Developmental Morphology Quantification and Biomass Response to Seasonal Defoliation of Short, Mid, and Tall Grasses of North America

by Leobardo Richarte-Delgado, BS, MS.

A Dissertation

Wildlife, Aquatic, and Wildland Science and Management

Submitted to the Graduate Faculty of Texas Tech University in Partial Fulfilment of the Requirements for the Degree of

DOCTOR OF PHILOSOPHY

Approved

Carlos Villalobos Chairperson of the committee

Charles West Terry Mclendon Robert Cox Ron Sosebee

Mark Sheridan Dean of the Graduate School

August, 2018

Texas Tech University, Leobardo Richarte-Delgado, August 2018

ACKNOWLEDGMENTS

I would like to thank to my main advisor Dr. Carlos Villalobos as well as all my committee members for their advice and support preparing this manuscript. I also would like to thank Dr. D. Wester for his statistics help. Special thanks to my family for all their support in the distance, to my girlfriend and friends for their endless support and advise through the darkest hours of this journey, but overall to God.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

TABLE OF CONTENTS ACKNOWLEDGMENTS ...... ii ABSTRACT ...... v LIST OF TABLES ...... viii LIST OF FIGURES ...... xiii CHAPTER I ...... 1 Literature Cited...... 3 CHAPTER II ...... 4 Grasslands of North America ...... 4 Shortgrass prairie ...... 5 Mixed grass prairie ...... 6 Southern mixed prairie ...... 6 Northern mixed prairie ...... 7 Tallgrass prairie ...... 8 Grass species description ...... 8 Clipping to Simulate Grazing ...... 13 Clipping and forage yield production ...... 14 Developmental morphology and its importance in grasses ...... 16 Literature Cited...... 18 CHAPTER III ...... 24 Abstract ...... 24 Introduction ...... 25 Materials and Methods ...... 27 Results ...... 32 Discussion ...... 39 Conclusions ...... 46 Literature Cited...... 48 Tables ...... 51 CHAPTER IV ...... 57 Abstract ...... 57 iii

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Introduction ...... 59 Material and Methods ...... 60 Results ...... 65 Discussion ...... 78 Conclusions ...... 90 Literature cited ...... 92 Tables ...... 97 Figures ...... 106 CHAPTER V ...... 118 Abstract ...... 118 Introduction ...... 119 Material and Methods ...... 121 Results ...... 124 Discussion ...... 126 Literature Cited...... 131 Tables ...... 133 Figures ...... 138 CHAPTER VI ...... 158 LITERATURE CITED ...... 162 APPENDIX ...... 174

Texas Tech University, Leobardo Richarte-Delgado, August 2018

ABSTRACT

This study was conducted during the 2015 and 2016 growing seasons (June -

November) and consisted of two separate experiments. The first study was conducted during the 2015 growing season under greenhouse conditions where developmental morphology and tiller recruitment were evaluated. The second study was a two-year study performed under field conditions where biomass allocation influenced by clipping intensities were evaluated. Main objective was to determine how developmental morphology stage affects biomass production in short, mid, and tall grasses of North

America. Grasses evaluated in this study were the short-grass species blue grama (BG), the mid-grass species sideoats grama (ST), the introduced species WW-B Dahl (WB), and the tall grass species switchgrass, where four cultivars were evaluated: Kanlow (KL),

Alamo (AL), cultivar (I), and cultivar (II).

At the beginning of 2015 growing season 90 plants were established in individual

19-L pots and grown under greenhouse conditions. Plants were irrigated at rates to simulate Lubbock annual precipitation and adjusted to the growing season (70% of the total). Developmental morphology was evaluated monthly from June to November using the Nebraska system where mean stage count (MSC) index was calculated. One-way analysis of variance was performed at each evaluation date looking at differences in MSC values among species. Experimental treatments were grass species: 1) AL 2), BG 3), ST

4), KL 5), CI and 6) CII, with 15 replications.

MSC was affected (P<0.05) by grass species at each sampling time. AL most of the time presented significantly higher MSC values in relation to BG and ST at each measurement date, higher MSC values indicates that AL completes its growth cycle

Texas Tech University, Leobardo Richarte-Delgado, August 2018

faster. However, there was no clear difference between BG and ST. Our results indicated that BG and ST expended the same time to move from growth stage to growth stage and kept a low MSC index even late in the growing season.

The field portion of this study was designed to quantify total biomass allocation to main grass structures and how this was affected by developmental morphology and defoliation intensities. At the beginning of 2015 and 2016 growing season 252 plants were stablished in 19-L pots and grown under field conditions. Grasses were exposed to moderate and heavy utilizations, at thee phenological stages. Total plant biomass was harvested at the end of the growing seasons and separate, into aerial tillers, crowns, and roots. Experimental treatments were composed of three factors and several levels by factor. Factors: A was grass species, with 4 levels (BG, ST, KL, and WB). Factor B was clipping intensities, with 3 levels (0%,50%, and 75%.) Factor C) was phenological stage with 3 levels (vegetative, reproductive, and post-reproductive). In total there were 36 treatments with 7 replications per treatment. Response variables evaluated were aerial tillers biomass, crown biomass, root biomass, total biomass, aboveground to belowground ratio, and water use efficient (WUE). Analysis of variance, including test of normality, and homogeneous variances were performed for each response variable.

Tukey’s (HSD) test at P<0.05 were conducted to test differences among treatment means.

Biomass accumulation to the aerial tiller portion was significantly higher than crown and roots. Close to 40% of the belowground biomass was crown structures and

60% roots. Switchgrass was the species with lower defoliation tolerance, followed by ST and WB, while BG showed the higher defoliation tolerance. Heavy utilization during the vegetative stage produced under-compensation biomass values while moderate utilization

Texas Tech University, Leobardo Richarte-Delgado, August 2018

regardless of plant’s morphological stage produced compensatory values. Clipping, regardless of intensity, reduced roots biomass and favored shoot production. The results of this study illustrate the importance of incorporate developmental morphology as a meaningful variable in the design of grazing schemes due to its significant influence in plant biomass response to defoliations.

vii

Texas Tech University, Leobardo Richarte-Delgado, August 2018

LIST OF TABLES

3. 1 Soil fertility analysis results from soil collected at the Texas Tech Native Rangeland from the top 30 cm, during the 2015 growing season, before mix with sand soil, Lubbock TX, USA...... 51

3. 2 Soil texture analysis results from soil collected at the Texas Tech Native Rangeland from the top 30 cm, during the 2015 growing season, before mix with sand, Lubbock TX, USA...... 51

3. 3 Amount of water applied to each 19-L pot coming from irrigation and precipitation sources during the 2015 and 2016 growing season at the Texas Tech Native Grassland, Lubbock TX, USA...... 51

3. 4 Monthly precipitation and average monthly temperature for 2015 and 2016 growing season at the Texas Tech Native Grassland, Lubbock Texas, USA (West Texas Mesonet, 2016)...... 52

3. 5 Transplantation, establishment and forage collection dates of plants used in this study, during the 2015 growing season, under field conditions, at the Texas Tech Native Grassland, Lubbock TX, USA...... 52

3. 6 Transplantation, establishment and forage collection dates of plants used in this study, during 2016 growing season, under field conditions, at the Texas Tech Native Grassland, Lubbock TX, USA...... 52

3. 7 Biomass production (g/pot) means and standard error of the mean of four grass species, collected during vegetative stage, separate by species and structure, growth under field conditions during the 2015 and 2016 growing seasons, at the Texas Tech, Native Rangeland, Lubbock, TX, USA...... 53

3. 8 Biomass production (g/pot) means and standard error of the mean of four grass species, collected during the reproductive stage, separated by species and structure, growth under field conditions during the 2015 and 2016 growing seasons, at the Texas Tech, Native Rangeland, Lubbock, TX, USA...... 53

3. 9 Biomass production (g/pot) means and standard error of the mean of four grass species, collected during post-reproductive stage, separated by species and structure, growth under field conditions during the 2015 and 2016 growing seasons, at the Texas Tech, Native Rangeland, Lubbock, TX, USA...... 54

3. 10 Proportion of total biomass and standard error of the mean allocated to each grass structure by phenological stage of BG plants, growth during 2016 growing season under field conditions at the Texas The Native rangeland, Lubbock TX, USA...... 54

3. 11 Proportion of total biomass and standard error of the mean allocated to each grass structure by phenological stage of KL plants, growth during 2015 and

viii

Texas Tech University, Leobardo Richarte-Delgado, August 2018

2016 growing seasons under field conditions at the Texas The Native rangeland, Lubbock TX, USA...... 55

3. 12 Proportion of total biomass and standard error of the mean allocated to each grass structure by phenological stage of WB plants, growth during 2016 growing season under field conditions at the Texas The Native rangeland, Lubbock TX, USA...... 55

3. 13 Proportion of total biomass and standard error of the mean allocated to each grass structure by phenological stage of ST plants, growth during 2015 and 2016 growing seasons under field conditions at the Texas The Native rangeland, Lubbock TX, USA...... 56

3. 14 Aboveground to belowground ratio of four grass species, at three phenological stages during the 2015 and 2016 growing, under field conditions at the Texas The Native rangeland, Lubbock TX, USA...... 56

4. 1 Biomass (g/pot) allocated to the aerial tillers of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 97

4. 2 Biomass (g/pot) allocated to the crown of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 97

4. 3 Biomass (g/pot) allocated to the root portion of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 98

4. 4 Total plant biomass (g/pot) of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 98

4. 5 Water use efficiency (g H2O/g of dry biomass/pot) of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 99

4. 6 Aboveground to belowground ratio of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 99

Texas Tech University, Leobardo Richarte-Delgado, August 2018

4. 7 Biomass (g/pot) allocated to the aerial tillers of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 100

4. 8 Biomass (g/pot) allocated to the crown of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 101

4. 9 Biomass (g/pot) allocated to the root portion of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 102

4. 10 Total plant biomass (g/pot) of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 103

4. 11 Water use efficiency (g H2O/g of dry biomass/pot) of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 104

4. 12 Aboveground to belowground ratio of BG, ST, KL, and WB species affected by five defoliation intensity by plant phenological stage combination, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA...... 105

5. 1. Amount of water applied per individual plant of switchgrass, sideoats grama, and blue grama under greenhouse conditions during the 2015 growing season Lubbock TX, USA...... 133

5. 2 Water applied per pot per irrigation event and the total amount of water applied per pot during the 2015 growing season calculated based on 69 irrigations evets (once every three days) using 70% of the Lubbock average precipitation and surface area of different pot size...... 133

5. 3 Morphological measurement and development morphology stage evaluation date at the TTU Greenhouse facility during 2015 growing season...... 133

5. 4 Primary and secondary growth stages, numerical indices and descriptions for growth stage and development of perennial grasses (Moore et al. 1991) ...... 134

5. 5 MSC of six grasses: two established switchgrass cultivars, Alamo (AL) and Kanlow (KL), and two unknown switchgrass types, cultivar I (CI) and cultivar II

Texas Tech University, Leobardo Richarte-Delgado, August 2018

(CII), blue grama (BG) and sideoats grama (ST), evaluated during the 2015 growing season under greenhouse conditions at the TTU PSS greenhouse, Lubbock TX. USA...... 135

5. 6 MSC of four switchgrass types: two established switchgrass cultivars, Alamo (AL), Kanlow (KL), and two unknown types, cultivar I (CI) and cultivar II (CII), evaluated during the 2015 growing season, under greenhouse condition at the TTU PSS greenhouse, Lubbock TX. USA...... 136

5. 7 Monthly MSC of six grasses: two known established switchgrass cultivars, Alamo (AL) and Kanlow (KL), two unknown types, cultivar I (CI) and cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during the 2015 growing season, under greenhouse conditions, at the TTU PSS greenhouse, Lubbock TX. USA...... 137

A. 1 Analysis of variance for aerial biomass production of ST and KL species evaluated during the 2015 growing season...... 174

A. 2 Analysis of variance for crown biomass production of ST and KL species evaluated during the 2015 growing season...... 175

A. 3 Analysis of variance for root biomass production of ST and KL species evaluated during the 2015 growing season...... 176

A. 4 Analysis of variance for total biomass production of ST and KL species evaluated during the 2015 growing season...... 177

A. 5 Analysis of variance for aboveground to belowground biomass ratio of ST and KL species evaluated during the 2015 growing season...... 178

A. 6 Analysis of variance for WUE of ST and KL species evaluated during the 2015 growing season...... 179

A. 7 Analysis of variance for aerial biomass production of BG, ST, KL and WB species evaluated during the 2016 growing season...... 180

A. 8 Analysis of variance for crown biomass production of BG, ST, KL and WB species evaluated during the 2016 growing season...... 181

A. 9 Analysis of variance for root production of BG, ST, KL and WB species evaluated during the 2016 growing season...... 182

A. 10 Analysis of variance for total biomass production of BG, ST, KL and WB species evaluated during the 2016 growing season...... 183

A. 11 Analysis of variance for aboveground to belowground biomass ratio of BG, ST, KL and WB species evaluated during the 2016 growing season...... 184

Texas Tech University, Leobardo Richarte-Delgado, August 2018

A. 12 Analysis of variance for WUE of BG, ST, KL and WB species evaluated during the 2016 growing season...... 185

C. 1 Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during July, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA...... 186

C. 2 Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during August, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA...... 186

C. 3 Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during September, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA...... 186

C. 4 Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during October, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA...... 187

C. 5 Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during November, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA...... 187

xii

Texas Tech University, Leobardo Richarte-Delgado, August 2018

LIST OF FIGURES

4. 1 Aerial biomass (gr; SEM) of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 106

4. 2 Crown biomass (gr; SEM) of ST and KL and WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 107

4. 3 Root biomass (gr; SEM) of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 108

4. 4. Total biomass (gr; SEM) of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 109

4. 5 Aboveground to belowground biomass ratios of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 110

4. 6 Water use efficiency (g H2O/g of dry biomass) of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 111

4. 7 Aerial biomass (gr; SEM) of BG, ST, KL WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 112

4. 8 Crown biomass (gr; SEM) of BG, ST, KL WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 113

4. 9 Root biomass (gr; SEM) of BG, ST, KL WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 114

xiii

Texas Tech University, Leobardo Richarte-Delgado, August 2018

4. 10 Total biomass (gr; SEM) of BG, ST, KL WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 115

4. 11 Aboveground to belowground biomass ratio of BG, ST, KL and WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 116

4. 12 Water use efficiency (g H2O/g of dry biomass) of BG, ST, KL and WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA...... 117

5. 1 Number of tillers per plant evaluated at five sampling times of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG), and sideoats grama (ST), during the 2015 growing season growth under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA...... 138

5. 2 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of Alamo (AL) switchgrass plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA. .. 139

5. 3 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of Kanlow (KL) switchgrass plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA. .. 140

5. 4 Percentage of tillers in vegetative, elongation, flowering and seed set stage of cultivar I (CI) switchgrass plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA. .. 141

5. 5 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of cultivar II (CII), switchgrass plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA...... 142

5. 6 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of blue grama (BG) plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA...... 143

5. 7 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of sideoats grama (ST) plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA...... 144

5. 8 Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in Alamo switchgrass at five sampling dates during the 2015 growing season grown under greenhouse conditions...... 145 xiv

Texas Tech University, Leobardo Richarte-Delgado, August 2018

5. 9 Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in Kanlow switchgrass at five sampling dates during the 2015 growing season grown under greenhouse conditions...... 146

5. 10 Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in Cultivar I switchgrass at five sampling dates during the 2015 growing season grown under greenhouse conditions...... 147

5. 11 Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in Cultivar II switchgrass at five sampling dates during the 2015 growing season grown under greenhouse conditions...... 148

5. 12 Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in blue grama at five sampling dates during the 2015 growing season grown under greenhouse conditions...... 149

5. 13 Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in sideoats grama at five sampling dates during the 2015 growing season grown under greenhouse conditions...... 150

5. 14 Mean stage count (MSC) and standard deviation (SMSC) for Alamo switchgrass Alamo grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA...... 151

5. 15 Mean stage count (MSC) and standard deviation (SMSC) for Kanlow switchgrass grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA...... 152

5. 16 Mean stage count (MSC) and standard deviation (SMSC) for cultivar I switchgrass grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA...... 153

5. 17 Mean stage count (MSC) and standard deviation (SMSC) for cultivar II switchgrass grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA...... 154

5. 18 Mean stage count (MSC) and standard deviation (SMSC) for blue grama grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA...... 155

5. 19 Mean stage count (MSC) and standard deviation (SMSC) for sideoats grama grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA...... 156

5. 20 MSC of Alamo (AL), Kanlow (KL), sideoats grama (ST), cultivar I (CI) and cultivar II (CII) in relation to day of the year (DOY), evaluated under greenhouse conditions during the 2015 growing season, Lubbock TX, USA...... 157

Texas Tech University, Leobardo Richarte-Delgado, August 2018

CHAPTER I

INTRODUCTION

Proper grazing management is vital to healthy rangelands and producer profitability (Heitschmidt 1982). Currently there are rangelands in the US and the world where proper grazing management techniques have not been applied, causing economic and environmental problems. One of the best tools for improving grazing management is the implementation of grazing schemes. Those grazing schemes have to be designed to consider factors such as environmental conditions, type of grazing animal, plant species and, plant response to defoliation events during the growing season (Reardon and Merril,

1976; Reece et al. 1996; Norton 1998, Howery et al. 2000). Rangeland characteristics such as species composition, forage production, grazing utilization, and forage quality can be modified by intensity and timing of grazing (Robinson et al. 1952; Dovel 1996) but how those timing and grazing intensities impact grasses at the individual plant level, especially, those that have distinct morphological characteristics such as short-shoots and long-shoots is not well-known. Characterizing the developmental morphology of grasses over the growing season and recognizing the differential impacts that defoliation events have on them based on changes in their developmental cycle, might be very important aspect to consider before planning grazing schemes. Tall grasses respond in a different way than short grasses to defoliation events (Robinson et al. 1952; Branson 1956) but what is the magnitude of that difference in terms of biomass production, and during which developmental stage, are those differences more detrimental or beneficial for the plant?

Texas Tech University, Leobardo Richarte-Delgado, August 2018

I assessed those questions looking at grass total biomass production in three major components: aboveground biomass, which is related to light competition and forage production for cattle; crown biomass production which is related to grass energy storage and an indicator of next year potential biomass production; and root biomass production, which is related to access to water and nutrients. Considering the vital importance of knowing the developmental morphology of grasses to create successful grass management programs (Moore et al. 1991), there are just few studies focusing on this subject (Mitchell 1997; Hendrickson et al. 1998) and these were mainly conducted on mixed and tall grass prairie. There is not a comparative study where the developmental morphology of short, mid and tallgrass prairie grasses is measured under common conditions.

This study was designed to evaluate the developmental morphology and morphological changes of common warm season grasses used on Texas rangelands, as well as their biomass production and allocation in response to different defoliation intensities applied during critical developmental stages: vegetative, reproductive and post-reproductive. To accomplish my objectives, I designed two studies. The first was a one-year study conducted under greenhouse conditions during the 2015 growing season, where I evaluated grass species developmental morphology and morphological differences. The second study was designed to evaluate the response of aboveground and belowground biomass production of short, mid, and tall grasses to light and severe grazing utilizations at three phenological stages, conducted under field conditions during the 2015 and 2016 growing seasons.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Literature Cited

Branson, F.A. 1956. Quantitative effects of clipping treatments on five range grasses. Journal of Range Management. 92: 86-88. Dovel, R.L., 1996: Cutting height effects on wetland meadow forage yield and quality. Journal of Range Management. 49:151-156. Heitschmidt, R.K. Kothmann, N.M. Rawlins, W.J., 1982. Cow-calf response to stocking rates, Grazing systems and winter supplementation at the Texas Experimental Ranch. Journal of Range Managements 35, 204-210. Hendrikson, J.R., L. E. Moser., K.J. Moore, and SS. Waller. 1998. Morphological development of 2 warm-season grasses in the Nebraska Sandhills. Journal of Range Management. 51(14)456-462 pp Howery, L.D., J.E. Sprinkle, and J.E. Bowns. 2000. A summary of Livestock Grazing Systems Used on Rangelands in the Western United States and Canada. College of Agriculture and Life Scienses, University of Arizona (Tucson, AZ). 7 p. Mitchell. R.B., Moore, K. J., Lowell, E., Fritz, J. O., and Redfeaan, D. D. 1997. Predicting developmental Morphology in Switchgrass and Big Bluestem. Agronomy & Horticulture- faculty Publications. Paper 67. Norton, B.E., 1998. The application of grazing management to increase sustainable livestock production. Animal production in Australia. 22, 15-26. Reardon, P.O., Merril L.B., 1976 Vegetative response under various grazing management systems in the Edwards Plateau of Texas. Journal of Range Management. 29, 195- 198. Reece, P.E., Brummer, J. E., Engel, R. K., Northrup, B.K., Nichols J. T., 1996. Grazing date and frequency effects on prairie sandreed and sand bluestem. Journal of Range Management 49, 112-116. Robinson, R.R., V.G. Sprague, and A.G. Lueck. 1952. The effect of irrigation, nitrogen fertilization, and clipping treatment on persistence of clover and on total and seasonal distribution of yields in a Kentucky bluegrass sod. Agronomy Journal 44: 239-244. Moore, K.L., L.E. Moser, K. P.Vogel, S. S. Waller, B. E. Johnson, and J. F. Pedersen. 1991. Describing and quantifying growth stages of perennial forage species. Agronomy Journal. 83:1073-1077.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

CHAPTER II

LITERATURE REVIEW

Grasslands of North America

Rangelands are classified as all the areas of the world that are not barren deserts, farmed, or covered by bare soil, rock, ice or concrete (SRM 1989). Under this definition rangelands, include deserts, forests, and all-natural grasslands. Grasslands occupy around

40% of the worlds land area, excluding Antarctica and Greenland and around one billion people depend on them (Suttie et al 2005). In the United States, due to the diversity in climate, topography, and edaphic conditions, there are at least 15 different types of ecosystems under this classification (Holechek et al. 2003). A major percentage of the grasslands in North America are located in the center of the United States, known as the

Great Plains. This large amount of land is located east of the Rocky Mountains across the landscape and ends a little west the Mississippi River, and from Canada to Mexico in its north to south orientation (Shafer et al. 2014). The plains are made up of a broad range of ecosystems including rangelands, marshes, and deserts (Shafer et al. 2014). Plains has a distinct east-west gradient in average precipitation, with 300 mm in northern New

Mexico to almost 1000 mm in some areas in the tallgrass prairie at the most eastward end of the region (Holechek et al. 2003). This environment presents three distinguishing characteristics: 1) it exhibits a comparatively level surface of great extent, 2) it is largely treeless, and 3) it is a region where rainfall is insufficient for the ordinary intensive agriculture common to lands of a humid climate.

The Great Plains grasslands can be divided into three major areas due to changes in environmental conditions, mainly precipitation and evapotranspiration gradients,

Texas Tech University, Leobardo Richarte-Delgado, August 2018

which also define the type of vegetation, wildlife, and economic activities of the region.

The first of these areas is the shortgrass prairie, which is located on the west side of the

Great plains, on the east side of the Rocky Mountains. This area has the lowest annual precipitation regime, of the three regions ranging from 300 mm to 500 mm. The second area is the mid grass prairie, which is located between short and tallgrass prairie. Annual precipitation is higher than in the shortgrass prairie, ranging from 300 to 700 mm. The third area is the tallgrass prairie, located between the mid grass prairie and the eastern deciduous forest. This area receives the highest precipitation, ranging from 500 to 1000 mm. This difference in climate conditions, mainly available moisture, coupled with grazing pressure, promotes morphological adaptations for the grass species that dominate each portion of the Great Plains. The shortgrass prairie is dominated by short grasses such as blue grama (Bouteloua gracilis) and buffalograss (Bouteloua dactyloides) which are grazing tolerant. Mixed prairie is dominated by a mixture of short and midgrasses such as sideoats grama (Bouteloua curtipendula), blue grama, buffalograss, little bluestem (Schizachyrium scoparium) which have a moderate degree of tolerance to severe grazing pressures. Finally, tallgrass prairie present tall grass species such as little bluestem (Schizachyrium scoparium), which dominates the uplands, and big bluestem

(Andropogon gerardii), which dominates the lowlands. These two species comprise about

80% by weight of tallgrass prairie climax composition (Holechek et al. 2003).

Shortgrass prairie

The shortgrass prairie extends from northern New Mexico into northern

Wyoming. Parts of this type are scattered through central Wyoming, western South

Dakota, and southern Montana. Because of low precipitation, much of this area was not

Texas Tech University, Leobardo Richarte-Delgado, August 2018

cultivated and remains as rangeland. Shortgrass prairie is the third most important western range type from the standpoint of livestock production. The climate of the area is characterized by cool winters and warm summers. Annual precipitation ranges between

300 mm and 500 mm with 60% to 75% of precipitation coming from slightly rain evenly distributed over the summer. This type of climate is favorable to warm-season grasses such as blue grama, which have shallow but extensive root systems.

Soils of this type are largely Mollisols. However, sandy soils in the order Entisol and clay soils in the order Vertisol are scattered through the area. Midgrasses such as little bluestem occupy the sandy soils, while the heavy clay soils are dominated by western wheatgrass (Pascopyrum smithii). Medium-textured soils support primarily blue grama and buffalograss. The vegetation of the shortgrass prairie is relatively simple, since blue grama and buffalograss compromise 70% to 90% of the composition by weight. The third grass species associated with this type is western wheatgrass. Grass species in this area evolved under grazing pressure. As a result, they have morphological and physiological characteristics that make them quite resistant to grazing. An important shrub associated with this type is winterfat (Ceratoides lanata) (Holechek et al. 2003).

Mixed grass prairie

Mixed grass prairie can be divided into Southern Mixed Prairie and

Northern mixed prairie (Holechek et al. 2003).

Southern mixed prairie

The southern mixed prairie is the most important western range for livestock production. It extends from eastern New Mexico to eastern Texas and from southern Oklahoma to northern Mexico. Precipitation varies from 300 mm in eastern

Texas Tech University, Leobardo Richarte-Delgado, August 2018

New Mexico to 700 mm in central Texas. Over most of the area, the frost–free period is at least 180 days. Soils are primary Mollisonls, Entisols, and Aridsols because of the wide range of soli land climatic conditions, both productivity and vegetation are variable.

The southern mixed prairie has a long history of grazing, dating back to the early seventeenth century when the Spaniards started bringing livestock into the area. This land type also received considerable use by buffalo (Bison bison). Most of the grasses associated with this type evolved with grazing and are relatively grazing-resistant.

Important grass species are; blue grama, buffalograss, little bluestem, vine mesquite

(Panicum obtusum), various threeawn species (Aristida sp.). Areas with sandy, deep soils occur through the southern mixed prairie. Mesquite (Prosopis glandulosa) and several others noxious species create serious problems to livestock producers over most of the southern mixed prairie, particularly when overgrazing occurs (Holechek et al. 2003).

Northern mixed prairie

The northern mixed prairie is that portion of the Great Plains extending northward from the Nebraska-south Dakota state lines. This type includes a western half of North and South Dakota and South Dakota, the eastern two-thirds of Montana, the northern one-fourth of Wyoming, and the southeastern part of Alberta and southern Saskatchewan in Canada. Climate of this region is characterized by long severe winters with warm summers. Precipitation ranges from 300 mm to 650 mm, with two-thirds coming during the summer and the rest during the spring. Average frost-free period ranges between 140 and 100 days depending on location. Major soils associated to this area are Mollisols. The northern mixed prairie supports the highest diversity of grasses of all western range type it has short, mid, and tallgrasses as well as both cool and warm season grasses. Cool

Texas Tech University, Leobardo Richarte-Delgado, August 2018

season grasses such as bluebunch wheatgrass (Pseudoroegneria spicata) and various bluegrasses (Poa spp.) provide a good early spring feed. Little bluestem, blue grama, and sideoats grama provide high-quality summers and fall forage (Holechek et al. 2003).

Tallgrass prairie

The tallgrass prairie is located in the central United States east of the mixed and shortgrass prairies and west of the deciduous forest. The major remaining range areas of tallgrass prairie are the Flint Hills of eastern Kansas and the Osage Hills of Oklahoma.

These two areas are continuous and remain because of thin, rocky soils. The climate of the tallgrass prairie is sub-humid, mesic, and temperate. Along the southeastern boundary, precipitation averages 1000 mm, 500 mm in the northern portions, boundary.

Higher precipitation is required for tallgrass prairie in the south than in the north because of higher precipitation. Most of the precipitation (75%) comes during the summer growing season. The soils are primarily Mollisols. These are deep, very fertile, and largely free from rocks. The Topography tends to vary from flat rolling hills. Tallgrass prairie evolved under grazing by wild ungulates (American bison). It is grazing resistant due to the high amount and favorable timing of precipitation. Four grass species that characterized the tallgrass prairie are little bluestem, which dominates the uplands, and big bluestem, which dominates the lowlands, indiangrass (Sorghastrum nutans) and switchgrass (Panicum virgatum) are the other two major grasses (Holechek et al. 2003).

Grass species description

Grass species considered in this study are representative of the three major grasslands areas of North America. Blue grama was used as the representative species from the shortgrass prairie, sideoats grama as representative from the mixed grass prairie;

Texas Tech University, Leobardo Richarte-Delgado, August 2018

and we used four switchgrass types (Alamo, Kanlow, and two new recently reported

[Quitaque canyon I and II]) representing the tallgrass prairie. WWB- Dahl was included as a nonnative grass which is being established in the southern Great Plains due to its grazing tolerance and biomass production abilities.

Blue grama

Blue grama (Bouteloua gracilis (Willd. Ex Kunth) lag. Ex Griffiths (BOGR2) is a major warm season grass found through the Great Plains. The plant is fairly short, reaching 25 to 50 cm, with narrow basal leaves of 8 to 15 cm. Blue grama grows in definite bunches and reproduces by tillering and by seed. Blue grama can be found growing in association with buffalograss, western wheatgrass, needlegrass (Nassella pulchra), and in some areas the bluegrasses. Blue grama has good drought, fair salinity, and moderate alkalinity tolerances. In dormant state, it will tolerate burning. It does not tolerate dense shade, flooding, and high-water table or acid soils (Natural Resources

Conservation Service 2002).

Sideoats grama

Sideoats grama (Bouteloua curtipendula (Michx.)Torr.) is a deep rooted perennial grass. The crown will spread very slowly by means of extremely short, stout rhizomes. A midgrass, it has rather wide leaves and very distinct inflorescence consisting of a zigzag stalk with small compressed spikes arranged at even intervals, in vegetative stage, the grass is easily recognized by the long, evenly spaced hairs attached to the margins of the leaf near its base. Sideoats grama possesses the C4 photosynthetic pathway common to warm-season grasses (Waller and Lewis 1979). It has a widespread distribution eastward from the Rocky Mountains to near the east coast except in the southeast. This species

Texas Tech University, Leobardo Richarte-Delgado, August 2018

grows effectively in the drier mid-grass prairie section of the Great Plains that has an annual rainfall of 300-500 mm and occurs naturally in mixed stands with the blue grama and little bluestem, it is better adapted to calcareous and moderately alkaline soils than to neutral or acidic soils (Leithead et al. 1971).

Switchgrass

Switchgrass (Panicum virgatum) is a native in the continental United States except for California and the Pacific Northwest. It is a perennial, coarse, bunch grass that grows from 0.5 to 3.0 m tall, with depth roots up to 3 m (Porter 1966; Moser and Vogel

1995). Switchgrass leaves tend to be erectophile and may have stomata on both sides

(amphistomic). Variation in this latter trait has not been related to the upland/lowland categories (Awada et al. 2002). Rhizomes vary in how extensively they grow, with consequences for general plant habit. Plants that produce shorter rhizomes form tight bunches, while plants with more active rhizomes may be essentially sod forming (Beaty et al. 1978). It is distributed from Canada to Central America and from the Atlantic coast to Nevada in habits varying from dry uplands to wet wetlands (Hitchcock 1951).

