. 0... 0 hW1111.-111-m-11111-- -.m11111------m.1.1111111_m1- .00. m . .2... fl... .0: 50... 2.0 3. 50:3 .00.. .~59— cw 0...; P200 a. 0 U0 uO—m as» oucgawot “CO—A .: 0—90» .22 c. 0.0.. :3 u. n 3 00... so... Sci-0.300.. 0...... .3 03: 0 0 0 0 .0 0 00 0 00 0 00 00 0 00 0 0. 0 00 0 0. 0 0. 00 0 00 0 .0. 0 00. 0 00. 0 00. 0 00. 0.0 0 m 0. .000 0.. 0 00. 0 00. 0 00 000 0 M 0. .00. 0 0 0 00 0 0. 0 0. 0 0. 00 0 00 0 0 0 0 0 .0 0 0. 0 .. 00 0 00 0 00. 0 00. 0 .0. 0 00. 0 00 00. 0 0 0. 000. 0 000 0 0.0 0 00. 0 00. 0 00 000 0 m 0. 000. 0 00 0 0. 0 0. 0 0. .0 . 00 00 0 0. 0 00 0 00 0 00 .0 0.00 00 0 0.. 0 0.. 0 00. 0 00 00. 0..0 0 0. 0.0. 0 00. 0 0.. 0 0.. 0 00. .0. 0.00 m 0. 0.0. 0 00 0 00 0.. 00 0.0 0. 0 . 0. 00 0 00. 00 0 0 0 00 ... 00 0.. 0. 0.. 0. 00 0.00. 00 0 00. 0.0 .0. 0.0. 00. 0.0. 00. 0.0. 00 00. 0..00 . 0. 00. 0 00. 0 00. 0 0. 00. 0 .. 00. 0.0 00 00. 0.000 m 0. 00. 0.. 0 0. 0. 0.. 00 ..0 0. 0.. 00 00. 0.00 00 0 00 0H .0 0.. 00 0.. 0. 0.. 0. 00 0.00 00 0.0 .00 0.0 00. 0.0 00. 0.0 00. 0.0 .0. 000 0.00. 0 0. 00.0 0 0. 0.0 0 .. 00. 0... 00. 0... 00. 0.0 00 00. 0.0.0 0 0. 0000 0. 00 0 . 00 0.. 0. 0.. 00 ..0 00 .0. 0.00. 00 0H. .0 .H. 00 ... 0. 0.. 00 0.0 00 00 0.000 00 0... 000 0... 0.0 0.0. 00. 0,0. 0.. 0... 00. 000 0.000 m 0. 0000 0 0. 000 0 0. 00. 0 0. 00. 0.0. 00. 0.0. 00 000 0.0.0 0 0. 00.0 0 0 0.. 00 0.0 00 0.. 00 0.0 00 0.0 00 0.. 0 00 00 0 0 0H. 00 0.. 00 0.. 0. 0.0 00 0.0 0. 00. 0.00 00 0 0. 000 0.0 0.0 0,0. 00. 0.0. 00. 0.0. .0. 0.0 00 000 0.... 0 0. 0.00 0 0 000 0 0 00. ..0. 000 0... 00. 0.0. 00. 0.0 00. 000 0.00. m 0. 0.00 0.. 00 0.. 00 0. 0. ..0 00 0.. 00 0 0 00 00. 0 00 00 0M. 00 .H. .. 0.. 0. 0.. 0. 0.. 0. 0.. 0. 00 0.00 00 0.. 000 0.0 000 ..0 0.0 0.0. 00. .,.. 00. 0 0 00. 0.0 0.00. 0 0. 000 0 0 00. 0 0 000 0.0 00. 0.0. 0.. 0... 00. 0.0 00. .00 0.00 m 0. 0.0 0H. 00 0H0 00 0.0 00 0.0 00 0.0 00 .0 0 00 00 0H. 0. 0H. 00 0.. .0 0.. .0 00 0.00 00 0 0 00 0 0. 00. 0.0. 00. 0.0 00. 0.. 00. 000 0 00 m 0. .00 0 0 0.. 0 .. 0.. 0.0. 0.0 0.0 00. 000 0.00 m 0. .00 0”. 00 0H0 00 0.0 00 0.0 00 00 0.0 00 0”. 0. 0H. 00 0.. 00 0.0 00 .0 0.0 00 . 0 00. 0 0 00. 0.0 00. 0.0 .0. 000 0.0. 0 .. 00.0 0 0 0.. 0 0 .0. ..0 .00 0.0 00. 0.0 0.0 u 0. 0000 0 0 0 00 0 00 0 00 00 0 00 .H. 0. 0.. 00 0.. 00 00 0.. 00 0 .0 0 00 0 00. 0 .0. 00. 0 0 0. 0.00 . 0 00 0.0 00. 0.0 00. 00. 0.0 0 00 0.00 .. . 1P 0 0 .- .. . .. 0 0 0 50$. :30 0 33 0 0 a 0 0.... 0 101 I ~ .013. 0020 II PIMI PHI. P0IH. PnIp ~ .. 0 Ann...“ €30 .. 88 ...u. .0. 000.0 0:0 . 00000. 00 A 0 0 .. TE. .5 5...: v... S. 59.3 .03 .22 c. 2.3 :3 00 ~ 8 .20 It. 3.0.8:... 0...: .3 02: .22 E 0.3 :3 a. 0 8 3.0 It. 3.0.2.03- 05... .3 03: 87 "at mu m- flot C 6 n in" LIII In 1m. tdlo “- "an hum h- "0! a S It 6" uh 1- I912. tabla A5 . Lu! 1...» a) u mm (a) In.) L." m (L) m um: (I) (-.) 'Ilnt Sun Length ”03.3%: I [ U [‘l E l E I [,9 Oltl M 0 1 6 7 O.“ N N 20 Sill .. .0- 5‘ .N C .0- .N 33 20 SH! O. .— IO SIN on .N 5: ~— KN .- 82 N Na- . n .0 IO 5/2‘ 00 .00 IR “N .N go it 0.. o.- 5:: £9 .- FUD VI .n N:- fit 00 .N ER ‘II Ill 00 CN ON "N o'— .- - N —0 gm “0 3 '- O" .N ‘8 '58 NI! "'3 IO Oil C/IS NO on 53 IO OHS 3/23 IO 6]“ IO 6]?! 2II.O IIS I IO 3‘ 6/2’ 7/6 0° IO "U O I70 0 O O 0 I7! II II I" 73 5 HS 61.5 27.2 IO III) 9’ IO “I I02 IO "20 00 II as '72 IO 7]?!) 88 IN ”‘3 IO 7/27 06 ER 102 O I74 0 IO O O 770 I” IO "27 Plant hour-nu fr. "at fl I u 6.11 m. In "72 hole Al. Plant noun-nu "on Plot 0! 7 at all Lu. 1» I972. Table A7. Loaf LOW"! (L) and men (I) (-.) L001 Length (L) 004 mu- (I) (-.) 'Iont l 'L_T If! Loaf g 1 3 8 Length 5cm O. ‘N "a 20 SI" .0 .— 3: gm 20 SH! on “N no 0 .— O. .— IO 5/26 5/ 26 Oil “‘9‘ MN .- C .— O. . . .— 88 .. no. 83 .— .0 On O/I I” I2 no 15 I0 .5 LI mm .H n H .- IS 2.! ll I7) "J 2.3 '7 29 IO ; 169.! 577 Q 70.. I5 II Oil! "'8 IO ‘12) C. "0 I27 6123 IO 612’ 192 ’.I 20 I0.0 .I I27 I2 7” 27 U” N C I2I.S 52.5 IO 7/6 ”O I. “.0 I. I2) ’.O IO ‘5‘ I2! IO ”I! IO ”I! III 726 .2 IO "20 2I§ O O O HO II 7” ’3 "'5 "IO ”27 £9 ”22 mu no. "on mu "- !lu I 1 u an uh 1» 1972. 1.10 A! . "It mu 9!. nu fl 9 I! an uh 1- 1972 L007 L010 (L) and “in (I) (-.) Lou mm (L) a: mu (I) (1..) 7 T—T I f PLO. z 2 T "on: Santa-«h '1 on: i O MTLT'l—LT 0|!- L00.“ 3“?! 0.0. 2.0 N. C'- 2“ ‘9 O.- N a. ‘— 19 $110 100 4.0 0 1.0 .0 II 14 17 $710 $720 0’ new N no .N §3 ON .0- g: h N 10 512‘ .O .0— in: .. Na- 10 ‘71 fl. .- n “C .N 3:: .H .— 6/1 o" 16.4 NN .H gs: gs: O. O!- 3: 33 K. 33' 10 ‘10 g“ ._N on a PO g? H“ 28 N «nu» 88 .. NO 83 "a 6/15 210 10.1 1) .6 13.0 17‘ 12.4 101 10.0 1.5 14 .0 1! 1.1 1.2 1‘ 10.1 1.0 1 15 5‘0 100 10 6/15 'aun 83 .. F. ON H. ON ,— 6/23 230 10.5 .0 21 .S 20 210 10.7 C . I‘N Ul‘ 6/20 210 2 2.1 11.0 .7 0.0 N. 00- 10.5 1 . 250 21 O. “N 16‘ 1 . 31 10 7/13 9.7 .5 129 24 I16 70 10 7/6 107 27 0 .S 210 I! 10 7/20 10) 0 0 0 g: 10 7/13 0 181 0 31 22 203 10 7/27 . N lIa 7720 89 DO 103 12 735 72 7127 Yale ‘12- "out mun-nu 9n- Mot M 3 It Gull Lot. in 1972. Plant mun-nu fro- !Iot 0| 2 at 6011 Lake In 1972. 10010A11. Lou mm (L) and mm M (u.) Lu! Lunch (L) M I160: (I) (-J If: L009 2 J Plant Scar! Length 00!. 0 7 Date — a. _p 5/10 53 5110 O. '5' 10 5/2‘ 0.0 8o caca 6.. ‘ N 10 572‘ .N .-— g: 5. RN 3: r~ou 1..J N CU! '— g3? NH .61 N O — .0 RN .- n .- vs N N .— 10 611 .0 an N C a— u—. .N h '0 p- O. o.- .N p- i! K— “‘3 10 6’0 169 102 20 9.0 2.6 "N 6/15 .N NN '- Q .- “ll g: .H oi.- N a— “‘3 10 ‘12) 210 0 100 10 0 I! .l 15! 11.0 257 10.2 2) 27 7/6 7/13 ”‘8 10 7/1) 0 255 0 0 0 0 102 0 202 12.0 0 2‘ 0 100 12.0 10 033 $0 7/20 120 01 C73 116 10 7/20 10 7/27 10 7/27 1.10 A14. "an: numu fl. mu 0 S at In" Lalo ‘- 1972 rm. Al). "on: “ma 9v. rm on 4 at am an in 1972. J. E 5 ' s 5 3 i ‘ 3 17 _r 1%! L557 2 3 I 5 U P1ant a San Lunatic Dita 2 3 4 T—T'rTT—T Lu! 1 '10»! In San Long“ 00:. 5.2 .5 74 10 Q C. N0- 3! 5/10 74 5.2 .4 10 .- .’ ~P 3:0 20 5/10 on .N gs PO ON 33 U804 H— :3 £3 “a 10 5/1 C. ‘— gm 5:: Nut! on 5/25 a-H pi!» N 0 — 0.. .N SR .— pN 0'" .Q RN .0 .— “N :5.- N 10 5/1 5.0 O. .i.$ g: 'N an '- 'N .H CO KN ('9 N '58 .— Fl. £3 10 5/15 ”N “c- 10 5/8 10 5/23 10 5/15 10 5/29 D— uJoJ 150 45 2 4 10. 1. 207 25 242 11.0 20 10.0 3.2 20 2.1 12.3 250 1 2 4 150 34 §§ Q. N 10 5723 0° 10 7/5 00 10 5/29 232 0 174 0 0 21 0 21 0 243 12.0 43 10 7/13 0 0 125 0 ‘. N N “‘8 10 7/5 0 151 0 159 7/20 193 0 0 10 7/13 15 139 7 110 0 175 15 243 77 59 707 10 7/27 173 15 0 29 0 220 224 0 0 10 7/20 90 0 0 18 223 23 10 7/27 table A16. Plant mun-nu 1m plot (I 7 It Gull Lalo 1a 1972. Table AIS. Plant chur-mu from Not 0| 6 It 6011 Ln. 1» 197? L047 Lonqth (L) and l1dth (I) (II.) Lu! Length (L) and mom (I) (-.) Lee! 2 V H E i I U Scan Length L Plant T 3 8 19 5/15 5.2 .C N— C N O p— 20 5/18 5.0 2.4 122 35 10 5/1 125 35 217 54 V. .0 10 5/1 10 5/0 10 5/5 9.0 0 152 0 0‘ .N v NO ON g3 film 8 N .N C. N N '- §8 23. 15. 10 5/15 00 ON n I‘ .. ON 10 5/15 10 5/23 192 0 0 9.7 5.8. m— 8:: *3 10 5729 0" ~-- 147 1 10 . 510 99 4.2 10 5/29 32 0‘ “u- h ¢ —~ 1 19 12.0 242 13.0 241 1.4 1.0 141 15 133 530 107 10 7/5 10 7/5 212 0 0 0 11.9 242 37 12.0 234 13 15 1.4 155 19 755 105 31.7 23.2 Y 50 10 7/13 3 33 7/13 0 212 23 0 0 227 35 254 15 14.0 247 0 751 120 10 7/20 10 7/20 154 0 37 0 505 45 10 7/27 10 7/27 1051. A18. "an: nun-«Ls "a p1oL G 9 at 5011 Late in 1972. 1.51. A17. "an: mun-Ms 9m plot (II a u Gull Lake in 1972. Lu! Longth (L) and um» (H) (-.) L557 ngth (L) and 818th (I) (-.) O .— g :54 -§ _ 3.4 I 3 0m 3' 19 5/18 2.0 ”N "N ”‘8 19 5/18 10 5/25 .64 ‘0- Ina 10 5/1 5.0 .8 129 25 7.8 1.3 175 9.5 157 27 1. 21 9.4 1.0 145 23 228 24 no Ou— .— In 50 10 5/1 mm KN In. ‘— 33 O 10 5/8 177 9.0 .4 0 9.8 171 22 8.2 3.2 10 5/8 275 2.7 51 7.9 178 57 503 143 F0 10 5/15 00 171 1 3.0 52 12.1 10 5/23 0" ON ON 598 107 128.8 115.4 7 SO 10 5/23 Ou- 144 9.0 111 15 .5 29 1. 