Switchgrass is successful in occupying sites with different geographical and environmental conditions because it poses a high degree of variability (Porter 1966). This species is one of the most important dominant species of the tallgrass prairie of North

America (Weaver and Fitzpatrick 1934; Weaver 1954). When used as forage, switchgrass is usually grazed (Balasko et al. 1984; Jung et al. 1988; Anderson 2000; Moore et al.

2004); but it can also be used for hay (Balasko and Burner 1981; Sanderson 2000;

Mclaughlin et al. 2004) and silage (Burns et al. 1993). In addition to its wide geographic distribution, switchgrass exhibits great adaptability to diverse edaphic conditions. Porter

Texas Tech University, Leobardo Richarte-Delgado, August 2018

(1966) grouped switchgrass populations into two broad “forms” based on their usual position in the landscape. The “lowland” form was associated with lower, more hydric locations, while the “upland” form was more common at higher, more mesic sites.

Geographically, populations with the upland form tend to be better adapted from mid-to northern latitudes, while lowland types are typically better adapted to lower latitudes. In this study, we are evaluating four switchgrass cultivars which are described below:

Switchgrass Quitaque Canyon

This switchgrass cultivar was collected three years ago in the Quitaque Canyon near Amarillo, Texas. A couple of plants were collected from two mother plants on the field. Even though both plants seemed very similar, we suspect that they might be different ecotypes based on some morphological characteristics. For instance, one of them which are being identified as a cultivar I (CI) is taller and present thicker stems than the other one identified as cultivar II (CII). Cultivar I was also easier to propagate base on personal observations. Currently, there is no information available about these switchgrass cultivars. For that reason one of the objectives of this project is to evaluate their morphological characteristics, developmental morphology, and response to clipping intensities across the growing season in relation to two well-known switchgrass cultivars

(Alamo and Kanlow) in order to find desirable forage production traits.

Switchgrass Alamo

Alamo is a lowland type switchgrass was released from the USDA Natural

Resources Conservation Service (NRCS) James E. ‘Bud’ Smith Plant Materials Center in

Knox City, Texas in 1978. Alamo was originally collected along the Frio River in Live

Oak County, Texas. Alamo is adapted throughout the majority of the United States.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Performance is the best on moderately deep to deep sandy to clay loam soils (Natural

Resources Conservation Service 2012).

Switchgrass Kanlow

Kanlow is a lowland type switchgrass that was released as a cultivar in 1963 in cooperation with the Kansas Agricultural Experiment Station (KAES) and the

Agriculture Research Service. Kanlow is 6 to 8 feet tall at maturity. It has deep root system 3 m or more and is strongly rhizomatous. The original germoplasm that produced

Kanlow was collected by Soil Conservation Service (SCS) employees in a lowland area near Wetumka, Oklahoma in 1957. Plants were selected for leafiness, vigor, and retention of green matter late in the fall (Natural Resources Conservation Service 2012).

WW-B. Dahl [Bothriochloa bladhii (Retz) S. T. Blake]

WW-B Dahl, formerly known as WW-857 is one of the most recent old-world bluestems (OWB) cultivars released in Texas. It acquired its name in honor of the late Dr.

Bill Dahl, long time professor of the Department of Range and Wildlife Management at

Texas Tech University (Dewald et al. 1995). This cultivar has its origin in the grazing lands of Pakistan (Foy et al. 1987). However, in 1960 WW-Dahl seed was collected in

Manali, India and brought to the Oklahoma Agricultural Experimental Station at

Stillwater, OK where it was grown under the designation of A-8965. After 15 years of adaptation, it was selected as a superior OWB and released in 1994 jointly by the USDA-

ARS, USDA-SCS, Texas Tech University, and the Texas Agricultural Experimental

Station to be used in the central and southern Texas (Bell and Caudle 1994; Dewald et al.

1995). WW-Dahl Old World bluestem is a warm-season, tufted, perennial bunchgrass with an upright growth habit, dark green forage. Average plant height is 0.7 to 0.9 m with

Texas Tech University, Leobardo Richarte-Delgado, August 2018

seed stalks of 1.25 to 1.75 m. WW-B Dahl OWB is well adapted to the High Plains region, but it has been more successful in the southern high plains and central southern

Texas (McCollum 2000). It is not salt tolerant and requires well-drained soils in areas receiving from 15 to 35 inches of annual rainfall (Bell and Caudle 1994). This cultivar is well adapted to sandy loam and clay soils with a pH from 6.7 to 8.4

Clipping to Simulate Grazing

Clipping is often used in grazing studies to simulate the effects of grazing animals on plants, the assumption is that plants respond to clipping in the same way as regular grazing. Clipping consists of removal of photosynthetic tissue from plants at various heights and frequencies (Albertson et al. 1953). The use of clipping treatments to simulate the effects and responses of grazing by animals on plants has a long history

(Jones et al. 1937; Brant and Ewalt 1939) and even today clipping is used regularly to simulate grazing effects (Herrero-Jauregui et al. 2014), although some researchers have questioned the validity of using data obtained by clipping for predicting plants response to grazing (Brown and Munsell, 1945; Castle 1953), but research studies provide conflicting results. Some articles report similar biomass production (Robinson et al.,

1937; Brandt and Ewalt 1939) while in others production decreased (Bryant and Blaser

1967). Both grazing and clipping involve the removal of plants biomass (Herrero-

Jauregui et al. 2014), but the two methods differ as to which tissues are removed. These aspects are related to the action of the grazing animals over the individual plant and across the land scape. Burritt (2015), the main differences between grazing and clipping as: 1) livestock tend to graze plants to variable heights, 2) grazing removes less plant material, 3) animals remove specific parts rather than the whole plant, 4) plant size and

Texas Tech University, Leobardo Richarte-Delgado, August 2018

form might change because of selection of certain individual plants within a species, 5) differential effect on build-up of plant litter and 6) intraspecific competition within a plant community, is affected differently. Xiliang et al. (2015) also pointed out that grazing is not completely replicated by clipping because in clipping the influence of trampling and excrement and urine disposal are not taken in consideration. Other authors also consider tearing action as and aspect that is not present in clipping and that might negatively affect plant regrowth after grazing (Bryant and Balser 1967).

Clipping and forage yield production

Plant species differ in their ability to tolerate defoliation (Dahl and Hyder 1977).

The response of grasses to clipping depends on several factors such as timing, intensity, frequency, environmental conditions, and plant morphology (Lang and Barnes, 1942;

Albertson et al. 1953) and their relative effects on grass biomass production can vary over each one of the major plant structures of grasses. These major grass structures are aboveground biomass (forage), crown (transition zone between tiller and roots), and belowground biomass (roots). Most scientific studies focus on defoliation effects on aboveground biomass because this information is easier to gather and is a clear indicator of forage production. Some studies have documented that with an increase in frequency and amount of tissue removed by clipping there a decrease in grass production on midgrasses (Canfield 1939; Weaver and Hougen 1939; Stoddart 1946; Whitman and

Helgeson 1946; Baker et al. 1947; Blaisdell and Pechanec 1949; Kennedy 1950; and

Albertson, et al. 1953). However, the response of shortgrasses to frequency and intensity of clipping is more variable. Lang and Barnes (1942) found that clipping short grasses tends to increase production. According to Branson (1956) grasses with elevated

Texas Tech University, Leobardo Richarte-Delgado, August 2018

vegetative apical meristems (midgrasses and tallgrasses) generally tend to be less resistant to grazing. Other studies have shown that clipping height generally had a smaller influence on forage yield than clipping date. Dovel (1996) found that forage yields of grass-sedge and sedge associations decreased linearly as clipping height increased. He found that raising the clipping height from 5 to 15 cm reduced total forage yields by 63% and 52% for sedge and grass-sedge associations respectively. In a study of the effect of clipping height on Kentucky bluegrass (Poa pratensis L.)-white clover (Trifolium repens) pasture, Robinson et al. (1952) observed an increase on forage yield as clipping height decreased. Frequency of clipping is another factor affecting forage yield, Aldous (1930) found that vegetation removal at short intervals caused a decrease in grass plant density compared to the same amount removed but at longer intervals. On the other hand, moderately grazing pastures seem to have a positive effect on yield production. Tomarek

(1948), in a study on western Kansas, reported grater yield production on moderately grazed pastures than on the ungrazed or heavily grazed pastures.

There are some studies reporting the effects of defoliation on roots, but the information is more limited than that related to the aboveground portion of grasses. Both root and shoot growth are inversely proportional to the intensity of clipping (Graber

(1931; Branson 1956). Heavy clipping intensities may to have a beneficial effect on root production in comparison to moderately and no clipped plants, over short time periods, but after some years heavily clipped intensities tend to reduce root production in comparison to areas unclipped or moderately clipped (Albertson et al. 1953). Moderate clipping intensities may increase root production over time compared to unclipped treatments. Few studies report on the effect of defoliation on crown biomass production

Texas Tech University, Leobardo Richarte-Delgado, August 2018

of grasses, and most of them were performed under greenhouse conditions (Staton 1983;

Villanueva 2008). Timing of defoliation also has a substantial impact on grass production. In general, grasses respond better when defoliated during early growth stages or late in the growing season, and tend to reduce forage production or increase mortality when defoliation occurs during active reproduction stage (Stoddart 1946).

Developmental morphology and its importance in grasses

Several vital processes in grasses such as forage production and energy balance are mandated by developmental morphology processes occurring over the growing season. These series of structural changes displayed by organisms from inception to maturity and growth are collectively referenced as developmental morphology (Esau

1960). The aboveground portion of grasses are composed of multiple tillers originating from axiliary buds. These tillers consist of a series of phytomers successively differentiated from an apical meristem. Phytomers are defined as the basic growth unit in grass and consist of a blade, sheath, node, internode and axiliary bud (Hyder 1972; Briske

1991). An accurate identification of the growth stage of perennial grasses is an important consideration in the application and timing of forage management practices such as plant establishment, timing of grazing or defoliation, prescribed burning, pesticide application, and fertilization (Moore et al. 1991). Therefore, management activities especially grazing management schemes should be designed base on plant development (Frank et al. 1993).

In grasses, developmental morphology determines plant architectural organization, influences accessibility and palatability to herbivory and affects regrowth after defoliation (Briske 1991). Developmental morphology in grasses is dynamic (Moore and

Moser 1995), affected by genetic and environmental factors (Hendrikson et al. 1998).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

There are marked differences among short, mid, and tallgrasses in terms of grazing resistance which are linked to developmental morphology, one of the most important of which is grazing tolerance. Most short and midgrasses such as blue grama and sideoats grama, produce short shoots throughout most of the growing season. Those short shoots maintain their apical meristem close to the soil level and are inaccessible to cattle, therefore, after grazing, the apical meristem is active and producing new material, generating a faster recovery process after defoliation. On the other hand, long-shoot plants, which are the main types present in most of the tall grasses (Branson 1953) tend to elevate their apical meristem early in the growing season exposing its apical meristem to potential removal by grazing. Once an apical meristem is removed, the tiller is not able to keep growing and forage production stops (Dahl 1995). This is one of the main reasons why these species tend to decrease under heavy grazing pressure and being replaced by mid and short grasses (Branson 1953). Eventually, all grass types will elevate their apical meristem once floral induction starts but in the case of short grasses this will happened later in the growing season coffering greater grazing resistance over tall grasses. There are several methods to quantify developmental morphology in annual species (Haun

1973; Large 1954; Simmons et al. 1985; Ritchie et al. 1989). However, perennial grasses differ from annual species making developmental morphology harder to quantify. It was not until Moore et al. (1991) developed a methodology to quantify developmental morphology that the attention was focused on range grasses (Mitchell 1997; Hendrickson et al. 1998; Villanueva 2008).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Literature Cited

Aldous, A.E. 1930. Effect of different clipping treatments on the yield and vigor of prairie grass vegetation. Ecology 11: 752-759. Albertson, F.W., A. Riegel, and J. L. Launchbaugh. 1953. Effects of different intensities of clipping on short grasses in West-central Kansas. Ecology. 34:1-20. Anderson, B.E. 2000. Use of warm-season grasses by grazing livestock. In: Native Warm-Season Grasses: Research Trends and Issues. pp. 147–158. Anderson, B. E. and Moore, K. J., Eds., CSSA Special Pub. No. 30. Crop Science Society of America, Madison, WI. Arredondo, J.T., and Douglas A. Johnson. 1998. Clipping effects on root architecture and morphology of 3 range grasses. Journal of Range Management. 51(2): 207-213. Baker, M.L., V. H. Arthaud, E. C. Conrad and L. C. Newell. 1947. Effects of time of cutting on yields and feeding values of prairie hays. Univ. of Nebr. Bull. 385. Balasko, J.A., and Burner, D.M. 1981. Effects of cutting management on yield, quality, and vigor of switchgrass grown without fertilization. Agron. Abstr. Madison, WI Balasko, J.A., D.M. Burner, and W.V. Thayne. 1984. Yield and quality of switchgrass grown without soil amendments. Agron. J. 76: 204208. Beaty, E.R., J.L. Engel, and J.D. Powell. 1978 Tiller development and growth in switchgrasses. J. Range Management. 31:361:365 Belsky A.J. 1986. Does herbivory benefit plants? A review of the evidence. Am. Nat 127: 870-892. Bell, J.R. and D. M. Caudle. 1994. Management of Old World Bluestems. Established under the Conservation Reserve Program in Texas. Soil Conservation Service. Temple, TX. Blaisdell, J. And J.D. Pechanec. 1949. Effects of herbage removal at various dates on vigor of bluebunch wheatgrass and arrowleaf balsam root. Ecology 30 (3): 298- 305. Blackstock, D.A., E. R. Blakley., C. T. Landers., W. M. Koos., and L. A. Putman. 1979. United States Department of Agriculture-Natural Resources Conservation Service Soil Survey of Lubbock County, TX. Bradbury, Stand. 2007. Ecological Site Description. United States Department of Agriculture-Natural Resources Conservation Service. http://esis.sc.egov.usda.gov/Welcome/pgApprovedSelect.aspx?type=ESD. July 03, 2010. Branson, F.A. 1953. Two new factors affecting resistance of grasses to grazing. J. Range Manage. 6:162-121.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Brant, P.T., and H. P. Ewalt. 1939. Pasture yields as measured by clip plots by grazing dairy cows. J. Dairy Sci. 22:451-452 Brown, B.A., and R. I. Munsell. 1945 Deterioration of clipped caged areas in permanent pastures J. Am. Soc. Agron. 37:542-548 Briske, D.D. 1991. Developmental morphology and physiology of grasses. p. 85-108. In: Grazing Management: An Ecological Perspective. R. K. Heitschmidt and J.W. Stuth (eds.) Timber Press, Portland Oregon. Bryant, H.T. and R. R. Blaser. 1967. Effects of clipping compared to grazing of Ladino Clover-orchardgrass and Alfalfa-orchardgrass mixtures. American Society of Agronomy. Vol 60 (2). 165-166. Bukey, F.S., and J. E. Weaver. 1939. Effects of frequent clipping on the underground food reserves of certain prairie grasses. Ecology 20: 246-252 Burns, J.C., Fisher, D. S., and Pond, K. R. 1993. Ensiling characteristics and utilization of switchgrass preserved as silage. Postharvest Biol. Tech. 3: 349– 359. Burrit, B. 2015. Livestock Grazing in Public Lands https://publiclandgrazing.org/clipping-does-not-simulate-grazing/ (accessed 21 September 2017). Canfield, R.H. 1939. The effect of intensity and frequency of clipping on density and yield of black grama and tobosa grass. U. S. Dept. Agr. Tech. Bul. 681. Casler, M.D., Vogel, K. P., Taliaferro, C. M. and Wynia, R. L. 2004. Latitudinal adaptation of switchgrass populations. Crop Sci. 44: 293–303 Castle, M.E. 1953. Grassland production and its measurement J. British. Grassland Soc. 8(3):195-211 Crafs, R.E. and G. E. Glendening. 1942. How to graze blue grama on southwestern ranges. U. S. Dept. Agr. Leaflet 215: 1-8. Crawley, M.J. 1983. Herbivory: The dynamics of animal-plant interactions. Blackwell: London Scientific Publications. Dahl, B.E., 1995. Developmental Morphology of plants. p 22- 55. In: D. J. Bedunah and R.E. Sosebee (Eds.). Wildland Plants: Physiology Ecology and Developmental Morphology. Society for Range Management. Denver, CO. Dahl, B.E., and D. N. Hyder. 1977. Developmental morphology and management implications. P. 258-290. in R. E. Sosebee (ed.), Rangeland plant physiology. Soc. Range Management. Denver, CO. Dewald, C.L., P. L. Sims, and W. A. Berg. 1995. Registration of “WW-B. Dahl” Old World Bluestem. Crop Sci. 35:937. Esau, K. 1960. Anatomy of seed plants. Wiley & Son, New York. 376p. 19

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Ehrenreich, J.H. 1959. Burning and clipping on growth of native prairie in Iowa. Journal of Range Management.12 (3): 133-137. Frank, A.B., K. H. Sedivec, and L. Hofmann. 1993 Determining grazing redlines from native and tame pastures. North Dakota State Univ. Extension Serv. Bull. R-1061, Fargo, ND. Floyd, E.K., and Harold H. Hopkins. 19961. Content of underground parts of grasses as affected by clipping. Journal of Range Management. 14(1): 9-12. Graber, L.F., N. T. Nelson, W. A. Luekel, and W. B. Albert. 1927. Organic food reserves in relation to the growth of alfalfa and other perennial herbaceous plants. Wisconsin Agr. Exp. Sta. Res. Bull. 80. 128 p. Haun, J.R. 1973. Visual quantification of wheat development. Agron. J. 65:116-119. Hitchcock and Chase 1951) Hitchcock, A. S. 1951. Manual of the grasses of the U.S. USDA Misc. Publ. 200. 2nd ed. U.S Gov. Print. Office, Washington, D.C. Herrero-Jáuregui C, Schmitz M, Pineda F. 2014. Effects of different clipping intensities on above-and below-ground production in simulated herbaceous plant communities. Plant Biosystems-An International Journal Dealing with all Aspects of Plant Biology. 150 (3): 468-476 Hyder, D.N. 1974. Morphogenesis and management of perennial grasses in the Unites States, pp. 89-88. In: Plant morphogenesis as the basis for scientific management of range resources. Proceedings of the workshop of the U.S/Australian rangelands panel. Berkeley Calif. March 29-April 5, 1971. U.S. Dep. Agri. Misc. Public. 1271. Holechek, J.L., Rex D. Pieper, and Carlton H. Herbel. 2003. Range management principles and practices. Fifth edition. Jones, T. R., Ewalt, and J. R. Haag 1937 A comparison of pasture returns from actual grazing and clipping plot. Jung, G.A., J.A. Shaffer, and W. L Stout. 1988. Switchgrass and big bluestem responses to amendments on strongly acid soil. Agron. J. 80:669-676. Kennedy, W.K. 1950. Simulated grazing treatments, effect on yield, botanical composition, and chemical composition of a permanent pasture. Cornell Univ. Agr. Exp. Sta. Memoir 295 Lang, Robert, and O.K. Barnes. 1942. Range forage production in relation to time and frequency of harvesting. Wyo. Agr. Expt. Sta. Bull. 253: l-32. Large, E. C. 1954. Growth stages in cereals, illustration of the Feekes scale. Plant Phatol. 3:128-129.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Leithead, H.L., Y.L. Yarlett, and T.N. Shiflet. 1971. 100 native forage grasses in 11 southern states. USDA-SCS Agric. Handb. 389. U.S. GOV. Print Office. Washington,D.C. Ludvíková, V, Pavlů VV, Gaisler J, Hejcman M, Pavlů L. Long term defoliation by cattle grazing with and without trampling differently affects soil penetration resistance and plant species composition in Agrostis capillaris grassland. Agriculture, Ecosystems & Environment. 2014;197(12):204–11. McLaughlin, M.R., Fairbrother, T. E., and Rowe, D. E. 2004. Nutrient uptake by warm- season perennial grasses in a swine effluent spray field. Agron. J. 96: 484–493. Moore, K.J., White, T. A., Hintz, R. L., Patrick, P. K., and Brummer, E. C. 2004. Sequential grazing of cool- and warm-season pastures. Agron. J. 96: 1103–1111. Moore, K.L., L.E. Moser, K. P.Vogel, S. S. Waller, B. E. Johnson, and J. F. Pedersen. 1991. Describing and quantifying growth stages of perennial forage species. Agronomy Journal. 83:1073-1077. Moore, K.J., and L. E. Moser. 1995. Quantifying developmental morphology of perennial plants. Crop sci. 35: 37-47. Moser, L.E., and K.P. Vogel. 1995. Switchgrass, big bluestem, and indiangrass. P. 409- 420 in R.F. Branes et al. (ed.) Forages: An introduction to grassland agriculture. 5th ed. Iowa State Univ. Press., Ames. Oesterheld, M., McNaughton S. J. 1991. Effects of stress and time for recovery on the amount of compensatory growth after grazing. Ocelogia 85:305-313. Porter, C. 1966. An Analysis of Variation Between Upland and Lowland Switchgrass, Panicum Virgatum L., in Central Oklahoma. Ecology, 47(6), 980-992. Release brochure for Kanlow switchgrass (Panicum Virgatum) 2012. USDA-Natural Resources Conservation Service. James E. ”Bud” Smith Plant Material Center, Knox City, TX 79529. May 2012 Release brochure for Alamo switchgrass (Panicum Virgatum). 2012. USDA-Natural Resources Conservation Service. James E. ”Bud” Smith Plant Material Center, Knox City, TX 79529. May 2012 Ritchie, S.W., J.J. Hanway, and G.O. Benson. 1989. How a corn plant develops, Special Rep. 48, Extension Serv., Iowa State Univ., Ames. Robinson, R.R., H. Pierre, and R. A., Akerman. 1937. A comparison of grazing and clipping for determining the response of permanent pastures to fertilization. J. Am. Soc. Agron. 29:349-359. Sanderson, M.A. 2000. Cutting management of native warm-season perennial grasses: Morphological and physiological responses. In: Native Warm- Season Grasses: Research Trends and Issues., pp. 133-146.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

SAS Institute Inc. 2012. Using JMP 10. Cary, NC: SAS Institute Inc. Sears, P.D., V.C. Goodall, and P.P. Newbold. 1948. The effect of sheep droppings on yield, botanical composition, and chemical composition of pasture. New Zeland J. Sci. and Tech. 30:231-250. Shafer, M.D. Ojima, J.M. Antle, D. Kluck, R.A. McPherson, S. Petersen, B. Scanlon, and K. Sherman, 2014: Ch 19: Great Plains. Climate Change Impacts in the United States: The Third National Climate Assessment, J.M. Melillo, Terese (T.C.) Richmond, and G.W. Yohe, Eds., U.S. Global Change Research Program, 441-461. Simmons, S.R., E.R. Oelke, and P.M. Anderson. 1985. Growth and Development of spring wheat. Univ. of Minnesota Agric. Extension Folder AG-FO2547. Minneapolis, MN. SRM. 1989. A glossary of terms used in range management, 3rd ed. Soc. Range Manage., Denver, CO. Stoddart, L.A. 1946. Some physical and chemical responses of Agropyron spicatum to herbage removal at various season. Utah Agr. Expt. Sta. Bull. 324. Stanton, N. 1983. The Effect of Clipping and Phytophagous Nematodes on Net Primary Production of Blue Grama, Bouteloua gracilis. Oikos, 40(2), 249-257. Society for Range Management. 1989. A glossary of terms used in range management. 3d ed. Society of Range Management, Denver CO. Suttie, J.M., Reynols S.G, Botello C. Eds. 2005. Grasslands of the World. Food and agriculture organization of the United Nations, Plant production and protection Series (Food Agriculture Organization, Rome), No. 34. Tomanek, G.W. 1948. Pasture types in western Kansas in relation to intensity of utilization in past years. Fort Hays Kansas State Coll. Studies No. 13: 171-196. USDA-Natural Resources Conservation Service. 2002. Plant fact sheet blue grama (bouteloua gracilis). Villanueva-Avalos, J.F. 2008. Effect of defoliations patterns and developmental morphology on forage productivity and carbohydrates reserves in WW-B Dahl grass [Bothriochloa bladhii (RETZ) S.T. BLAKE]. Ph. D. Dissertation. Texas Tech University. 311 p. Waller, S.S., and J.K. Lewis. 1979. Occurrence of C3 and C4 photosynthetic pathways in North American grasses. J. Range Manage. 32:12-82. Weaver, J.E. and V.H. Hougen. 1939. Effect of frequent clipping on plant production in prairie and pasture. Amer. Midl. Naturalist 21: 396-414.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

West Texas Mesonet. 2015. http://www.mesonet.ttu.edu/mesonet-precipitation.htm (accessed 20 May 2015). Whitman, W.C., and E.A. Helgeson. 1946. Range vegetation studies. N. Dakota Agr. Expt. Sta. Bull. 340. Xiliang, L.Z. Wu., X. Hou., W. Badgery, H. Gou, Q. Zhao, N. Hu, J. Duan. W. Ren. 2015. Contrasting Effects of Long-Term Grazing and Clipping on Plant Morphologicla Plasticity: Evidence from Rhizomatus Grass. Plos one. 10(10).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

CHAPTER III

BIOMASS ALLOCATION PATTERNS IN SHORT, MID, AND TALL GRASS

SPECIES OF NORTH AMERICA

Abstract

There are three main morphological grass types which dominate the rangelands of

North America. Morphological differences among these grasses might influence biomass allocation patterns to the main grass structures (aerial tillers, crown and roots) as a result of resource limitation. The objective of this study was to identify biomass allocation patterns among plant structures in short, mid and tall grass species. This study was performed during the 2015 and 2016 growing seasons under field conditions. Species evaluated were blue grama, sideoats grama, switchgrass cultivar Kanlow, as common species of the short, mixed and tallgrass prairie of North America, respectively. In addition, we used WW-B. Dahl as reference species due to its high productivity. 21 plants per species were established in 19-L pots and grew until biomass collection. Plants were harvested during the vegetative, reproductive and post-reproductive phenological stages. Total plant biomass was separated into aerial tillers, crown and roots. An analysis of variance was conducted to detect differences in biomass allocation means amount among grass structures. There were significant differences in the amount and percentage of biomass allocated to each grass structure. Results showed that regardless of phenological stage, all grasses, besides KL, allocated significantly higher biomass portions to the aerial tillers, followed by roots and finally crown. Even though roots allocated higher biomass than crowns, there was no significant difference between them in most of the species. WB was the species which produced significantly higher total

Texas Tech University, Leobardo Richarte-Delgado, August 2018

biomass. Biomass differences between tall grass KL and mid grass ST were not as significant as we expected, finally BG presented the lower biomass production all he species. In most of the cases biomass allocation patterns followed our hypothesis; however, KL significantly allocated higher biomass to the belowground portion, even though KL is tall grass species we expected higher biomass in the aboveground portion.

Our results suggested that biomass accumulation in grass structures is a dynamics process affected by species and phenological stage.

Introduction

In north American grasslands there are three main grass morphological types, short, mid and tall grasses midgrass, we presume that each one of these types present different strategies in terms of resources allocations which provide them different advantages to dominate a given area. Short grasses dominate arid areas, mid grasses the transition zone between arid and mesic zones, finally tall grasses dominate most mesic zones. This assumption is based on Tilman (1988) postulates, he stated that “due to the physical separation of above and belowground resources, plants face an unavoidable trade-off between the abilities to compete for these resources: in order to obtain a higher portion of one resource plants must allocate more biomass to structures involved in the acquisition of that resource at the expense of allocation of biomass to structures involved in the acquisition of another resources” (p. 319)”. As these morphological grass types dominate areas where the supply of resources varies so biomass allocation patterns among grass structures should vary too. Traditionally, grass structures have been divided into aboveground biomass (aerial tilers) and belowground biomass (crown and roots).

Most of the studies do not make a distinction between crown and roots considering both

Texas Tech University, Leobardo Richarte-Delgado, August 2018

the belowground portion (Shuster 1964; Aerts et al. 1990; Herrero-Jauregui 2016; Olff et al. 1990, McNaughton et al. 1998, Snyman 2003): however, a more accurate way to understand biomass allocation to structures involved in resource acquisition might be by the separation of belowground biomass into crown and roots (Stanton 1983, Milchunas and Lauenroth 2001). Since both structures are very distinctive and perform distinct roles in the plant resource acquisition process. Roots are in the deeper portion of the soil profile, and are these in charge of nutrients and water acquisition, soil development and stability (Bartos and Sims 1974). In contrast, crown does not have a significant role in the nutrient acquisition process, considering that its main function is to store carbohydrates as well as the production of new tillers (Derengibus 1982). Roots and crowns represent a substantial proportion of the total biomass in grassland ecosystems (Caldwell 1987), however they are not as frequently study as the aboveground section (Chapin et al. 1987) which has a direct economic importance to grazing management systems (Neary et al.

1999). Fewer information is available on roots and especially on crowns, being the main reasons laborious and inaccurate sampling techniques (Richards 1984; Flores et al. 2013).

Even nowadays, it is not well understood how total biomass production in grasses is distributed among plant structures, and how those allocation patterns change across the growing season. The main objective of this study was to determine the biomass allocation patterns of short, mid and tall grass species common to the north American grasslands into their main plant structures (aerial tillers, crown and roots). The second objective was to identify if there are differences in those allocation rates across the growing season. We hypothesized that tallgrasses, which are considered to be the dominant species in areas where light is a limiting resource would allocate more of the resources building

Texas Tech University, Leobardo Richarte-Delgado, August 2018

aboveground structures rather than on the crown or roots. In the same way, we believe that short grass species will allocate more of their resources to produce roots and maximize the water acquisition because they dominate areas where water is scarce

(Bartos and Sims 1974).

Materials and Methods

Site description

To evaluate biomass allocation patterns of short, mid and tall grasses across the growing season iconic species from each group were chosen. Species used in this study were blue grama (BG), sideoats grama (ST) and switchgrass cultivar Kanlow (KL), for shortgrass, mid-grass and tall grass prairie, respectively, additionally we used WW-B.

Dahl (WB) as a species reference due to its high biomass production and drought tolerance which is regularly used in West Texas improved pastures. Vegetal material was collected from different sites. Blue grama was collected from three randomly selected plants from Texas Tech University Native Grassland. Sideoats, and switchgrass cultivar

Kanlow were collected from the Knox City Plant Material Center. Finally, two WW-B.

Dahl plants were randomly collected from an improve pasture established around 15 years ago in the Justiceburg Ranch located 55 miles south east of Lubbock.

This study was performed during the 2015 and 2016 growing seasons. At the beginning of each growing season 21 plants per species were stablished and growth in

19-L pots under homogenous environmental conditions. Plants were transplanted mid-

July and harvested on November of each year. This study was conducted at the Texas

Tech University Native rangeland (33°36'14.78"N, 101°53'50.44"W) at 992-m elevation.

This rangeland is approximately 65 hectares located in the northwest section of Lubbock,

Texas Tech University, Leobardo Richarte-Delgado, August 2018

TX. The area has dry steppe climate with mild winters. Main annual precipitation is 481 mm, with 73% occurring during the warm season, April through October (Southern

Regional Climate Center 2015). Warm season rainfall often occurs, as a result, of thunderstorms. May, June, and July are the main growth months for perennial warm season grasses (Blackstock et al. 1979). Average normal temperature on summer is 24.69 oC while in winter is 6.12 oC (Southern Regional Climate center 2015). Vegetation on the area consists of mid and shortgrass species. Grass species common to this site are sideoats grama, blue grama, buffalograss, sand dropseed (Sporobolus cryptandrus) and

Arizona cottontop (Digitaria californica). The more commonly found forbs, scarlet globemallow (Sphaeralcea coccinea [Nutt.]), Engelmann’s daisy (Engelmannia peristenia [Raf.]), baby white aster (Chaetopappa ericoides) and annual forbs. The primary woody species found are mesquite (Prosopis glandulosa) and plains pricklypear

(Opuntia polyacantha); however, trees are seldom found on this site (Bradbury 2007).

Soil collection

Soil was collected from the Texas Tech Native grassland in an area that presents

Amarillo soil type predominantly (Table 3.1 and 3.2). Soil depth is 2 m, however we collected just the top 30 cm, this portion is friable, mildly alkaline, reddish fine sandy loam (Blackstock et al. 1979). Soil was mixed with 20% sand, air dried and passed through a 0.5 cm sieve, after soil mixture was completed 19-L pots (30 cm deep and 29 cm diameter) were filled and kept under field conditions inside the Texas Tech Native

Rangeland until plant transplantation.

Plant establishment process

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Mature grass plants were collected at the beginning of the 2015 and 2016 growing seasons and gently divided into cuttings. Two cuttings per pot were transplanted to ensure the establishment of at least one plant; at the end of the establishment process cuttings were thinned to one per pot. For the extend of this study, a cutting was a tiller separated from the crown of a mother plant on early vegetative stage with viable roots. During the establishment process, pots were light irrigated every day during the morning to ensure an easy and fast establishment. Success plant establishment was considered when transplanted cuttings started to produce new tillers from the basal crown, once this happened experimental irrigation regime started.

Irrigation

Plants were irrigated three times a week during the length of the study, applying

480 mL per irrigation event (69 irrigation events). Irrigation needs were calculated according to the long-term average precipitation (481 mm/yr) for Lubbock assuming 70% of the precipitation occurs from May through October (336 mm) (West Texas Mesonet

2015) and determining the proportional amount of water that a 19-L pot (660 cm2 in area) might capture under that precipitation regime. Total amount of water applied to each pot per growing season was close to 30 liters (Table 3.3). Irrigations rates were modified according to precipitation events throughout the growing season.

Sample collection

To evaluate the biomass allocation patters seven plants per species where harvested during the vegetative, reproductive and post- reproductive phenological stages

(Table 3.5 and 3.6). At each collection time, total biomass per plant was harvested and

Texas Tech University, Leobardo Richarte-Delgado, August 2018

separated into aerial tiller, crowns and roots. Aerial tillers (aboveground portion) were collected by clipping all the tillers 0.5 cm above ground level. Belowground biomass was collected by carefully washing the roots with tap water over a 0.5 cm mesh. Belowground portion was further divided into crown (transition between aerial tillers, and roots) and roots. Biomass samples where air dried, until constant weight. Finally, once samples were completely dry were weighted and biomass was recorded.

Experimental design and analysis

Biomass allocation in this study was analyzed using two different approaches, the first one, was analyzing the amount of biomass allocated to each grass structure, per grass species, at each phenological stage (aerial tillers, crown and roots), and the second approach was to look at changes in percentages of total biomass allocated to each grass structure by species, across the growing season. Expressing biomass allocation in a giving structure by percentages of the total biomass help us to understand and compare in a better way changes in biomass allocation across the growing season.

Biomass allocation by phenological stage

Response variables considered in this approach were aerial biomass, crown biomass and roots biomass production. The experimental design to analyze these variables was first planned to have a balance design with all grass species evaluated in

2015 and 2016 growing seasons, however, we were unable to establish BG in the first year and we added WB to the second evaluation year, resulting in an unbalance CRD design because just KL and ST were evaluated during 2015 and 2016 growing seasons, while BG and WB just during the 2016. As a result, we performed an initial analysis, just

Texas Tech University, Leobardo Richarte-Delgado, August 2018

considering the species evaluated in both years seeking for significance on the year term, using the following experimental design: CRD factorial with three main factors and several levels per factor. Factor A: species, 1) ST and 2) KL. Factor B: collection time: 1)

Vegetative, 2) Reproductive and 3) Post-reproductive) and factor C: year; 1) 2015 and 2)

2016, each treatment was a combination factors by levels, so we had 12 treatments with 7 replications per treatment. Each 19-L pot was considered as the experimental unit. In total we had 84 experimental units. Since our data violated the assumption of homogenous variances (Levene’s test), we log10 transformed it. Once analysis was complete, we found out that the year term was not significant, then we used a new approach to include all the species in the same analysis. We procced to combine the data of the species evaluated in both years (KL and ST), as a result, the treatments involving these species have twice the number of replications while species evaluated during just one growing season (BG and WB) have 7 replications per treatment, while the year term was not considered in this new experimental design. Experimental design used to analyze our data were a CRD factorial with two main factors and several levels per factors. Factor

A: species with four levels; 1) BG, 2) KL, 3) ST and 4) WB. Factor B: collection time; 1)

Vegetative, 2) Reproductive and 3) Post-reproductive). Each treatment is a combination factors by levels, as a result we got 12 treatments with 14 replications per treatment involving ST and KL and 7 replications per treatments involving BG and WB.

Experimental unit was the 19-L pot. In total we have 504 experimental units. Data were analyzed using JMP statistical software (SAS Institute 2012). All data calculations and interpretation were performed using the transformed data, however, for presentation reasons data were transformed back to the geometric scale.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Biomass proportions per grass structure

The experimental deign to analyze percentage data per species was a completely randomized design (CRD) factorial with two factors and several levels per factor. Factors were two, A) phenological stage with three levels; 1) Vegetative, 2) Reproductive and 3)

Post-reproductive. Factor B) Grass structure, with three levels: 1) Aerial tillers, 2) Crown and 3) Roots. Treatments were a combination of levels per factors (3x3=9) with 7 replications per treatment for BG and WB and 14 replications for KL and ST. Data were analyzed using JMP statistical software (SAS Institute 2012).

Results

Biomass allocation by phenological stage

Vegetative stage

At this early point in the growing season, WB produced the higher total biomass

(16.02 g) followed by KL (12.33 g), ST (7.32 g) and BG (2.65 g). WB produced 25% more biomass than the tall grass species KL, twice more biomass than the mid grass species (ST) and six times more than the shortgrass species (BG) (Table 3.5). Biomass production per structure was different among the grass species. WB allocated higher biomass amounts to the aerial tillers (7.99 g) followed by roots (4.55 g) and finally crown

(3.47 g). WB aerial tillers production was significantly higher that roots and crown portions, however there were no differences (P>0.05) between biomass allocated in roots and crowns (Table 3.7). KL and ST presented a similar pattern in biomass production, these species allocated significantly higher biomass to the aerial tillers (4.93, 3.00 g, respectively) followed by roots (4.10, and 2.51g) and finally the lower biomass amount

Texas Tech University, Leobardo Richarte-Delgado, August 2018

was allocated to crowns (3.28 and 1.80 g). ST and KL allocated significantly higher biomass to the roots than crowns (Table 3.7). Finally, BG which allocated slightly higher biomass amounts to the aerial tillers (1.02 g), followed by roots (0.87 g) and finally crown (0.74 g), however there were not significant differences detected (Table 3.7). By this early stage in the growing season all the species besides KL invested more resources to build the aboveground portion, in relation to the belowground, in general biomass allocation to the aerial tillers was almost twice the one allocated to crows in WB, ST and

BG, and slightly higher in KL. In the same way these species allocated slightly more resources to the roots than to the crows. At this point of the growing season all species allocated more biomass to the aerial tillers, then roots and finally crowns.

Differences in biomass production by structure among grasses

WB produced the highest aerial biomass (7.99 g) of all the species at this point of the growing season followed by KL (4.93 g), ST (3.00 g) and finally BG (1.02 g). WB biomass was higher (P<0.05) then the rest of species. KL produced significantly higher biomass than ST, finally BG produced significantly lower aerial biomass than all the other species. Moving to crown biomass, WB again produced the heavier basal crowns

(3.47 g), followed by KL (3.28 g), ST (1.80 g) and BG (0.74 g). There were significant

(P<0.05) differences in the amount of biomass allocated to this structure among our grass species. There were no differences between WB and KL however those species produced significantly heavier crowns than ST and BG. BG produced again significantly lighter crowns than all the other species. Finally, root biomass production, again WB produced higher biomass (4.55 g), followed by KL (4.10 g), ST (2.51 g) and BG (0.87 g). There were significant (P<0.05) differences in the amount of root biomass produced by these

Texas Tech University, Leobardo Richarte-Delgado, August 2018

grass species, these patterns were similar as the patterns described in crown production.

There was not significant difference between WB and KL, however, those species produced significantly higher roots than ST and BG. Finally, BG which produced significantly lower root biomass than the rest of the species (Table 3.7). At this point of the growing season, WB produced the highest amount of biomass allocated to the aerial tillers, even higher than the tall grass species (KL), however, both species produced crown and roots with similar weights, basically, the difference in biomass production between WB and KL was driven by higher WB potential to produce aerial biomass. The tall grass species (KL) produced 60% more biomass than the mid grass species (ST) at each grass structure. Finally, the difference between ST and the short grass species (BG) were even bigger (between 2.5 and 3 times) than those differences between mid and the tall grass species.

Reproductive stage

WB produced the highest total biomass (25.05 g) followed by KL (14.70 g), ST

(11.55 g) and BG (5.61 g). WB produced 70% more biomass than the tall grass species

(KL), twice more biomass than the mid grass species (ST) and five times more than the short grass species (BG) (Table 3.8). This species allocated biomass differently among structures at this point of the growing season. WB produced higher biomass amounts in the aerial tillers (16.07 g), then roots (4.55 g) and finally to the crown (3.47 g). Similar response was found on KL and BG where biomass production was higher in the aerial tillers (6.14, 3.29 g) than roots (5.12, 1.32 g), and higher amount of root biomass than crowns (3.42, 0.99 g, respectively). All these species produced significantly higher amounts of aerial tillers, compared to root and crowns and significantly higher roots

Texas Tech University, Leobardo Richarte-Delgado, August 2018

biomass compared to crown biomass. Finally, ST presented a slightly different pattern.

ST allocated higher amount of biomass to the aerial tillers (5.05 g) followed by roots

(3.56g) and finally crown (2.93 g), however, there was no (P>0.05) difference between aerial tillers and roots, finally, biomass allocated to roots were higher than biomass allocated to the crown (Table 3.8).

Differences in biomass production by structure among grasses

During the reproductive stage WB produced the highest aerial biomass (16.07 g) of all the species, followed by KL (6.14 g), ST (5.05 g) and finally BG (3.29 g). WB aerial biomass was significantly higher than the rest of the species, in contrast, there were no significant differences between ST and KL, finally, BG produced significantly lower aerial biomass amounts than all other species. Moving to biomass allocated to the crown,

WB produced the heavier weights (3.63 g), followed by KL (3.42 g), ST (2.93 g), and BG

(0.99 g). There were significant differences in the amount of biomass allocated to this structure among our grass species. There were no significant (P>0.05) differences in the biomass allocated to the crown between WB, KL, and ST, however, all these species produced significantly higher crown weights that BG. Finally, moving to root biomass production, WB produced the highest root biomass (5.34 g), followed by KL (5.12 g), ST

(3.56 g), and BG (1.32 g). There were no differences (P>0.05) between WB and KL, however, those species produced significantly higher root amounts than ST and BG.

Finally, ST produced higher root biomass than BG (Table 3.6). WB was once again the highest biomass producer among all the species in this study, at this point of the growing season, however, there were no significant differences in crown and root biomass production between WB and KL. The same response was observed during vegetative

Texas Tech University, Leobardo Richarte-Delgado, August 2018

stage. According to our results, WB produced higher total biomass than KL due to its greater potential to produce aerial tillers (16.07 vs 6.14 g). Differences between the tall grass species (KL) and the mid grass (ST) were shorter in relation to vegetation stage.

The only significant difference between both species was found on root biomass where

KL produced higher amounts than ST. There were no significant differences in the aerial tillers and crown biomass production between both species. Finally, the difference between BG and ST biomass production decreased in relation to the previous sampling (2 times versus 2.76 in vegetative stage).

Post-Reproductive stage

In this study, the post-reproductive stage came out as the time during the growing season where our grass species reached their peak of biomass production. WB produced the higher amount of total biomass (33.64 g) followed by KL (26.60 g), ST (15.54 g) and

BG (6.21 g). WB produced 26% more biomass than the tall grass species (KL), twice more biomass than the mid grass species (ST) and five times more than the shortgrass species (BG) (Table 3.9). There were differences in biomass production per structure at this sampling time (P<0.05). WB and ST presented a similar pattern in biomass allocation. These species allocated higher biomass to the aerial tillers (20.70 and 7.88 g), followed by roots (7.16 and 4.19 g) and finally the lowest biomass to the crown (5.77 and

3.46 g). Both species allocated significantly higher biomass amounts to the aerial tillers in relation to roots and significant higher biomass allocation to roots over crowns (Table

3.7). KL presented a different pattern, higher biomass allocation was present in roots

(10.05 g), followed by aerial tillers (8.74 g) and crowns (7.81 g). KL produced significantly higher root biomass than aerial tillers and crowns, however, there was no

Texas Tech University, Leobardo Richarte-Delgado, August 2018

difference (P>0.05) between biomass allocated to the aerial tillers and crowns. Finally,

BG produced higher biomass amounts in the aerial tillers (3.16 g) followed by roots (1.57 g) and crown (1.46 g). BG produced significantly higher aerial tiller biomass than roots and crowns, however, there was no difference between roots and crowns (Table 3.9).

Biomass production results by this sampling date were different in relation to the patterns observed in previous collections. WB was the species that produced the highest amount of biomass in each one of the structures during the vegetative and reproductive sampling times, however by this collection KL produced significantly heavier crowns and roots than the rest of the species.

Differences in biomass production by structure among grasses

The species that produced the highest biomass in the aerial portion was WB

(20.70 g), followed by KL (8.74 g), ST (7.88 g) and BG (3.29 g). WB produced higher

(P<0.05) aerial tiller biomass than the rest of the species, moreover, there was no difference between KL and ST, finally BG produced significantly lower aerial tiller biomass than the rest of the species (Table 3.9). Talking about crown biomass production, there were differences among species. KL produced the highest crown biomass (7.81 g), followed by WB (5.77 g), ST (3.46 g), and BG (1.46 g). KL produced significantly higher biomass than all the other species. WB produced higher biomass than ST and BG.

In contrast, BG produced significantly lower crown biomass among all the grass species

(Table 3.9). Finally, talking about root biomass, KL produced the higher biomass (10.05 g), followed by WB (7.16 g), ST (4.19 g) and BG (1.57 g). There were significant

(P<0.0) differences among grass species in terms of roots biomass production. KL produced significantly higher root biomass than the other species. WB produced higher

Texas Tech University, Leobardo Richarte-Delgado, August 2018

biomass than ST and BG, finally ST produced significantly higher roots biomass than BG

(Table 3.9).

Percentage of total biomass allocation per structure

There were differences in the proportion of total biomass allocated to each grass structure across the growing season per species (Table 3.10-3.13). In BG the proportion of total biomass allocated to aerial tillers was lower (P<0.05) during the vegetative state

(38.7%) and increased to similar percentages during vegetative (58.4%) and post- reproductive (53.6%) stages (Table 3.10). In the case of crown biomass, BG presented significantly lower percentages during the reproductive stage (17.8%) while percentage accumulation was similar at vegetative (28.17%) and post-reproductive (22.13%), finally, roots presented a similar pattern to aerial tillers. Significantly higher percentage of total biomass was allocated to roots during the vegetation stage (33.10%) and similar percentages during reproductive (23.6%) and post-reproductive (24.2%) (Table 8). In the case of KL our analysis was not able to detect significant differences (P>0.05) among phenological stages in terms of percentages of total biomass allocation on each grass structure (Table 3.11). The exotic species WB presented similar biomass allocation patterns to BG. WB allocated significantly lower percentages of total biomass (49.8%) to the aerial tillers during the vegetative stage, then increased to similar amounts by reproductive (64.4%) and post-reproductive (61.4%) stages. WB allocated significantly higher proportion of biomass to the crowns during vegetative (21.7%) and post- reproductive (17.2%) stages, and lower percentages during the reproductive stage

(14.7%). Finally, this species allocated the higher proportion of biomass to the roots during the vegetative stage (28.4%), and lower and similar amounts during reproductive

Texas Tech University, Leobardo Richarte-Delgado, August 2018

(20.7%) and post-reproductive (21.3%) (Table 3.12). ST allocated the lower percentage of the total biomass to the aerial tillers during the vegetative (40.7%) and reproductive stages (42.9%), and significantly higher percentage at the post-reproductive stage

(49.9%). Talking about crown and root, there were some differences in the proportion of total biomass allocated to these structures, however these differences were not significantly different (P>0.05) among the growing seasons (Table 3.13).

Discussion

Biomass allocation to the aerial tillers

In this study, regardless of phenological stage, all grasses allocated the highest biomass proportion to the aerial tillers. The only exception was KL, which during the post-reproductive stage allocated slightly higher biomass to the roots. Our finding agrees with Tilman (1988) who postulated that due to the shift in nutrient limited to light-limited environments late successional species (BG, ST, and KL) allocate more biomass to the shoots to increase their competence ability for light. In contrast, Staton (1983) working with BG under greenhouse conditions reported 26%, 29% and 45% of biomass allocation to shoots, crown and roots, respectively. A reason that might be influenced the lower amount of biomass allocated to shoots could be the differences in biomass sampling.

Staton (1983) considered part of the shoots biomass to all the structures 5 cm above soil level, in contrast, in our study we considered aerial biomass all the structures above soil level. In the other hand, there are some studies which reported higher biomass allocation to the belowground section. Sims and Singh (1978) working in shortgrass prairie reported

21.7% of total biomass to the aerial tillers and 78.2% to the belowground section with a shoot to root ratio of 0.28 while Herrero Jauregui (2016) reported 70% of total biomass to

Texas Tech University, Leobardo Richarte-Delgado, August 2018

roots and 30% to aboveground portion with shoot to root ratio of 0.42, Milchunas and

Vandever (2013) also working in the shortgrass prairie reported 79% biomass in the belowground and 21% to the aboveground with a ratio of 0.26. It is important to mention that these studies were performed in grasslands which have been stablished for a long period of time, therefore, belowground biomass included both annual increments and standing crop biomass from previous years. In contrast, the aboveground portion does not accumulate biomass amounts from previous years because it is continuously removed.

This might be the main reason to explain such a big difference between below and aboveground production in these studies. Biomass harvested in our study considered just the biomass generated during one growing season. As a result, in our study we found a more balance aboveground to belowground ratio. According to the literature (Lane et al.

1998 and 2000) the average aboveground biomass for shortgrass prairie is 57.5 g/m2, mixed grass prairie is 232.5 g/m2 and tall grass prairie is 410 g/m2, approximately. Based on these results tall grass prairie produces 7 times more biomass than shortgrass prairie, and 1.76 times more than mixed grass prairie, finally mixed grass prairie produces 4 times more aerial biomass than shortgrass prairie. Our results showed that by post- reproductive stage when the peak in biomass production was reached, the tall grass species (KL) produced just 2.8 times more biomass than the shortgrass (BG), 1.12 times more biomass than the mid grass (ST), finally the mid grass (ST) produced 2.54 times more than the shortgrass (BG). Differences in aboveground biomass production between the species in our study were not as big as the ones reported in the literature. This might be influenced by the fact that all the species in our study were grown under soil and moisture conditions common to the shortgrass prairie, while the data reported in the

Texas Tech University, Leobardo Richarte-Delgado, August 2018

literature, was collected from sites dominated for the actual plant communities exposed higher resources availability (moisture and soil fertility). This might have limited the performance of ST and KL to fully reach their potential in our study.

Biomass allocation to roots and crowns

The second structure were these species stored more biomass was roots, however in most of the cases there was no a significant difference with crowns. There is a lack of information about biomass allocation to the crown in the literature, since most of the studies evaluating belowground biomass do not make a distinction between both structures. It is important to point out that when this separation is not considered root biomass is over estimated by almost 100% and therefore all the calculations based on such estimation (e.g. potential nutrient and water absorption). Our results showed that of the amount of biomass allocated to the belowground portion a considerable amount ranging from 40% to 45% can be classified as crown biomass. Stanton (1983) reported that BG allocated 29% of the total biomass to the crown and 45% to the roots, while Sims and Singh (1978) reported 17.14% of total biomass to the crown and 47.47% to roots.

Our results fit in between that range (22% and 24% for crown and roots, respectively).

Higher discrepancies between biomass allocation to roots between our study and Sims and Singh (1978) study might be related to the standing crop biomass carry over effect, previously discussed. Finally, biomass allocation to the crown section was the lowest percentage in all species at each phenological stage (Table 8-11), which agrees with Sims and Singh (1978) and Stanton (1983).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Discussion by species

Blue grama (BG)

Initial hypothesis regarding to BG biomass allocation was that this species, being a short grass adapted to dry environments, where the most limiting resource is moisture, would allocate higher resources in the belowground portion, specially roots to increase water acquisition. The results of our study partially support this hypothesis, since we observed this behavior, but just early in the growing season (vegetative stage) when BG produced significantly higher root biomass in relation to crowns and aerial tillers (Table

3.10) however after vegetative stage, BG allocated higher resources to produce aerial tillers, this make sense during reproductive stage when grasses shift most of their energy to produce reproductive structures (Owensby et al. 1977). After reproductive stage root and crown production experienced a small increment until the post-reproductive stage.

This increment was explained by a reduction in aerial tiller biomass allocation, however, shoot to root ratio was >1 during reproductive and post-reproductive stages (Table 3.14), which indicates that BG sends a big part of their energy to produce leaves and tillers during most of the growing season, these results contradicted our initial hypothesis.

Finally, by the post-reproductive stage, we observed a decrease in the percentage of total biomass allocated to the shoots, while root biomass remaining basically the same, however crown experienced a significant increment in biomass allocation. This increment might be related to the production of new tillers during the fall regrowth (Sosebee et al.

2004). Similar behavior was observed in WB.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Sideoats grama (ST)

We hypothesized that ST being a mid-grass would share biomass allocation characteristics of BG and the tall grass species, however, ST aboveground to belowground ratio at any time of the growing season was >1 (Table 3.14) which indicates that during the entire growing season ST constantly allocates higher biomass to the belowground section, especially to roots than to the aerial portion. The ability of ST to allocate higher portions of its resources to the roots than to aerial portion would indicate a competitive advantage to dominate in areas where water is a limiting resource (Tilman

1988). ST tends to allocate higher amounts of biomass to the belowground portion early at the growing season (close to 60%) and progressively decreases until the end of the growing season, while the inverse happened to aerial tillers which after the vegetative stage tend to increase in biomass allocation reaching its maximum level by the end of the growing season (Table 3.14). ST presented the most balance biomass allocation among plant structures across the growing season from the species in this study. In contrast,

Wilsey and Polley (2006) working with ST in the black prairie of Texas, reported a shoot to root ratio of 2.39 which is more than 2 times higher than the 0.99 ratio in our study, it is important to consider that Wilsey and Polley (2006) study was performed under wetter conditions (864 mm), since ST moisture demands were covered it might shifted resource allocation to the aerial portion and better compete for sunlight. Difference in biomass allocation patterns between the same species, under different resources availability environments shows that the species has the plasticity to adapt to different environmental conditions; reorganizing the way how energy is distributed to get better access of the limiting resource, which fits Tilman (1998) theory.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Kanlow (KL)

KL being a tall grass species was expected to allocate the higher proportion of its total biomass to the aerial tillers, as this species is found in environments characterized by the presence of other tall grasses and trees where sunlight is apparently the most limiting resource (Money 1972). However, biomass allocation patterns in our study showed that KL allocated significantly higher biomass to the belowground portion mainly to the roots (Table 3.11). Aboveground to belowground ratio on KL was never even close to 1, at any phenological stage (Table 3.14). Some literature on tall grasses

(Wilsey and Polley 2006) reported a 3.12 ratio in indiangrass (Sorghastrum nutans) in the black prairie of Texas. This ratio is extremely higher in relation to our results. This tremendous difference in biomass allocation to shoots could be attribute to differences in moisture availability between studies, in Wilsey and Polley (2006) study the precipitation was 864 mm while in our study we simulated the precipitation of the shortgrass prairie during the active growing season (Table 3.3). It might be that KL being a species adapted to amore mesic conditions once it was growth under lack of moisture and nutrients its response was to send more resources to build roots, aiming to get access to moisture.

Similar behavior was reported by Caldwell (1987) and Aerts et al. (1990) in grass and shrub species growth in low nutrient environments in relation to more fertile conditions, authors explained that it was a plant response to increase their competitive ability for water and nutrients.

WW-B. Dahl (WB)

WB being an exotic species selected for its superior biomass production characteristics (Dewald et al. 1995) we hypothesized that WB would allocate high

Texas Tech University, Leobardo Richarte-Delgado, August 2018

amount of biomass to aerial structures this expectation was confirmed with the data from this study (Table 3.10). Aboveground to belowground ratio of WB was close to 1 during vegetative stage and >1 for the rest or the growing season (Table 3.12). WB is considered a dry tolerant species (McCollum 2000; Veneciano and Frigeiro 2003), however its biomass allocation to roots was the lowest among the species evaluated in this study, ranging between 21% to 28% during the growing season (Table 3.12). So how a species with low biomass allocated to the roots can perform well in dry semiarid environments, the answer to this question might be related not to the actual biomass but to a higher root surface area which can be provided by finer and lighter roots. This contradicts Tillman

(1988) theory, where plants will allocate more resources to build structures involved in the acquisition of that limiting resource. Similar observations were reported by Aerts and

Van der Aart (1990) when studying biomass allocation in grasses exposed to a gradient of nutrient supply. Aerts and Van der Aart (1990) concluded that resource acquisition is not always proportional to the biomass invested by the organisms to acquire that resource.

This is especially true for light, where light capture is more related to specific leaf area rather than leave biomass and for water absorption which is related to root biomass but mainly to roots surface area. Root surface area is higher on finer and lighter roots.

Similarities between BG and WB

Among the species considered in this study BG and WB were the ones that exhibited a similar biomass allocation patterns among the growing season. WB and BG presented shoot to root ratios close to 1 during vegetative stage, a maximum ratio during reproductive stage and small decrease by the end of the growing season however those ratios are much bigger on WB. Both species were the only ones that allocated more than

Texas Tech University, Leobardo Richarte-Delgado, August 2018

half of their total biomass to the aerial tillers after vegetative stage (Table 3.14). Even though, BG and WB present different morphological characteristics being WB considered as tall or mid grass and BG as short grass, both species share two main characteristics that could help us to understand why they present similar biomass allocation patterns. These two species are well known for its grazing and drought tolerance (Milchunas and Lauenroth 1989; Dewald et al. 1995; Lauenroth 2008).

Conclusions

Total biomass allocation in our study changed with the advance in the growing season. Lower biomass was reported during the vegetative stage, while the peak in biomass production was observed during the post-reproductive stage. Our study showed that total biomass distribution among main grass structures, varies depending on the growing season and the species. During the vegetative stage all the species besides KL allocated the highest biomass proportion to the roots. In contrast, the peak biomass allocated to the of aerial tillers was reached during the reproductive stage except for ST.

The highest proportion of crown biomass was presented during the vegetative stage decreasing during reproductive and increasing again be the end of the growing season.

Biomass allocation to main grass structures by species partially supported our hypothesis originated from Tilman (1998) postulates. The tall grass species (KL) allocated higher biomass to the belowground portion, but this was attributed to the lack of moisture forcing this species to generate more roots and get enough water. BG and ST, both species produced even aboveground and belowground portions, however ST invested slightly more biomass in the roots section which agrees with our initial hypothesis.

Biomass allocation patterns in WB confirmed our hypothesis, that WB being a mid-grass

Texas Tech University, Leobardo Richarte-Delgado, August 2018

exotic species selected for its high forage productivity potential would allocate higher biomass to the aerial component. Finally, this study proves the importance to separate the belowground portion of the biomass into crown and roots, because as high as 40% of its biomass which is mistakenly considered as roots when is actually crown biomass. Over estimating root biomass would cause problems calculating variables such as water and nutrient acquisition.