3.3 12.8 225 134 10.8 37 539 158 10 5/29 178 37 570 144 75.5 45.9 10 5/29 00 10.0 138 1.0 27 1.4 11.3 183 12.5 213 1.8 20 2.0 11.3 224 138 31 593 55 10 7/5 OO 10 7/5 0 174 0 0 0 14 25 .9 9.8 201 582 135 98 17 an N— 10 7/13 0 0 0 0 208 39 257 31 to clap .— 11.1 277 12 1.5 15 15 278 12.5 20 159 892 4.5 131 33.9 2 10 7/13 0 140 0 0 0 0 44 10.0 182 0 11.5 205 .5 35 35 817 120 121 33 .8 5.2 10.2 10 Y 50 7/20 0 14 0 215 .5 5 5 9 11 32 1 $8 10 7/20 91 112 0 235 0 173 0 159 15 0 27 0 33 0 38 734 50 10 7/27 00 134 0 0 177 0 28 197 29 10 7/27 Tab): A20. PIant nonsurtnunts from plot 0L 2 at Gu11 Lake in 1972. Table A19. Plant Ilasurcnnnts from plot 0L 1 at Gull Lot. in 1972. Leaf Length (L) and Hidth (8) (na.) Loaf Length (L) and 918th (H) (In.) Leaf P1anL 10 T T f f V T H Date n Scars Length ‘L 17’ 2 To Lu! 91in! Scars Length L Date 195 53 115 4.5 35 2.2 248 57 10 5/8 37 212 58 5/8 10 5/15. OK O'- n O .— 7 13.2 50 12.7 10 5/15 KO ”N g: 0‘ ON 73 2.5 15.5 315 2.5 11.8 253 248 50 508 119 10 5/23 251 83 545 150 42.5 35.1 10 5/23 24 15.4 323 59 200 41 715 324 178 775 88 32.0 23.0 7' $0 10 5/29 35 35 315 13.0 291 2.7 '2 U‘ 239 12 70 1 794 73 45.5 28.2 i 50 10 5/29 9.0 .8 RN CN n . 1 20 2.5 17.4 309 43 47.0 37.2 i' 50 10 775 °— .— 245 22 19 15.9 302 2.2 854 194 55 39 2.0 45 4 22.0 'x' 50 10 7/13 11 7/13 238 14 7.5 .5 158 82 972 113 25.1 18.5 "‘53 10 7/20 180 49 1031 137 -. :59» ~— 10 i 50 22.3 17.2 7/20 14.2 33 2.3 135 782 112 ON 00 .— 10 7/27 215 22 3.0 8 1 12 150 15.2 303 14.7 271 15 .8 15 1. 847 55 10 i so 7/27 la51a A22. Plant leasurelants frul plot 0L 4 at 5011 Late 1n 1972. table A21. Plant measure-ents free plot 0L 3 at 6011 Lake In 1972. Leef Length (L) end 814th (I) (II.) Leaf Length (L) and 111dth (ll) (-.) To eaf Plant Scars Length Leaf Plant To Scars Length Date 8 1 Date ON '9!- '— . 5/8 ND Q'- Is In .— a." UN 5/8 333 177 58 51 0.9 7 ”‘8 10 5/15 00 ON 192 2.3 72 10.8 233 11.4 0 27 "C ION 155 70 254 75 371 50 10 5/15 258 32 475 71 0” on N Y 50 1 10 5/23 11.7 254 1 74 2.3 37 2.7 554 134 10 5/23 4'9 10 5/29 00 251 14 8.3 2.4 275 29 KG 0 0'- e 19 9.2 293 12.7 275 42 2.4 1.5 11.5 275 7.2 321 170 53 823 84 10 5/29 10 7/5 151 55 2.5 22 2.3 17 870 77 7" 5. Ne— 10 7/5 20. 755 158 15.5 14. 48 43 i 10 7/13 10 7/13 222 57 984 82 10 7/20 1 31 1. 15.2 253 1023 184 12.0 313 12.5 251 125 54 1. 32 14.8 287 3.0 2 2 lo 1' 50 7/20 0° 00 12.0 242 0 1.5 35 0 15 0 15 1. 157 14 10 7/27 92 Table A24. Plant leaSurenents fro. plot 0L 5 at Gull Lake (n 1972. Table A23. Plant measurements fral plot 0L 5 at Gull Lake in l972. Leaf Length (L) and 818th (H) (en.) Leaf Length (L) and width (9) (ll.) 2 ‘U ’L" 11 Leaf Plant To Scars Length L 2 ‘l—T Plant To Date 2 Leaf Scars Length Date Ne— .— N N 10 5/8 00 can 523 ON ON '— O .— Ne- OF. 10.5 2.0 45 320 215 55 10 5/15 10 5/15 10 5/23 5/23 v-N “N .— h N an UN 88 N " “II— M 88 N. 0‘ 10 5/29 MAB ”N N O Na— 2 .9 297 14.8 11 . Ga- 10 6.4 540 225 9.0 277 19.3 144 85 2.2 77 5/29 10 7/5 5.5 .5 253 11.9 237 8.7 142 2.5 25 2.3 22 2.1 22 5 2 195 15. u 24 5 7 10 7/5 0° 11 252 22 13.8 317 1.5 38 184 51 15.5 825 171 9.1 102 i' 50 10 7/13 10 7/13 0 203 0 0 0 0 259 12 11.4 1. 1039 123 10.3 7.0 9.5 10.4 7 $0 10 7/20 00 4 292 0 278 250 .8 22 0 12 0 279 13. 3 45 1 1. 225 18.8 22 158 14. 48 831 183 1020 153 10 7/20 147 1092 195 10? 50 7/27 1.5 .4 11.3 1x3 11 7/27 Table 425. Plant manhunt: fru Plot a. a at Gull Lake In 1972 table A25. Plant eeesumnte free plot (I. 1 at Gull Lake 1n 1972. Leaf Length (L) and 918th (I) (ll.) Leaf Len th L and Uldth I II. Scars Length L Date Scars Length 05%. 40. °— '- M O I". N NO on (us 10 5/8 7.0 0 152 0 ”h .— Ills: 10 5/8 384 207 39 53 18.4 .4 12 10 5/15 10 5/15 10 5/23 NU" Or- 10 5/23 0114 Me- "I 10 N N. o'- 714 132 i' l7.6 0 13.2 10 5/29 10 5/29 12.8 257 30 N— .e— '- 253 28 1O 7/5 0 0 255 0 7 15.5 79 54 4. 797 23.5 19.5 10 7/5 331 18 10 8.3 794 215 5. 10.3 85 37 3.1 7/13 14.0 12. 230 . 5 259 10 7/13 241 17 319 151 0 3 0 885 181 10 7/20 00 OO 10 7/20 93 252 14.0 15.5 1 15 195 15.2 59 34 2.1 975 2.7 10.5 1 10 7 50 7/27 10 i so 7/27 1.51. A28. Plant measurements fro. Plot 00 at Gull Late in l972. lable A27. Plant Ieesureeents from Plot 0L 9 at Gull Lake in 197?. Leaf Length L) and Hldth (H) (II.) Leaf Length (L) and 1mm: (11) ('1.) 2 3 ’r—TT—fi 19.2 La; L Plant Length Scars Date 192 Leaf 8 Plant Length L Scars Date 7 3 7.8 42 9 231 231 42 335.4 184.8 i 50 10 5/9 ”0- ON 102 55 233 39 10 5/8 8.0 .8 143 21 253 50 447.4 203.0 i 50 501.0 10 5/15 10 5/15 00 G!- O 9.0 155 23 NM Oe- ,— 1 N 1 00 P'- '- 20 121 9.7 2. 283 75 275.5 72 14 I SO 10 5/25 10 5/23 00 10 5/29 RE Re- 32 N 0. ON 10 5/29 8.0 0 155 44 GO ON .— 132 17 .9 9.3 9.7 3 IO 2 231.3 77.4 f SD 7/5 0° 10 7/5 10.0 159 0 19 0 0 0 174 .9 5.0 174 21 O'- 25 82 35 330 107 50 2.5 35.5 1 10 7/13 00 10 7/13 117 138 0 52 0 27 5.0 313 114 10 7/20 251 33 0 0 12.0 283 27 0 0 175 34 1055 118 10 7/20 10 7/27 00 §° 281 0 0119 m.— 1 1 8 10 2.5 1025 181 15.8 9.4 101 28 1. 7/27 94 7...; S 53.. 2. 3. 52.3 :3 .~50— e. 01.4 ——:u a. _o “0.; lug. nae-Ilsaueae ace—s .cn¢ o—a-h 0 an o o~ MN v~ so am 0 on— o 05— vo~ m- 000 h c— n~x~ o - 0 MN 0 ON ON a. on on o «n— 6 amp 0 ca— oo~ o—— —o~ u o— o~\~ o m o m~ a. o— as am o mo— 0 ——~ new w—— moo u c. npxn o o 0 —~ 0 an —v an on am 0 mam o vo— o m—~ o—~ mn— —vo M O— exn o cw 0 on. o - n~ Q— on an 0 amp 0 new a «on ao~ ~N— non m o— o~xo - a. on —.— s— o— o~ «a on .a mop o.o— FQ— n.0, mam o—N ON— com m o— o~xo — um m.— sn v.— an - s~ 00 on .u so— ~.a pop 0.0 no— n—N amp «no u o— o—xo w an —.~ on ~.p n~ ~n on no an a pup o.o om— —.~ asp asp asp n—n h o. axe u . 8 L g H u w 59.3 c 33 » uco.‘ a w 0 up on c on o oo— 9 so —nm 0 M op n~x~ o - o «N c n~ o vN .2, c on 0 cm. o «up 0 «mp 0 mo— vnm o m o— o~xs o o o w— 0 ~— 9 v. o - mm c on 0 so— o 95— o a“. c ——m o o~— mom 0 m o— npxs o a o F. Q. —N c.— - on o.oo— on o ~n- a Nm— 0.0 wo— n.m —o— ——n o.n~v m o— 0\~ o N— o o. o _— a. ¢~ o.~ av 00 a on o Nm— 0 Km. 0 amp s.—— vow — —— opp ohm o h o— o~xo o n~ n.— o— n.— m— n.— v~ n.~ ~n cc n.oo~ on a po— o.o o¢p ~.—— 00— —.~— ~o~ o.~_ pp— one m.nco M o— owxo m. _ Q. —N v.— o. m.— cu v.— o~ pm ~.vn an m.o ov— n.a sop 0.0— mop —.—— oo— v.~— —o— cum o.—vn m. o. o—xo ~.— —~ v.— o~ a. _— o.p en —.~ on ~v ~.—n_ an ~.o Pm— n.~ no— ~.o om— n.o sm— «.0 amp «ow o.~o~ h o_ axe .;w 4 (a. tux x 4 aw 4 1 4 sauce; nL-uw c cage 0 v n ~ 8.04 «Mp ace—s fl. 2: 53.. v... 3. 59.3 23 E. 5 2.... :3 u. 8 S: 8: 3.823.... :3: .02 .3: APPENDIX B AVERAGE FEEDING SCARS PER STEM IN 1972 GULL LAKE PLOTS BY DATE 95 Tab1e 81. Average feeding scars per stem in 1972 GU11 Lake p1ots by date. 1972 P1ot 5/18 5/26 6/01 6/08 6/15 6/23 6/29 7/06 7/13 7/20 7/27 OE 1 2.5 ' 9.8 33.2 66.9 ‘145.0 419.8 213.9 284.2 68.0 .0 . .0 DE 2 .0 10.6 44.0 107.0 161.4 293.5 129.5 221.8 41.0 .0 .0 OE 3 2.8 13.0 19.6 12.4 14.5 13.0 5.0 5.3 5.3 .0 .0 GE 4 4.3 14.1 40.4 60.7 233.4 361.8 145.1 201.2 77.2 .0 .0 DE 5 5.3 13.7 11.2 47.5 224.3 300.2 211.8 120.2 61.5 .0 .0 E 6 4.5 14.4 7.8 19.6 11.0 8.4 3.5 5.7 6.5 .0 .0 DE 7 2.8 19.8 41.0 94.4 121.4 263.0 158.2 69.6 .0 .0 .0 DE 8 3.9 12.8 10.9 189.5 156.8 387.6 132.3 121.5 .0 .0 .0 CE 9 3.4 14.5 15.2 17 9 22.2 12.5 5.5 4.7 .7 .0 .0 0M 1 1.8 7.7 16.4 50.7 88.2 128.8 54.0 23.0 19.2 .0 0M 2 1.8 13.2 29.6 55.4 146.1 288.8 108.8 81.6 .0 .0 0H 3 1.8 5.0 21.6 8.7 6.2 10.0 7.1 17.9 .0 .0 0M 4 1.3 9.2 19.2 29.6 35.2 85.8 90 0 29.6 24.5 .0 .0 0M 5 1.3 10.6 23.6 95.7 134.4 49 1 38.5 41.8 .0 .0 0M 6 1.3 14.4 11.3 8.4 12.0 14.2 6.2 10.5 4.5 .0 0H 7 3.3 14.7 27.4 21.7 31.4 30.5 19.6 31.7 4.0 .0 0M 8 3.3 11.8 25.0 25.1 '128.8 75.5 68.7 33.9 18.9 .0 01 9 3.3 10.2 19.3 9.1 3.3 6.7 8.6 21.9 6.2 .0 0L 1 9.6 13.2 45.5 46.6 57.8 22.1 20.1 22.3 0L 2 9.3 35.7 61.1 32.0 47.0 46.4 25.1 10.0 0L 3 4.2 9.0 4.8 1.1 20.7 6.6 3.0 5.0 0L 4 4.8 10.9 26.6 9.3 34.9 20.1 12.5 15.6 0L 5 5.6 54.3 139.3 14.9 55.7 30.2 30.8 12.5 0L 6 2.9 4.0 5.2 5.6 16.8 16.5 10.3 9.6 0L 7 7.0 14.7 16.1 8.9 23.5 36.5 8.7 16.2 0L 8 9.2 18.4 54.1 12.6 96.7 18.3 .0 12.7 0L 9 2.9 6.0 6.2 3.5 21.3 10.5 1.6 12.6 OI 140.7 508.7 555.7 .0 551.1 .0 .0 .0 ON - 262.8 341.4 643.5 0 423.0 .0 .0 .0 00 336.4 447.4 501.0 0 231.3 12.5 .0 5.1 96 APPENDIX C NET SURFACE AREA PER STEM IN 1972 GULL LAKE PLOTS BY DATE 97 Tab1e C1. Net surface area (cmz) stem in P10t 061 052 063 054 065 0E6 057 osa 0E9 o61 onz on: 064 ons 0H6 0H7 0H8 0H9 0L1 0L2 013 014 015 ‘oL6 0L7 0L6 0L9. or ON on 1972 Gu11 Lake p1ots by date. Date (month, day, year) 5187? 52672 60172 60672 61572 62372 62972 70672 71372 72072 72772 13.66 35.9. 43.45 5.,28 “5.“0 44.24 25.23 14.36 0.00 ,o.00 0.00. 0.00 31.73 43.11 60.67 52.52 47.10 34.25 14.78 0.00 0.00 0.00 12.14 30.06 37.46 51.55 50.20 54.56 32.53 21.43 0.00 0.00 0.00 16.41 31.26 45.46 63.45 77.49 59.69 “5-53 15~59 0'00 “-00 0°00 11.64 24.53 40.16 61.66 46.44 “3-60 3“-5“ 17-50 “-00 “-00 “-00 12.22 32.71 39.96 50.27 46.93 “7-87 39°50 35°19 2'“9 “-0" 01°“ 13.35 30.10 35.44 56.90 56.47 52.02 35.74 21.55 0.00 0.00 0.00 12.07 33.21 37.66 56.21 51.45 36.67 55.16 12.76 2.00 0.00 0.00 15.47 37.65 36.77 .63.94 57.02 52.61 46.64 4.01 3.43 0.00 0.00 5.91 20.73 25.06 35.31 72.42 83.32 33-8“ “5'13 23-0“ “-00 5.91 15.26 27.37 42.33 64.46 75-43 37-37 “-55 “-00 0°00 5.91 12.36 23.16 35.49 56.12 71.35 13.36 21.89 2.62 0.00 5.62 14.53 24.62 41.53 53.72 75.02 44.61 33.47 2.59 0.00 0.00 5.62 25.22 38.66 65.90 54.73 51.49 48.33 12.11 0.00 0.00 5.62 26.25 36,09 51.30 97.51 53.91 56.71 22.06 10.16 0.00 6.10 30.59 35.50 57.55 67.26 56.62 “7.52 22.15 3.10 0.00 6.10 25.77 37.87 66.08 70.10 65.74 52.53 14.64 .50 0.00 6.10 17.14 30.28 35.03 58.33 36.02 30.46 17.25 6.63 0.00 21.08 51.76 70.52 115.67 92.69 62.96 57.25 21.65 27.93 46.99 74.31. 120.65 102.38 '86.23 59.05 7.85 20.91 53.03 53.00 77.60 62.44. 59.46 46.65 23.32 22.59 “2.21 53.91 70.97 63.16 51.36 0.00 7.15 22.01 59.58 73.25 69.36 66.45 69.16 21.99 24.06 15.70 “2.51 50.99 66.43 101.26 61.49 17.31 10.12 21.19 46.76 57.90 54.52 66.07 66.66 47.64 26.33 34.53 55.07 77.15 86.58 40.97 65.48 0.00 18.27 22.96 51;q3 53.13 72.51 93.62 71.02 0.00 14.95 1.2.70 55.23 43.69 1.45 5.71 0.00 0.00 0.00 39.57 42.74 40.61 19.63 16.31 0.00 ‘0.00 0.00 32.43 31.53 17.14 5.06 9.99 13.69 .74 9.46 98 APPENDIX 0 LIFE EXPECTANCY OF LEAVES IN DEGREE-DAYS ABOVE 42°F 99 0.000. 0.5505 0.H005 0.500 0.050 5.000 0.000 0.000 0.505 .0 0.000 5.0005 0.00HH 0.050 0.000 0.0005 0.000 0.000 0.055 H010 0.000 0.050 0.0505 0.0005 5.000 5.000 H.000 5.500 0.000 H 00— 5.050 0.000 0.000 0.050 0.000 0.550 0.050 0.000 0.000 m 005 0.0005 0.000 0.0005 0.000 0.000 0.000 0.050 5.500 0.000 0 00H 0.000 0.005 5.000 0.0005 5.000 0.000 5.050 0.000 0.000 H 00 5.005 0.050 5.500 H.000 0.005 0.000 0.000 0.000 0.050 m 00 0.000 0.0005 0.5555 0.0005 0.000 0.000 0.000 0.000 0.500 0 00 0.500 0.005 0.000 0.000H 0.0005 0.0005 0.000 0.000 0.500 H 0 0.000 0.0055 0.0505 0.000H 5.5555 5.000 0.000 0.500 0 0 0.000 0.000 0.5005 0.005H 0.0005 0.505 0.000 5.000 0.500 0 0 0.005 0.H00 0.055 0.055 0.000 0.005 0.055 0.005 0.050 2 00H 0.000 0.000 0.055 0.000 0.000 0.000 5.005 0.000 2 00 0.050 0.005 0.005 0.500 0.000 0.050 0.000 0.505 5.000 2 0 0.005 0.000 0.000 0.000 0.500 0.000 5.000 5.505 0.000 2 005 0.00H 5.000 0.500 0.000 5.000 0.000 0.500 0.500 0.000 2 00 5.000 0.000 5.000 0.500 0.000 0.050 5.500 0.000 0.000 2 0 5.500 5.005 5.005 5.005 0.050 5.005 5.055 0.000 H.050 0010 0.5055 H.5omH 0.000H 0.0005 5.000 5.000 0.000 0.000 0.0H0 00 0.500 0w0005 0.000 0.005 0.0H0 0.000 0.505 0.000 00 - 0 0 5 0 0 0 0 0 5 05050 mmmHu 0060 .0000 m>onm m500-mmg0m0 =5 mm>mmH 50 0ucmuumaxm 0550 .H0 05005 100 APPENDIX E THE TIME SPENT IN LEAF CLASSES ESTIMATED FROM LEAF LONGEVITY DATA (TIME IN °D>42°F) 101 000 000 005 005 005 555 000 005 505 0 000 500 550 500 000 500 500 500 005 H0-0 0005 055 050 005 00 005 050 000 000 H005 0005 005 005 005 500 055 000 000 000 0005 0005 000 000 005 000 000 000 000 000 0005 000 000 005 005 000 050 050 000 000 H00 000 500 005 055 005 500 550 000 000 000 500 005 000 005 000 H05 000 0005 0005 000 500 000 000 050 500 500 0055 HO0H H0 0005 000 005 000 000 050 055— 000 00 000 050 050 000 000 000 000 005 000 00 500 005 000 500 005 000 000 000 5055 2005 000 505 050 000 500 000 500 H00— :00 000 000 H05 000 055 05H 500 000 0005 :0 000 005 000 000 000 050 000 505 5005 200— 005 005 050 505 005 050 5H0 0505 000 200 0005 000 000 500 H05 050 000 550 000 20 005 050 005 005 000 000 000 500 0505 . 00-0 050 000 555 005 500 050 005 005 505 005 00 000 005 005 005 000 000 005 000 00 05 0 0 5 0 0 0 0 0 5 05050 00050 5000 .50000A00 :5 05500 0000 005>m0cop 5005 5000 umpmswumm mammoHu 5005 :5 unwam mew» 000 .50 05000 102 APPENDIX F STEM AND HEAD DENSITIES FROM GULL LAKE PLOTS 103 Tab1e F1. Stem and head density measurements from 0011 Lake in 1972. (Stems/2 1inear row foot) (n = 1, except for 8/9 (2 t SE (n))) Stems Heads PLOT 5/12 5/25 6/16 6/29 7/11' 7/16 8/9 “1§G¥“ GE 1 3s 27 22 20 20 23.95? 1.16é20) 23.OO$1.22 2 GE 2 27 34 29 24 22 23 22.71; 1.60 7) 22.43;1.43 CE 3 43 24 25 26 25 27.70¥ .92(2O) 22.40; .93 DE 4 46 , 3O 24 29 25 22.10- .76(2O) 21.85; .77 GE 5 26 43 27 23 27 26 26.00: 1 64(10) 25.70.1 63 GE 6 31 22 22 25 22 24.2Of 1.13(2O) 23 60$1 08( DE 7 55 21 20 27 21 22.65; .89(20) 22 20; 85( DE 6 24 36 20 29 25 25 27.20; 2 56(10) 27 1O-2 44( GE 9 44 29 24 27 26 29.80- 1 49(20) 29 5551 44( OM 1 25 54 47 37 39 33.75; .91(20) 33 45; .88(2 OM 2 20 16 26 43 30 40 24.00- 2.94( 7) 23 57-2.89( 7 gm 2 3O 41 35 4O 42 36.55; 1.03(2O) 36 05$ .96(2O 15 56 36 45 39 34.50- 1.16(2O) 34 25-1.16(20 OM 5 14 30 46 42 4O 45 32.66t 3.61( 7) 32 43:3 72 OM 6 20 46 31 42 45 33.25f 1.37(20) 33 1531.35(2 OM 7 34 44 52 45 4O 36.15f 1 29(20) 35 4Oi1.3O(2 OM 6 13 26 46 39 4O 42 39.14; 4.66( 7) 36 71i4.46( OM 9 13 44 26 46 43 30.60- 1.61(2O) 3O 4511.79(2 0L 1 26 31 35 15 22.401 1.73(1O) 21 80:1 55(1 OL 2 23 33 20 19 16.33f 3.19( 6) 16 00:3 02( CL 3 36 29 15 20 21.203 1.41(1o) 20 90-1 31(1 0L 4 23 25 20 15 16.40; 1 56(10) 16 3031 49(1 0L 5 29 33 17 15 13.50- 1.62( 6) 13 17-1.60( 6 0L 6 3O 27 20 17 19 40} 2.66 10 19 90t2 56 0L 7 26 57 16 22 23 30- 2.94 10 22 90:2 77 CL 6 36 41 20 19 37 00: 5.46( 6) 35 67i4 39 CL 9 39 46 20 20 23 00f 2.70( 6) 23 001 70 104 105 Tab1e F2. Stem and head densities from field 5-53 G011 Lake in 1972 (Stems/2 1inear foot). (n = 1), except for 8/9 (i -SE(n)) P1ot 5/12 5/19 6/12 6/19 6/27 7/10 7/17 8/9 Stems 101 13. 12. 32. 33. 21. 33. 30. 24.6512.OO(2O) 102 14. 19. 36. 26. 27. 27. 25. 21.6531.25(2O) 103 16. 22. 37. 25. 26. 22. 23. 20.4031.66(2O) 201 24. 19. 34. 26. 26. 20. 21. 20.6O;1.15(2O) 202 16. 20. 41. 31. 22. 26. 25. 26 45-1.99(2O) 203 16. 20. 35. 27. 19. 24. 25. 21.3511.74(2O) 301 13. 20. 26. 25. 21. 23. 26. 21.5511.52(2O) 302 11. 18. 31. 23. 20. 24. 25. 20.3511.02(2O) 303 12. 13. 26. 21. 24. 29. 30. 23.75i1.08(20) 401 17. 24. 33. 32. 24. 23. 23. 20.35: .67(20) 402 12. 19. 42. 30. 21. 24. 25. 19.10: .62(20) 403 16. 22. 4O. 31. 21. 22. 21. 21.6ot1.09(20) Heads 101 - - - 24.4ot1.61(20) 102 - - 21.4031.11(2O) 103 - 19.9031 56(20) 201 - - 20.6Of1.O9(2O) 202 - - - 26.0031.65(2O) 203 - - - 21.0031 69(20) 301 - - - 20.6511.35(2O) 302 - - - 19.65: .67(20) 303 - - - 23.5531.O1(2O) 401 - - - 20.00: .62(20) 402 - - - 16.95: .61(20) 403 - - 21.5031.02(2O) 106 5.056.66 6.6 56.56 6.6 06.66 6.666.60 6,606.66 6.0 06.6m 6.6 66.56 6.666.60 6,566.65 6.006.60 6.6 06.66 6.6 66.66 6.566.56 H.~6~.56 «.6 66550 5.6 66.56 6.066.65 6.066.55 6,600.06 6.5506.66 5.6 66.60 5.606.60 5.~06.mm 6.6 66.00 6.656N.66 6.666.