Further research need it

Due to the plasticity in biomass allocation among sctures in response to resource limitation exhibited by species in this study and previous studies, further research efforts are needed to accurately define biomass distribution among grass structures. The replication of studies like this under different environmental conditions (moisture, fertilization and light intensity) will gave us a better understanding of how resource allocation change in response to limited resources.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Literature Cited

Aerts, R., R.G.A Boot, and R.J.M. van der Aart. 1990. The relation between above-and belowground biomass allocation patterns and competitive ability. Oecologia. 87:551-5. Bartos, D.L., and P. L. Sims. 1974. Root Dynamics of shortgrass ecosystem. Journal of Range Management. 27(1):33-36. Caldwell, M.M. 1987. Competition between root systems in natural communities, p. 167- 185. In Gregory, J.V. Lake., and D.D. Rose [ed.] Root development and function. Cambridge Univ. Press, Cambridge. Chapin, F.S. III, A.J. Bloom, C.B. Field, and R.H. Waring. 1987. Plant response to multiple environmental factors. BioScience 41: 29-36. Coyne, P.I., M.J. Trlica and C.E. Owensby. 1995. Carbon and Nitrogen Dynamics in Range Plants. In: Bedunah D.J. and R.E. Sosebee. Eds. Wildland plants Physiological Ecology and Developmental Morphology. Society for Range Management. Denver, CO. Derengibus, V.A., M.J. Trlica, and D.A. Jamenson. 1982. Organic reserves in herbage plants: their relationships to grassland management, p 315-344, in M. Rechcigl. Jr. [ed.] Handbook of agriculture productivity. Vol. I. Plant productivity. CRC Press, Boca Raton, FL. Dewald, C.L., P. L. Sims, and W. A. Berg. 1995. Registration of “WW-B. Dahl” Old World Bluestem. Crop Sci. 35:937 Fitter, A.H., and R.K.M. Hay. 1981. Environmental physiology of plants. Academic Press. London. 355 p. Flores, R.L and B. Tracy. 2013. Root Characteristics of Perennial Warm-Season Grasslands Managed for Grazing and Biomass. Agronomy. 3:508-523. Herrero-Jauregui, C., M.F. Schmitz & F.D. Pineda. 2016.Effects of different clipping intensities on above- and below-ground production in simulated herbaceous plant communities. Plant Biosystems. 150(3) 468-476. Korner, C. and U. Renhardt. 1987. Dry matter partitioning and root length/leaf ratios in herbaceous perennial plants with diverse altitudinal distribution. Oecologia. 74: 411-418. Lane, D.R., D.P. Coffin, and W.K. Lauenroth. 1998. Effects of soil texture and precipitation on above-ground next primary productivity and vegetation structure across the central grassland region of the Unitec States. Journal of vegetation Science 9:239-250. Lane, D.R., P. Coffin, and W.K. Lauenroth. 2000. Changes in grassland canopy structure across precipitation gradient. Journal of vegetation Science. 11:359-368.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Lauenroth, W.K., D.G. Milchunas, O.E. Sala, I.C. Burke. J.A. Morgan. 2008. Net Primary Production in the Shortgrass Steppe in: W. K. Lauenroth and I. C. Burke, editors. Ecology of the shortgrass steppe: A long-term perspective. Oxford University Press, New York. Lauenroth, W.K. 2008. Vegetation of the shortgrass steppe in: W. K. Lauenroth and I. C. Burke, editors. Ecology of the shortgrass steppe: A long-term perspective. Oxford University Press, New York. McCollum, T. 2000. Old World Bluestem pastures management strategies. Texas Agricultural Extension Service. Amarillo, TX. McNaughton, S.J., R.W. Ruess, and S.W. Seagle. 1998. Large mammals and process dynamics in African ecosystems. BioSciense 38:794-799. Milchunas, D.G. and W.K. Lauenroth. 2001. Belowground Primary Production by Carbon Isotope Decay and Long-term Biomass Dynamics. Ecosystems. 4: 139- 150. Milchunas, D.G. and W.K. Lauenroth. 1989. Three-Dimensional Distribution of Plan Biomass in Relation to Grazing and Topography in the Shortgrass steppe, Oikos. 55(1):82-86. Milchunas, D.G. and M.W. Vandever. 2013. Grazing effects on aboveground primary production and root biomass of early-seral, mid-seral, and undisturbed semiarid grassland. Journal of Arid Environments. 92:81-88. Mooney, H.A. 1972. The carbon balance of plants. Ann. Rev. Ecol. Syst. 3:315:346. Neary, D.G., C.C. Klopatek, L.F. DeBano, and P.F. Folliott. 1999. Fire effects on belowground sustainability: a review and synthesis. Forest Ecology and Management 122: 51-71. Olff, H., J. Van Andel and J.P. Bakker. 1990. Biomass and Shoot/Roots allocation of five species from a grassland succession series at different combinations of light and nutrient supply. Functional Ecology. 4(2) 193-200. Owensby, C.E., E.F. Smith, and J.R. Rains. 1997. Carbohydrates and nitrogen reserve cycles for continuous, season-long and intensive-early stocked flint Hills bluestem range. J. Range Management. 30:258-260. Richards, J.H. 1984. Roots growth responses to defoliation in two Agropyron bunchgrasses: field observations with an improved root periscope. Oecologia 64:21-25. SAS Institute Inc. 2012. Using JMP 10. Cary, NC: SAS Institute Inc. Sims, P.L., J.S. Singh, and W.K. Lauenroth. 1978. The structure and function of ten western North American grasslands: I. Abiotic and vegetational characteristics. Journal of Ecology 66:251-285.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Shuster, J.L. 1964. Root development of Native Plants Under Three Grazing intensities. Ecology. 45(1): 63-70. Snyman. 2003. Rangeland degradation in a semi-arid south Africa- I: influence of seasonal root distribution, root/shoot ratios and water-use efficiency. Journal of Arid Environments. 1-25 p. Sosebee, R.E., D. B. Wester, J. C. Villalobos, C. M. Britton, C. Wan, and H. Nofal. 2004. How grasses grow – How plant growth relates to grazing management. 2nd National Conference on Grazing Lands, Proc. Nashville, TN. Stanton, N. 1983. The effects of clipping and Phytophagous Nematodes on Net primary production of Blue Grama, Bouteloua gracilis. Oikos. 40(2): 249-257. Tilman, D. 1988. Plant strategies and the dynamics and structures of plant communities. Princeton University Press, Princeton, New Jersey. Wilsey, B.J., Polley, H.W. 2006. Aboveground productivity and root-shoot allocation differ between native and introduced grass species. Oecologia 150, 300-309. Veneciano, J.H. and K. L. Frigerio. 2003. Efecto de la defoliación de primavera-verano sobre los rendimientos, composición, de la materia seca y contenido proteico del material diferido de gramíneas megatérmicas. INTA, Argentina. RIA. 32 (1): 515. West Texas Mesonet. 2016. http://www.mesonet.ttu.edu/mesonet-precipitation.htm (accessed 20 May 2016).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Tables

Table 3. 1 Soil fertility analysis results from soil collected at the Texas Tech Native Rangeland from the top 30 cm, during the 2015 growing season, before mix with sand soil, Lubbock TX, USA. Nutrient kg/ha Nitrogen (mineral) 67 Phosphate (P) 16

Potash (K2O) 67 A&L Plains Agricultural Laboratories, Lubbock TX

Table 3. 2 Soil texture analysis results from soil collected at the Texas Tech Native Rangeland from the top 30 cm, during the 2015 growing season, before mix with sand, Lubbock TX, USA.

Component Percentage

Sand 62

Silt 20 Clay 18 Soil texture classification Sandy loam

A&L Plains Agricultural Laboratories, Lubbock TX

Table 3. 3. Amount of water applied to each 19-L pot coming from irrigation and precipitation sources during the 2015 and 2016 growing season at the Texas Tech Native Grassland, Lubbock TX, USA. 2015 2016 Month PP (l) Irrig1 (l) Mean Temp (oC) PP (l) Irrig (l) Mean Temp (oC) July 4.85 4.32 27 0.02 6.24 30 August 0.25 5.12 27 10.64 4.64 26 September 1.12 3.84 25 4.46 1.76 22 October 9.01 1.6 18 1.91 2 20 November 0.27 1.28 10 1.07 0.36 13 Total 15.5 16.16 18.09 15 1Amount of water applied per pot once every three days

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 3. 4. Monthly precipitation and average monthly temperature for 2015 and 2016 growing season at the Texas Tech Native Grassland, Lubbock Texas, USA (West Texas Mesonet, 2016). 2015 2016 Month PP mm Mean Temp (oC) PP mm Mean Temp (oC) July 69.3 27 0.24 30 August 3.5 27 151.9 26 September 16 25 63.6 22 October 128.7 17 27.3 20 November 3.8 10 15.2 12 Total 221.4 258.4

Table 3. 5. Transplantation, establishment and forage collection dates of plants used in this study, during the 2015 growing season, under field conditions, at the Texas Tech Native Grassland, Lubbock TX, USA. Biomass collection Species Transplant Establish Vegetative Reproductive Post-Reprod BG 20-Jun 10-Jul 25-Aug 4-Sep 12-Nov KL 19-Jun 11-Jul 25-Aug 4-Sep 12-Nov ST 20-Jun 10-Jul 25-Aug 10-Sep 12-Nov

Table 3. 6. Transplantation, establishment and forage collection dates of plants used in this study, during 2016 growing season, under field conditions, at the Texas Tech Native Grassland, Lubbock TX, USA. Biomass collection Species Transplant Establish Vegetative Reproductive Post-Reprod BG 16-Jun 12-Jul 3-Sep 13-Sep 5-Nov KL 22-Jun 13-Jul 27-Aug 12-Sep 5-Nov ST 22-Jun 13-Jul 27-Aug 13-Sep 5-Nov WB 15-Jun 2-Jul 3-Sep 13-Sep 5-Nov

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 3. 7. Biomass production (g/pot) means and standard error of the mean of four grass species, collected during vegetative stage, separate by species and structure, growth under field conditions during the 2015 and 2016 growing seasons, at the Texas Tech, Native Rangeland, Lubbock, TX, USA. Structure Species Total Aerial tillers Crown Roots WB 7.999 (1.11) A1a2 3.471 (1.102) Ab 4.557 (1.11) Ab 16.028 KL 4.938 (1.082) Ba 3.288 (1.083) Ac 4.103 (1.090) Ab 12.33 ST 3.005 (1.62) Ca 1.8 (1.084) Bb 2.512 (1.064) Ba 7.321 BG 1.026 (1.146) Da 0.749 (1.138) Ca 0.879 (1.089) Ca 2.656 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same species row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Table 3. 8. Biomass production (g/pot) means and standard error of the mean of four grass species, collected during the reproductive stage, separated by species and structure, growth under field conditions during the 2015 and 2016 growing seasons, at the Texas Tech, Native Rangeland, Lubbock, TX, USA. Structure Species Total Aerial tillers Crown Roots WB 16.071 (1.067) A1a2 3.637 (1.114) Ac 5.342 (1.115) Ab 25.071 KL 6.148 (1.084) Ba 3.428 (1.077) Ac 5.125 (1.078) Ab 14.702 ST 5.058 (1.090) Bca 2.93 (1.068) Ac 3.563 (1.084) Bb 11.552 BG 3.294 (1.119) Ca 0.993 (1.070) Bb 1.324 (1.173) Cb 5.611 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same species row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 3. 9. Biomass production (g/pot) means and standard error of the mean of four grass species, collected during post-reproductive stage, separated by species and structure, growth under field conditions during the 2015 and 2016 growing seasons, at the Texas Tech, Native Rangeland, Lubbock, TX, USA. Structure Species Total Aerial tillers Crown Roots WB 20.703 (1.055) A1a2 5.777 (1.049) Ac 7.167 (1.049) Ab 33.649 KL 8.74 (1.083) Bb 7.81 (1.056) Bb 10.052 (1.086) Ba 26.604 ST 7.886 (1.059) Ba 3.462 (1.084) Cc 4.191 (1.066) Cb 15.540 BG 3.168 (1.124) Ca 1.467 (1.132) Db 1.579 (1.070) Db 6.215 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same species row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Table 3. 10. Proportion of total biomass and standard error of the mean allocated to each grass structure by phenological stage of BG plants, growth during 2016 growing season under field conditions at the Texas The Native rangeland, Lubbock TX, USA. Stage Aerial tillers Roots Crown Vegetative 0.387 (0.017) A1a2 0.331 (0.015) Aab 0.281 (0.009) Ab Reproductive 0.584 (0.012) Ba 0.236 (0.013) Bb 0.178 (0.012) Bb Post- Rep 0.536 (0.028) Ba 0.242 (0.021) Bb 0.221 (0.014) Ab 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 3. 11. Proportion of total biomass and standard error of the mean allocated to each grass structure by phenological stage of KL plants, growth during 2015 and 2016 growing seasons under field conditions at the Texas The Native rangeland, Lubbock TX, USA. Stage Aerial tillers Roots Crown Vegetative 0.401 (0.022) A1a2 0.330 (0.015) Aab 0.268 (0.017) Ab Reproductive 0.412 (0.024) Aa 0.356(0.017) Aa 0.230 (0.013) Ab Post- Re 0.330 (0.018) Bab 0.378 (0.018) Aa 0.290 (0.0084) Ab 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Table 3. 12. Proportion of total biomass and standard error of the mean allocated to each grass structure by phenological stage of WB plants, growth during 2016 growing season under field conditions at the Texas The Native rangeland, Lubbock TX, USA. Stage Aerial tillers Roots Crown Vegetative 0.498 (0.013) B1a2 0.284 (0.012) Ab 0.217 (0.010) Ab Reproductive 0.644 (0.013) Aa 0.207 (0.010) Bb 0.147 (0.010) Bc Post- Re 0.614 (0.0090) Aa 0.213 (0.008) Bb 0.172 (0.007) Ab 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 3. 13. Proportion of total biomass and standard error of the mean allocated to each grass structure by phenological stage of ST plants, growth during 2015 and 2016 growing seasons under field conditions at the Texas The Native rangeland, Lubbock TX, USA. Stage Aerial tillers Roots Crown Vegetative 0.407 (0.010) B1a2 0.340 (0.0103) Aa 0.244 (0.0103) Ab Reproductive 0.429 (0.0109) Aa 0.302 (0.0105) Ab 0.248 (0.0105) Ab Post- Re 0.499 (0.0105) Aa 0.265 (0.0105) Ab 0.219 (0.0105) Ab 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Table 3. 14. Aboveground to belowground ratio of four grass species, at three phenological stages during the 2015 and 2016 growing, under field conditions at the Texas The Native rangeland, Lubbock TX, USA. Phenological stage Species Vegetative Reproductive Post-Re WB 0.992 1.809 1.591 KL 0.669 0.701 0.493 ST 0.686 0.751 0.996 BG 0.631 1.404 1.155

Texas Tech University, Leobardo Richarte-Delgado, August 2018

CHAPTER IV

EFFECTS OF CLIPPING INTENSITY AND SEASON OF DEFOLIATION IN

BIOMASS PRODUCTION OF SHORT, MID, AND TALL GRASSES OF NORTH

AMERICA

Abstract

Grazing schemes are a very important tool to maintain a balance between cattle production and rangeland health, these schemes must be design considering type of grazing animal, topography, weather and vegetation species response to defoliation.

Although, not all grass species respond in the same way to defoliations specially if they are defoliated early or later in the growing season. The differences in response of plants after defoliation is related to the developmental morphology stage at which them are at time of defoliation, even though this is a very important factor to take in consideration, there is a lack of information in this regard. The objective of this study was to identify the effects of moderate and heavy utilization on plant biomass allocation to the main plant structures in short, mid and tall grass species. This study was performed during the 2015 and 2016 growing seasons under field conditions. Species evaluated were blue grama, sideoats grama, switchgrass cultivar Kanlow, as common species of the short, mid and tall grass prairie of North American, respectively. In addition, we used WW-B. Dahl as reference species due to its high productivity. Plants were established on a 19-L pots, and growth until biomass collection at the end of the growing season. Plants were clipped with 50% and 75% of the total aboveground biomass during the vegetative and reproductive phenological stages. At the end of the growing season (mid-November) total plant biomass was harvested. Biomass was separated into aerial tillers, crown and roots.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

An analysis of variance was conducted per response variable to detect significant differences among the defoliations treatments combinations. Response variables in this study were aerial tiller, crown, roots and total biomass as well as aboveground to belowground ratio and WUE. There was a significant (P<0.05) three-degree interaction between species, defoliation intensity and phenological plant stage for each response variable. Variables response to defoliation treatments was similar in all the species except for KL. In general, heavy utilization at plant’s vegetative stage (75xVeg) was the treatment that significantly reduced biomass productions in all grass structures. In contrast, moderate utilization at plant’s reproductive stage (50xRep) was the treatment combination that always produced similar values to control plants, and in some cases, even higher values. In conclusion, biomass production in these species was significantly affected by our defoliations treatments. The effects on biomass production varied depending on the species, plant’s morphological stage, and clipping intensity. However, moderate utilization in most of the cases produced compensation values, in contrast, heavy utilization especially early in the growing season generated under-compensation biomass values in most of the species. BG was the species than responded in a better way to our defoliations treatments even over-compensation was observed in total biomass production. In contrast, KL has the worse response, where all defoliation scenarios significantly reduced its biomass production. The results of this study highlight the importance of consider plants phenological stage as an important variable while designing and grazing scheme.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Introduction

Most of the cattle production industry and several game species such as deer and other wild ungulates relay on the aerial biomass production of grasses and other vegetation species to cover their daily nutrient requirements. In the case of cattle most of their diet is based on grasses, for that reason since the creation of the range management science in the US by Arthur Sampson in the early 1900’s (Holechek 1981), one of the main objectives was to define an adequate utilization of grass species looking for balance between maximum cattle production and rangeland health. One tool to reach this goal is the implementation of grazing schemes. Grazing schemes in order to be successful have to be design according to type of grazing animal, topography, weather and vegetation species response to defoliation (Howery et al. 2000). Literature have showed that not all species respond in the same way to defoliations (Lang and Barnes 1942; Kennedy 1950; and Albertson et al. 1953; Branson 1956). Most of the literature focus in the effects of defoliation in forage production (Albertson 1953; Cable 1971; Richard and Caldwell

1985; Olson and Richards 1988) while others focused on the impact on underground organs mainly roots (Weaver and Hougen 1939; Crider 1955; Painter and Delting 1981,

Milchunas and Vandever 2013) being the main factors to study the impact of defoliation intensity and frequency, however there is a lack of information about the response of grasses to defoliations during a given developmental morphology stage (Briske 2015).

Developmental morphology is an important variable to consider when designing grazing schemes because forage production and energy flow depends the plant’s growth stage

(Esau 1960), mainly driven by the location of the apical meristems (Briske 1991; Dahl et al. 1995). When apical meristem is removed from a tiller, it tends to reduce biomass

Texas Tech University, Leobardo Richarte-Delgado, August 2018

production, and, in some cases, production is complete stopped. Tillers tend to elevate its apical meristem once internode elongation occurs right before plants start the transition from vegetative to reproductive stage, but this change is does not happen at the same time in all the species (Dahl et al. 1995). The main objective of this study was to evaluate the biomass production response of short, mid and tall grasses to clipping intensities at two plant’s developmental morphology stages, the specific objectives were to assess the impacts of defoliations treatments in the biomass allocation to the main plant structures; aerial tiller, crown, roots, individually, as well as, in the total plant biomass in the species mentioned above. Finally, we would like to determine if overcompensation is present in this species as a response of forage utilization.

Material and Methods

Site description

Dahl (WB) as a reference due to its high biomass production and drought tolerance which is regularly used in West Texas improved pastures. Vegetal material was collected from different sites: Blue grama was collected from three randomly selected plants from Texas

Tech University Native Grassland while sideoats grama, and switchgrass cultivar Kanlow were obtained from the Knox City Plant Material Center. Finally, two WW-B. Dahl plants were randomly collected from an improve pasture established around 15 years ago in the Justiceburg Ranch located 55 miles south east of Lubbock.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

This study was performed during the 2015 and 2016 growing seasons. At the beginning of each growing season 63 plants per species were stablished and growth in

19-L pots under homogenous environmental conditiona. Plants were transplanted mid-

July and harvested on November of each year (Table 3.3 to 3.4). This study was conducted at the Texas Tech University Native rangeland. This rangeland is approximately 65 hectares located in the northwest section of Lubbock, TX

(33°36'14.78"N, 101°53'50.44"W) at 992-m elevation. The area has dry steppe climate with mild winters. Main annual precipitation is 481 mm, with 73% occurring during the warm season, April through October (NOAA 2015). Warm season rainfall often occurs, as a result, of thunderstorms. May, June, and July are the main growth months for perennial warm season grasses (Blackstock et al. 1979). Average normal temperature on summer is 24.69 oC while in winter is 6.12 oC (NOAA 2015). Vegetation on the area consists of mid and shortgrass species. Grass species common to this site are sideoats grama, blue grama, buffalograss, sand dropseed (Sporobolus cryptandrus) and Arizona cottontop (Digitaria californica). The more commonly found forbs, scarlet globemallow

(Sphaeralcea coccinea [Nutt.]), Engelmann’s daisy (Engelmannia peristenia [Raf.]), baby white aster (Chaetopappa ericoides) and annual forbs. The primary woody species found are mesquite (Prosopis glandulosa) and plains pricklypear (Opuntia polyacantha); although, trees are seldom found on this site (Bradbury 2007).

Soil was collected from the Texas Tech Native grassland in an area of predominantly Amarillo soil type. This soil depth is 2 m, however we collected just the top 30 cm, this portion is friable, mildly alkaline, reddish fine sandy loam (Blackstock et al., 1979). Soil was mixed with 20% sand, air dried and passed through a 0.5 cm sieve,

Texas Tech University, Leobardo Richarte-Delgado, August 2018

after soil mixture was completed, posts (30 cm deep and 29 cm diameter) were filled and kept under field conditions inside the Texas Tech Native Rangeland until plant transplantation was performed.

Plant establishment process

Mature grass plants were collected at the beginning of the 2015 and 2016 growing seasons and gently divided into cuttings. Two cuttings per pot were transplanted to ensure the establishment of at least one plant; at the end of the establishment process cuttings were thinned to one per pot. For the extend of this study, a cutting was a tiller separated from the crown of a mother plant on early vegetative stage (no elongated stems) with viable roots. During the establishment process, pots were light irrigated every day during the morning to ensure a fast establishment. Success plant establishment was considered when transplanted cuttings started to produce new tillers from the basal crown, once this happened the experimental irrigation regime started.

Irrigation

Plants were irrigated three times a week during the length of the study, applying

2015) and determining the proportional amount of water that a 19-L pot (660 cm2 in area) will capture under that precipitation regime. Total amount of water applied per pot per growing season was close to 30 L (Table 3.1). Irrigations rates were modified with the presence of precipitation events.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Treatment application and sampling methods

Grasses were exposed to three clipping intensities, applied at three stages during the growing season. Clipping treatments were applied when target species were in the vegetative (V), reproductive (R) and post-reproductive (PR) stages. As several vital processes in grasses such as forage production, internode elongation, and energy balance are mandated by a series of developmental morphology processes occurring over the growing season (Esau 1960), this could influence how grasses respond to defoliation. The vegetative stage is characterized by leaf growing, reproductive stage is characterized by seedheand developing, pollination occurs, and seed develops (Barnhart 1999). Finally, post-reproductive stage is characterized by the ending of reproductive activities.

Defoliation treatments consisted of remove different portions of aboveground biomass of target plants. At each treatment application date, three different clipping intensities were applied; 0%, 50% and 75% of the stubble height. Clipping intensities were proposed base on Crafts and Glendening (1942) study which pointed out that, 50% is the optimal range of utilization for short grass species and is the fundamental basis for the common grazing strategy (take half and left half), 0% utilization was used as control, and 75% utilization will simulate heavy grazing intensity. Clipped material was stored in paper bags, weighted and set inside drying room at a temperature of 50 °C for at least 48 hours until constant weight.

Total plant biomass was harvested at the end of the growing season (mid-

November) and was separated into the three main structures, those structures were aerial tillers, crowns and roots. Aerial tillers (aboveground portion) were collected by clipping all the tillers 0.5 cm above ground level. Belowground biomass was collected by

Texas Tech University, Leobardo Richarte-Delgado, August 2018

carefully washing the roots with tap water over a 0.5 cm mesh in order to collect as much material as possible. Belowground portion was divided into crown and roots by cutting the samples right in transition between both structures. Biomass samples where air dried, until constant weight. Finally, once samples were completely dry were weighted and biomass was recorded.

Experimental design

All data were transformed to the log10 scale before statistical analysis was performed in JMP due to a violation in homogeneous variances and normality assumptions, once data were transformed to the log10 scale the assumption of homogeneous variances and normality was fulfilled in all the variables except for aboveground to belowground ratio. Response variables in this study were aerial tillers biomass, crown biomass, root biomass, total biomass, aboveground to belowground ratio and water use efficient (WUE) grams of water to produce 1 gr of dry biomass.

Data from each growing season was evaluated separately as unequal number of species was established each year. During the 2015 growing season just KL and ST were the only species evaluated while in the 2016 growing season we got four species; KL, ST,

BG and WB. For both evaluations the experimental design to analyze each response variable was a 3-way analysis of variance with three factors and several levels per factor; for the 2015 growing season evaluation, factors and levels were the following: factor: A) grass species, with 2 levels: 1) ST and 2) KL. Factor B) clipping intensities, with 3 levels; 1) 0% 2) 50% and 3) 75%. Factor C) phenological stage, with 3 levels; 1) vegetative, 2) reproductive and 3) post-reproductive. Each treatment was a combination of factors x levels. For this evalustion, we had 2x3x3 equal to 18 treatments and 7

Texas Tech University, Leobardo Richarte-Delgado, August 2018

replications per treatment, in total we have 126 experimental units. In the same way for the 2016 analysis, factors and levels were the following: Factors: A) grass species, with 4 levels: 1) BG 2) ST, 3) KL, 4) WB. Factor B) clipping intensities, with 3 levels; 1) 0%

2) 50% and 3) 75%. Factor C) phenological stage with 3 levels; 1) vegetative, 2) reproductive and 3) post-reproductive. Each treatment was a combination of factors x levels. For this nalisys, we had 4x3x3 equal to 36 treatments and 7 replications per treatment, in total we have 252 experimental units. Treatments were assigned randomly to each experimental unit. Data were statistically analyzed using jump statistical software using a full factorial arrangement (SAS Institute 2012).

Of the total treatment combinations just five were used because the rest were not relevant to the interpretation of this study. The treatments that I focused were 50% utilization during the vegetative stage (50xVeg), 50% utilization during the reproductive stage (50xRep), 75% utilization during the vegetative stage (75xVeg), 75% utilization during reproductive stage (75xRep), and 0% utilization during post-reproductive stage

(controls).

Results

All the response variables analyzed in this study were affected by a three-degree interaction (P<0.05) between plant phenological stage, species and clipping intensity

(Tables A1 to A.12).

Aerial tillers biomass

Defoliation treatments affected (P<0.05) the biomass allocation to the aerial tillers

(Table 4.1 and 4.7), however, not all the species responded in the same way. In BG heavy utilization during reproductive stage (75xRep) was the treatment that produced the

Texas Tech University, Leobardo Richarte-Delgado, August 2018

highest biomass values (4.14 g) however was no (P>0.05) different from the biomass produced by control plants (3.591g) or plants treated with moderate defoliation during reproductive stage (3.901 g). In contrast, the lowest aerial biomass values were found on plants under 75xVeg (2.60g) this value was significantly lower than control plants (Table

4.7). ST and KL were the species that were evaluated during the 2015 and 2016 growing seasons. ST plants produced similar aerial biomass values in both years. During the 2015 season, the highest biomass was found on control plants (8.661 g) nevertheless was no statistically different from values under 50xVeg (8.016g) but both treatments were higher than the rest. In contrast, the lowest values were found on plants treated with 75xRep

(4.292 g), this value was significantly lower than the rest of the treatments (Table 4.1). In the 2016 season, aerial biomass responded in a slightly different manner. The highest value was found in plants treated with 50xRep (8.392 g) being not different (P>0.05) from values found in control plants (7.182 g) and 50xVeg (7.961 g). In contrast, the lowest values were found on plants treated with 75xVeg (4.159 g), this value was significantly lower than the rest of the treatments (Table 4.7). KL plants produced slightly higher aerial tillers biomass during the 2015 growing season in relation to 2016, however, no statistical difference was found. In 2015 controls had the highest aerial biomass production (11.212 g), which was not different (P>0.05) from plants treated with

50xVeg (9.561 g), both treatments produced significantly higher biomass than the rest. In contrast, the lowest values were found on plants treated with 50xRep although this value was not significantly different from the values on 50xRep, 75xVeg, and 75xRep (Table

4.1), whereas, during 2016 the highest biomass was found on control plants (6.813 g) being not statistically different from 75xRep treatment (6.227 g) while both treatments

Texas Tech University, Leobardo Richarte-Delgado, August 2018

produced significantly higher biomass than the rest. In contrast, the lowest value was found on plants treated with 75xVeg (4.276 g) which were statistically different from

50xVeg and 50xRep treatments. Finally, WB biomass allocation to the aerial tillers was significantly affected by our defoliation treatments. The highest biomass (22.807 g) was found in plants under the 50xRep treatment. This value was slightly higher than control plants (20.703 g) however there were no significant differences between them.

Significantly lower values (14.959 g) were found on plants treated with moderate defoliation during the vegetative stage (50xVeg) (Table 4.7). Overall, tiller biomass production was affected by defoliation treatments and species combination. In BG, ST, and WB biomass production under at least one defoliation treatment was higher than the biomass in control plants although those differences were not big enough to be statistically significant. In BG, ST, and WB significantly lower biomass values were found on plants treated with heavy utilization during the vegetative stage (75xVeg). In contrast, KL responded in a totally different manner. KL aerial biomass decreased in relation to controls under any defoliation treatments, besides 50xVeg which produced compensatory values.

Crown biomass

Biomass allocated to the crowns was significantly affected by the defoliation treatments in each grass species (Table 4.2 and 4.8). In BG, plants under moderate utilization during the reproductive phenological stage (50xRep) stimulated biomass production to the crowns (1.874 g), this value was statistically higher even than controls

(1.467 g). In contrast, the lowest biomass (P<0.05) was found on plants treated with

75xVeg (1.088 g) (Table 4.8). ST biomass allocation to the crown was significantly

Texas Tech University, Leobardo Richarte-Delgado, August 2018

affected by our defoliation treatments, this response was slightly different among growing seasons. In 2015, significantly higher biomass values were found on plants under 50xVeg treatments (4.973 g), this value was statistically different from control plants (3.097 g). In contrast, in 2016 the highest values were found in control plants

(3.871 g), although this value was not significantly different from 50xVeg (3.698 g). In both years, 75xVeg treatment produced significantly lower biomass amounts (2.026 and

2.014 g, 2015 and 2016, respectively) than controls (Table 4.2 and 4.8). Defoliation treatments significantly affected biomass allocation to crowns in KL species (Table 4.2 and 4.8). There were small differences in plant response to defoliation treatments among years however these differences were not significant. During the 2015 season, significantly higher values were found on control plants (8.457 g) while in 2016 significantly higher values were found under 50xVeg treatments (8.172 g). In both years, significantly lower values in relation to controls were found in plants treated with

75xVeg (2.666 and 4.765 g, 2015 and 2016, respectively). Finally, biomass allocation to crowns was significantly affected by defoliation treatments on WB plants. The highest biomass production (6.977 g) was present under plants treated with moderate utilization during the reproductive stage (50xRep). This amount was significantly higher than the rest of the treatments including controls (5.777 g). In contrast, the lowest biomass was reported on plants under the 50xVeg (4.109 g) and 75xVeg (4.341 g) treatments (Table

4.8). In summary biomass allocated to the crowns showed overcompensation only on BG and WB plants under moderate utilization during the reproductive 50xRep.

Compensation was observed on plants exposed to moderate defoliation in both phenological stages (vegetative and reproductive). In contrast, significantly lower

Texas Tech University, Leobardo Richarte-Delgado, August 2018

biomass production was found in BG, ST, and KL species treated under 75xVeg treatments. While WB significantly lower biomass was found on plants treated during vegetative stage without distinction in clipping intensity. At the crown level it seems that moderate utilization regardless to plants phenological has a neutral in biomass production in relation to control plants. These results showed that native grasses such as BG and ST, and the introduce WB have a similar response to our defoliation treatments. In contrast,

KL responded in a different way, where basically all defoliation treatments reduced its crown biomass.

Root biomass

Roots biomass production responded differently to the defoliation treatments depending on the grass species (Table 4.3 and 4.9). In BG, the highest root biomass was found on plants treated with moderate defoliation during the reproductive stage (2.025 g), this amount was statistically higher than control plants (1.579 g). In contrast, the lowest roots biomass was found under 75xVeg treatment (1.075 g), this value was significantly lower than controls while the rest of the treatments produced mean values which were no statistically different (P>0.05) from controls (Table 4.9). ST root biomass was significantly (P>0.05) affected by our defoliation treatments. ST responded slightly different in 2015 in relation to 2016 season, but those differences were not statistically significant (P>0.05). In 2015. The highest root biomass value was found on plants under

50xRep treatment (5.135 g), which was significantly higher than controls (3.667 g) but were no statistically different from plants treated with 50xVeg (4.003 g) while significantly lower biomass values were found on plants treated with 75xVeg treatment

(2.226 g) (Table 4.3). In 2016, ST response was a little different, the highest biomass was

Texas Tech University, Leobardo Richarte-Delgado, August 2018

found in controls (4.791 g), however this amount was not different from plants under

50xRep (4.181 g) which produced the highest biomass in the previous season. In contrast, significantly lower biomass values were obtained on plants treated with 75xVeg (2.938 g)

(Table 4.9) which was the treatment that produced significantly lower values on 2015 season as well. KL root biomass was significantly affected by defoliation treatments. KL plants responded in a slightly differently way during the 2015 in relation to 2016 season although this difference was no statistically significant. In 2015, the highest root biomass was found in control plants (9.001 g) this value was significantly higher than the rest of the treatments. In the other hand, significantly, lower values were found on plants under the 75xVeg treatments (2.806 g) although this value was not different from the 3.406 g produced by plans treated with 50xVeg (Table 4.3); while in 2016, KL root biomass production presented different numbers, however they followed the same pattern as in

2015. Significantly higher values were found in controls (11.105 g), and significantly lower biomass values on plants under 75xVeg (3.611 g) (Table 4.9). Finally, we also found differences in the biomass production of roots influenced by our defoliation treatments in WB plants. Controls produced the higher roots biomass values (7.167 g) among all treatments however this value was not statistically different from plants treated with 50xVeg stage (6.158 g). In contrast, significantly lower roots biomass was produced on the other three defoliation treatments and no significant differences were detected among them (Table 4.9). In summary, roots biomass was significantly affected by our defoliations treatments. The lower roots biomass means were found on plants treated with

75xVeg treatments in all plants, besides WB where the lower values were found on

50xVeg treatments. BG was the only species where over-compensation was found

Texas Tech University, Leobardo Richarte-Delgado, August 2018

(50xRep). Roots biomass compensation was found in ST and WB in at least one treatment. In contrast, KL responded in negative way, where all defoliation treatments produced significantly lower biomass than control plants.