- _.660.6, 6.506.56 6.5 06.66 6.5566.N6 5.656.66 6,650.06 6.006.60 6.0 66.56 6._~66.66 0.666.66 6.006.50 6.FHN.NN 5.5.06.06 6.6 66.66 6.606.66 6.606.60 6.066.66 N.N 06.66 5.6 00.56 6.606.60 6.506.60 6.606.50 F.m 06.66 6.6 06.66 6.600.66 «.m06.6m 6.006.00 m.6 06.66 6.6 06.66 5.606.66 6.000.65 5.606.66 5.6.06.56 6.0 06.0” 64656.5N ~466N.6~ 6.N60.66 0.6 66.60 6.oFHN.66 6.606.66 6.60N.6~ 6.006.00 6.6 06.66. 6.5 06.66 6.666.60 N 666.N~ 16.015 .0004 .0000 .0010 1.515 N6 A 66 ,, 50 .1. c .00 «.16 6560 6666 6064 _536 5626 6660 0.6264 ~\6sm66 6060 565562 6060 562062 6.... 565062 06060650H 0653060 0003600 06060500H 0653060 0003600 umpmmngH 0650060 0003600 665666666 005 005 00 00 005 005 005 00 00 00 0 H510 mgum\z 05050 .m65 .00 0500» ' 107 Tab1e F4. Stem and head densities fromGuil Lake field 8-10 in 1972 (STems/Z linear foot). (2 t SE (n)) Piot DATE 00 01 ON Stems 6/13 21.67;].7sé3g 28.00: .58 3) 30.0037.02(3) 6/20 20.33-].45 3 30.67;4.37 3) 25.00:1.53(3) 6/26 18.67ti.45(3) 21.33-].45(3) 20.67i1.76(3) 7/11 12.33$1.45(3) 23.00t2.08(3) 21.67i1.45(3) 7/18 13.33_ .88(3) 23.33: .88(3) 20.33: .88(3) 8/9 16.1of1.16(10) 25.5oti.31(10) 20.70: 1.01(10) Heads 8/9 13.7ot1.16(10) 23.2011.34(10) 26.30: .99(10) APPENDIX G WET AND DRY WEIGHT MEASUREMENTS FROM ALL PLOTS STUDIED 108 Table 61. Dry weight (gr)/2 linear foot (n = 1) taken from field 5-53 at Gull Lake in 1972. Date ‘ Plot 607 614 621 628 705 712 101 9.37 20.59 21.60 32.56 36.54 45.40 102 10.77 15.35 27.40 34.80 46.59 47.88 103 5.21 13.83 14.37 27.96 25.57 25.43 201 9.70 11.85 24.99 29.96 44.33- - 202 10.11 17.00 36.68 36.09 42.84 38.51 203 6.85 15.33 23.84 30.93 36.51 - 301 9.20 18.84 28.93 49.65 40.72 302 4.59 9.98 18.77 27.84 23.89 303 9.03 12.83 34.76 36.68 33.26 401 6.75 13.43 23.61 35.54 19.20 42.56 402 9.52 11.89 26.42 25.32 32.16 66.59 403 7.72 11.80 25.87 .57 46.88 30.72 109 110 06.605 00.060 60.060 60.000 55.060 00.055 06.00 60.06 66.0 00.6__ 600 06.66 66.600 05.66. 00.500 06.66 00.550 05.65 00.50 00.00 00.500 000 65.05 60.600 50.000 66.56 00.500 06.005 60.06 66.00 00.5 00.50 _00 60.66 60.665 00.005 05.000 00.665 00.600 56.05 00.50 06.6 06.005 606 66.00 00.000 06.655 05.66 00.050 00.500 60.06 06.00 05.00 0_.60 006 56.060 60.66 56.600 65.060 06.660 00.060 06.66 60.00 66.60 05.550 006 00.66 00.000 06.000 00.000 66.060 06.050 00.06 65.00 06.00 00.000 600 66.600 60.550 66.66_ 06.060 50.000 06.660 60.00 66.06 56.00 00.660 000 66.600 06.060 50.600 00.660 65.000 05.065 06.05 60.06 00.00 05.600 .00 56.600 06.060 06.060 66.60 60.600 05.00 56.06 00.00 06.00 00.06 605 66.600 06.06 06.00. 060.060 66.665 06.060 00.06 60.00 00.66 05.665 000 66.600 60.600 00.660 56.000 00.000 00.000 00.05 66.00 00.00 00.050 500 605 005 055 605 006 _06 506 066 006 006 0000 6000 0000 0600.: 02.000 006.063 003 .06 0300 .0560 00 0063 0000 06 66-6 05000 00000_ 0 00 111 Table (I1 Dry weight of stems (gr.) i (n)from water level plots at Gu11 Lake in 1972. Stem Weight by Date Plot 609 616 626 629 706 713 720 727 OD .23(20) 29(10) .45(lO) .55(10) .34(10) .45(10) .47(10) .25(ll) ON .27(20) .36(lO) .81(lO) .96(10) .93(lO) l.22(10) l.24(10) l.02(10) OI .28(20) 57(10) .86(10) 1.06(10) 1.51(10) l.25(10) l.87(10) 1.43(l0) Head Weight by Date Plot 609 616 626 629 706 713 720 727 OD .05(1) .16( 7) .O7( 7) .27( 7) .09( 7) ON .22(6) 24(10) .60(10) .66(10) OI 20(7) 27(10) .51(lO) .56(10) 1.07( 9) .58(10) 112 .om u c 6 .FN n c 6 .ON u 0 .00 u c n .m 0 00.0 00.0 00. P mN.F 00. MM. NN. F0. 0 mm. P om.0 mm. P No.0 on. we. wN. m_. m m0. 0 00.0 «M. 0 FM.F om. 0M. 0N. _p. 0 6mm. 0 0m. 0 mm.0 Nm. 0M. ON. no. 0 60M.N mm. 0 00.0 00.0 mm. 00. mN. op. m 6N_.P 0m. 0 mm.0 00.0 Fm. om. my. 000. 0 6mo.0 cm.p mo.p mm. 0M. 0N. NFF. M wN._ pm.0 M_.N mo.0 00. N0. m0. m—. N Nw.0 mm.0 FN.F 0N.— 0w. o0. MN. op. 0 00 00.0 mm.— 00.0 N¢.F N0. mm. 0m. 0N. NF. op. 0 mo.N um.N 0_.N mN.F no.0 00. 0M. MN. M0. 00. m mm.0 00.0 MN.— mm.0 ON.F N0. om. mN. 00. N 0M.N m0.” 0m.0 00.0 mo.— NN.P 00. M0. 0 0M._ ww.0 00.0 No.0 N_.F mo. 0 00. M0. 00. m mo.N mm.0 m5 0 00. 0 00.0 NN. 0 mm. NM. mo. 0 Fm.p Nwo.N o0. P 05 P 0Mm. 0 mm. 0N. M0. 00. M No.0 ww.~ m5 F no. 0 0w. 0mN.F ow. mN. 00. or. mo. N 00.0 no N no.N 00.0 Nm. 0mm. mm. MN. MP. 00. 0 20 No.0 om.N wo.N mN.N vo.N 0m.0 00. MN. mo. 0 N0.0 00.0 om._ mo.N NN.P Mo.0 mm. mm. 00. 000. w No.N mo.N mN.N ¢F.N m0.N 0m.0 0M._ mm. 6MN. 000. 0 No.0 Pm.N m¢.N ow.N 00.0 wv.p 00.0 ON. 00. 000. o M0.0 mo.N 00.0 ~05 F w0.0 _N.— M0. 00. :00. m mm.0 wo.N Nm.N NN. N MN.0 00.0 mm. on. mp. 0 mM.N mo.— NF.M MM. N mo.P om. 0MN. 000. M om.0 mm.0 00.N oo.N 00.0 00. 0 Fm. 600. :mo. N wM.P Po.N ¢¢.N NN.N mm.0 om. mo. 60N. 00. 0 mo 0N0 0N0 M00 000 0N0 MNo mFo moo Poo mNm w—m 0000 00 .5 6060 .0606: c603 0666x6 00 .NN00 00 60606 6060 0030 5600 62606 06 0.00v 000063 M00 .00 60060 113 Dry weight (gr.) (i(n)) of Heads from Gu11 Lake plots in 1972. Table GS. Date 713 623 629 Plot (((( (((( (((E(((( ((((((((( 000090000 111'] 111-II 558621606 890274120 .IIqI. all-l1] ((((((((( ((((((((( ((((((((( ((( (((((( 1'] .II (((((( 508782 555655 123456789 E 0 706881494 000790030 1|].ll 11.-11l- ))))))))) ((((((((( 1123456789 067806223 543344444 \l’ ) )) 9 7 09 1| ( ( (( 7 5 70 5 4 52 )))) ))) 21lr01l 40] (((( (U( 9104 300 2033 353 123456789 L O APPENDIX H NET WEIGHT. PLANT WEIGHT, STEM AND HEAD DENSITIES FROM THE 1973 AND 1974 PLOTS 114 Tab1e H1. Net weight of foliage at Gu11 Lake 1973 (grams/2 iinear foot) (1 sampie/piot/day). Lbs. of Water 5/22/73 6/04/73 6/15/73 6/28/73 51919- N/Acre Condition 8-11 Irrigated 10 28 61 229 Norma] . 1o 52 88 150 Drought 6 50 78 151 50 Irrigated 9 47 198 240 50 Norma] 7 86 177 187 50 Drought 6 61 119 206 100 Irrigated 7 94 187 250 100 Normal 5 112 155 267 100 Drought 8 67 146 294 115 116 Table H2. Plant height and stem density measurements of oats from. Collins Road 1973 (n= 10). Plant Height Stems/2 (cm) Linear Ft Field Date X SE X SE 4 5/24/73 12.28 1.871 5/31/73 8.20 0.72 19.20 3.46 6/11/73 17.70 0.81 40.30 4.052 6/12/73 29.80 1.60 7/02/73 76.60 2.18 36.10 2.93 7/13/73 93.80 1.75 41.50 3.16 7/18/73 98.30 1.53 41.70 3.62 7/26/73 92.50 3.39 31.40 5.33 7/29/73 99.50 1.75 32.00 3.823 7/29/73 25.30 3.97 15 5/29/73 6.65 0.67 15.20 2.23 6/11/73 20.70 1.28 54.90 6.852 6/12/73 30.70 2.73 7/02/73 85.00 1.11 38.10 3.73 7/13/73 102.30 0.38 35.10 2.70 7/18/73 101.30 2.17 36.00 4.15 7/26/73 103.30 1.71 45.40 3.86 7/29/73 104.10 1.27 44.70 2.553 7/29/73 33.20 2.58 n = 7 2 plant length from stem samples 3 head density Table H3. 117 Plant height and stem density data summary. Field 2, oats, 1974 Collins Road. Plant Height (cm) (n = 10) Stems/2 Linear Ft. Date X SE X SE May 24 7.85 0.17 21.10 3.36 June 5 —- -- 38.10 4.40 10 29.30 1.04 31.30 4.40 13 33.60 0.64 47.70 6.18 18 39.40 1.42 39.00 4.15 20 47.40 1.27 35.40 2.37 25 59.80 1.10 41.10 3.64 27 68.00 1.88 37.80 5.10 July 2 81.70 2.19 36.80 1.33 8 93.40 1.71 31.20 2.08 12 95.00 2.34 34.80 2.96 16 96.10 1.40 35.90 3.15 19 94.50 1.81 36.90 3.57 24 94.20 1.54 37.20 2.04 Aug. 1 94.29 1.98 32.00 2.94 1 32.88 9.50 Dry weight of foliage 1 28.31 9.13 Dry weight of heads 1 28.20 8.02 Head density 5 22.65 1.98 Head density (n = 20) APPENDIX I HEAD AND SEED WEIGHTS FROM ALL PLOTS STUDIED 118 Table 11. Head weights (Gr.) from Gu11 Lake in 1973. Oven Field Plant Tiller Dry 5-59 1 0 .25 2 0 .09 4 0 1.12 5 0 .46 6 0 .20 8 0 .48 9 0 .68 10 0 1.37 5-61 1 0 1.53 1 l .89 2 0 2.29 2 1 1.16 3 0 2.29 3 1 1.00 4 0 2.82 4 1 .34 5 0 2.59 5 1 .93 6 0 2.38 6 1 1.51 7 0 1.00 7 1 .61 7 2 .02 8 O 1.59 8 1 .60 9 O 1.66 9 l 2.99 10 0 1.92 10 1 .83 119 Table 11 (Cont'd.). Field Plant 120 Tiller O N O M 50 N 50 M 100 N -‘ mmm-h-hwwNNN-d-fl (TIN mam—- mmmmbbwwww—I—Ia—i N‘O-‘O—‘ON-‘O-‘O OOO wN-‘O-‘OWN—‘OWN-‘O OOOO Table 11 (cont'd.). Field Plant 121 Tiller 100 M mmbwww—I 0 I U'thNd 0 R mth—1 0 D U14>00N—‘ _J 50 I WM 50 R th—I' 50 0 01¢de dOON-‘OO 00000 0000 COO 00000 00000 00000 d 122 Tab1e Il (cont'd.). Field Plant Tiller Dry 100 I whoa—- u—lN—l . O C O O N 100 R _l O O N —l 100 D —-'N O I N on U'lN—‘ 00000 COO 0000 —l —l U"! 05 O \1 01¢de 123 Table 12. Head weights (Gr.) from Collins Road in 1973. Plant Tiller Oven Field Number Number Dry OOkDCDCDNOi-b-bNN—I ooo—aooo—ao—Joo N w —-J—‘ 124 Table 13. Leaf longevity, 1972: head weights (grams) from Gull Lake, f1e1d 5-53. Bag Head Seed Stem Tiller No. Head Ht. Seed Ht. No. Weight Height No. No. Leaves / Plant / Plant 1 1.00 .88 1 0 8 1.00 .88 2 1.13 .97 2 0 8 1.13 .97 3 .68 .60 3 0 8 .68 .60 4 1.11 .80 4 0 8 1.11 .80 5 .74 .61 5 0 8 .74 .61 6A .53 .51 6 2 5 68 1.30 1.09 6 O 8 1.83 1.60 7 1.30 1.11 7 0 8 1.30 1.11 8 1.62 1.34 8 0 8 1.62 1.34 10A .22 .23 10 1 6 108 1.17 1.06 10 0 8 1.39 1.29 125 Table I4. Head weights from Gu11 Lake and Collins Road in 1973. Number of Air Oven Field Heads Dry Dry OI 100 153.70 136.72 OR 100 191.01 169.12 OD 100 77.99 69.49 SDI 100 183.40 162.49 50R 100 170.49 151.90 50D 100 162.80 141.52 1001 100 150.91 133.82 100R 100 150.13 134.62 1000 100 174.53 154.85 ON 100 166.96 146.72 OM 100 136.22 120.00 SON 100 248.15 212.07 50M 100 178.38 148.77 lOON 100 203.61 179.29 100M 100 133.77 118.41 4 100 114.52 99.85 4 sprayed 100 109.67 95.69 15 100 137.29 119.93 126 Table 15. Head and seed weight (gr.) from leaf longevity data (Aug. 1), 1974 Collins Road. Plant Tiller Head Wt. Seed Ht. 1 0 1.00 .82 1 1 .68 .54 2 0 1.01 .85 2 2 .57 .52 3 0 1.73 1.54 3 1 1.04 .90 3 2 .62 .54 4 O 1.23 1.12 4 2 .76 .61 5 O 1.19 1.11 6 O 1.26 1.10 7 O 1.08 .91 7 l .74 .63 8 0 1.36 1.15 9 0 1.15 1.00 10 0 1.46 1.37 11 O .92 .73 11 1 .26 .20 12 0 .90 .71 12 l .58 49 13 0 .60 .50 14 O .50 .30 15 O 1 26 1.07 15 1 55 .45 15 2 50 .40 16 0 1.25 1.07 16 1 .43 .33 16 2 .63 50 17 0 1.03 87 17 1 .40 31 18 O .78 61 18 2 .42 34 19 0 1.19 1 06 20 O 1.36 1 20 20 1 .47 39 20 2 45 .38 21 -0 1 17 1.02 21 2 .60 53 22 0 .95 77 22 1 .76 67 127 Table 15 (cont'd.). Plant Tiller Head Ht. Seed Wt. 22 2 .59 . .50 23 0 .37 .32 24 0 .91 .79 25 O .58 .50 25 2 .32 .27 26 O 1.24 1.13 26 1 57 .49 26 2 48 .43 27 O 1.17 1.09 27 2 .36 30 28 0 1.00 .94 28 1 .52 .50 29 O .68 .52 29 2 .07 .04 30 O 1.17 1.01 30 1 .31 27 128 Table 16. Leaf longevity, 1972: head weights (grams) from Gu11 Lake, field 5-55. Bag Head Seed Plant Tiller No. No. Weight Height No. No. Leaves 10 1.16 .94 1 O 9 1A .35 .23 1 1 7 1B .08 .09 1 2 6 1C .02 .04 l 4 3 2 1.23 1.00 2 O 9 . 3A 1.10 .87 3 0 9 3B .38 .28 3 4 4 48 1.60 1.25 4 O 10 4A .82 .62 4 4 6 SE 1.53 1.20 5 0 9 5A .96 .84 5 1 6 6 1.57 1.27 6 0 9 78 .1.21 .92 7 0 9 8 1.65 1.29 8 O 9 98 1.71 1.30 9 0 9 9A .66 .58 9 2 6 108 2.24 1.78 10 O 9 10A .33 .11 10 l 6 129 Table 17. Summary of oat yield statistics from Gu11 Lake, 1972. Field No. Head Seed No. Heads Height Weight DE 1 100 1.34 1.17 DE 2 50 1.34 1.06 DE 3 100 1.50 1.25 DE 4 100 1.43 1.22 DE 5 54 1.17 1.02 DE 6 100 1.57 1.26 DE 7 100 1.41 1.20 DE 8 37 .98 .84 DE 9 100 1.26 1 01 OM 1 100 1.05 88 OM 2 55 .90 76 OM 3 100 1.16 92 OM 4 100 .97 .77 OM 5 28 1.02 .83 OM 6 100 1.14 .92 '0M 7 100 1.18 .88 OM 8 42 1.09 .79 OM 9 87 1.06 .87 0L 1 100 1.03 75 CL 2 23 .74 67 0L 3 100 .75 .49 0L 4 100 .79 57 0L 5 9 1.16 81 0L 6 100 .91 64 CL 7 100 .80 51 CL 8’ 30 1.07 81 101 100 1.45 1.25 102 100 1.40 1.21 103 100 1.20 .60 201 100 1.59 .84 202 100 1.57 1.29 203 100 1.12 1.00 301 100 1.64 1.41 302 100 1.36 .64 303 100 1.51 1.37 401 100 93 78 402 100 1 6O 1 35 403 100 . 1:56 1.31 130 Table I7 (cont'd.). Field No. Head Seed No. Heads Weight Height 5-53U 100 1.22 1.06 5-53S 100 1.45 1.19 5-55 100 1.51 1.20 5-63 100 1.69 1.34 8-10 OI 100 1.04 ‘ .85 8-10 ON 100 .85 .68 8-10 OD 100 .16 .08 8-10 100 1.22 .94 8-12 100 1.32 1.13 8-14 100 1.59 1.33 APPENDIX J KERNEL WEIGHTS FROM ALL PLOTS STUDIED 131 Tab1e J1. Kernel weights on August 14, 1972, at Gu11 Lake. 1000 No. of Kernel Kernel Field Plot Kernels Height (gr) Height (gr) 8-10 01 1000 22.73 22.73 ON 1000 23.20 23.20 OD 468 6.98 14.91 8-12 1000 27.99 27.99 8—14 1000 24.00 24.00 5—53 Sprayed 1000 26.62 26.62 5-53 Unsprayed 1000 25.28 25.28 5-55 1000 27.79 27.79 5—63 1000 28.60 28.60 DE 1 1000 25.29 25.29 DE 4 1000 25.28 25.28 OE 5 1000 24.28 24.28 DE 8 1000 24.18 24.18 OE 9 1000 23.95 23.95 OM 1 1000 24.49 24.49 OM 2 1000 24.82 24.82 OM 3 1000 24.32 24.32 OM 5 912 21.43 23.50 0M 6 1000 24.00 24.00 0M 7 1000 23.50 23.50 0L 1 1000 20.32 20.32 0L 2 771 13.77 17.86 0L 3 1000 16.70 16 70 0L 4 1000 20.02 20.02 0L 5 340 6.61 10.44 0L 7 1000 16.50 16.50 132 Table 02. Kernel weights from oat fields at Gu11 Lake in 1973. Ht. of 1000 Kernel Stem or No. of Kernels Height Date Field Plot Replicate Kernels (Grams) (Grams), 7—31 8-11 OI 1 23 .37 16.09 2 5 .04‘ 8.00 3 36 .80 22.22 4 9 .09 10.00 5 33 .86 26.06 SCI 1 20 .22 11.00 2 27 .51 18.89 5 16 .22 13.75 1001 1 12 .10 8.33 3 46 1.00 21.74 4 70 1.72 24.57 5 . 49 1.04 21.22 OR 1 4 .10 25.00 2 17 .52 30.59 3 31 .70 22.58 4 44 1.06 24.09 5 38 1.11 29.21 50R 1 20 .62 31.00 2 68 1.91 28.09 3 34 .89 26.18 4 35 .87 24.86 100R 1 82 1.55 18.90 2 72 1.41 19.58 5 49 1.04 21.22 00 1 27 .61 22.59 2 10 .27 27.00 3 14 .27 19.29 4 31 .61 19.68 5 26 .48 18.46 500 1 33 .82 24.85 2 33 .78 23.64 3 38 .95 25.00 4 22 .27 12.27 5 15 .19 12.67 Table 02 (cont'd.). 134 Ht. of 1000 Kernel Stem or No. of Kernels Weight Date Field Plot Replicate Kernels (Grams) (Grams) 7-31 8-11 1000 1 73 2.20 30.14 2 50 1.23 24.60 3 24 .42 17.50 4 51 1.42 27.84 5 5 .01 2.00 8- 1 9-17 OM 1A 12 .14 11.67 2A 1 .01 10.00 5A 74 1.64 22.16 50M 1A 20 .29 14.50 3A 7 .09 12.86 4A 70 1.05 15.00 5A 11 .21 19.09 100M 1A 34 .40 11.76 3A 24 .42 17.50 3B 7 .05 7.14 3C 54 1.15 21.30 4A 71 1.09 15.35 5A 42 .93 22.14 58 55 1.39 25.27 0N 1A 33 .69 20.91 18 81 2.02 24.94 2A 35 .88 25.14 28 37 .79 22.57 20 86 2.29 26.63 3A 6 .08 . 13.33 38 43 .90 20.93 4A 11 .10 9.09 4B 14 .20 14.29 5A 35 .63 18.00 5B 35 .77 22.00 5C 73 1.82 24.93 lOON 1A 18 .23 12.78 18 70 1.29 18.43 1C 35 .50 14.29 10 58 .83 14.31 - 3A 40 .81 20.25 3B 11 .11 10.00 30 33 .35 10.61 3D 39 .95 24.36 4A 10 .17 17.00 48 24 .52 21.67 135 Table J2 (cont’d.). Ht. of 1000 Kernels Stem or No. of Kernels Height Date Field Plot Replicate Kernels (Grams) (Grams) 8- 1 9-17 100M 5A 31 .81 26.13 58 3 .02 6.67 5C 18 .38 21.11 50 49 .95 19.39 5-59 1A 16 .19 11.88 2A 6 .09 15.00 4A 64 .91 14.22 5A 27 .38 14.07 6A 15 .17 11.33 8A 23 .34 14.78 9A 25 .62 24.80 10A 50 1.28 25.60 5-61 1A' 37 .79 21.35 18 60 1.34 22.33 2A 50 1.08 21.60 28 80 2.13 26.63 3A 37 .92 24.86 38 78 2.09 26.79 4A 21 .28 13.33 48 81 2.57 31.73 5A 35 .89 25.43 58 80 2.41 30.13 6A 49 . 1.44 29.39 68 75 2.23 29.73 7A 4 .01 2.50 78 30 .47 15.67 70 57 .78 13.68 8A 26 .52 20.00 88 54 1.48 27.41 9A 56 1.51 26.96 98 97 2.75 28.35 10A 34 .73 21.47 108 71 1.73 24 37 8- 2 8-11 01 1000 20.88 20.88 501 1000 20.90 20.90 1001 1000 20.70 20.70 0R ' 1000 22.62 22.62 50R 1000 22.92 22.92 100R 1000 21.01 21.01 136 Table 02 (cont'd.). Mt. of 1000 Kernel Stem or No. of . Kernels Height Date Field Plot Replicate Kernels (Gravs) LGrams) 8— 2 8-11 OD 1000 20.40 20.40 500 1000 24.19 24.19 1000 1000 22.69 22.69 9-17 OM 1000 20.83 20.83 50M 1000 21.71 21.71 100M 1000 19.04 19.04 ON 1000 24.59 24.59 SON 1000 23.64 23.64 lOON 1000 23.47 23.47 8- 3 5-59 1000 20.60 20.60 5-61 1000 23.52 23.52 Field 0-2 0-6 0-7 0-13 Table J3. Yield estimates from oat fields at Collins Road August 1, 1974. Head Dry Ht. (gr.) No. Heads 117.90 100 143.85 100 119.43 100 94.21 100 137 Seed Dry Wt. (gr.) 80.00 100.48 81.98 56.40 1000 Kernel Ht. 23.03 A 24.57 24.48 22.95 138 Table J4 . Kernel.weight development. Field 4 - oats, Collins Road 1973. (X i o, N = 20 except N = 19 on July 29) Date Seeds/Head Seed wt./Head Ht./1000 Kernels July 9 41.45 2 24.49 ' .28 t .18 6.81 i 1.70 13 44.35 i 25.55 .49 i .28 . 