Total plant biomass

Total plant biomass is the sum of all the aboveground (aerial tillers biomass) and belowground structures (crown + roots). Total plant biomass as well as the other response biomass variables was significantly affected by our defoliation treatments (Tables 4.4 and

4.10). In BG, the highest total biomass was found on plants treated with 50xRep treatment (7.837 g) this mean was higher (P<0.05) than controls (6.723 g). In contrast, the lowest value was found in 75xVeg (4.818 g) which was statistically different from the rest of the treatments (Table 4.10). Defoliation treatments affected (P<0.05) total biomass production in ST (Table 4.4 and 4.10). Total biomass production in ST was similar in

2015 and 2016, however the significance of the defoliation treatment varied. In the 2015 season, the highest biomass production was found in plants under 50xVeg treatment

(17.235 g) although this value was not significantly higher than control plants (15.503 g).

In the other hand, the lowest biomass values were found on 75xRep (10.961 g) and

75xVeg (11.467 g) treatments both means were statistically different from controls

(Table 4.4). During the 2016 season, the highest total biomass value was found in plants under 50xRep treatment (16.378 g) but this value was not significantly different from controls (16.075 g), while significantly (P<0.05) lowest values were found on the 75xVeg treatment (8.661 g) (Table 4.10). ST responded in the same way during 2015 and 2016 growing seasons. In both years ST plants under 50xRep treatment produced similar total biomass than control plants, however, in 2015 50xVeg produced the highest biomass

Texas Tech University, Leobardo Richarte-Delgado, August 2018

amounts, in the same way, in both years the lowest biomass values were found on plants under the 75xVeg treatments, these values were significantly different from controls.

These results showed that there was no significant over-compensation of total biomass in

ST plants in response to defoliation treatments, but at the same time these results are also showing that ST total biomass does not decrease in relation to controls if moderate defoliation is applied during the reproductive stage. In the other hand, ST total biomass is negatively impacted when severe utilization is applied during the vegetation stage

(75xVeg).

Defoliation treatments affected total biomass production in KL (Table 4.4 and

4.10). Total biomass production was similar in 2015 and 2016 seasons, however the significance of the defoliation treatments varied. In 2015 growing season, the highest biomass production was found in controls (28.881 g) value which was significantly higher than the rest of the treatments, while, the lowest biomass production was found on plants under 75xVeg treatment (12.328 g) (Table 4.4). On the other hand, plants in the

2016 growing season produced slightly different biomass values but in general they followed then same pattern as the ones in the 2015 growing season. Significantly higher biomass values on controls (25.245 g) and the lowest values on the 75xVeg treatment

(12.744 g) (Table 4.10). Finally, in WB, the highest total biomass was found on plants treated with 50xRep (36.433 g) nonetheless this value was not different (P>0.05) than controls (33.733 g). In contrast, the lowest values were found in plants treated with

50xVeg (23.624 g), this value was significantly different from control plants but not different from 25.938 g found on plant under 75xVeg treatment (Table 4.10). Our results suggested that WB total biomass is improved by moderate utilization during the

Texas Tech University, Leobardo Richarte-Delgado, August 2018

reproductive stage. In summary total biomass production was improved by at least one defoliation intensity by phenological stage combination in relation to controls in BG, ST, and WB. These results suggest that in the species above total biomass production is stimulated by clipping. In contrast, KL showed the opposite response where total biomass production was significantly decreased by any defoliation treatment. Finally,75xVeg was the treatment that significantly decreased total biomass production in BG, ST and KL species.

Water use efficiency (WUE)

WUE express the grams of water utilized by a species to produce 1 gram of dry matter, in this study WUE is an equivalent of total plant biomass productions because all the species were exposed to a fixed amount of water which varied slightly from growing season to growing season (Table 3.1). WUE of each species was affected significantly

(P<0.05) by our defoliation treatments (Table 4.5 and 4.11). In BG, the lowest WUE values were found on plants treated with 50xRep (3835.9 gr H2O/gr DM) this value was statistically different from controls (4471.6 gr H2O/gr DM). In contrast, the higher values were found in the 75xVeg treatment (6239 gr H2O/gr DM) this value was significantly different from control plants as well (Table 4.11). The most efficient plants were those exposed to moderate utilization during the reproductive stage. These plants used 43% less water than controls to produce the same amount of biomass, while control plants and plants exposed to moderate utilization during the reproductive stage presented the same

WUE (4.5 liters of water to produce 1 gram of dry matter). In contrast, plants treated with heavy utilization during the vegetative stage proved to be the least efficient group (using

34% more water than the controls). ST was evaluated during the 2015 and 2016 growing

Texas Tech University, Leobardo Richarte-Delgado, August 2018

seasons. WUE slightly varied from growing season to growing season, however this difference was not statistically different (P>0.05). During the 2015, the lowest WUE values were found in plants under 50xVeg (1570 gr H2O/gr DM), however this value was not different from controls (1745.3 gr H2O/gr DM). In the other hand, significantly higher values were found on plants treated with 75xRep (24.68 gr H2O/gr DM) (Table 4.5).

While on the 2016, WUE values slightly varied but they presented similar response to the ones in the previous season. In 2016, the lowest WUE values was found on controls

(1860 gr H2O/gr DM) which was not different (P>0.05) from 1879.3 found in plants under 50xVeg and 50xRep (1825.8 gr H2O/gr DM) treatments. The highest value was found on plants treated with 75xVeg (3452.7 gr H2O/gr DM) this value was statistically different from controls and the rest of the treatments (Table 4.11). According to this study, the most WUE plants were the controls and those exposed to moderate utilization regardless of developmental morphology stage (1.79 liters of water to produce 1 gram of dry matter). Intermediate WUE was found in plants exposed to heavy utilization during the reproductive stage, this group used 35% more water than the most efficient plants.

Finally, the less efficient group expended twice the amount of water than controls. In this group we found the plants exposed to heavy utilization during the vegetative stage. KL plants were evaluated in 2015 and 2016 growing seasons (Table 4.5 and 4.11). In both growing seasons WUE was affected by our defoliation treatments. During 2015, the lowest values were found on control plants (756.3 gr H2O/gr DM), this value was significantly lower than the rest treatment means. The higher values were found on plants treated with 75xVeg (1772 gr H2O/gr DM) this value was statistically different from controls, although was not different from plants under 50xRep treatment (1576 gr H2O/gr

Texas Tech University, Leobardo Richarte-Delgado, August 2018

DM) (Table 4.5). WUE responded in like manner during the 2016 evaluation. The lowest

(P<0.05) WUE values were found on control plants (1184 gr H2O/gr DM). In contrast the highest values (P<0.05) were found on plants under 75xVeg (2346 gr H2O/gr DM) (Table

4.11). According to these results, there were three distinguishable groups among WUE means. The most efficient plants were the controls which in average required 0.970 litters of water to produce 1 gr of dry matter, the second group required 53% more water than the most efficient group (defoliated during the reproductive stage). Finally, the third group was the least efficient. These plants were treated with severe utilization during the vegetative stage (required 93% more water than controls). Finally, WUE on WB plants was also significantly affected by defoliation treatments (Table 4.11). The lowest values were found in plants under 50xRep (864 gr H2O/gr DM) treatment however this value was not different (P>0.05) from controls (933 gr H2O/gr DM), these two treatments used significantly fewer water than the rest of the treatments. In contrast, the highest values were found under plants treated with 50xVeg (1333 gr H2O/gr DM) but this value was not statistically different from plants under 75xRep (1214 gr H2O/gr DM) treatment.

Based in the mean separation analysis, WUE showed a clear distinction between two main groups. The first group was formed by the most efficient plants, those plants were controls and plants exposed to moderate utilization during the reproductive stage, in average thy required 0.90 litters of water to produce 1 gam of dry matter. The second was the least efficient group, formed by plants treated during the vegetative stage regardless of clipping intensity, which required in average 33.5% more water than the previous group. These results suggest that WB WUE can be improved by moderate utilization

Texas Tech University, Leobardo Richarte-Delgado, August 2018

during the reproductive stage. In contrast, any defoliation during the vegetative stage and severe utilization applied at reproductive stage significantly reduces it.

Aboveground to belowground biomass ratio

Aboveground to belowground ratio was calculated as the division of aboveground biomass fraction (Aerial tillers) by the total belowground biomass section which is the sum of crown and root biomass. In the literature this ratio is also called shoot to root ratio. Aboveground to belowground ratio was (P<0.05) affected by defoliation treatments

(Table A5 and A11). Ratios responded differently to clipping treatments depending on the grass species (Table 4.6 and 4.12). In BG, the highest ratio was present on plants treated with 75xRep (1.351), this ratio was significantly higher than control plants

(1.159). In contrast, the lowest ratio was found on plants under 50xRep treatments

(0.994) which is significantly different from controls (Table 4.6). Aboveground to belowground ratios were also significantly affected by defoliation treatments in ST. The effects of year were significant on ST ratios, as a result, these ratios responded in a differently way depending on the year. During 2015 the highest ratio was found on plants treated with 75xVeg (1.348), although this value was not statistically different from control plants (1.273). The opposite respond was found on plants under 75xRep (0.648) and 50xRep (0789) as they produced lower (P<0.05) ratios in relation to controls (Table

4.6), while on the 2016 season significant higher values were found in plants treated with

75xRep (1.161), value which was significantly higher than the control (0.823). In contrast, the lowest (P<0.05) ratio was found on control plants (0.823) (Table 4.12). This ratio in KL plants showed a different response to defoliation treatments depending on the growing season evaluation. During the 2015, the highest ratio was found on plants treated

Texas Tech University, Leobardo Richarte-Delgado, August 2018

with 50xVeg (1.397) this value was higher (P<0.05) than control plants (0.636) which presented the lower ratio values for KL in this year, being not different from 75xVeg

(1.236) (Table 4.6). During the 2016 growing season, values were different but kept the same pattern as in 2015. The highest ratio was found in plants under 50xRep (0.506) this value was lower than in the previous year (1.397) in the same way the lowest biomass ratios were found on control plants (0.371) (Table 4.12). In summary aboveground to belowground ratio in KL presented a similar response in terms of means separation, however ratios were bigger on 2015 growing season than in 2016. In 2015 two treatments produced ratios bigger than 1, while in 2016 none produced ratios even close to 1.

According to these results, any defoliation intensity during vegetative stage help to improve this ratio in KL. Finally, aboveground to belowground ratios in WB were significantly affected (P<0.05) by the defoliation treatment combination, although there was no a very clear distinction between mean groups (Table A.12). The highest values were found on plants treated with 75xVeg (1.845), this ratio was significantly different from controls which produced the lowest ratios of all the treatments (1.593). In contrast, ratios found in control plants were not statistically different from the ratios found in the other three treatments (Table 4.12). In summary the effects of our defoliation treatments on aboveground to belowground ratio varied depending on species, higher ratios (P<0.05) than controls where found on plants exposed to heavy utilization during the vegetative stage on all the species. In contrast, control plants presented (P<0.05) the lowest ratios among treatments means in ST, KL, and WB. In KL all the defoliations treatments produced rations higher than controls, the opposite response was observed in WB where just one treatment (75xVeg) produced significantly higher ratios than control plants.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Discussion

Aerial biomass

Aerial biomass response to defoliation intensities depended on the interaction between species, clipping intensity and plant phenological stage. In general, plants exposed to severe defoliations (75%) produced significantly lower biomass in relation to controls (under-compensation). We originally hypothesized that for short shoot species such as BG, ST and WB, any defoliation intensity during the vegetative stage would not cause drastic reduction in aerial biomass, however we found that among all the treatment combinations, heavy utilization during the vegetative stage in BG, ST and KL was the treatment that produced the lowest aerial biomass values. In contrast, moderate utilization

(50%) yielded compensation values in BG and ST, so here we found two totally different plant responses to defoliations applied during the vegetative stage. When plants were exposed to severe defoliations; aerial biomass was significantly reduced, however when they were exposed to moderate utilization (50%) there was not a negative effect in relation to control, except for KL which even under moderate utilization produced under- compensation values. The interaction effects between plant’s developmental morphology stage and defoliation are not well understood (Briske et al. 1995). Grass response to defoliation during the vegetative stage is not well understood and there are just few studies which looked at this variable (Vogel and Bjugstad 1968; Briske et al. 1995), moreover, contradictory results were observed. Positive effects were characterized by tiller stimulation (Jameson and Huss 1959; Vogel and Bjugstad1968; Cable 1971; Olson and Richards 1988). In contrast, tillering suppression was reported in big bluestem

(Andropogon gerardi), little blue stem and Indian grass (Sorghastrum nutans) (Vogel and

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Bjugstad 1968). In our study, response to defoliation seems to be driven by defoliation intensity while in the studies mentioned above defoliation intensity was not reported.

According to our results defoliation intensity was the key factor explaining the difference in response among short and long shoot species, since, during the vegetative phenological stage, either short or long shoots plants kept tillers apical meristems close to the soil surface, protected from defoliation (Richard and Branson 1953; Caldwell 1985; Dahl et al. 1995). Poor aerial biomass performance on heavy utilization in BG, ST, and WB was unexpected and might not be related to the removal of the apical meristem, we believe that this reduction was associated to a negative effect that heavy defoliations had in root growth. According to previous studies, root elongation and production stops between 18 to 25 days after heavy defoliations (>60%) (Crider 1955; Painter and Delting 1981). The stoppage in root growth, for as long as three weeks, in the long run could have accounted by the significant reduction in aerial biomass in heavily defoliated plants in relation to controls due to a reduction in potential water and nutrient acquisition (Christie and

Moorby 1975; Boot and Mensumk 1990). Root stoppage in our study was confirmed looking at the root biomass values (Table 4.3 and 4.9), as those plants produced significantly lower root biomass than controls. In contrast, plants under moderate utilization (50%) during the same stage produced aerial biomass compensatory values.

Neutral or compensatory effects in root grasses under moderate utilization (<50%) are reported in the literature too (Shuster, 1964; Milchunas and Vandever 2013).

In contrast, plants defoliated during the reproductive stage responded in a better way than when they were defoliated in the vegetative stage, this response was unexpected. We hypothesized that either severe or moderate forage utilization in short

Texas Tech University, Leobardo Richarte-Delgado, August 2018

and long shoot species during the reproductive stage would reduce aerial biomass in relation to controls because at this developmental morphology stage tillers had already elevated the apical meristems, expositing them to be easily removed by defoliation

(Branson 1953; Dahl 1995), surprisingly, we found that in BG, ST, and WB even under heavy utilization (75%) produced as much aerial biomass as the control. The aerial biomass stimulation by defoliation events during the reproductive stage was present in

BG, ST, and WB but not in KL. The key aspect to explain that difference might not be the long or short shoots plants classification that we hypothesized at the beginning of the study; but by the continuous production of tillers across the growing season, this characteristic is referred in the literature as asynchronous tiller production (Briske et al.

1995). BG, ST, and WB present this pattern of tiller recruitment, based on this characteristic we can assume that when defoliations occurred during the reproductive stage, older tillers where removed stimulating young tiller production, even to the point to generate biomass values comparable to control plants. Tiller stimulation after old tillers removal is reported in the literature due to release younger tillers from apical dominance. Apical dominance is referred as the physiological process by which an apical meristem produced auxins which inhibit bud production (Younger 1972; Hilman 1984;

Murphy and Briske 1992). Other studies also report increase in new tiller production after grazing by increase irradiance (Langer 1972; McNaughton 1979; Gold and Caldwell

1989) based on these morphological considerations we can understand the positive response of aerial biomass on plants treated during the reproductive stage. However, this positive response was not observed in KL. KL aerial biomass had a negative response to defoliations in the same way KL also present a different tiller production pattern than

Texas Tech University, Leobardo Richarte-Delgado, August 2018

BG, ST, and WB. KL produced a lower number of tillers and most of those them were recruited early in the growing season (synchronous tiller production) leading to a homogeneous tiller maturation, as a result, when KL plants were defoliated during the reproductive stage those culmed tillers died or responded very slowly producing biomass

(Briske 1995) this situation generated a significant decrease aerial biomass production in

KL plants in relation to the others. Similar situation was reported by Burrit and Reid

(2012) and Mott et al. (1992) which mention that plants that produce tillers across the entire growing season such as buffel grass (Cenchrus ciliaris) and tanglehead

(Heteropogon contortus) have higher grazing tolerance than synchronous plants. The concept of long and short shoot is very important for forage production response to defoliations, but it became critical if he grass present synchronous tiller recruitment.

Defoliation treatments produced slightly higher aerial biomass in at least one treatment combination on BG, ST, and WB in relation to control plants, however, the differences were not big enough to be significant, similar response was observed by

Albertson (1953) working with blue grama under different grazing intensities found slightly higher forage production on plants exposed to moderate utilization (60%) than on ungrazed areas, as a result, this study failed to found overcompensation in aboveground biomass production in response to defoliation treatments. Similar results were reported in the literature where overcompensation in aboveground biomass had been reported in just few studies, most of the time performed under greenhouse conditions (Painter and

Delting 1891) while overcompensation under field conditions is hard to find

(Damhoureyeh and Harnett 2002) due to stresses associated with competition and limited

Texas Tech University, Leobardo Richarte-Delgado, August 2018

resources availability (Maschinski and Whitham 1989; Vinton and Harnett 1992; Harper

1997).

In contrast, under-compensation was found on all species exposed to severe utilization during the vegetative stage, moderate utilization during the vegetative stage in

WB, and in all the treatments except for 50xVeg during 2015 and 75xRep during 2016, in

KL plants. Under-compensation is a common response of grazing on forage production in grasses (Neiland and Curtis 1956; Damhoureyeh and Harnett 2002;) however in this study it was related just to a very specific grazing conditions which were heavy utilization applied at the vegetative stage (75xVeg) regardless of long or short shoot classification. The response of the tall grass (KL) was very different, under-compensation was found in almost all defoliations combinations these results agreed with Damhoureyeh and Harnett (2002) which reported under-compensation in the tall grass sorghum nutans exposed to 50% utilization in the Konza prairie, by Harnett (1989) who reported significantly lower aerial biomass in switchgrass exposed to defoliation treatments and by

Neiland and Curtis (1956) who found lower tillering in big blue stem defoliated during the reproductive stage, this findings support Branson’s (1953) statement that tall grasses are more sensitive to grazing than short and mid grasses. Finally, compensation was found on moderate utilization regardless of season and even heavy utilization during reproductive stage in ST, BG and WB. The results of this study suggested that it is possible to maintain a healthy and productive short and mid grass rangeland community just with the application of adequate range management practices such as moderate plant utilization (take half and leave half) regardless of the plants phenological stage, however grazing practices in tall grass species would be more conservative as any defoliation

Texas Tech University, Leobardo Richarte-Delgado, August 2018

intensity regardless plants phenological stage reduced aerial biomass production in a significantly way.

Crown biomass

There are few studies looking at the effect of defoliations in grass crown biomass.

Staton (1983) working with blue grama under greenhouse conditions reported a slightly decrease of 9% of biomass allocated to crowns in plants exposed to moderate and heavy utilization in relation to controls, while there was not difference between moderate and heavy utilization. In contrast, Milchunas and Laurenroth (1989) working under field conditions reported no effects of heavy grazing (75% utilization) in relation to ungrazed sites. The results in our study varied depending on the species and plant morphology stage. Over-compensation was just found on BG and WB, in plants exposed to moderate utilization during the reproductive stage. The fact that this treatment produced heavier crown structures than controls, might be and indicative that these treatments could potentially benefit plants resprout as heavier crown biomass is related to a higher TNC carbohydrates concentration therefore higher tiller production potential than lighter crowns. The production of heavier crowns could be the result of two main factors 1) the stimulation of biomass or 2) the relocation of biomass (energy) from somewhere else in the plant to this portion. In this stusy, the higher amount of biomass in the crown seems not being driven by biomass reallocation from other plants structures, as biomass production of the other structures (aerial tillers and roots) was also higher on plants exposed to the same treatments. A different response was observed in KL during the

2016 growing season where moderate defoliations regardless plant’s phenological stage produced compensation values. These values seem to be the result of biomass relocation

Texas Tech University, Leobardo Richarte-Delgado, August 2018

from aerial tillers to crowns. In the other hand, under-compensation was found in all the species exposed to severe utilization but during the vegetative stage. Finally, crown biomass in plants exposed to moderate utilization regardless of plant’s phenological stage produced compensatory values in all the species. Here again there was a neutral effect of defoliation treatments if plants are exposed to moderate utilizations (50%) and a detrimental effect if plants are heavily defoliated during the vegetative stage.

Root biomass

Defoliation treatment combinations significantly affected the biomass allocated to the roots in all the grass species evaluated in this study. Root biomass over-compensation was just present on BG, in plants treated with moderate utilization during the reproductive stage, this treatment also promoted over-compensation in crowns in BG as well. Root biomass over-compensation in BG is not reported in the literature, however,

Shuster (1964) evaluating the effects of moderate and high utilization in relation to ungrazed plants in a BG dominated community found that under moderate utilization

(40%) plants produced significantly larger lateral spread root systems. In contrast, under- compensation was found in all species curiously under the same defoliation treatmetn; this treatment was heavy utilization during the vegetative stage (75xVeg). These results support previous evidence which suggest that grasses under heavy defoliations (>60%) significantly reduced root biomass (Crider 1955; Shuster 1964; Richards and Caldwell

1985; Thorton and Millard 1996), while moderate utilizations during the reproductive stage did not reduce root biomass in any species besides KL. BG was the species that responded in a better way to defoliations, since just one treatment reduced roots biomass significantly, that treatment was heavy utilization during the vegetative stage. ST

Texas Tech University, Leobardo Richarte-Delgado, August 2018

responded negatively to heavy defilations regardless plant’s stage, while WB root biomass was significantly decreased by heavy utilizations regardless of plant phenological stage and even to moderate utilization during the vegetative stage. Finally, the worse response was found on KL plants, where all treatments produced significantly lower root biomass that controls. In this study, plants exposed to moderate utilization

(50%) produced higher roots biomass than those exposed to heavy utilizations (75% utilization) which agrees with previous studies. Thorton and Millard (1996), working with festuca, lolium perenne and Poa tribvials reported in average 5.84 times more root biomass on plants exposed to moderate than to those exposed to heavy utilizations. In the same way, plants exposed to moderate utilizations but only during the vegetative stage produced roots biomass similar than controls in BG, ST, and WB, this response fits with previous studies performed in a shortgrass community which reported no difference in root biomass between ungrazed and moderate grazed areas (Shuster 1964; Milchunas and

Vandever 2013). The fact that root biomass production responded differently to the same grazing intensity depending on plant’s phenological stage, highlights the importance of considering plants developmental morphology stage when designing a grazing scheme and not just the percentage of utilization as it is indicated in most of the grazing management recommendations.

Total plant biomass

Total biomass production bein the sum the three structures mentioned before, this variable responded in a like manner as how those structures did when we looked at them individually. Total biomass over-compensation was a response very uncommon to find, in fact overcompensation was just found on BG plants exposed to moderate utilization

Texas Tech University, Leobardo Richarte-Delgado, August 2018

during the reproductive stage. These results agreed with most of the literature which pointed out that over-compensation in grasses under field conditions is hard to find

(Damhoureyeh and Harnett 2002). Even though some authors have suggested that overcompensation is being observed in grasses in the Serengeti (McNaughton 1976 and

1979), it is hard to define if overcompensation really present because, those articles just evaluated the aboveground biomass without considering the effects of grazing in the belowground portion of the plants. As a result, that overcompensation referred by them, could be the result of energy reallocation to the shoots as an expenses of biomass reduction in the belowground structures of the plants, then total plant over-compensation might not be present. However, this assumption is hard to prove because belowground biomass was not reported in such studies. In our study, we are confident that overcompensation was real as the entire plant was harvested. The most common response of total plant biomass in BG and ST was compensation. Compensation in these species was found in plants under moderate utilization regardless of plant phenological stage and even in plants exposed to severe utilization during the reproductive stage. Moreover, BG total biomass was just significantly reduced in one out of the four utilization scenarios.

These results support the idea that BG present the highest grazing tolerance of the species evaluated in this study, these results agree with Alberton (1953) who mention that shortgrass prairie is very difficult to destroy unless put under cultivation. WB responded slightly different, total biomass compensation was found only on plants exposed to moderate utilization during the reproductive stage, the rest of treatments produced under- compensation. These results where unexpected as we hypothesized that WB due to its morphological characteristics such as tiller production, short shoot classification would

Texas Tech University, Leobardo Richarte-Delgado, August 2018

help it to stimulate biomass production after grazing. In contrast, KL responded in a totally different manner, there was no compensatory or over-compensatory effects in KL total biomass production, every single treatment combination, produced under- compensation values. These results support the studies which classify tall grass species as less grazing tolerant which under severe defoliations tend to decrease in the presence of mid and short grass species such as BG and ST (Branson 1953). Finally, under- compensation was found in all grass species exposed to heavy utilization during the vegetative stage which was totally unexpected.

Aboveground to belowground ratio

Above to belowground ratios were significantly affected by defoliations intensity in this study, previous studies had demonstrated that grazing intensity can modify this ratio (Marshall and Sagar 1968; Ryle and Powell 1975; Ourry et al. 1990; Arredondo and

Jonhson 1998; Damhoureyeh and Harnett 2002), mainly by stimulating aboveground response and reducing root growth (Crider 1955; Damhoureyeh and Harnett 2002), this effect is more dramatic on plants subjected to heavy grazing intensities (>60%) (Crider

1955; Thornton and Millard 1996). Equivalent results were observed in this study. The treatment that reduced the most aerial tillers, crown and root biomass production in all the species (75xVeg), was also the treatment that produced significantly higher aboveground to belowground biomass ratios, which indicates that severe utilization during the vegetative stage overall reduces total biomass production, but the reduction in the belowground section is bigger in relation to the aboveground portion. This response might be logical as defoliation directly affects photosynthetically capacity of the plants by the removal of leaves and tillers, as a result, the capacity to fixed carbon is

Texas Tech University, Leobardo Richarte-Delgado, August 2018

significantly reduced (Heichel and Turner 1986; Painter and Delting 1981), while the root system remains intact, under this assumption; it is easy to understand that after defoliation, grasses will concentrate most of their resources to recover those structures that had been lost instead of generate more of those that already in place such as roots. In contrast, values significantly lower than controls were found just in BG plants, exposed to moderate utilization during the reproductive stage, in the majority of treatments defoliation intensities tend to improve slightly or significantly this ratio in relation to controls which could be a trait that suggest grasses adaptation to defoliation.

Aboveground to belowground ratios significantly differed among grass species. WB produced the highest rations, followed by BG and ST which produced similar values.

Finally significantly lower ratios were found in the tall grass species (KL), where values were not even close to 1. These results agreed with Wilsey and Polley (2006) study, which after comparing native versus introduced grass species in North America concluded that introduce species have a much higher aboveground productivity and lower root biomass that native ones, being this one of the main characteristics for which those species are selected and established in new environments aiming to increase forge production for cattle. In summary, all the grass species responded to defoliations by increasing resource allocation to the aboveground portion of the plant, even KL which in this study was the species which sent more resources to the belowground section. These results indicated that range manager can manipulate the defoliations intensity to increase forage production.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Water use efficiency (WUE)

WUE was affected by defoliation treatments in the same way as total biomass, this is easily explained because WUE values were calculated using the total biomass produced and a fixed amount of water for each growing season. The least efficient plants using water where those under the treatments that produced a reduction in total plant biomass. This treatment was heavy utilization during the vegetative stage for all the species, while the most efficient where those exposed to moderate defoliations during the vegetative stage in BG, ST, and WB; and control plants in KL, which where the treatments that produced the higher total biomass values. The results of this study proved that a good grazing management practices can alter water use efficiency in this grasses species, highlighting the importance of use good management practices, to improve the use of this resource which is very limited in semiarid environments such as the Southern

Great Plains of North America. According to these results, utilizations above 75% of the available forage during the vegetative stage could increase up to 70% the amount of water to produce the same amount of dry total biomass than ungrazed plants. While BG,

ST, and WB under moderate utilization during the reproductive stage could even decrease the amount of water by 3.6% in relation to control plants. This is very significant in semiarid areas where drought is usually present. These results showed that rangelands under adequate management schemes area able to use water as efficiently as unglazed areas while areas under overgrazing conditions requires 70% more water to produce the amount of biomass ungrazed areas. Bringing this scenario to the Southern

Great Plains in a blue grama-sideoats grama community with an average precipitation of

480 mm, an overgrazed community will require 816 mm precipitation to produce the

Texas Tech University, Leobardo Richarte-Delgado, August 2018

same amount of biomass that a well-managed rangeland. These results get even more dramatic with the presence of drought.

Conclusions

The results of this study suggest that biomass production of the studied species can be significantly affected by clipping intensities and by the developmental morphology of the plant at the time of defoliations. The short grass species (BG), the mid grass (ST) and the introduced WW-Dahl (WB) responded in a better way to moderate utilization regardless of phenological stage and even heavy utilizations during the reproductive stage, producing compensation biomass values and even over- compensation. In contrast, the tall grass switchgrass Kanlow (KL) responded in a negative way to any defoliations scenarios producing under-compensation values, even under moderate utilizations. These results reinforce the theory that shortgrass species can handle grazing in better way than tall grass species. Biomass allocation through the main plants structures on each species depended on the plant’s morphological stage and clipping intensity, in all the structures, heavy utilization during the vegetative stage produced the lowest biomass values among defoliation treatments which were significantly different from controls, while moderate utilization regardless of plant’s morphological stage produced compensatory values. In all species, clipping reduced roots biomass and favored shoot production, pattern which seems to increase with the increase in the percentage of forage utilization. This characteristic might be an adaptation that grasses developed, as a result, of frequent grazing.

The results of this study partially support the over-compensation theory proposed by McNaughton (1976) as total biomass over-compensation was found in BG exposed to

Texas Tech University, Leobardo Richarte-Delgado, August 2018

moderate utilization during the reproductive stage, although this response was not detected in rest of species. Compensation was observed in plants exposed to moderate utilization regardless of season of use in all the species except for KL, finally biomass under-compensation was a common result of plants exposed to heavy defoliations at the beginning of the growing season which suggests that plants are not able to totally recover from forage utilization in the same growing season after heavy defoliations events.