11.07 i 1.94 16 49.95 i 24.48 .73 i .44 13.99 i 2.34 19 49.50 i 19.97 .79 i .39 15.42 i 3.03 26 43.15 1 21.75 .66 i .37 15.11 t 3.09 29 48.42 _ 18.13 .77 2.66 + H- .35 15.60 H- 139 Table J5. Kernel weights from oat fields at Collins Road in 1973. Nt. of 1000 Kernel Stem or No. of Kernels Height Date Field Plot Replicate Kernels (grams) (Grams) 7-29 0-4 1 600 9.62 16.03 2 260 3.92 15.08 3 1000 15.29 15.29 4 585 7.34 12.55 5 106 1.69 15.94 6 575 8.93 15.53 7 1000 18.12 18.12 8 1000 16.51 16.51 9 865 14.99 17.33 10 960 15.98 16.65 0-15 1 1000 18.05 18.05 2 1000 21.50 21.50 3 125 2.19 17.52 4 920 15.27 16.60 5 665 12.48 18.77 6 930 20.38 21.91 7 1000 16.71 16.71 8 945 17.80 18.84 9 720 11.04 15.33 10 1000 22.70 22.70 8- 6 O- 4 1A 70 1.02 14.57 2A 23 .29 12.61 28 17 .21 12.35 4A 69 1.22 17.68 48 35 .53 15.14 6A 66 1.17 17.73 7A 14 .10 7.14 8A 20 .30 15.00 88 67 .99 14.78 9A 62 1.14 18.39 10A 59 1.21 20.51 108 48 .86 17.92 0- 4 1000 17.10 17.10 0- 4 Sprayed 1000 16.23 16.23 0-15 1000 19.81 ' 19.81 140 Table J6. Kernel weights from oats field at Collins Road. August 1, 1974. Air Dry Oven Dry Ht. of 71000 Kernel Ht. of 1000 Kernel No. of Kernels Height No. of Kernels Height Field Stem Kernels (Grams) (Grams) Kernels - (Grams) (Grams) 0-2 1 64 .88 . 13.75 64 .80 12.50 1A 44 .59 13.41 45 .52 11.56 2 44 .95 21.59 43 .88 20.47 28 34 .56 16.47 34 .48 14.12 3 83 1.69 20.36 84 1449 17.74 3A - 46 .99 21.52 48 .90 18.75 38 31 .59 19.03 31 .54 17.42 0-2 4 55 1.21 22.00 55 1.10 20.00 48 34 .63 18.53 39 .67 17.18 5 64 1.19 18.59 65 1.11 17.08 6 57 1.18 20.70 57 1.10 19.30 7 63 .96 15.24 61 .86 14.10 7A 43, .64 14.88 43 .58 13.49 8 67 1.23 18.36 68 1.12 16.47 0-2 9 58 1.08 18.62 58 .99 17.07 10 79 1.45 18.35 81 1.31 16.17 .11 36 .75 20.83 38 .70 18.42 11A 11 .18 _16.36 13 .19 14.62 12 43 .74 17.21 43 .69 16.05 12A 26 .52 20.00 26 .48 18.46 13 34 .51 15.00 35 .48 13.71 0-2 14 25 .35. 14.00 25 .32 12.80 15 71 1.10 15.49 65 .97 14.92 15A 31 .47 15.16 31 .41 13.26 158 31 .47 15.16 33 .44 13.33 16 42 1.14 27.14 45 1.05 23.33 16A 16 .37 23.13 17 .32 18.82 168 26 .54 20.77 26 .48 ' 18.46 0-2 17 50 .92 18.40 50 .85 17.00 17A 27 .34 12.59 27 .32 11.85 18 52 .65 12.50 52 .61 11.73 188 21 .27 12.86 30 .32 10.67 . 19 56 1.14 20.36 57 1.03 18.07 20 66 1.28 19.39 66 1.18 17.88 20A 24 .40 16.67 26 .39 15.00 0-2 208 26 .42 16.15 26 .40 15.38 21 56 1.07 19.11 59 .98 16.10 218 31 .61 19.68 31 .52 16.77 22 45 .89 19.78 ‘ 45 .76 16.89 22A 39 .66 16.92 43 .64 14.88 '228 36 .56 15.56 40 .49 12.25 23 20 .40 20.00 21 .31 14.76 141 Table J6 (cont'd.). Air Dry Oven Dpy_, Wt. of 1000 Kernel, ‘Nt. of’ '51000 Kernel— No. of Kernels Weight No. of Kernels Height Field Stem .Kernels (Grams) (Grams) Kernels (Grams), (Grams) 0-2 24 49 .88 17.96 49 .77 15.71 25 31 .57 18.39 31 .48 15.48 258 21. .32 15.24 21 .26 12.38 26 59 1.22 20.68 59 1.09 18.47 26A 30 .59 19.67 30 .49 16.33 27 '54 1.11 20.56 55 1:01 18.36 278 17 .29 17.06 19 .30 15.79 0-2 28 50 .93 18.60 5 .88 17.60 28A ' 35 .49 14.00 35 .46 13.14 29' 36 .60 16.67 35 .55 15.71 298 5 .07 14.00 5 .05 10.00 30 48 1.12 23.33 50 1.05 21.00 30A 16 .30 18.75 16 .26 16.25 308 20 .44 22.00 16 .28 17.50 APPENDIX K IRROMETER READINGS FROM GULL LAKE IN 1972 142 mm mm m_ om Z< oouo— _m mm mm no N— o— z< oono— mm mm mm mm NF om Z< oouop mm mm Om cm NF ON A o z< oouop «N mm ON mm _— w m m z< oouop —N mm mm mm o— v o o 24 oouop @— —N mm xv OF N m N :4 oouo— N— am ON ON mV 0— o w mm z< oonop @— ow om mo ow o— c F— cm Z< oouop NF mm m— mm ow ~F m 0— ON z< oouop o— we w— 00 mm ¢ N op mp 0v 2Q m—uv N mm 0— oo mm m N OP op mv Ea omuN N no w— mm mm OF N— o— m— wv I; ooum— m 00 mp 00 mm o— F— a DP we Z< oouop m we mp ow AM o_ FF m m_ we z< mpnw N mm m— mm om OF m m my cc mm Z< omuop 0 cc op mm mm op m w v— mm om mm in oouNF m %—:w om 0— me ON m— Om Om m N— mu 00 v0 Nu z< omuop om mm my mm mp NP Nv om m —— ON _0 0m mm z< omuop mm mm m_ mm @P mp wv me 0 OF N9 N0 mv Om 2a Omnv RN m— v— cm mF op Pm Fm m op mu mm mv om vm 2m omnc —N mp VF FN mp Pp N— mm m OF mm Rm om m— mm in omu¢ @— op mp m— mm or o o vm m NF mm 00 we N— NN 2a ooump op ON mp om Om KN op m mm m N— mm mm —m mm mm In omuv v— mp mp mm 0 mm m 0 cm o_ o_ co mm ov ON #v Ea oonmp NF «P m— up 0 —N w o_ mm —P NF ow mm mm —_ om z< ooum m mczw pm .8 2m .2 .2 .3 :2 296.5 £562 688:: 2985 $562 6382: 538 5.52 we: 8.8 40 AM—IGV 20 m3 Nplm A:m—. l HGNLZV _._.lm Azmp I mquv Oplw upmrm .A_owu:muoa Lmumz _womv Nan cw mxmb F—su um mocwvmmc LoumEoch .Px mpamh 143 APPENDIX L FIELD NOTES ON CEREAL LEAF BEETLE LARVAL BEHAVIOR 144 Table L1. Field notes on cereal leaf beetle larval behavior. On June 14, 1 large larva was watched for 1 hour from 3:35 pm. The day was mostly cloudy, about 75°F, and the wind was about 15 mph. At 3:35, the larva was moving toward the leaf apex. In about 3 minutes it had moved 3 cm. At that time, it stopped and raised its abdomen 12 times in the next 3 minutes. At 3:50, it again raised its abdomen 7 times in 30 seconds. At 3:57, it lifted its abdomen a single time. At about 4:03, the larva moved about 0.2 cm. toward the leaf end. At 4:07, the larva turned completely around on the leaf and oriented toward the stem. The turn took nearly 1 minute. At 4:10, the abdomen was raised about 4 times in 15 seconds. At 4:22, the abdomen was raised a single time, followed at 4:24 with 2 raises. At 4:30 the larva raised its abdomen 4 times in 15 seconds, and 8 times in 45 seconds at 4:35. June 20 was sunny, warm (about 85°F) with a light breeze. One large larva was watched from 1:55 to 2:55. At 1:55, the larva was 3 cm. from the leaf tip. It proceeded to the tip and back down the leaf, probing on both edges of the leaf. At 2:00, the larva was 6.2 cm. from the leaf tip. By 2:01, the larva had turned to face the leaf tip again. At 2:02, the larva turned again to face the base. At 2:05 the larva moved to a new leaf crossing over where they touched. By 2:06 the larva returned to the first leaf and headed toward the tip, crawling sometimes on the leaf edge. Between 2:10 and 2:11, the larva moved 6 cm. to leaf tip and 145 146 Table Ll (cont'd.). started to backtrack. At 2:13 the larva stopped crosswise on the leaf after returning 4.5 cm. and began feeding. By 2:20, the scar was .6 cm. long and the body position was somewhat diagonal down- ward on the leaf. At 2:28 a second feeding scar was started next to the first with the body toward the leaf tip. At 2:30 the larva was diagonal and continued to feed. The feeding scar was about 1.3 cm. long. At 2:40 the scar was about 2.0 cm. long and by 2:44 it was 2.7 cm. long. At 2:48 a new scar was started while feeding downward on the plant. The larva was removed at 2:55. A large larva was watched from 11:35 am to 12:35 pm on July 8. The weather was hot, 90°F, humid, with a light breeze. The larva was on the second from the top leaf, 13.5 cm. from the stem. The leaf was 28.8 cm. long. The larva was somewhat disturbed as a leaf of a neighboring plant hit it and it moved slowly in response. By 11:39 the larva had turned around on the leaf to face the leaf tip. The larva then remained inactive until 12:35. There was considerable feeding damage distad from the larva on the leaf. APPENDIX M FORTRAN LISTING OF THE PLANT MODEL 147 Table Ml. Parameter descriptions and initial values used in the simulation. Name Description Value BUSHELS Grain yield in bu/acre O C Dummy variable - CROUTG Array of intermediate rates of germination 0 CROUTH Array of intermediate rates of head stage 0 CROUT 1 Array of intermediate rates of leaf class 1 O CROUT 2 Array of intermediate rates of leaf class 2 0 CROUT 3 Array