Finally, this study showed that WUE can be significantly alter by defoliation treatments, a significant increase in WUE in relation to controls was only present in BG plants exposed to moderate utilization during the reproductive stage while heavy utilization during the vegetative stage significantly reduced WUE in all the studied species close to 75%. This highlights the importance of use adequate stocking rates specially for semiarid environments where drought is commonly present such the

Southern Great Plains of north America. The results of this study emphasize the preponderance of incorporate plant’s developmental morphology stage as meaningful variable in the design of grazing schemes due to its considerable influence in plant biomass response to defoliations.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Literature cited

Albertson, F.W., A. Riegel, and J. L. Launchbaugh. 1953. Effects of different intensities of clipping on short grasses in West-central Kansas. Ecology. 34:1-20. Arredondo, J.T., and Douglas A. Johnson. 1998. Clipping effects on root architecture and morphology of 3 range grasses. Journal of Range Management. 51(2): 207-213. Barnhart, S.K. 1999. How pasture plants growth. Iowa State University. University extension. Blackstock, D.A., E. R. Blakley., C. T. Landers., W. M. Koos., and L. A. Putman. 1979. United States Department of Agriculture-Natural Resources Conservation Service Soil Survey of Lubbock County, TX. Boot, R.G.A. Mensuk, M., 1990. Plant and soil 129, 291-299. Size and morphology of root systems of perennial grasses from contrasting habitats as affected by nitrogen supply. Branson, F.A. 1953. Two new factors affecting resistance of grasses to grazing. J. Range Manage. 6:162-121. Branson, F.A. 1956. Quantitative effects of clipping treatments on five range grasses. Journal of Range Management. 92: 86-88. Bradbury, Stand. 2007. Ecological Site Description. United States Department of Agriculture-Natural Resources Conservation Service. http://esis.sc.egov.usda.gov/Welcome/pgApprovedSelect.aspx?type=ESD. July 03, 2010. Briske, D.D. 1991. Developmental morphology and physiology of grasses. p. 85-108. In: R.K. Hitschmidt and J.W. Stuth (eds.) Grazing Management: an ecological perspective. Timber press, Portland, Oregon. Briske, D.D., and J.H. Richards. 1995. Plant Responses to Defoliation: A physiological, Mophological and Demographic Evaluation. P 635- 55693. In: D. J. Bedunah and R.E. Sosebee (Eds.). Wildland Plants: Physiology Ecology and Developmental Morphology. Society for Range Management. Denver, CO. Burritt, B., and C. Reid. 2012. Carbohydrate reserve theory: what you learned might be wrong. Utah university cooperative extension. Cable, D.R. 1971. Growth and development of Arizona cottontop (Trichachne californica [Benth.] Chase). Bot. Gaz. 132:119-145. Caldwell, M.M., J.H. Richards, D.A. Johnson, R.S. Novak, and R.S Dzurec. 1981. Coping with herbivory: photosynthetic capacity and resource allocation in tow semiarid Agropyron bunchgrasses. Oecologia. 50: 14-24.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Christie, E.K., Moorby, J., 1975. Physiological responses of semi-arid grasses. the influence of phosphorus supply on growth and phosphorus absorption. Australian journal of agricultural research 26 423-436. Crafs, R.E. and G.E. Glendening. 1942. How to graze blue grama on southwestern ranges. U. S. Dept. Agr. Leaflet 215: 1-8. Crider, F.J. 1955. Root-growth stoppage resulting from defoliation of grass. USDA-SCS. Washington D. C. Tech Bull. No. 1102. Dahl, B.E., 1995. Developmental Morphology of plants. p 22- 55. In: D. J. Bedunah and R.E. Sosebee (Eds.). Wildland Plants: Physiology Ecology and Developmental Morphology. Society for Range Management. Denver, CO. Damhoureyeh, S.A., and D. Hartnett. 2002. Variation in grazing tolerance among three tallgrass prairie plant species. American journal of Botany. 89(10): 1634-1643. Esau, K. 1960. Anatomy of seed plants. Wiley & Son, New York. 376p. Harper, J.L., 1977. Population biology of plants. Academic Press, London. Harnett, D.C. 1989. Density- and growth stage-dependent responses to defoliation in tow rhizomatous grasses. Oceologia 80:414-420. Heichel, and, G.H., and N.C. Turner. 1983. CO2 assimilation of primary and regrowth foliage of red maple (Acer rubrum L.) and red oak (Quescus rubra L.); response to defoliation Oecologia 57: 14-19. Hilman, J.R. 1984. Apical dominance. P. 127-148. In M.B. Wilkins (ed.) Advance plant physiology. Ptiman publ. London. Herrero-Jáuregui, C., Schmitz M, Pineda F. 2014. Effects of different clipping intensities on above-and below-ground production in simulated herbaceous plant communities. Plant Biosystems-An International Journal Dealing with all Aspects of Plant Biology. 150 (3): 468-476. Hyder, D.N., 1972. Defoliation in response to vegetative growth. P. 302-3017. In: V.B. Younger, and C.M. Mckell (eds.) The biology and utilization of grasses. Academic press, New York. Hyder, D.N. 1974. Morphogenesis and management of perennial grasses in the Unites States, pp. 89-88. In: Plant morphogenesis as the basis for scientific management of range resources. Proceedings of the workshop of the U.S/Australian rangelands panel. Berkeley Calif. March 29-April 5, 1971. U.S. Dep. Agri. Misc. Public. 1271. Hodkinson, K.C. 1974. Influence of partial defoliation on photosynthesis, photorespiration and transpiration by Lucerne leaves of different ages. Aust. J. Plant Physiology 1:561-578.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Holechek, J.L., Rex D. Pieper, and Carlton H. Herbel. 2003. Range management principles and practices. Fifth edition. Howery, A.L., J.E. Sprinkle and J.E. Browns. 2000. A summary of livestock grazing systems used on rangelands in the Western States and Canada. Cooperative Extension. University of Arizona. Issoufou, M., M. Zaman-Allah, A. Ferchichi and E. Ferjani. 2008. Clipping effects on the growth Variation, Water Use Efficiency and Photosynthetic Activity in Buffel Grass (Cenchrus ciliaris L.) Poaceae. Asian Journal of Plant Sciences. 7(1): 95-99 Langer, R.H.M. 1972. How Grasses Grow. Edward Arnold Ltd., London. Gold, W.G., and M.M. Caldwell. 1990. The effects of spatial pattern of defoliation on regrowth of tussock grass. II. Canopy gas exchange. Oceologia 81:437-442. Jameson, D.A., D.L. Huss. 1959. The effect of clipping leaves and stems on number of tillers, herbage weights, root weights, and food reserves of little blue stem. J. Range Management. 12:122-126. Kennedy, W.K. 1950. Simulated grazing treatments, effect on yield, botanical composition, and chemical composition of a permanent pasture. Cornell Univ. Agr. Exp. Sta. Memoir 295 Lang, Robert, and O.K. Barnes. 1942. Range forage production in relation to time and frequency of harvesting. Wyo. Agr. Expt. Sta. Bull. 253: l-32. Maschinski, J., and T.G. Whitman. 1989. The continuum of plant responses to herbivory the influences of plant association, nutrient availability, and timing. Am. Nat. 134:19 Marshall, C., and G.R. Sagar. 1968. The distribution of assimilates in Lolium multiflorum Lam. Following different defoliation. Ann. Bot. 32: 715-719. McNaughton, S.J. 1976. Serengeti migratory wildebeest: facilitation of energy flow by grazing. Science 191:92-94. McNaughton, S.J. 1979. Grazing as ab optimization process: grass-ungulate relationship in the Serengeti, Am. Nay. 113:691-703. Milchunas, D.G. and M.W. Vandever. 2013. Grazing effects on aboveground primary production and root biomass of early-seral, mid-seral, and undisturbed semiarid grassland. Journal of Arid Environments. 92:81-88. Milchunas, D.G. and W.K. Lauenroth. 1989. Three-Dimensional Distribution of Plan Biomass in Relation to Grazing and Topography in the Shortgrass steppe, Oikos. 55(1):82-86. Mott, J.J., M.M. Ludlow, J.H. Richards, and A.D. Parsons. 1992. Effects of moisture supply in the dry season and subsequent defoliation on persistence of the savanna

Texas Tech University, Leobardo Richarte-Delgado, August 2018

grasses Themeda triandra, Heteropogon contortus and panicum maximun, Aust. J. Agric. Res. 43: 241-260. Murphy, J.S. and D.D. Briske. 1992. Regulation of tillering by apical dominance: Chronology, interpretive value, and current perspectives. J. Range Management 45: 419-419. Neiland, B.M. and J.T. Curtis. 1956. Differential responses to clipping of six prairie grasses in Wisconsin. Ecology 37:355-365 NOAA. 2011. National oceanic and atmospheric administration http://www.srcc.lsu.edu/climateNormals/ (accessed 20 May 2015). Olson, B.E., and J.H. Richards. 1988. Tussock regrowth after grazing; intercalary meristem and axillary bud activity of Agropyron desertorum. Oikos 51: 374-382. Ourry, J. Boucaud, and J. Salette. 1990. Partitioning and remobilization of nitrogen during regrowth in nitrogen-deficient ryegrass. Crop Sci. 30: 1251-1254. Painter, E.L., and J.K. Delting. 1981. Effects of Defoliation on Net Photosynthesis and regrowth of Western Wheatgrass. Journal of Range Management. 34(1): 68-71. Richards, J.H., and M.M. Caldwell. 1985. Soluble carbohydrates, concurrent photosynthesis and efficiency in regrowth following defoliation: A field study with Agropyron species. J. Appl. Ecol. 22:907-920. Ryle, G.J., and C.E. Powell. 1975. Defoliation and regrowth in the gramineous plant: the role of current assimilates. Ann. Bot. 39:297-310. SAS Institute Inc. 2012. Using JMP 10. Cary, NC: SAS Institute Inc. Shuster, J.L. 1964. Root development of Native Plants Under Three Grazing intensities. Ecology. 45(1): 63-70. Snyman. 2004. Rangeland degradation in a semi-arid south Africa- I: influence of seasonal root distribution, root/shoot ratios and water-use efficiency. Journal of Arid Environments. 1-25 p. Snyman, H.A., and Founche, H.J. 1991. Production and water-use efficiency of semi-arid grassland of South Africa as affected by veld conditions and rainfall. Water South Africa (17): 263-268 Stanton, N. 1983. The effects of clipping and Phytophagous Nematodes on Net primary production of Blue Grama, Bouteloua gracilis. Oikos. 40(2): 249-257. Thornton, B., and P. Millard. 1996. Effects of severity of defoliation on root functioning in grasses. Journal of Range Management. 49(5)443-447. Villanueva-Avalos, J. F. 2008. Effect of defoliations patterns and developmental morphology on forage productivity and carbohydrates reserves in WW-B Dahl

Texas Tech University, Leobardo Richarte-Delgado, August 2018

grass [Bothriochloa bladhii (RETZ) S.T. BLAKE]. Ph. D. Dissertation. Texas Tech University. 311 p. Vinton, M.A., and D.C. Harnett. 1992. Effects of bison grazing on Andropogon gerardii and Panicum virgatum in burned and unburned tall grass prairie. Oecologia 90:374-382. Vogel, W.G., and A.J. Bjugstad. 1968. Effects of clipping on yield and tillering of little bluestem and big blue stem, and indiangrass. J. Range Management 21:136-140. Weaver, J.E. and V.H. Hougen. 1939. Effect of frequent clipping on plant production in prairie and pasture. Amer. Midl. Naturalist 21: 396-414. West Texas Mesonet. 2015. http://www.mesonet.ttu.edu/mesonet-precipitation.htm (accessed 20 May 2015). Wilsey, B.J., Polley, H.W. 2006. Aboveground productivity and root-shoot allocation differ between native and introduced grass species. Oecologia 150, 300-309. Younger, V.B. 1972. Physiology of defoliation and regrowth. In. V.B. Younger and C.M. McKell (eds.) The biology and utilization of grasses, p 292-303. Academic press, New York and London.

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Tables

Table 4. 1. Biomass (g/pot) allocated to the aerial tillers of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean KL ST Control 11.212 (1.047) A1a2 8.661 (1.067) A b 9.937 50xVeg 9.561 (1.104) A a 8.016 (1.078) A a 8.789 50xRep 6.032 (1.091) B a 6.261 (1.074) B a 6.147 75xVeg 6.791 (1.044) BC a 6.434 (1.053) B a 6.613 75xRep 7.421 (1.049) C a 4.292 (1.093) C b 5.857 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Table 4. 2. Biomass (g/pot) allocated to the crown of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean KL ST Control 8.457 (1.041) A1a2 3.097 (1.079) B b 5.777 50xVeg 3.379 (1.117) C b 4.973 (1.148) A a 4.176 50xRep 2.853 (1.116) C a 2.639 (1.118) BC a 2.746 75xVeg 2.666 (1.099) C a 2.026 (1.213) D b 2.346 75xRep 5.264 (1.083) B a 2.395 (1.107) CD b 3.830 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 4. 3 Biomass (g/pot) allocated to the root portion of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean KL ST Control 9.001 (1.055) A1a2 3.667 (1.062) B b 6.334 50xVeg 3.406 (1.116) C a 4.003 (1.136) AB a 3.705 50xRep 4.829 (1.092) B a 5.135 (1.133) A a 4.982 75xVeg 2.806 (1.086) C a 2.226 (1.365) C a 2.516 75xRep 4.969 (1.111) B a 4.144 (1.101) AB a 4.557 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Table 4. 4. Total plant biomass (g/pot) of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean KL ST Control 28.881 (1.031) A1a2 15.503 (1.053) AB b 22.192 50xVeg 16.492 (1.093) BC a 17.234 (1.085) A a 16.863 50xRep 13.861 (1.071) C a 14.251 (1.077) B a 14.056 75xVeg 12.328 (1.052) C a 11.467 (1.052) C a 11.897 75xRep 17.824 (1.054) B a 10.961 (1.074) C b 14.392 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 4. 5. Water use efficiency (g H2O/g of dry biomass/pot) of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species 1Means Treatment Mean KL ST in the Control 756.536 (1.031) A1a2 1745.371 (1.053) AB b 1250.95 same column 50xVeg 1324.814 (1.093) B a 1570.041 (1.085) A b 1447.428 50xRep 1576.431 (1.071) C a 1898.794 (1.077) B b 1737.613 75xVeg 1772.331 (1.052) C a 2359.591 (1.052) C b 2065.961 75xRep 1225.819 (1.054) B a 2468.831 (1.074) C b 1847.325 followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Table 4. 6. Aboveground to belowground ratio of KL and ST species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean KL ST Control 0.636 (1.053) B1 b2 1.273 (1.063) A a 1.909 50xVeg 1.397 (1.09) A a 0.891 (1.143) B b 1.144 50xRep 0.781 (1.109) B a 0.789 (1.081) BC a 0.785 75xVeg 1.236 (1.073) A b 1.348 (1.197) A a 1.292 75xRep 0.718 (1.081) B a 0.648 (1.078) C a 0.683 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 4. 7. Biomass (g/pot) allocated to the aerial tillers of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean BG ST KL WB Control 3.591 (1.095) B1C c2 7.182 (1.087) AC b 6.813 (1.071) A b 20.703 (1.054) AB a 9.572 50xVeg 3.155 (1.111) B d 7.961 (1.11) A b 5.464 (1.099) B c 14.959 (1.046) C a 7.884 50xRep 3.901 (1.125) BA d 8.392 (1.081) A b 5.123 (1.091) BC c 22.807 (1.11) A a 10.055 75xVeg 2.604 (1.111) C d 4.159 (1.035) C b 4.276 (1.085) D b 16.746 (1.065) CD a 6.946 75xRep 4.147 (1.094) A d 6.403 (1.126) B b 6.227 (1.083) A b 17.904 (1.099) AD a 8.670 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

100

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 4. 8. Biomass (g/pot) allocated to the crown of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean BG ST KL WB Control 1.467 (1.132) A1 c2 3.871 (1.144) A b 7.213 (1.101) A a 5.777 (1.048) B a 4.582 50xVeg 1.625 (1.113) AB c 3.698 (1.094) A b 8.172 (1.093) A a 4.109 (1.093) C b 4.401 50xRep 1.874 (1.091) A c 3.733 (1.156) A b 7.059 (1.089) AC a 6.977 (1.098) A a 4.910 75xVeg 1.088 (1.135) C c 2.014 (1.113) B b 4.765 (1.084) D a 4.341 (1.098) C a 3.052 75xRep 1.413 (3 1.1) B c 2.396 (1.128) B b 6.817 (1.101) C a 6.131 (1.08) B a 4.189 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

101

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 4. 9. Biomass (g/pot) allocated to the root portion of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean BG ST KL WB Control 1.579 (1.071) B1 d2 4.791 (1.093) A c 11.105 (1.062) A a 7.167 (1.086) A b 6.160 50xVeg 1.413 (1.088) B c 3.991 (1.113) B b 5.544 (1.109) B a 4.384 (1.115) B b 3.833 50xRep 2.025 (1.136) A d 4.181 (1.129) AB c 4.492 (1.083) C b 6.158 (1.075) A a 4.214 75xVeg 1.075 (1.082) C d 2.398 (1.122) D c 3.611 (1.121) D b 4.663 (1.074) B a 2.936 75xRep 1.629 (1.137) B c 3.087 (1.119) C b 5.735 (1.126) B a 4.962 (1.078) B a 3.853 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

102

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 4. 10. Total plant biomass (g/pot) of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean BG ST KL WB Control 6.723 (1.072) B1 a2 16.075 (1.074) A b 25.245 (1.065) A c 33.733 (1.053) A d 20.444 50xVeg 6.271 (1.079) B a 15.911 (1.069) A b 19.217 (1.096) B c 23.624 (1.049) C d 16.255 50xRep 7.837 (1.112) A a 16.378 (1.105) A b 16.767 (1.076) B b 36.433 (1.071) A c 19.353 75xVeg 4.818 (1.091) C a 8.661 (1.059) C b 12.744 (1.078) C c 25.938 (1.052) BC d 13.040 75xRep 7.229 (1.096) AB a 11.964 (1.112) B b 18.871 (1.094) B c 29.119 (1.084) B d 16.795 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

103

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 4. 11. Water use efficiency (g H2O/g of dry biomass/pot) of BG, ST, KL and WB species affected by five defoliation intensity by plant phenological stage combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean BG ST KL WB Control 4471.641 (1.072) B1 a2 1860.129 (1.074) C b 1184.491 (1.065) C c 933.891 (1.053) C d 2112.538 50xVeg 4793.436 (1.079) B a 1879.309 (1.069) C b 1556.036 (1.096) B c 1333.526 (1.049) A d 2390.576 50xRep 3835.905 (1.112) C a 1825.817 (1.105) C b 1783.439 (1.076) B b 864.691 (1.071) C c 2077.463 75xVeg 6239.189 (1.09) A a 3452.731 (1.059) A b 2346.316 (1.078) A c 1214.548 (1.052) AB d 3313.196 75xRep 4158.658 (1.096) BC a 2499.374 (1.112) B b 1584.692 (1.094) B c 1081.864 (1.084) B d 2331.147 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same stage row followed by the same lower-case letter are not significantly different (P>0.05, HSD).

104

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 4. 12. Aboveground to belowground ratio of BG, ST, KL, and WB species affected by five defoliation intensity by plant phenological stage combination, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangelands, Lubbock TX, USA. Species Treatment Mean BG ST KL WB Control 1.159 (1.087) B1C c2 0.823 (1.126) D b 0.371 (1.074) C b 1.593 (1.038) B a 0.9865 50xVeg 1.023 (1.088) BD c 1.021 (1.121) BC c 0.397 (1.016) C b 1.752 (1.093) AB a 1.048 50xRep 0.994 (1.049) D c 1.058 (1.069) AB a 0.442 (1.086) B b 1.712 (1.117) AB a 1.051 75xVeg 1.191 (1.088) C b 0.934 (1.091) C c 0.506 (1.051) A d 1.845 (1.084) A a 1.119 75xRep 1.351 (1.046) A b 1.161 (1.076) A c 0.494 (1.061) AB d 1.602 (1.044) B a 1.152 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD). 2Means on the same stage row followed by the same lower-case letter are not significantly different (P>0.05, HSD

105

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Figures

Control 50xVeg 50xRep 75xVeg 75xRep 14 12 a a 1 10 a a c b b bc 8 b

biomass (g) biomass 6 c

Dry 4 2 0 ST KL Species

Figure 4. 1 Aerial biomass (gr; SEM) of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Dry biomass means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

106

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep 10 a 9 8 7 b 6 c

5 1 a c c biomass (g) biomass 4 ab c 3 d bd Dry 2 1 0 ST KL Species

Figure 4. 2 Crown biomass (gr; SEM) of ST and KL and WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Dry biomass means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

107

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep 10 a 9 8 7 b c 6 c ab a1 ab

5 b biomass (g) biomass 4 b

Dry c 3 2 1 0 ST KL Species

Figure 4. 3 Root biomass (gr; SEM) of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Dry biomass means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

108

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep 35 a 30

25 b e 20 ab1 ce a bc

biomass (g) biomass c b 15 c

Dry 10

0 ST KL Species

Figure 4. 4. Total biomass (gr; SEM) of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Dry biomass means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

109

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep 1.6 a b 1 1.4 a b 1.2 b bc 1 a a c 0.8 a 0.6 Above/below Above/below ratio 0.4 0.2 0 ST KL Species

Figure 4. 5 Aboveground to belowground biomass ratios of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Aboveground to belowground ratio means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

110

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep 3000 c c 2500 a 2000 ab1 c b c b WUE 1500 b

1000 a

500

0 ST KL Species

Figure 4. 6 Water use efficiency (g H2O/g of dry biomass) of ST and KL plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2015 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1WUE within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

111

Texas Tech University, Leobardo Richarte-Delgado, August 2018

26 Control 50xVeg 50xRep 75xVeg 75xRep c 24 22 ac 20 d 18 d b 16 14 12 biomass (g) biomass 10 a a ac a ac

Dry c 8 ce e 6 1 c c b c ac a 4 b 2 0 BG ST KL WB Species

Figure 4. 7 Aerial biomass (gr; SEM) of BG, ST, KL WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Dry biomass means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

112

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep

10 a 9 a 8 ac c c ac 7 a d 6 b 5 a a a b

biomass (g) biomass 4 b b 1 b Dry 3 a ab a 2 c 1 0 BG ST KL WB Species

Figure 4. 8 Crown biomass (gr; SEM) of BG, ST, KL WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Dry biomass means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

113

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep 14 a 12 10 a 8 c b a b b biomass (g) biomass b 6 ab c b b a d Dry 4 b c a1 a a c 2 0 BG ST KL WB Species

Figure 4. 9 Root biomass (gr; SEM) of BG, ST, KL WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Dry biomass means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

114

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep

40 a a 35 c 30 a bc b 25 b b 20 a a a b

biomass (g) biomass 15 c d

1 b Dry 10 a a a ab b 5 0 BG ST KL WB Species

Figure 4. 10 Total biomass (gr; SEM) of BG, ST, KL WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Dry biomass means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

115

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep 2.5

2.0 b ab ab a a 1.5 b ad1 d e ac c be bc c a /below /below ratio 1.0 d ab be ed

Above a 0.5

0.0 BG ST KL WB Species

Figure 4. 11 Aboveground to belowground biomass ratio of BG, ST, KL and WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1Aboveground to belowground ratio means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

116

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Control 50xVeg 50xRep 75xVeg 75xRep

7000 c 6000 a a1 5000 ab b 4000 b c WUE 3000 c a a a b b b 2000 a b bc a a c 1000 0 BG ST KL WB Species

Figure 4. 12 Water use efficiency (g H2O/g of dry biomass) of BG, ST, KL and WB plants exposed to five defoliation intensity by plant phenological stage treatment combinations, evaluated during the 2016 growing season under field conditions at the Texas Tech Native Rangeland, Lubbock TX, USA. 1WUE means within the same grass species marked with the same lower-case letter are not significantly different (P>0.05, HSD).

117

Texas Tech University, Leobardo Richarte-Delgado, August 2018

CHAPTER V

DEVELOPMENTAL MORPHOLOGY OF SIX GRASSES OF NORTH

AMERICA

Abstract

This study was performed during the 2015 growing season under greenhouse conditions in the Plant and Soil Science greenhouse, Texas Tech University. Fifteen plants of each of these grass species were established in plastic pots and grown under uniform soil and environmental conditions. Two cuttings per plant were transplanted into each pot and irrigated daily for two weeks to allow for plant establishment, then thinned to one plant per pot. Species included in this study were blue grama (BG), sideoats gram

(ST) and switchgrasses. Four genotypes of switchgrasses were included: Alamo (AL) and

Kanlow (KL) cultivars plus two unknown switchgrass types, type I (CI) and type II (CII).

The main objective of this study was to determine developmental morphology and tiller recruitment differences among these species representative of the tree major grasslands of

North America. Developmental morphology and number of tillers per plant were evaluated once a month from July to November. Developmental morphology was evaluated using the MSC methodology. An analysis of variance was performed at each evaluation date to determine significant differences in MSC among the grasses. The results of this study indicated significant differences in MSC among species at every evaluation time. KL showed the highest MSC values at every evaluation. There were no significant differences between AL and CI, but CII had lower MSC values than the other switchgrass types. BG and ST had the higher number of tillers and lower MSC values than the switchgrasses at each evaluation date. Early internode elongation and lack of fall

118

Texas Tech University, Leobardo Richarte-Delgado, August 2018

regrowth in switchgrass were the main reasons for those differences. Based on the results of this study, we conclude that there is a difference in developmental morphology and tiller recruitment pattern between switchgrasses and the short and mid-grass species.

However, there were no differences between the short grass (BG) and the mid grass (ST), both of which seem to follow the same maturation and tiller recruitment pattern over the growing season.

Introduction

The great plains of the United States can be divided into three major areas due to changes in environmental conditions, mainly precipitation and evapotranspiration gradients. Those major areas are shortgrass, mid-grass, and tallgrass prairie. The shortgrass prairie is dominated by blue grama (Bouteloua gracilis) and buffalograss

(Bouteloua dactyloides), which are grazing tolerant. The midgrass prairie is dominated by a mixture of short and mid grasses, including sideoats grama (Bouteloua curtipendula), blue grama, buffalograss, and little bluestem (Schizach scoparium) The tallgrass prairie is characterized by little bluestem which dominates the drier uplands, and big bluestem

(Andropogon gerardii) with dominates the more mesic lowlands. These two species comprise about 80% by weight of tallgrass prairie climax composition (Holechek et al.

2003).

Several processes in grasses, such as forage production and energy balance, are mandated by developmental morphology occurring throughout the growing season. In grasses, developmental morphology determines plant architecture organization, influences accessibility and palatability to herbivores and affects regrowth after defoliation (Briske 1991). Developmental morphology is dynamic (Moore and Moser

119

Texas Tech University, Leobardo Richarte-Delgado, August 2018

1995) and is affected by several factors, the main ones being genetics and environmental conditions (Hendrikson et al. 1998). There are marked differences among short, mid, and tall grasses in terms of grazing resistance which are linked to developmental morphology, one of the most important one being grazing tolerance. Most short, and some mid grasses produce short shoots through most of the growing season. These short shoots maintain their apical meristems close to the soil surface and are inaccessible to most grazing animals. Therefore after grazing, the apical meristem is still active, producing new material and generating fast recovery after defoliation. On the other hand, long shoots plants, also known as culmed shoots, are the main types present in most tall grasses

(Branson, 1953). These species tend to elevate their apical meristem early in the growing season exposing the apical meristems to potential removal by grazing. Once an apical meristem is removed, the tiller is not able to keep growing and forage production stops

(Hyder 1974; Dahl 1995). This is one of the main reasons why these species tend to decrease under heavy grazing pressure and are replaced by mid and short grasses

(Branson 1953).

Most studies evaluating the developmental morphology of grasses have concentrated on single species or species within the same growth form (Villanueva 2008;

Aurangzaib 2015). However, few developmental morphology studies have been conducted that evaluate differences in developmental morphology and tiller recruitment patterns among grasses of different growth forms under uniform conditions. The main objective of this study was to identify developmental morphology and morphology characteristics that could affect grazing tolerance among these species characteristic of the North American grasslands. Additional objectives were to detect developmental

120

Texas Tech University, Leobardo Richarte-Delgado, August 2018

morphology and tiller recruitment differences among two unknown switchgrass types (CI and CII) recently reported in the South Plains of US, and to detect developmental morphology and tiller recruitment differences between those two unknown types (CI and

CII) and the well-known switchgrass cultivars Alamo (AL) and Kanlow (KL). The last objective was to relate these developmental morphology and tiller recruitment findings to possible differences among short, mid and tall grasses.

Material and Methods

This study was conducted in the department of Plant and Soil Science greenhouse on the Texas Tech University campus. Fifteen plants of each grass were established in plastic nursery pots.

Soil was collected from the Texas Tech University native rangeland, located in the northwest section of Lubbock, TX (33°36'14.78"N, 101°53'50.44"W) soil type was

Amarillo fine sandy loam (Blackstock et al., 1979). Soil was collected from the top 30 cm, mixed with 20% sand, dried, and passed through a 0.5 cm sieve, then used to fill the pots.

Three sizes of pots were used in order to account for differences in aboveground and belowground architecture of the study species. All switchgrass types were established in 19-L (30 cm deep, 29 cm diameter) pots. Sideoats grama, in 11 L (21 cm deep and 22 cm diameter) pots and blue grama plants in 3.78 L pots (16 cm deep, 29 cm diameter)

(Table 5.1).

121

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Plant establishment

At the beginning of the 2015 growing season, two cuttings per grass species were transplanted to individual pots to ensure the establishment of at least one plant. A cutting was a tiller separated from the crown of a mother plant at early vegetative stage (no elongated stems) with viable roots. At the end of the establishment process, pots were thinned to one plant per pot. Plants were lightly irrigated each day during the morning to facilitate establishment. Plant establishment was considered successful when transplanted cuttings started to produce new tillers from the basal crown. This had occurred by two weeks after transplanting after which the experimental irrigation regime started.

Plant material collection

Blue grama (BG) vegetative material was collected from randomly selected plants from Texas Tech University native grassland. Sideoats (ST), switchgrass cultivar Alamo

(AL), and switchgrass cultivar Kanlow (KL) were collected from the Knox City Plant

Material Center, located in North Central Texas. Quitaque Canyon switchgrass I (CI) and

II (CII) were obtained from two mother plants collected by Dr. Ron Sosebee and Dr.

Russ Pettit. These plants had been established on the Texas Tech University Campus for one year moved inside the greenhouse during December of 2014, and cloned in May

2015

Irrigation

The experimental irrigation regime started once the plants were established.

Plants were irrigated three times a week during the length of the study. Water applied varied according to the surface area of the pots (Table 5.2). Irrigation amounts were calculated according to the long-term average precipitation (480 mm/yr) for Lubbock and

122

Texas Tech University, Leobardo Richarte-Delgado, August 2018

assuming that an average of 70% (336 mm) of the precipitation occurs from May through

November (West Texas Mesonet 2015).

Data collection

Developmental morphology and morphological measurements

Developmental morphology measurements were performed in on of each 15 plants per grass species, or types in the case of switchgrass, monthly from plant establishment until the end of the growing season (Table 5.3). Plant location inside the greenhouse was changed regularly to ensure random and equal environmental conditions.

At each evaluation date, number of tillers per plant was counted and the developmental morphology was quantified based on the mean stage by count (MSC) system (Moore et al. 1991). The MSC system was designed for use in forage and range management studies and is based on the ontogeny of individual tillers, considering four primary growth stages: vegetative, elongation, reproductive, and seed ripening (post-reproductive).

Within each primary stage, subsequent secondary growth stages were defined according to specific morphological events. Each stage has a mnemonic code and numerical index associated with it to be used for quantitative purposes (Table 5.4). Morphological development was estimated using these numerical indices to quantify the developmental morphology of every tiller and every plant. The MSC was calculated as:

4.9

푴푺푪 = ∑(푠푖푥푁푖) ∕ 퐶 푖=1

Where: MSC= means stage count, i = 1 to 4.9, Si= stage of growth: Ni= number of tillers found in the stage S, and C= Total number of tillers. To interpret the variability in maturity that exits within tiller populations at each evaluation time, the standard deviation of the MSC (SMSC) per plant was calculated by: 123

Texas Tech University, Leobardo Richarte-Delgado, August 2018

4.9 (푠 − 푀푠퐶)2푥푁 푆 = √∑ 푖 푖 푚푠푐 퐶 푖=1

Experimental design

To determine significance of MSC differences among grass species at each month, an analysis of variance was performed on data from each evaluation time (July,

August, September, October, November) from data each month we performed a completely randomized design (CRD) (Steel and Torrie 1980), with six treatments represented by the six grass species (AL, KL, CI, CII BG and ST) and fifteen replications per treatment. Each pot was considered as an experimental unit. Data were evaluated to test normality and homogeneous variances. Statistical analyses were performed in JMP statistical software (SAS Institute 2012).