of intermediate rates of leaf class 3 O CROUT 4 Array of intermediate rates of leaf class 4 O CROUT 5 Array of intermediate rates of leaf class 5 O CROUT 6 Array of intermediate rates of leaf class 6 0 CROUT 7 Array of intermediate rates of leaf class 7 0 CROUT 8 Array of intermediate rates of leaf class 8 0 CROUT 9 Array of intermediate rates of leaf class 9 O D Dummy variables - DAY Actual date simulation was run 0 - DELG Mean time in germination stage in D>42 175 DELH Mean time in head stage in oD>42 755 DEL 1 Mean time in leaf class 1 stage in oD>42 134 DEL 2 Mean time in leaf class 2 stage in °D>42 128 DEL 3 Mean time in leaf class 3 stage in °D>42 13o DEL 4 Mean time in leaf class 4 stage in gD>42 125 DEL 5 Mean time in leaf class 5 stage in oD>42 210 DEL 6 Mean time in leaf class 6 stage in oD>42 238 DEL 7 Mean time in leaf class 7 stage in oD>42 126 DEL 8 Mean time in leaf class 8 stage in oD>42 117 DEL 9 Mean time in leaf class 9 stage in D>42 236 DT Change in time--increment for model updating l ENERGY Time integral of net leaf surface area/acre 0 ENPLANT ENERGY/plant O FEEDPDD Feeding per degree day - FIEPAC First instar feeding equivalents/acre - FIEPFT First instar feeding equivalents/sq. ft. - HD Density of heads/acre O HEADNT Mean weight of a head (gr/head) - I Indexing variable - 148 Ill, “41 (J1 149 Table Ml (cont'd.). Name Description Value II Indexing variable - KG Distribution constants for germination delay 50 KH Distribution constants for head delay 25 K1 Distribution constants for leaf class 1 delay 25 K2 Distribution constants for leaf class 2 delay 25 K3 Distribution constants for leaf class 3 delay 25 K4 Distribution constants for leaf class 4 delay 25 K5 Distribution constants for leaf class 5 delay 25 K6 Distribution constants for leaf class 6 delay 25 K7 Distribution constants for leaf class 7 delay 25 K8 Distribution constants for leaf class 8 delay 25 K9 Distribution constants for leaf class 9 delay 25 M Indexing variable 0 - MAXT Maximum time for the simulation to run ( D>42) 2800 MM Indexing variable - N Indexing variable 2 - NETSA Net leaf surface area (mm /acre) 0 NITER Number of iterations of the model to complete the run 56 NPPRINT Number of iterations OLDP Old value of probit of first instar equivalent - P Value of probit of FIE - PFEED Percent of total leaf area fed on single last update 0 PLANTIN Planting time in °D>42 425 PLANTS Plants/acre from the no. of germinating seeds 0 RFEED Rate of feeding for each leaf class (% of foliage present) 0 RGERM Rate of plant, i.e. primary stem, production 0 RHD Rate of head maturation (output from leaf class 10) 0 RMORT Rates of mortality of stems by leaf class (no. /acre/ D) 0 RSA Rates of surface area production by leaf class (mm2 /stem/OD) 0 RSS 'Rates 3f surface areasenescence by leaf class (mm /stem/o D) O RSTEM Rate of production of stems 0 RTILLER Rate of tiller production 0 150 Table Ml (cont'd.). Name Description Value R1 Output rate of stems from leaf class 1 (no/acre/O 0D) 0 R2 Output rate of stems from leaf class 2 (no/acre/0 0D) 0 R3 Output rate of stems from leaf class 3 (no/acre/0 0D) 0 R4 Output rate of stems from leaf class 4 (no/acre/0 0D) 0 R5 Output rate of stems from leaf class 5 (no/acre/OD) 0 R6 Output rate of stems from leaf class 6 (no/acre/ D) 0 R7 Output rate of stems from leaf class 7 (no/acre/OD) 0 R8 Output rate of stems from leaf class 8 (no/acre/OD) 0 R9 Output rate of stems from leaf class 9 (no/acre/ D) 0 SA Array of net surface area/stem for each leaf class 0 SAXSD Array of net surface area/stem times stem density for each leaf class 0 SD Stem density array for each leaf class (stem/acre) O 306 Seed density--number of seeds still to germinate O SEEDS Number of seeds/acre planted 370000 SEEDNT Height (gr) of seed/head O SPRADAY 0D>42 of actual time that spraying occurred for CLB O STEMS Number of stems/acre 0 T Time in OD>42°F after seeding for plant growth 0 WATCH Time of day simulation was run - YIELD ‘gr/acre of seed 0 Table M2. 1==- RDSRAM 1111114; I 1 AVE}: 11:: 1") a: A~\J r g: x J d.\.Jr +CRUUTS( UMMLu/11H3.3 1(H111IU 11xfiflii.1u.aJ11J)vfiflfl;hl. “111.21 }" F41 13(11i 1" {'J 1. 1': KW 1J11 l (i C 511133.1 U915 HfiTfi Ufilfi (7 3M 0} u' 'I V \‘s.- Hf Klefle +0) DATA +01 Hfllfi 1LTFH Riv NATO b; 0816 NE 11 11:11.41' 1.111 111 i..9} UHIHLwW.HDIS: tNiILHMLAflT. 1 l 531:1«11Lf111 ‘1 PM M1815 . 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I. 3 i3: N APPENDIX N CLB EGGS AND LARVAE PER TEN STEMS IN 1972 GULL LAKE PLOTS 158 Eggs/larvae per 10 stems at Gu11 Lake p10ts in 1972 (per 20 stems on May 18). Table N1. July June May 25 29 26 23 15 31 18 120001010 Ill/Ill], 000000000 040100020 I’ll/Ill, 312000101 990560830 1 1 435576317 122321222 141112112 [Ill/I’ll 573609373 123312122 000000000 I’ll/I’ll 120863779 111212221 123456789 E 0 200120020 I’ll/Ill, 213002310 341120020 351217321 3303m0550 ‘II/l/llll 1m0401441 Aha/0350060 ll/l/l/I/ 834652551 154100022 ///////// 083033405 312222222 4421 0 ///l I 9054 6 2433 3 0 0 0 l l l 5 2 5 2 2 1 123456789 M 0 000001000 I’ll/I’ll 000000000 432120002 I’ll/Ill, 443554301 320240010 I’ll/III], .83314n145 034.119.0310 ///////// 127220130 1 1 220100000 I’ll/Ill, 569302765 123456789 IL 0 . 000 Ill 000 410 III 000 350 1 III. 520 5 /35 13 /24 0 / 5 23 I49 17 /4O 6 [35 01 ON 00 159 APPENDIX 0 SEASONAL ELYTRA LENGTHS 0F EMERGING CLB ADULTS FROM THE 1972 GULL LAKE PLOTS 160 Table Ol. Seasonal elytra lengths (mm) of emerged cereal leaf beetles from l972 Gull Lake plots. Females Males __ __ No. Beetlgs Plot X S.D. n X S.D. n Beetles / Ft OD 3.62 .10 5 3.41 .17 8 13 1.44 ON 3.67 .14 44 3.47 .14 54 98 10.89 01 3.71 .15 53 3.46 .13 53 106 11.78 0E1 3.61 .13 3 3.48 -- 1 4 .44 0E2 3.83 .05 3 -- -- 0 3 .33 0E4 3.66 .11 7 3.54 .25 2 9 1.00 OES 3.62 .17 35 3.41 .14 28 63 7.00 0E7 3.72 .11 12 3.49 .18 11 23 2.56 0E8 3.75 .11 7 3.52 .13 9 16 1.78 0M1 3.77 .11 6 3.68 .18 4 10 1.11 0M2 3.76 .16 22 3.52 .11 23 45 5.00 0M4 -- -- 0 3.56 .11 2 2 .22 0M5 3.87 .13 6 3.62 .03 2 8 .89 0M7 3.69 .09 4 -- -- 0 4 .44 0M8 3.72 .11 14 3.57 .08 14 28 3.11 0L1 4.00 ' -- 1 -— -- 0 1 .11 0L2 3.78 .04 6 3.58 .03 2 8 .89 0L4 3.83 .06 3 —- —- 0 3 .33 0L5 3.80 ‘ .14 20 3.59 .11 15 35 3.89 0L7 3.90 .08 2 . 3.60 -— 1 3 .33 0L8 3.88 -- 1 3.36 .23 2 3 .33 161 APPENDIX P CLB PUPAL CELL SAMPLE ASSESSMENT AT GULL LAKE IN 1972 162 Table F”. Pupal cell assessment, Gull Lake plots, 1972. CLB Tetrastichus julis Cells Cells Live with with Lemonhaous Dead Dead Emergence Larvae Dead Emergence curtus Plot Larvae Adults Holes /Cells Larvae Holes Cells Unsure Total 00 0 ON . 