Results

Plant tiller recruitment

Tiller recruitment was a similar within the switchgrass types. CII plants produced the higher number of tillers per plant among cultivars (8.4), then Alamo (7.3), CI (7.1), and KL (5.8), they presented a similar recruitment pattern across the growing season

(Figure 5.1). Switchgrass cultivars as early as August had already produced between 50% and 60% of their total tiller production in the whole growing season and one month later by September they had produced more that 90% of their total tillers, the only exception was CII, which by this date had produced 70% of its total tillers. On the other hand, BG and ST produced a higher number of tillers BG (18.6) and ST (27.8), which were recruited in a different manner. BG and ST by august had produced just between 20% and 30% of their total amount of tillers, by September where close to 50% and even one

124

Texas Tech University, Leobardo Richarte-Delgado, August 2018

month before plants were harvested in October presented between 65% and 70% of their total tiller production while the switchgrass cultivars basically do not recruit any more tillers after September.

Mean Stage count (MSC) scores

There were significant differences in mean stage count among the grass species at every sampling date evaluation except July (Table 5.5). MSC during July ranged from

1.4 to 1.7 and these values corresponded to differences among substages of vegetation stage rather than species differences. In August, the highest MSC was found in KL (2.99) which was significantly higher than all others, including the other three switchgrass types. The other significant difference was between BG (2.17) and CI (2.51) and AL

(2.54). During August, even though there were significant differences among some grasses, all the species were considered to be in different substages of the elongation stage, with KL getting close to elongation. During September, all the grasses were in advanced stages of elongation except for KL which was in reproductive stage (3.33). The

KL MSC was significantly higher than the rest of the grasses (Table 5.5). At this sampling date, there were no significant differences between the other switchgrasses which were in the latest stages of elongation, getting close to the reproductive stage. BG and ST had the lowest September MSC means (2.32 and 2.50, respectively) which were significantly different from the other grasses, except for ST and CII. In October, KL was in the seed stage set stage (milky) and again was the grass with significantly higher MSC mean (4.43; Table 5.5). CI had the second highest value (3.97) and was at the end of reproductive stage and the begging of seed set stage. Three grasses had intermediate

MSC means (AL, 3.59; CII, 3.56; ST 3.29), all three in the middle of reproductive stage

125

Texas Tech University, Leobardo Richarte-Delgado, August 2018

(inflorescence fully emerged). BG was at the end of elongation stage and had a mean

MSC values lower that the other grasses. The last evaluations were performed by mid-

November. All switchgrass types were in post-reproductive substages while BG and ST were just starting the reproductive (floral induction) stage. The highest MSC mans were for KL (4.68) and CI (4.64) corresponding to seed physiological maturity. The other two switchgrasses had a lower MSC means (AL= 4.07; CII = 4.19) were in early stages of seed maturation. BG and ST had the lowest MSC values (3.14 and 3.00, respectively), and were in the early reproductive stage.

Discussion

The first objective of this study was to determine developmental morphology and tiller recruitment characteristics for the two unknown switchgrass types (CI and CII), to test the hypothesis that they might be different types based on morphological differences.

In terms of developmental morphology, our results showed that CI and CII had similar patterns until September when both grasses were in substages of elongation stage and had similar number of tillers. However in October and November CI was in a more advanced developmental stage. In October, CI was starting seed set stage while CII was in the middle of the reproductive stage, those differences were attributed to differences in the recruitment of young tillers late in the growing season, fall regrowth (Sosebee et al.

2004). The recruitment of young tillers caused a decrease in MSC scores for CII, while

CI tiller recruitment by this time has almost ended (Figure 5.4 and 5.5) causing a higher

MSC score. Similarly, CI has a more advanced developmental morphology stage (seed in hard dough) in November CII was in seed milk stage. In terms of total tiller production, both species produced similar number of tillers. CI produces an average of 7.1 tillers per

126

Texas Tech University, Leobardo Richarte-Delgado, August 2018

plant (Figure 5.1), while CII produced an average of 8.4. The main differences between the two types as to tiller production was in the timing of tiller development. CI produced

92% of its tillers by September while CII produced only 69% by then. CII produced a significant number of tillers tiller late in the growing season. This pattern was not observed among other switchgrass types but was observed in ST and BG. Based in these results it appears that CI and CII can be assumed to be different types. However genetic analysis are recommended for further study.

The second objective of this study was to determine if developmental morphology and tiller recruitment differences exist between the unknown (CI and CII) and the established switchgrass cultivars Alamo (AL) and Kanlow (KL). Our results showed slightly differences in MSC scores and number of tiller production among the four switchgrass types (Table 5.6). The established Alamo (AL) and Kanlow (KL) had significantly different MSC values between them across the growing season. KL had the highest MSC value at each evaluation date (except in July) which corresponded to a more advanced developmental morphology stage. Resulting from lower tiller production, lack of fall regrowth, and the production of 94% of its total amount of tillers as early in the growing season as September. In contrast, CI, CII, and AL had similar MSC scores from

July through September. After September, CII and AL continued to have similar MSC scores but CI had higher MSC values. In terms of tiller recruitment, all types produced similar number of tiller per plant (Figure 5.1), CII produced the highest number (8.4), however this number was not significantly different from the 5.8 tillers per plants produced by KL, which had the lowest number of total tiller produced per plant in this study. We found a small difference in tiller recruitment patterns, where CII recruited a

127

Texas Tech University, Leobardo Richarte-Delgado, August 2018

higher proportion of its tillers after September (close to 40%) while AL, CI and KL generated <10% in the same period (Figure 5.2 to 5.5). Base on the results of this study, we conclude that KL has a significantly different developmental morphology pattern than the other switchgrass types, tending to complete the growth cycle significantly faster, producing a lower number of tillers, and the majority of its tiller production occurring in the first two months of the growing season. These characteristics make this cultivar the least desirable one the four to incorporate in grazing systems because of a rapid decrease in forage quality (Plikerton and Cross 1992), On the other hand, we did not find differences between CI and AL in terms of developmental morphology. Both showed an intermediate growth cycle completion. Finally, CII prove to be the type which remained in vegetative stage longer and the only type which produced a considerable fall regrowth, making this type a more desirable to incorporate into grazing systems.

The final objective of this study was to detect possible developmental morphology and tiller recruitment differences among the three species representing short, mid, and tall grasses. We used Alamo switchgrass (AL) as representative species from the tallgrass prairie, sideoats grama (ST) as the mid-grass species, and blue grama (BG) as the shortgrass species.

There was a clear distinction between AL, BG and ST, based in the variables analyzed in this study. In terms of developmental morphology classification, AL completed the vegetative, elongation, and reproductive stages faster than BG and ST

(Table 5.5). This response has been previously reported in the literature (Mitchel et al.1997) for switchgrass and compared to big bluestem (Andropogon gerardii). In our

128

Texas Tech University, Leobardo Richarte-Delgado, August 2018

study, this response was driven by two main reasons. The first reason was an early internode elongation in AL plants which by mid-August were already in different substages of elongation. The second reason was the tiller development late in the growing in BG and ST, but not in AL. Mitchell and Moser (2000) reported that early internode elongation in switchgrass was influenced by shorter photoperiod; as switchgrass requires short day length for floral induction. This might be the reason why AL plants initiated early internode elongation in our study. Another important variable to consider with MSC values is SMSC. SMSC estimates the morphological tiller diversity within an experimental unit. A lower value means a more homogeneous tiller population and a higher number is related to a more heterogeneous tiller population. SMSC in all these species increased with an advance in the growing season (Figure 5.15 to 5.20). Similar results were reported by

Hendrickson et al. (1998) working with sandreed (Calamovilfa longifolia) and sand bluestem (Andropogon hallii) where SMSC increased from 0.1 at the beginning of the growing season to 0.8 at the end of the season. In addition, there were differences in tiller production between AL and BG and ST. AL produced significantly lower total number of tillers per plant (7.3) than BG (18.6) and ST (27.0). Not only were there differences in number of tillers, there were also differences in the timing of tiller development among these species. AL produced 90% of the total number of tillers as early as September while

BG and ST by this date had only produced 51% and 46%, respectively (Figure 5.1). ST and BG had and significant tiller recruitment late in the growing season, BG producing

30% and ST 35% of their total tiller population in the last month (mid-October to mid-

November) (Figure 5.1). This production of young tillers in BG and ST coincided with the elevation of the apical meristem, as plants started to move into reproductive stage

129

Texas Tech University, Leobardo Richarte-Delgado, August 2018

between mid-September and October (Table 5.7). Tiller development after apical dominance is released by the elevation or the removal of apical meristem has been observed in grass species and is defined as “tillering” (Rechenthin 1956), or as fall regrowth (Sosebee et al. 2004). In our study, this response was not observed in AL or in general, among Switchgrass types. The capability of BG and ST to generate new tillers throughout the growing season confers those plants with higher forage quality for cattle, even late on the growing season, as young tillers present a higher crude protein content and higher in vitro digestibility level than old and lignified tillers (Plikerton and Cross

1992). In contrast, AL produced new tillers early in the growing season. Therefore we concluded that AL has a significantly different developmental morphology cycle than BG and ST, characterized by faster completion of the growth cycle, the production of the majority of its tillers early in the growing season, and the lack of fall regrowth. In the other hand, BG and ST had developmental morphology and tiller recruitment across the growing season similar to each other the only difference between the two species was the higher number of tillers produced by ST and in relation to BG.

130

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Literature Cited

Aurangzib, M. 2015. Developmental morphology, biomass yield and composition differences among upland and lowland switchgrass (Pancum virgatum L.) ecotypes grown as a bioenergy feedstock crop. Ph.D Dissertation. Iowa State University. 139 p. Blackstock, D.A., E. R. Blakley., C. T. Landers., W. M. Koos., and L. A. Putman. 1979. United States Department of Agriculture-Natural Resources Conservation Service Soil Survey of Lubbock County, TX. Branson, F.A. 1953. Two new factors affecting resistance of grasses to grazing. J. Range Manage. 6:162-121. Briske, D.D. 1991. Developmental morphology and physiology of grasses. In: R.K. Hitschmidt and J. W. Stuth (eds.) Grazing Management: An Ecological Perspective. Timber Press, Portland, Oregon. Pp 85-108 Dahl, B.E., 1995. Developmental morphology of plants. In: D. J. Bedunah and R.E. Sosebee (Eds.). Wildland Plants: Physiology Ecology and Developmental Morphology. Society for Range Management. Denver, CO. pp 22- 55. Esau, K. 1960. Anatomy of Seed Plants. Wiley & Sons, New York. 376p. Hendrikson, J.R., L.E. Moser., K.J. Moore, and SS. Waller. 1998. Morphological development of 2 warm-season grasses in the Nebraska Sandhills. Journal of Range Management. 51: 456-462. Holechek, J.L., Rex D. Pieper, and Carlton H. Herbel. 2003. Range Management Principles and Practices. Fifth edition. Hyder, D.N. 1974. Morphogenesis and management of perennial grasses in the U.S. In: Plant Morphogenesis as the Basis for Scientific Management of Range Resources. USDA Misc. Publ. 1271. p. 89-98 Mitchel R.B., K.J., Moore, L.E. Moser, J.O. Fritz and D.D. Redfearn. 1997. Predicting developmental morphology in switchgrass and big bluestem. Agron. J. 89:827- 832. Mitchell R.B. and L.E. Moser. 2000. Developmental morphology and tiller dynamics of war-season grass swards. In: K.L., Moore. and B.E. Anderson (eds.) Native Warm-Season Grasses: Research Trends and Issues. Agronomy Society of America. Madison Wisconsin. 200 pp. NOAA. 2011. National Oceanic and Atmospheric Administration http://www.srcc.lsu.edu/climateNormals/ (accessed 20 May 2015). Plikerton B.W. and D.L Cross. 1992. Forages. Cooperative Extension Service Clemson University. 3 p.

131

Texas Tech University, Leobardo Richarte-Delgado, August 2018

SAS Institute Inc. 2012. Using JMP 10. Cary, NC: SAS Institute Inc. Sosebee, R. E., D. B. Wester, C. Villalobos, C.M. Britton, C. Wan, and H. Nofal. 2004. How Grasses Grow – How Plant Growth Relates To Grazing Management. Second National Conference on Grazing Lands. Nashville TN. Pp 60-71. Steel, R.G.D. and J.H. Torrie. 1980. Principles and Procedures of Statistics. McGrawHill Book Co., New York. Villanueva-Avalos, J.F. 2008. Effect of defoliation patterns and developmental morphology on forage productivity and carbohydrates reserves in WW-B Dahl grass [Bothriochloa bladhii (RETZ) S.T. BLAKE]. Ph. D. Dissertation. Texas Tech University. 311 p.

132

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Tables

Table 5. 1. Amount of water applied per individual plant of switchgrass, sideoats grama, and blue grama under greenhouse conditions during the 2015 growing season Lubbock TX, USA. Species Water applied (mL) per plant Pot size (l) Switchgrass 24400 19 Sideoats grama 21900 11 Blue grama 18600 3.8

Table 5. 2 Water applied per pot per irrigation event and the total amount of water applied per pot during the 2015 growing season calculated based on 69 irrigations evets (once every three days) using 70% of the Lubbock average precipitation and surface area of different pot size. Number of Water per irrigation Total water per Pot size (l) Area (cm2) irrigation events event (mL) pot (l) 19 660 69 310 22.19 11 380 69 180 12.56 3.78 201 69 100 6.90

Table 5. 3 Morphological measurement and development morphology stage evaluation date at the TTU Greenhouse facility during 2015 growing season. Measurement Date DOY 1st July15 190 2nd Aug 3 215 3rd Sep 11 254 4th Oct 18 291 5th Nov15 319

133

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 5. 4. Primary and secondary growth stages, numerical indices and descriptions for growth stage and development of perennial grasses (Moore et al. 1991) Stage Index Description Vegetative-Leaf development V0 1.0 Emergence of the first leaf V1 (1/N*)+0.9 First leaf collared V2 (2/N)+0.9 Second leaf collared Vn (n/N)+0.9 Nth leaf collared Elongation-Stem elongations E0 2.0 Onset of stem E1 (1/N)+1.9 First node palpable or visible E2 (2/N)+1.9 Second node palpable or visible En (n/N)+ 1.9 Nth node palpable or visible Reproductive-Floral development R0 3.0 Boot stage R1 3.1 Inflorescence emergence or first spikelet visible R2 3.3 Spikelets fully emerged or peduncle not emerged R3 3.5 Spikelets fully emerged or peduncle fully elongated R4 3.7 Anther emergence or anthesis R5 3.9 Post-anthesis or fertilization Seed development and ripening S0 4.0 Caryopsis visible S1 4.1 Milk S2 4.3 Soft dough S3 4.5 Hard dough S4 4.7 Endosperm hard or physiological maturity S5 4.9 Endosperm dry or seed ripe * “n” is the event number (number of leaves and nodes) and “N” is the number of events in the primary stage (total number of leaves or nodes developed).

134

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 5. 5. MSC of six grasses: two established switchgrass cultivars, Alamo (AL) and Kanlow (KL), and two unknown switchgrass types, cultivar I (CI) and cultivar II (CII), blue grama (BG) and sideoats grama (ST), evaluated during the 2015 growing season under greenhouse conditions at the TTU PSS greenhouse, Lubbock TX. USA. Species July August September October November Mean AL 1.676 (0.077) A1 2.544 (0.026) B 2.871 (0.062) B 3.588 (0.481) C 4.069 (0.070) B 2.949 KL 1.498 (0.068) A 2.987 (0.091) A 3.329 (0.052) A 4.426 (0.070) A 4.676 (0.302) A 3.383 CI 1.640 (0.074) A 2.512 (0.102) B 2.914 (0.067) B 3.970 (0.072) B 4.643 (0.043) A 3.135 CII 1.602 (0.090) A 2.355 (0.054) BC 2.686 (0.085) BC 3.558 (0.039) C 4.190 (0.131) B 2.878 ST 1.713 (0.087) A 2.218 (0.119) BC 2.501 (0.090) CD 3.294 (0.106) C 2.995 (0.089) C 2.544 BG 1.526 (0.073) A 2.1658 (0.065) C 2.315 (0.044) D 2.95 (0.072) D 3.138 (0.062) C 2.418 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD).

135

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 5. 6. MSC of four switchgrass types: two established switchgrass cultivars, Alamo (AL), Kanlow (KL), and two unknown types, cultivar I (CI) and cultivar II (CII), evaluated during the 2015 growing season, under greenhouse condition at the TTU PSS greenhouse, Lubbock TX. USA. Species July August September October November Mean AL 1.676 (0.077) A 2.544 (0.026) B 2.871 (0.062) B 3.588 (0.481) C 4.069 (0.070) B 2.949 KL 1.498 (0.068) A 2.987 (0.091) A 3.329 (0.052) A 4.426 (0.070) A 4.676 (0.302) A 3.383 CI 1.64 (0.074) A 2.512 (0.102) B 2.914 (0.067) B 3.970 (0.072) B 4.643 (0.043) A 3.135 CII 1.602 (0.090) A 2.3553 (0.054) B 2.686 (0.085) B 3.558 (0.039) C 4.190 (0.131) B 2.878 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD).

136

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table 5. 7. Monthly MSC of six grasses: two known established switchgrass cultivars, Alamo (AL) and Kanlow (KL), two unknown types, cultivar I (CI) and cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during the 2015 growing season, under greenhouse conditions, at the TTU PSS greenhouse, Lubbock TX. USA. Month AL KL CI CII ST BG Mean July 1.676 (0.077) E 1.498 (0.057) D 1.640 (0.074) E 1.602 (0.090) D 1.713 (0.087) C 1.526 (0.073) C 1.609 August 2.544 (0.091) D 2.987 (0.097) C 2.512 (0.102) D 2.356 (0.054) C 2.218 (0.065) B 2.165 (0.026) B 2.463 September 2.871 (0.062) C 3.329 (0.032) C 2.913 (0.072) C 2.686 (0.085) C 2.501 (0.090) B 2.314 (0.044) B 2.769 October 3.588 (0.048) B 4.426 (0.047) A 3.970 (0.072) A 3.558 (0.039) B 2.995 (0.106) A 2.956 (0.072) A 3.582 November 4.069 (0.070) A 4.676 (0.024) A 3.464 (0.043) B 4.190 (0.131) A 3.294 (0.089) A 3.138 (0.062) A 3.805 1Means in the same column followed by the same upper-case letter are not significantly different (P>0.05, HSD).

137

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Figures

July August Sep October November 30

Tiller/plant 10

0 AL KL CI CII BG ST Species

Figure 5. 1 Number of tillers per plant evaluated at five sampling times of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG), and sideoats grama (ST), during the 2015 growing season growth under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA.

138

Texas Tech University, Leobardo Richarte-Delgado, August 2018

100 Vegetative Elongation Flowering Seed set 90 80 70 60 50 40 percentage (%) 30 20 Tiller 10 0 July August September October November Month

Figure 5. 2 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of Alamo (AL) switchgrass plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA.

139

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Vegetative Elongation Flowering Seed set 100 90 80 70 60 50

percentage (%) percentage 40 30

Tiller 20 10 0 July August September October November

Month

Figure 5. 3 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of Kanlow (KL) switchgrass plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA.

140

Texas Tech University, Leobardo Richarte-Delgado, August 2018

100 Vegetative Elongation Flowering Seed set 90 80 70 60 50

percentage (%) percentage 40

30 Tiller 20 10 0 July August September October November Month

Figure 5. 4 Percentage of tillers in vegetative, elongation, flowering and seed set stage of cultivar I (CI) switchgrass plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA.

141

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Vegetative Elongation Flowering Seed set 100 90 80 70 60 50 40

percentage (%) percentage 30 20

Tiller 10 0 July August September October November Month

Figure 5. 5 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of cultivar II (CII), switchgrass plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA.

142

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Vegetative Elongation Flowering Seed set 100 90 80 70 60 50

percentage (%) 40 30

Tiller 20 10 0 July August September October November

Month

Figure 5. 6 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of blue grama (BG) plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA.

143

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Vegetative Elongation Flowering Seed set 80 70 60 50 40

percentage (%) percentage 30

20 Tiller 10 0 July August September October November Month

Figure 5. 7 Percentage of tillers in vegetative, elongation, flowering, and seed set stage of sideoats grama (ST) plants at five sampling times during the 2015 season, grown under greenhouse conditions at the PSS greenhouse, Lubbock TX, USA.

144

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC 1.6 2.5 2.8 3.5 4.0 100% 90% 80% Vegetative Elongation 70% Flowering 60% Seed set 50% 40% 30% 20% 10% 0% Jul Aug Sep Oct Nov

Figure 5. 8. Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in Alamo switchgrass at five sampling dates during the 2015 growing season grown under greenhouse conditions.

145

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC 1.4 2.9 3.3 4.4 4.6 100% 90% Vegetative 80% Elongation 70% Flowering Seed set 60% 50% 40% 30% 20% 10% 0% Jul Aug Sep Oct Nov

Figure 5. 9. Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in Kanlow switchgrass at five sampling dates during the 2015 growing season grown under greenhouse conditions.

146

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC 1.6 2.5 2.9 3.9 4.6 100% 90% Vegetative 80% Elongation Flowering 70% Seed set 60% 50% 40% 30% 20% 10% 0% Jul Aug Sep Oct Nov

Figure 5. 10 Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in Cultivar I switchgrass at five sampling dates during the 2015 growing season grown under greenhouse conditions.

147

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC 1.6 2.3 2.6 3.5 4 .1 100% 90%

80% Vegetative 70% Elongation Flowering 60% Seed set 50% 40% 30% 20% 10% 0% Jul Aug Sep Oct Nov

Figure 5. 11. Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in Cultivar II switchgrass at five sampling dates during the 2015 growing season grown under greenhouse conditions.

148

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC 1.5 2.1 2.3 2.9 3.1 100% 90% 80% Vegetative 70% Elongation 60% Flowering Seed set 50% 40% 30% 20% 10% 0% Jul Aug Sep Oct Nov

Figure 5. 12. Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in blue grama at five sampling dates during the 2015 growing season grown under greenhouse conditions.

149

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC 1.7 2.1 2.5 3.2 2.9 100% 90% 80% 70% Vegetative Elongation 60% Flowering 50% Seed set 40% 30% 20% 10% 0% Jul Aug Sep Oct Nov

Figure 5. 13. Percentage tiller in vegetative, elongated, reproductive, and seed set growth stages in sideoats grama at five sampling dates during the 2015 growing season grown under greenhouse conditions.

150

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC Smsc 4.5

4.0 3.5 3.0 2.5 2.0

1.5 Mean stage Count stage Mean 1.0 0.5 0.0 190 215 254 291 319 DOY

Figure 5. 14 Mean stage count (MSC) and standard deviation (SMSC) for Alamo switchgrass Alamo grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA.

151

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC Smsc 5.0 4.5 4.0 3.5 3.0 2.5 stage Count stage 2.0 1.5 Mean 1.0 0.5 0.0 190 215 254 291 319 DOY

Figure 5. 15 Mean stage count (MSC) and standard deviation (SMSC) for Kanlow switchgrass grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA.

152

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC Smsc 5.0 4.5 4.0 3.5 3.0 2.5 stage Count stage 2.0

1.5 Mean 1.0 0.5 0.0 190 215 254 291 319 DOY

Figure 5. 16 Mean stage count (MSC) and standard deviation (SMSC) for cultivar I switchgrass grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA.

153

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC Smsc 4.5 4.0 3.5 3.0 2.5

stage Count stage 2.0 1.5

Mean 1.0 0.5 0.0 190 215 254 291 319 DOY

Figure 5. 17 Mean stage count (MSC) and standard deviation (SMSC) for cultivar II switchgrass grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA.

154

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC Smsc 3.5 3.0 2.5 2.0

stage Count stage 1.5

1.0 Mean 0.5 0.0 190 215 254 291 319 DOY

Figure 5. 18 Mean stage count (MSC) and standard deviation (SMSC) for blue grama grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA.

155

Texas Tech University, Leobardo Richarte-Delgado, August 2018

MSC Smsc 3.5 3.0 2.5 2.0

stage Count stage 1.5 1.0 Mean 0.5 0.0 190 215 254 291 319 DOY

Figure 5. 19 Mean stage count (MSC) and standard deviation (SMSC) for sideoats grama grown under greenhouse conditions during the 2015 growing season, Lubbock TX, USA.

156

Texas Tech University, Leobardo Richarte-Delgado, August 2018

AL KL CI CII ST BG 5.00 4.50 4.00 3.50

3.00

2.50 MSC 2.00

1.50

1.00 0.50 0.00 190 215 254 291 319 DOY

Figure 5. 20. MSC of Alamo (AL), Kanlow (KL), sideoats grama (ST), cultivar I (CI) and cultivar II (CII) in relation to day of the year (DOY), evaluated under greenhouse conditions during the 2015 growing season, Lubbock TX, USA.

157

Texas Tech University, Leobardo Richarte-Delgado, August 2018

CHAPTER VI

SUMMARY AND CONCLUSIONS

This study was conducted through the 2015 and 2016 growing seasons (June -

November) and consisted of two separated experiments. The first study was conducted during the 2015 growing season under greenhouse conditions were developmental morphology and tiller recruitment were evaluated. The second study was a two-year study performed under field conditions where biomass allocations influenced by clipping intensities was evaluated. The main objective was to determine how developmental morphology stage affects biomass production in short, mid, and tall grasses of North

America. Specific objectives were 1) determine biomass allocation of total plant biomass among the main grass structures of a grass plant (aerial tillers, crown and roots) affected by plant phenological stage. 2) to determine how moderate (50%) and heavy (75%) defoliation intensities modify those biomass allocation patters and 3) to identify if there are differences in developmental morphology and tiller recruitment across the growing season on the species evaluated in this study. Grasses evaluated in this study were the short grass species blue grama (BG), the mid grass species sideoats grama (ST), the introduced species WW-B Dahl (WB) finally the tall grass species switchgrass, where four types were evaluated: Kanlow (KL), Alamo (AL), cultivar I and cultivar (II). At the beginning of 2015 and 2016 growing season, plants were established in 19-L pots and irrigated according to the main annual precipitation in Lubbock. Developmental morphology was evaluated in each plant once a month from July to November, while plants under field conditions where defoliated with 50% and 75% forage utilization at vegetative, and reproductive phenological stages. Finally, total biomass produced per pot

158

Texas Tech University, Leobardo Richarte-Delgado, August 2018

was harvested at the end of the growing season and separated into aerial tillers, crown and roots. Analysis of variance were conducted to find differences among treatments means.

Biomass allocation to the aerial tillers, crown and roots was affected by plants phenological stage and plant species (P<0.05). Species in this study allocated significantly higher biomass to the aerial tillers, followed by roots and finally crowns at each sampling date. However, there were some differences at the species level. During the vegetative stage, biomass allocated to the main structures followed the same patterns.

At this sampling time there was not difference in biomass allocation between KL and

WB, both species always produced significantly higher biomass amounts than ST and

BG. In the same way, ST always produced significantly higher biomass than BG. During the reproductive stage biomass allocation patterns changed slightly in relation to previous samplings. Biomass allocation to aerial tillers was significantly higher in WB, there was no difference between KL and ST, finally significantly lower aerial tillers amounts were found in BG plants. There were no differences in biomass allocation to the crown between WB, KL and ST, while BG produced significantly lighter biomass among grasses as it was observed in the previous sampling. Finally, there were no differences in the biomass allocation to roots between WB and KL, which produced significantly higher roots biomass than ST and BG, while BG produced the lowest amount of root biomass.

By the end of the growing season when plants were in post-reproductive stage biomass allocation patterns changed again. WB produced significantly heavier aerial tillers, however KL produced significantly heavier crowns and roots. ST produced the same amount of aerial tillers biomass than the tall grass KL. In contrast, BG as in the previous

159

Texas Tech University, Leobardo Richarte-Delgado, August 2018

two samplings produced significantly lighter aerial tillers, crown and roots. The results of this study contradicted some of our hypothesis. The tall grass KL accumulated more of its resources to produce belowground structures instead of produce tillers and leaves which are structures need to compete for light in the tall grass prairie. There was a variation in biomass allocation among structures across the growing season, these grasses tend to send more resources to build roots and crown structures early in the growing season while, biomass allocation to the aerial portion increases during the reproductive phase.

Biomass production and allocation among main grass structures was significantly

(P<0.05) affected by a three-degree interaction between phenological stage, species and clipping intensity. The short grass species (BG), mid grasses (ST) and the introduced species (WB) responded in a better way to moderate utilization (50%) regardless of phenological stage and even to heavy utilization (75%) during the reproductive stage, producing biomass compensatory values. In contrast KL responded in a negative way to any defoliation scenarios producing under compensatory biomass values, even under moderate utilization (50%). Heavy utilization during the vegetative (75%xVeg) stage produced the lowest biomass values among defoliation treatments which were significantly different from controls, on the other hand, moderate utilization (50%) regardless of plant’s morphological stage produced compensatory values. In all species, clipping reduced roots biomass and favored shoot production in relation to control plants, which seems to increase with the increase in the percentage of utilization. This characteristic might be an adaptation that grasses developed, as a result, of frequent grazing. Finally, biomass under-compensation was a common result of plants exposed to heavy defoliations early in the season, which suggests that plants are not able to totally

160

Texas Tech University, Leobardo Richarte-Delgado, August 2018

recover from heavy grazing events within the same growing season, highlighting the importance of use grazing schemes.

Developmental morphology was affected (P<0.05) by grass species at each sampling time. AL presented significant higher MSC values in relation to BG and ST at each measurement date, higher MSC values indicates that AL completes its growth cycle faster than BG and ST, in the other hand, I did not find a clear difference between BG and ST. My results indicated that BG and ST expended the same time to move from growth stage to growth stage. Developmental morphology was influenced by tiller production. ST produced the highest number of tiller per plant which was almost 4 times bigger than AL and 1.5 bigger than BG. Tiller recruitment was also different. AL recruited 90% of its tillers by September while BG and ST just close to 50%. Moreover, a considerable production of tillers late in the growing season (mid-October to Mid-

November) in BG and ST (30% and 35%, respectively), contributed to a decrease in

MSC and generated plants with more heterogenous tiller classification which might give cattle the option to choose a higher forage quality diet, even late in the growing season, this phenomenon was not observed in AL.

The results of this study reinforce the theory that shortgrass species can handle grazing in better way than tall grass species. This study demonstrated the preponderance of incorporate plant’s developmental morphology stage as meaningful variable in the design of grazing schemes due to its significant influence in plant biomass response to defoliations.