1 5 2 8 01 5 5/1 3 9 0E1 1 1 0E2 3/1 1 0E4 1 1/1 2 1 5 0E5 9 21/5 6 20 0E7 5 15/3 4 12 0E8 1 6 ' 7 CHI 9 10/2 4 15 0M2 27 2/1 1 14 43 0M4 1 4/1 2 4 ONE 3 5/1 1 5 0M7 3 7/1 1 1 6 0M8 1 9 28/5 5 1 l 22 0L1 2 2 0L2 5 5 0L4 16/3 2 5 0L5 1 8 19/3 3 15 W 3 4/1 4 0L8 4 4 163 APPENDIX Q TETRASTICHUS JULIS EMERGENCE IN 1972 164 «\o mm\mH m~\oH , «\m m\m mm\h ~\o m\o IO\o .n\fi m\o oxo o \o o\c O\o 0\o 0\o o \o ”\o c \o 0\o 0\o 0\o o \o O\o O\o o \c O\o 0\o 0\o 0\o «\o o \o m\o oxo O\o c \o 0\o 0\o 0\o 0\o 0\o c \o C\o O\o o \o H\o 0\o c\o o\o 0\o o \H m\H m\H 0\H o \o 0\o 0\o 0\o 0\o mm\m M\H H\fi HH\o 0\o C\o O\o 0\o ¢ \H ¢\o m\o O\H mm\n o\o 0\o H\o O\o Q\o mH\m ”\o O\m ¢\m m \o 0\o 0\o 0\o 0\o H\o C\o 0\o oH\m H\m H\~ O\o m \o on O\o 0\o "\H. H\o o\o o\o n \o M\m 0\o 0\o o \o O\o m\o 0\o ~\o «\o 0\o czc ~20 .azo mmo “mom mmo. vmo Nmo fimo He 20 oo mkogm . FmHOP Hm mm mm «m Hm ma N“ v” NH ofi m span on 8 8N mean .Ammpanuxmopoev ~nmfl cw muopn oxug pane an oucmmgmeo mrprn ungu*ummgum» .po m—na» 165 Table 01 (cont'd.). PLOTS 0M5 0M7 0M8 0L1 0L2 0L4 0L5 0L7 0L8 June 26 0/0 0/0 0/35 0/0 0/0 0/0 0/0 0/0 0/0 28 0/0 2/6 .17/70 0/0 0/0 0/0 0/0 0/0 0/0 30 0/1 0/0 18/74 0/0 0/0 0/0 0/1 0/0 0/0 July 3 172 0/4 9/ 9 5 0/1 0/1 6/ 7 0/2 0/5 7 0/5 0/ 5 0/5 0/1 10 O/ 2 0/1 0/0 12 0/1 14 0/2 0/0 17 0/0 0/ 0 0/6 0/1 19 0/0 0/0 0/0 0/0 21 24 26 28 31 Total 1/9 2/11 50/202 0/0 0/11 0/5 0/9 0/0 0/0 166 APPENDIX R DEGREE-DAY ACCUMULATIONS FOR THE AREAS STUDIED 167 Table.Rl.. Cumulative degree days greater than 42°F at Gull Lake by date in 1972. MONTH DAY JAN FEB MAR APR MAY JUN JUL AUG SEP 1 0 3 13 43 258 832 1511 2423 3287 2 0 3 13 43 275 859 1540 2453 3287 3 0 3 13 45 281 890 1562 2475 3287 4 0 3 13 45 291 917 1580 2494 3287 5 0 3 13 47 303 939 1598 2515 3311 6 0 3 13 53 323 964 1618 2539 3331 7 0 3 15 53 333 985 1638 2557 3331 8 0 3 15 53 336 1009 1662 2575 3331 9 0 3 15 55 343 1029 1692 2593 3369 10 1 3 15 63 363 1039 1724 2611 11 1 3 21 72 375 1052 1762 2631 12 1 5 23 83 391 1075 1797 2663 13 1 5 23 92 411 1106 1829 2694 14 1 5 23 98 436 1142 1867 2729 15 1 5 23 108 451 1167 1897 2754 16 1 5 23 111 469 1183 1927 2778 17 1 5 23 122 490 1199 1957 2814 18 2 5 23 143 516 1219 1989 2852 19 2 5 25 156 541 1247 2025 2884 20 2 5 32 162 567 1275 2065 2914 21 2 5 41 165 596 1288 2106 2949 22 3 5 41 169 622 1304 2147 2986 23 3 5 41 171 648 1314 2187 3020 24 3 5 41 172 676 1328 2223 3046 25 3 5 41 176 703 1348 2247 3074 26 3 5 41 183 727 1371 2263 3108 27 3 5 42 192 751 1397 2287 3132 28 3 7 43 205 775 1424 2310 3162 29 3 10 43 219 799 1451 2334 3191 30 3 10 43 235 812 1481 2361 3223 31 3 10 43 235 816 1481 2389 3253 168 169 Table R2. Cumulative degree days greater than 42°F at Gull Lake by date in 1973. MONTH DAY JAN FEB MAR APR MAY JUN JUL 1 0 19 24 181 439 871 1732 2 0 21 29 187 458 897 1766 3 0 21 34 188 463 925 1797 4 O 22 35 188 467 955 1827 5 O 22 35 191 475 983 1854 6 0 22 46 200 488 1011 1882 7 0 22 60 208 506 1035 1916 8 0 22 63 213 526 1063 1953 9 0 22 65 214 546 1097 1991 10 0 22 71 214 566 1127 2025 11 0 22 87 214 581 1163 2051 12 0 22 92 215 592 1199 2077 13 0 22 95 216 600 1226 2117 14 0 22 110 219 604 1252 2152 15 0 22 126 230 611 1281 2177 16 0 22 129 242 621 1316 2201 17 2 22 129 248 626 1345 2225 18 8 22 129 264 633 1377 2255 19 12 22 131 285 645 1410 2289 20 12 22 131 311 659 1440 2323 21 12 22 131 335 675 1469 2350 22 12 22 131 353 696 1496 2382 23 12 22 133 364 713 1518 2414 24 12 22 138 373 730 1540 2446 25 14 22 143 381 752 1567 2483 26 17 22 148 389 768 1603 2521 27 18 22 153 397 785 1633 2551 28 18 22 158 402 804 1661 2573 29 18 22 163 406 817 1681 2598 30 18 22 171 418 831 1704 2628 31 18 22 175 418 847 1704 2660 170 Table R3. Cumulative degree days greater than 42°F at Collins Road in 1972. MONTH DAY JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC l 0 0 4 29 226 798 1514 2412 3254 3876 4110 4150 2 0 O 4 29 246 822 1546 2442 3278 3893 4122 4150 3 O O 4 30 255 853 1569 2469 3294 3916 4128 4150 4 0 0 4 31 275 883 1586 2487 3310 3936 4129 4150 5 0 0 4 31 288 904 1600 2506 3329 3956 4131 4150 6 0 0 4 34 308 931 1618 2530 3355 3974 4136 4150 7 O 0 5 34 316 953 1641 2551 3379 3980 4142 4150 8 0 O 5 34 320 979 1665 2571 3403 3991 4147 4150 9 O 0 5 34 327 1008 1693 2489 3419 3995 4147 4150 10 0 O 5 41 336 1018 1725 2605 3441 4002 4148 4150 11 0 0 9 49 354 1030 1761 2625 3463 4015 4149 4150 12 0 l 14 58 370 1050 1797 2654 3485 4027 4150 4150 13 0 1 14 68 387 1078 1831 2682 3513 4029 4150 4150 14 O 1 14 72 406 1114 1865 2718 3535 4041 4150 4150 15 O 1 14 79 423 1146 1894 2748 3553 4045 4150 4150 16 0 1 14 86 439 1166 1922 2768 3577 4054 4150 4150 17 O 1 14 96 461 1181 1951 2802 3613 4061 4150 4150 18 0 1 14 116 487 1204 1984 2838 3643 4061 4150 4150 19 0 l 14 132 509 1232 2018 2870 3667 4061 4150 4150 20 0 1 17 136 533 1268 2056 2898 3689 4063 4150 4150 21 O 1 25 142 563 1292 2096 2930 3710 4064 4150 4150 22 0 1 29 145 588 1306 2136 2966 3718 4070 4150 4150 23 0 1 29 146 614 1318 2175 2998 3726 4082 4150 4150 24 0 l 29 147 642 1330 2209 3029 3749 4083 4150 4150 25 0 1 29 149 668 1352 2239 3057 3776 4087 4150 4150 26 0 l 29 157 689 1375 2260 3089 3804 4092 4150 4150 27 0 1 29 164 711 1400 2282 3112 3822 4098 4150 4150 28 O 1 29 176 735 1426 2304 3140 3837 4106 4150 4150 29 0 1 29 191 762 1454 2327 3168 3858 4109 4150 4150 30 0 1 29 205 780 1483 2353 3197 3867 4109 4150 4150 31 O 1 29 205 785 1483 2381 3226 3867 4109 4150 4153 171 Tab1e R4. Cumulative degree days greater than 42°F at Collins Road in 1973. MONTH DAY JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV 1 0 30 36 174 415 833 1686 2629 3574 4207 4625 2 0 33 40 180 433 859 1720 2655 3612 4227 4627 3 0 33 44 181 442 887 1752 2681 3648 4249 4628 4 0 34 45 181 447 917 1780 2708 3686 4265 4628 ' 5 0 35 45 183 454 946 1808 2738 3720 4278 4628 6 0 35 54 192 464 975 1836 2771 3747 4289 4628 7 0 35 66 200 484 1000 1870 2803 3769 4307 4628 8 O 35 71 201 503 1031 1906 2841 3787 4331 4628 9 0 35 73 201 523 1065 1942 2878 3809 4353 4628 10 0 35 75 201 543 1095 1977 2910 3829 4375 4628 11 0 35 92 201 557 1135 2003 2941 3855 4398 4628 12 0 35 103 202 567 1172 2027 2970 3871 4423 4632 13 0 35 104 202 571 1199 2067 2997 3889 4443 4641 14 0 35 112 206 576 1223 2102 3025 3911 4457 4653 15 O 35 127 217 583 1253 2126 3051 3930 4475 4659 16 1 35 130 235 593 1287 2148 3077 3946 4484 4659 17 5 35 130 242 597 1311 2172 3105 3955 4492 4659 18 16 35 130 258 605 1336 2200 3132 3965 4497 4660 19 20 35 130 279 619 1368 2233 3162 3975 4505 4662 20 20 35 130 305 631 1400 2269 3194 3987 4518 4665 21 20 35 130 331 646 1428 2295 3214 4002 4527 4671 22 20 35 130 355 664 1454 2323 3232 4020 4539 4677 23 20 35 131 369 680 1476 2352 3252 4040 4552 4681 24 20 35 134 377 696 1500 2382 3278 4065 4568 4688 25 22 35 138 384 715 1526 2416 3306 4093 4588 4695 26 27 35 141 391 729 1557 2454 3343 4120 4599 4695 27 30 35 145 392 745 1587 2485 3385 4146 4606 4699 28 30 35 149 392 768 1615 2515 3427 4171 4611 4700 29 30 35 159 392 782 1635 2540 3465 4185 4616 4700 30 30 35 165 395 791 1657 2568 3501 4191 4619 4702 31 3O 35 167 395 807 1657 2599 3536 4191 4622 4702 172 Table R5. Cumulative degree days greater than 42°F at Collins Road in 1974. MONTH DAY JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV 1 0 12 19 75 382 798 1519 2449 3297 3817 4156 2 0 12 21 84 393 818 1553 2476 3311 3817 4170 3 0 12 36 96 403 837 1593 2505 3322 3820 4184 4 0 12 49 106 409 865 1630 2527 3333 3830 4186 5 0 12 52 107 415 895 1652 2551 3346 3849 4186 6 0 12 59 109 417 926 1678 2577 3361 3871 4186 7 0 12 67 111 420 957 1708 2601 3377 3881 4189 8 0 12 71 111 424 988 1744 2631 3402 3887 4195 9 0 12 73 111 426 1023 1782 2659 3429 3896 4201 10 0 12 74 116 434 1056 1819 2687 3457 3907 4206 11 0 12 74 125 444 1070 1843 2719 3489 3922 4210 12 0 12 74 140 454 1086 1865 2749 3521 3942 4211 13 0 12 74 158 457 1106 1898 2779 3549 3946 4211 14 0 12 74 174 473 1134 1940 2803 3559 3962 4211 15 0 12 74 177 491 1158 1976 2829 3577 3967 4211 16 0 12 74 182 501 1176 2002 2858 3589 3973 4211 17 0 12 74 190 521 1186 2030 2884 3611 3983 4213 18 0 12 74 199 535 1204 2066 2909 3629 3986 4218 19 0 12 74 202 553 1230 2100 2938 3651 3986 4222 20 0 12 74 212 569 1260 2128 2971 3676 3986 4225 21 1 12 74 230 594 1292 2148 3005 3689 3988 4225 22 1 12 74 250 626 1318 2175 3037 3697 3998 4225 23 1 12 74 255 648 1332 2197 3071 3702 4014 4231 24 1 12 74 259 663 1348 2223 3097 3711 4024 4238 25 2 12 74 265 675 1367 2251 3119 3727 4036 4238 26 5 12 74 277 687 1391 2283 3151 3745 4044 4238 27 8 13 74 300 696 1413 2317 3186 3767 4054 4238 28 8 17 74 328 708 1437 2346 3205 3792 4069 4238 29 8 17 74 351 732 1461 2338 3226 3810 4085 4238 30 10 17 74 373 756 1491 2403 3252 3815 4107 4238 31 12 17 74 373 780 1491 2427 3280 3815 4132 4238 "I111111111111111111111“