161

Texas Tech University, Leobardo Richarte-Delgado, August 2018

LITERATURE CITED

Aldous, A.E. 1930. Effect of different clipping treatments on the yield and vigor of prairie grass vegetation. Ecology 11: 752-759. Albertson, F.W., A. Riegel, and J. L. Launchbaugh. 1953. Effects of different intensities of clipping on short grasses in West-central Kansas. Ecology. 34:1-20. Aerts, R., R.G.A Boot, and R.J.M. van der Aart. 1990. The relation between above-and belowground biomass allocation patterns and competitive ability. Oecologia. 87:551-5. Anderson, B.E. 2000. Use of warm-season grasses by grazing livestock. In: Native Warm-Season Grasses: Research Trends and Issues. pp. 147–158. Anderson, B. E. and Moore, K. J., Eds., CSSA Special Pub. No. 30. Crop Science Society of America, Madison, WI. Arredondo, J.T., and Douglas A. Johnson. 1998. Clipping effects on root architecture and morphology of 3 range grasses. Journal of Range Management. 51(2): 207-213. Aurangzib, M. 2015. Developmental morphology, biomass yield and composition differences among upland and lowland switchgrass (Pancum virgatum L.) ecotypes grown as a bioenergy feedstock crop. Ph.D Dissertation. Iowa State University. 139 p. Baker, M.L., V. H. Arthaud, E. C. Conrad and L. C. Newell. 1947. Effects of time of cutting on yields and feeding values of prairie hays. Univ. of Nebr. Bull. 385. Balasko, J.A., and Burner, D.M. 1981. Effects of cutting management on yield, quality, and vigor of switchgrass grown without fertilization. Agron. Abstr. Madison, WI Balasko, J.A., D.M. Burner, and W.V. Thayne. 1984. Yield and quality of switchgrass grown without soil amendments. Agron. J. 76: 204208. Barnhart, S.K. 1999. How pasture plants growth. Iowa State University. University extension. Bartos, D.L., and P. L. Sims. 1974. Root Dynamics of shortgrass ecosystem. Journal of Range Management. 27(1):33-36. Beaty, E.R., J.L. Engel, and J.D. Powell. 1978 Tiller development and growth in switchgrasses. J. Range Management. 31:361:365 Belsky, A.J. 1986. Does herbivory benefit plants? A review of the evidence. Am. Nat 127: 870-892. Bell, J.R. and D. M. Caudle. 1994. Management of Old World Bluestems. Established under the Conservation Reserve Program in Texas. Soil Conservation Service. Temple, TX.

162

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Blaisdell, J. And J.D. Pechanec. 1949. Effects of herbage removal at various dates on vigor of bluebunch wheatgrass and arrowleaf balsam root. Ecology 30 (3): 298- 305. Blackstock, D.A., E. R. Blakley., C. T. Landers., W. M. Koos., and L. A. Putman. 1979. United States Department of Agriculture-Natural Resources Conservation Service Soil Survey of Lubbock County, TX. Boot, R.G.A. Mensuk, M., 1990. Plant and soil 129, 291-299. Size and morphology of root systems of perennial grasses from contrasting habitats a affected by nitrogen supply. Bradbury, Stand. 2007. Ecological Site Description. United States Department of Agriculture-Natural Resources Conservation Service. http://esis.sc.egov.usda.gov/Welcome/pgApprovedSelect.aspx?type=ESD. July 03, 2010. Branson, F.A. 1956. Quantitative effects of clipping treatments on five range grasses. Journal of Range Management. 92: 86-88. Branson, F.A. 1953. Two new factors affecting resistance of grasses to grazing. J. Range Manage. 6:162-121. Brant, P.T., and H. P. Ewalt. 1939. Pasture yields as measured by clip plots by grazing dairy cows. J. Dairy Sci. 22:451-452 Briske, D.D. 1991. Developmental morphology and physiology of grasses. p. 85-108. In: R.K. Hitschmidt and J. W. Stuth (eds.) Grazing Management: an ecological perspective. Timber press, Portland, Oregon. Briske, D.D., and J.H. Richards. 1995. Plant Responses to Defoliation: A physiological, Mophological and Demographic Evaluation. P 635- 55693. In: D. J. Bedunah and R.E. Sosebee (Eds.). Wildland Plants: Physiology Ecology and Developmental Morphology. Society for Range Management. Denver, CO. Brown, B.A., and R.I. Munsell. 1945 Deterioration of clipped caged areas in permanent pastures J. Am. Soc. Agron. 37:542-548 Bryant, H.T. and R.R. Blaser. 1967. Effects of clipping compared to grazing of Ladino Clover-orchardgrass and Alfalfa-orchardgrass mixtures. American Society of Agronomy. Vol 60 (2). 165-166. Bukey, F.S., and J. E. Weaver. 1939. Effects of frequent clipping on the underground food reserves of certain prairie grasses. Ecology 20: 246-252 Burns, J.C., Fisher, D S., and Pond, K.R. 1993. Ensiling characteristics and utilization of switchgrass preserved as silage. Postharvest Biol. Tech. 3: 349– 359.

163

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Burrit, B. 2015. Livestock Grazing in Public Lands https://publiclandgrazing.org/clipping-does-not-simulate-grazing/ (accessed 21 September 2017). Burritt, B., and C. Reid. 2012. Carbohydrate reserve theory: what you learned might be wrong. Utah university cooperative extension. Cable, D.R. 1971. Growth and development of Arizona cottontop (Trichachne californica [Benth.] Chase). Bot. Gaz. 132:119-145. Canfield, R.H. 1939. The effect of intensity and frequency of clipping on density and yield of black grama and tobosa grass. U. S. Dept. Agr. Tech. Bul. 681. Caldwell, M.M. 1987. Competition between root systems in natural communities, p. 167- 185. In Gregory, J.V. Lake., and D.D. Rose [ed.] Root development and function. Cambridge Univ. Press, Cambridge. Caldwell, M.M., J.H. Richards, D.A. Johnson, R.S. Novak, and R.S Dzurec. 1981. Coping with herbivory: photosynthetic capacity and resource allocation in tow semiarid Agropyron bunchgrasses. Oecologia. 50: 14-24. Casler, M.D., Vogel, K. P., Taliaferro, C. M. and Wynia, R. L. 2004. Latitudinal adaptation of switchgrass populations. Crop Sci. 44: 293–303 Castle, M.E. 1953. Grassland production and its measurement J. British. Grassland Soc. 8(3):195-211 Chapin, F.S. III, A.J. Bloom, C.B. Field, and R.H. Waring. 1987. Plant response to multiple environmental factors. BioScience 41: 29-36. Christie, E.K., Moorby, J., 1975. Physiological responses of semi-arid grasses. The influence of phosphorus supply on growth and phosphorus absorption. Australian journal of agricultural research 26 423-436. Coyne, P.I., M.J. Trlica and C.E. Owensby. 1995. Carbon and Nitrogen Dynamics in Range Plants. In: Bedunah D.J. and R.E. Sosebee. Eds. Wildland plants Physiological Ecology and Developmental Morphology. Society for Range Management. Denver, CO. Crafs, R.E. and G.E. Glendening. 1942. How to graze blue grama on southwestern ranges. U. S. Dept. Agr. Leaflet 215: 1-8. Crawley, M.J. 1983. Herbivory: The dynamics of animal-plant interactions. Blackwell: London Scientific Publications. Crider, F.J. 1955. Root-growth stoppage resulting from defoliation of grass. USDA-SCS. Washington D. C. Tech Bull. No. 1102.

164

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Dahl, B.E., 1995. Developmental Morphology of plants. p 22- 55. In: D. J. Bedunah and R.E. Sosebee (Eds.). Wildland Plants: Physiology Ecology and Developmental Morphology. Society for Range Management. Denver, CO. Dahl, B.E., and D.N. Hyder. 1977. Developmental morphology and management implications. P. 258-290. in R. E. Sosebee (ed.), Rangeland plant physiology. Soc. Range Management. Denver, CO. Damhoureyeh, S.A., and D. Hartnett. 2002. Variation in grazing tolerance among three tallgrass prairie plant species. American journal of Botany. 89(10): 1634-1643. Derengibus, V.A., M.J. Trlica, and D.A. Jamenson. 1982. Organic reserves in herbage plants: their relationships to grassland management, p 315-344, in M. Rechcigl. Jr. [ed.] Handbook of agriculture productivity. Vol. I. Plant productivity. CRC Press, Boca Raton, FL. Dewald, C.L., P.L. Sims, and W. A. Berg. 1995. Registration of “WW-B. Dahl” Old World Bluestem. Crop Sci. 35:937 Dovel, R.L., 1996: Cutting height effects on wetland meadow forage yield and quality. Journal of Range Management. 49:151-156. Ehrenreich, J.H. 1959. Burning and clipping on growth of native prairie in Iowa. Journal of Range Management.12 (3): 133-137. Esau, K. 1960. Anatomy of seed plants. Wiley & Son, New York. 376p. Fitter, A.H., and R.K.M. Hay. 1981. Environmental physiology of plants. Academic Press. London. 355 p. Flores, R.L., and B. Tracy. 2013. Root Characteristics of Perennial Warm-Season Grasslands Managed for Grazing and Biomass. Agronomy. 3:508-523. Floyd, E.K., and Harold H. Hopkins. 19961. Content of underground parts of grasses as affected by clipping. Journal of Range Management. 14(1): 9-12. Frank, A.B., K.H. Sedivec, and L. Hofmann. 1993 Determining grazing redlines from native and tame pastures. North Dakota State Univ. Extension Serv. Bull. R-1061, Fargo, ND. Gold, W.G., and M.M. Caldwell. 1990. The effects of spatial pattern of defoliation on regrowth of tussock grass. II. Canopy gas exchange. Oceologia 81:437-442. Graber, L.F., N.T. Nelson, W. A. Luekel, and W. B. Albert. 1927. Organic food reserves in relation to the growth of alfalfa and other perennial herbaceous plants. Wisconsin Agr. Exp. Sta. Res. Bull. 80. 128 p. Harnett, D.C. 1989. Density- and growth stage-dependent responses to defoliation in tow rhizomatous grasses. Oceologia 80:414-420. Harper, J.L., 1977. Population biology of plants. Academic Press, London. 165

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Haun, J.R. 1973. Visual quantification of wheat development. Agron. J. 65:116-119. Heichel and, G.H., and N.C. Turner. 1983. CO2 assimilation of primary and regrowth foliage of red maple (Acer rubrum L.) and red oak (Quescus rubra L.); response to defoliation Oecologia 57: 14-19. Heitschmidt, R.K. Kothmann, N.M. Rawlins, W.J., 1982. Cow-calf response to stocking rates, Grazing systems and winter supplementation at the Texas Experimental Ranch. Journal of Range Managements 35, 204-210. Hendrikson, J.R., L.E. Moser., K.J. Moore, and SS. Waller. 1998. Morphological development of 2 warm-season grasses in the Nebraska Sandhills. Journal of Range Management. 51(14)456-462 pp Herrero-Jauregui, C., M.F. Schmitz & F.D. Pineda. 2016.Effects of different clipping intensities on above- and below-ground production in simulated herbaceous plant communities. Plant Biosystems. 150(3) 468-476. Hilman, J.R. 1984. Apical dominance. P. 127-148. In M.B. Wilkins (ed.) Advance plant physiology. Ptiman publ. London. Hitchcock, A.S and A. Chase. 1951. Manual of the grasses of the U.S. USDA Misc. Publ. 200. 2nd ed. U.S Gov. Print. Office, Washington, D.C. Hodkinson, K.C. 1974. Influence of partial defoliation on photosynthesis, photorespiration and transpiration by Lucerne leaves of different ages. Aust. J. Plant Physiology 1:561-578. Holechek, J.L., Rex D. Pieper, and Carlton H. Herbel. 2003. Range management principles and practices. Fifth edition. Howery, L.D., J.E. Sprinkle, and J.E. Bowns. 2000. A summary of Livestock Grazing Systems Used on Rangelands in the Western United States and Canada. College of Agriculture and Life Scienses, University of Arizona (Tucson, AZ). 7 p. Hyder, D.N., 1972. Defoliation in response to vegetative growth. P. 302-3017. In: V.B. Younger, and C.M. Mckell (eds.) The biology and utilization of grasses. Academic press, New York. Hyder, D.N. 1974. Morphogenesis and management of perennial grasses in the Unites States, pp. 89-88. In: Plant morphogenesis as the basis for scientific management of range resources. Proceedings of the workshop of the U.S/Australian rangelands panel. Berkeley Calif. March 29-April 5, 1971. U.S. Dep. Agri. Misc. Public. 1271. Issoufou, M., M. Zaman-Allah, A. Ferchichi and E. Ferjani. 2008. Clipping effects on the growth Variation, Water Use Efficiency and Photosynthetic Activity in Buffel Grass (Cenchrus ciliaris L.) Poaceae. Asian Journal of Plant Sciences. 7(1): 95-99

166

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Jameson, D.A., D.L. Huss. 1959. The effect of clipping leaves and stems on number of tillers, herbage weights, root weights, and food reserves of little blue stem. J. Range Management. 12:122-126. Jones, T.R., Ewalt, and J. R. Haag 1937 A comparison of pasture returns from actual grazing and clipping plot. Jung, G.A., J.A. Shaffer, and W. L Stout. 1988. Switchgrass and big bluestem responses to amendments on strongly acid soil. Agron. J. 80:669-676. Kennedy, W.K. 1950. Simulated grazing treatments, effect on yield, botanical composition, and chemical composition of a permanent pasture. Cornell Univ. Agr. Exp. Sta. Memoir 295 Korner, C. and U. Renhardt. 1987. Dry matter partitioning and root length/leaf ratios in herbaceous perennial plants with diverse altitudinal distribution. Oecologia. 74: 411-418. Lane, D.R., D.P. Coffin, and W.K. Lauenroth. 1998. Effects of soil texture and precipitation on above-ground next primary productivity and vegetation structure across the central grassland region of the Unitec States. Journal of vegetation Science 9:239-250. Lane, D.R., P. Coffin, and W.K. Lauenroth. 2000. Changes in grassland canopy structure across precipitation gradient. Journal of vegetation Science. 11:359-368. Lang, Robert, and O.K. Barnes. 1942. Range forage production in relation to time and frequency of harvesting. Wyo. Agr. Expt. Sta. Bull. 253: l-32. Langer, R.H.M. 1972. How Grasses Grow. Edward Arnold Ltd., London. Large, E.C. 1954. Growth stages in cereals, illustration of the Feekes scale. Plant Phatol. 3:128-129. Lauenroth, W.K., D.G. Milchunas, O.E. Sala, I.C. Burke. J.A. Morgan. 2008. Net Primary Production in the Shortgrass Steppe in: W. K. Lauenroth and I. C. Burke, editors. Ecology of the shortgrass steppe: A long-term perspective. Oxford University Press, New York. Lauenroth, W.K. 2008. Vegetation of the shortgrass steppe in: W. K. Lauenroth and I. C. Burke, editors. Ecology of the shortgrass steppe: A long-term perspective. Oxford University Press, New York. Leithead, H. L., Y.L. Yarlett, and T.N. Shiflet. 1971. 100 native forage grasses in 11 southern states. USDA-SCS Agric. Handb. 389. U.S. GOV. Print Office. Washington,D.C. Ludvíková, V, Pavlů VV, Gaisler J, Hejcman M, Pavlů L. Long term defoliation by cattle grazing with and without trampling differently affects soil penetration resistance

167

Texas Tech University, Leobardo Richarte-Delgado, August 2018

and plant species composition in Agrostis capillaris grassland. Agriculture, Ecosystems & Environment. 2014;197(12):204–11. Maschinski, J., and T.G. Whitman. 1989. The continuum of plant responses to herbivory the influences of plant association, nutrient availability, and timing. Am. Nat. 134:19 Marshall, C., and G.R. Sagar. 1968. The distribution of assimilates in Lolium multiflorum Lam. Following different defoliation. Ann. Bot. 32: 715-719. McCollum, T. 2000. Old World Bluestem pastures management strategies. Texas Agricultural Extension Service. Amarillo, TX. McLaughlin, M.R., Fairbrother, T. E., and Rowe, D. E. 2004. Nutrient uptake by warm- season perennial grasses in a swine effluent spray field. Agron. J. 96: 484–493. McNaughton, S.J., R.W. Ruess, and S.W. Seagle. 1998. Large mammals and process dynamics in African ecosystems. BioSciense 38:794-799. McNaughton, S.J. 1976. Serengeti migratory wildebeest: facilitation of energy flow by grazing. Science 191:92-94 McNaughton, S.J. 1979. Grazing as an optimization process: grass-ungulate relationship in the Serengeti, Am. Nay. 113:691-703. Milchunas, D.G. and W.K. Lauenroth. 2001. Belowground Primary Production by Carbon Isotope Decay and Long-term Biomass Dynamics. Ecosystems. 4: 139- 150. Milchunas, D.G. and W.K. Lauenroth. 1989. Three-Dimensional Distribution of Plan Biomass in Relation to Grazing and Topography in the Shortgrass steppe, Oikos. 55(1):82-86. Milchunas, D.G. and M.W. Vandever. 2013. Grazing effects on aboveground primary production and root biomass of early-seral, mid-seral, and undisturbed semiarid grassland. Journal of Arid Environments. 92:81-88. Mitchell, R. B., Moore, K. J., Lowell, E., Fritz, J. O., and Redfeaan, D. D. 1997. Predicting developmental Morphology in Switchgrass and Big Bluestem. Agronomy & Horticulture- faculty Publications. Paper 67. Mitchell, R.B. and L.E. Moser. 2000. Developmental morphology and tiller dynamics of war-season grass swards chapter in: Moore K.L. and B.E. Anderson (Eds.) Native Warm-season Grasses: Research Trends and Issues. American society of America Madison Wisconsin. 200 pp. Mooney, H.A. 1972. The carbon balance of plants. Ann. Rev. Ecol. Syst. 3:315:346. Moore, K.J., White, T. A., Hintz, R. L., Patrick, P. K., and Brummer, E. C. 2004. Sequential grazing of cool- and warm-season pastures. Agron. J. 96: 1103–1111.

168

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Moore, K.L., L.E. Moser, K. P.Vogel, S. S. Waller, B. E. Johnson, and J. F. Pedersen. 1991. Describing and quantifying growth stages of perennial forage species. Agronomy Journal. 83:1073-1077. Moore, K.J., and L. E. Moser. 1995. Quantifying developmental morphology of perennial plants. Crop sci. 35: 37-47. Moser, L.E., and K.P. Vogel. 1995. Switchgrass, big bluestem, and indiangrass. P. 409- 420 in R.F. Branes et al. (ed.) Forages: An introduction to grassland agriculture. 5th ed. Iowa State Univ. Press., Ames Mott, J.J., M.M. Ludlow, J.H. Richards, and A.D. Parsons. 1992. Effects of moisture supply in the dry season and subsequent defoliation on persistence of the savanna grasses Themeda triandra, Heteropogon contortus and panicum maximun, Aust. J. Agric. Res. 43: 241-260. Murphy, J.S. and D.D. Briske. 1992. Regulation of tillering by apical dominance: Chronology, interpretive value, and current perspectives. J. Range Management 45: 419-419. Neary, D.G., C.C. Klopatek, L.F. DeBano, and P.F. Folliott. 1999. Fire effects on belowground sustainability: a review and synthesis. Forest Ecology and Management 122: 51-71. Neiland, B.M. and J.T. Curtis. 1956. Differential responses to clipping of six prairie grasses in Wisconsin. Ecology 37:355-365 NOAA. 2011. National oceanic and atmospheric administration http://www.srcc.lsu.edu/climateNormals/ (accessed 20 May 2015). Norton, B.E., 1998. The application of grazing management to increase sustainable livestock production. Animal production in Australia. 22, 15-26. Oesterheld, M., McNaughton S. J. 1991. Effects of stress and time for recovery on the amount of compensatory growth after grazing. Ocelogia 85:305-313 Olff, H., J. Van Andel and J.P. Bakker. 1990. Biomass and Shoot/Roots allocation of five species from a grassland succession series at different combinations of light and nutrient supply. Functional Ecology. 4(2) 193-200. Olson, B.E., and J.H. Richards. 1988. Tussock regrowth after grazing; intercalary meristem and axillary bud activity of Agropyron desertorum. Oikos 51: 374-382. Ourry, J. Boucaud, and J. Salette. 1990. Partitioning and remobilization of nitrogen during regrowth in nitrogen-deficient ryegrass. Crop Sci. 30: 1251-1254. Owensby, C.E., E.F. Smith, and J.R. Rains. 1997. Carbohydrates and nitrogen reserve cycles for continuous, season-long and intensive-early stocked flint Hills bluestem range. J. Range Management. 30:258-260.

169

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Painter E.L., and J.K. Delting. 1981. Effects of Defoliation on Net Photosynthesis and regrowth of Western Wheatgrass. Journal of Range Management. 34(1): 68-71 Plikerton B. W. and D. L Cross. 1992. Forages. Cooperative Extension Service Clemson University. 3 p. Porter, C. 1966. An Analysis of Variation Between Upland and Lowland Switchgrass, Panicum Virgatum L., in Central Oklahoma. Ecology, 47(6), 980-992. Reardon, P.O., Merril L.B., 1976 Vegetative response under various grazing management systems in the Edwards Plateau of Texas. Journal of Range Management. 29, 195- 198. Reece, P.E., Brummer, J. E., Engel, R. K., Northrup, B.K., Nichols J. T., 1996. Grazing date and frequency effects on prairie sandreed and sand bluestem. Journal of Range Management 49, 112-116. Release brochure for Kanlow switchgrass (Panicum Virgatum) 2012. USDA-Natural Resources Conservation Service. James E.”Bud” Smith Plant Material Center, Knox City, TX 79529. May 2012 Release brochure for Alamo switchgrass (Panicum Virgatum) 2012. USDA-Natural Resources Conservation Service. James E.”Bud” Smith Plant Material Center, Knox City, TX 79529. May 2012 Richards, J.H., and M.M. Caldwell. 1985. Soluble carbohydrates, concurrent photosynthesis and efficiency in regrowth following defoliation: A field study with Agropyron species. J. Appl. Ecol. 22:907-920. Richards, J.H. 1984. Roots growth responses to defoliation in two Agropyron bunchgrasses: field observations with an improved root periscope. Oecologia 64:21-25. Ritchie, S.W., J.J. Hanway, and G.O. Benson. 1989. How a corn plant develops, Special Rep. 48, Extension Serv., Iowa State Univ., Ames. Robinson, R. R., H. Pierre, and R. A., Akerman. 1937. A comparison of grazing and clipping for determining the response of permanent pastures to fertilization. J. Am. Soc. Agron. 29:349-359 Robinson, R. R., V.G. Sprague, and A.G. Lueck. 1952. The effect of irrigation, nitrogen fertilization, and clipping treatment on persistence of clover and on total and seasonal distribution of yields in a Kentucky bluegrass sod. Agronomy Journal 44: 239-244. Ryle, G.J., and C.E. Powell. 1975. Defoliation and regrowth in the gramineous plant: the role of current assimilates. Ann. Bot. 39:297-310.

170

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Sanderson, M. A. 2000. Cutting management of native warm-season perennial grasses: Morphological and physiological responses. In: Native Warm- Season Grasses: Research Trends and Issues., pp. 133-146. SAS Institute Inc. 2012. Using JMP 10. Cary, NC: SAS Institute Inc. Sears, P. D., V. C. Goodall, and P.P. Newbold. 1948. The effect of sheep droppings on yield, botanical composition, and chemical composition of pasture. New Zeland J. Sci. and Tech. 30:231-250. Shafer, M., D. Ojima, J.M. Antle, D. Kluck, R.A. McPherson, S. Petersen, B. Scanlon, and K. Sherman, 2014: Ch 19: Great Plains. Climate Change Impacts in the United States: The Third National Climate Assessment, J.M. Melillo, Terese (T.C.) Richmond, and G.W. Yohe, Eds., U.S. Global Change Research Program, 441-461. Shuster, J.L. 1964. Root development of Native Plants Under Three Grazing intensities. Ecology. 45(1): 63-70. Sims, P. L., J.S. Singh, and W.K. Lauenroth. 1978. The structure and function of ten western North American grasslands: I. Abiotic and vegetational characteristics. Journal of Ecology 66:251-285. Simmons, S.R., E.R. Oelke, and P.M. Anderson. 1985. Growth and Development of spring wheat. Univ. of Minnesota Agric. Extension Folder AG-FO2547. Minneapolis, MN. Snyman. 2004. Rangeland degradation in a semi-arid south Africa- I: influence of seasonal root distribution, root/shoot ratios and water-use efficiency. Journal of Arid Environments. 1-25 p. Snyman H.A., and Founche, H.J. 1991. Production and water-use efficiency of semi-arid grassland of South Africa as affected by veld conditions and rainfall. Water South Africa (17): 263-268 Sosebee, R.E., D.B. Wester, J. C. Villalobos, C. M. Britton, C. Wan, and H. Nofal. 2004. How grasses grow – How plant growth relates to grazing management. 2nd National Conference on Grazing Lands, Proc. Nashville, TN. SRM. 1989. A glossary of terms used in range management, 3rd ed. Soc. Range Manage., Denver, CO. Stanton, N. 1983. The effects of clipping and Phytophagous Nematodes on Net primary production of Blue Grama, Bouteloua gracilis. Oikos. 40(2): 249-257. Steel, R.G.D. and J. H. Torrie. 1980. Principles and procedures of statistics. McGrawHill Book Co., New York. Stoddart, L.A. 1946. Some physical and chemical responses of Agropyron spicatum to herbage removal at various season. Utah Agr. Expt. Sta. Bull. 324.

171

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Society for Range Management. 1989. A glossary of terms used in range management. 3d ed. Society of Range Management, Denver CO. Suttie, J.M., Reynols S.G, Botello C. Eds. 2005. Grasslands of the World. Food and agriculture organization of the United Nations, Plant production and protection Series (Food Agriculture Organization, Rome), No. 34 Thornton B., and P. Millard. 1996. Effects of severity of defoliation on root functioning in grasses. Journal of Range Management. 49(5)443-447. Tilman, D. 1988. Plant strategies and the dynamics and structures of plant communities. Princeton University Press, Princeton, New Jersey. Tomanek, G.W. 1948. Pasture types in western Kansas in relation to intensity of utilization in past years. Fort Hays Kansas State Coll. Studies No. 13: 171-196. USDA-Natural Resources Conservation Service. 2002. Plant fact sheet blue grama (bouteloua gracilis). Veneciano, J.H. and K. L. Frigerio. 2003. Efecto de la defoliación de primavera-verano sobre los rendimientos, composición, de la materia seca y contenido proteico del material diferido de gramíneas megatérmicas. INTA, Argentina. RIA. 32 (1): 515. Villanueva-Avalos, J. F. 2008. Effect of defoliations patterns and developmental morphology on forage productivity and carbohydrates reserves in WW-B Dahl grass [Bothriochloa bladhii (RETZ) S.T. BLAKE]. Ph. D. Dissertation. Texas Tech University. 311 p. Vinton, M.A., and D.C. Harnett. 1992. Effects of bison grazing on Andropogon gerardii and Panicum virgatum in burned and unburned tallgrass prairie. Oecologia 90:374-382. Vogel, W.G., and A.J. Bjugstad. 1968. Effects of clipping on yield and tillering of little bluestem and big blue stem, and indiangrass. J. Range Management 21:136-140. Waller, S. S., and J.K. Lewis. 1979. Occurrence of C3 and C4 photosynthetic pathways in North American grasses. J. Range Manage. 32:12-82. Weaver, J. E. and V.H. Hougen. 1939. Effect of frequent clipping on plant production in prairie and pasture. Amer. Midl. Naturalist 21: 396-414. West Texas Mesonet. 2016. http://www.mesonet.ttu.edu/mesonet-precipitation.htm (accessed 20 May 2016). Whitman, W.C., and E.A. Helgeson. 1946. Range vegetation studies. N. Dakota Agr. Expt. Sta. Bull. 340. Wilsey, B.J., Polley, H.W. 2006. Aboveground productivity and root-shoot allocation differ between native and introduced grass species. Oecologia 150, 300-309.

172

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Xiliang, L., Z. Wu., X. Hou., W. Badgery, H. Gou, Q. Zhao, N. Hu, J. Duan. W. Ren. 2015. Contrasting Effects of Long-Term Grazing and Clipping on Plant Morphological Plasticity: Evidence from Rhizomatus Grass. Plos one. 10(10). Younger, V.B. 1972. Physiology of defoliation and regrowth. In. V.B. Younger and C.M. McKell (eds.) The biology and utilization of grasses, p 292-303. Academic press, New York and London.

173

Texas Tech University, Leobardo Richarte-Delgado, August 2018

APPENDIX

ANALYSIS OF VARIANCE

Table A 1. Analysis of variance for aerial biomass production of ST and KL species evaluated during the 2015 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 17 3.1102 0.1830 20.6634 <.0001 Error 108 0.9562 0.0089 C. Total 125 4.0664 Interactions Species 1 0.7347 0.7347 82.9781 <.0001 Treat 2 0.3266 0.1633 18.4446 <.0001 Species*Treat 2 0.0685 0.0342 3.8672 0.0239 Stage 2 1.3118 0.6559 74.0825 <.0001 Species*Stage 2 0.0207 0.0104 1.1696 0.3144 Treat*Stage 4 0.4260 0.1065 12.0280 <.0001 Species*Treat*Stage 4 0.2219 0.0555 6.2649 0.0001

174

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 2. Analysis of variance for crown biomass production of ST and KL species evaluated during the 2015 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 17 4.2838 0.2520 18.0614 <.0001 Error 108 1.5068 0.0140 C. Total 125 5.7906 Interactions Species 1 1.0132 1.0132 72.6214 <.0001 Treat 2 0.0594 0.0297 2.1297 0.1238 Species*Treat 2 0.1983 0.0992 7.1070 0.0013 Stage 2 1.3692 0.6846 49.0704 <.0001 Species*Stage 2 0.8328 0.4164 29.8462 <.0001 Treat*Stage 4 0.5578 0.1395 9.9955 <.0001 Species*Treat*Stage 4 0.2530 0.0633 4.5336 0.002

175

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 3. Analysis of variance for root biomass production of ST and KL species evaluated during the 2015 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 17 3.3946 0.1997 10.6300 <.0001 Error 108 2.0287 0.0188 C. Total 125 5.4233 Interactions Species 1 0.8133 0.8133 43.2934 <.0001 Treat 2 0.1181 0.0591 3.1446 0.0471 Species*Treat 2 0.0791 0.0395 2.1042 0.1269 Stage 2 1.4536 0.7268 38.6905 <.0001 Species*Stage 2 0.7563 0.3781 20.1301 <.0001 Treat*Stage 4 0.1370 0.0342 1.8229 0.1296 Species*Treat*Stage 4 0.0373 0.0093 0.4966 0.7383

176

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 4. Analysis of variance for total biomass production of ST and KL species evaluated during the 2015 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 17 2.7345 0.1609 28.9416 <.0001 Error 108 0.6003 0.0056 C. Total 125 3.3348 Interactions Species 1 0.7472 0.7472 134.4468 <.0001 Treat 2 0.1570 0.0785 14.1279 <.0001 Species*Treat 2 0.0727 0.0364 6.5441 0.0021 Stage 2 1.1142 0.5571 100.2348 <.0001 Species*Stage 2 0.2782 0.1391 25.0267 <.0001 Treat*Stage 4 0.2662 0.0665 11.9725 <.0001 Species*Treat*Stage 4 0.0989 0.0247 4.4507 0.0023

177

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 5. Analysis of variance for aboveground to belowground biomass ratio of ST and KL species evaluated during the 2015 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 17 1.7507 0.1030 7.2582 <.0001 Error 108 1.5323 0.0142 C. Total 125 3.2830 Interactions Species 1 0.0029 0.0029 0.2020 0.654 Treat 2 0.1422 0.0711 5.0122 0.0083 Species*Treat 2 0.0304 0.0152 1.0717 0.346 Stage 2 0.4780 0.2390 16.8435 <.0001 Species*Stage 2 0.6157 0.3079 21.6987 <.0001 Treat*Stage 4 0.2768 0.0692 4.8777 0.0012 Species*Treat*Stage 4 0.2047 0.0512 3.6063 0.0085

178

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 6. Analysis of variance for WUE of ST and KL species evaluated during the 2015 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 17 3.7197 0.2188 39.3683 <.0001 Error 108 0.6003 0.0056 C. Total 125 4.3199 Interactions Species 1 1.8887 1.8887 339.8266 <.0001 Treat 2 0.7769 0.3884 69.8874 <.0001 Species*Treat 2 0.0675 0.0338 6.0746 0.0032 Stage 2 0.2157 0.1079 19.4084 <.0001 Species*Stage 2 0.2901 0.1451 26.0983 <.0001 Treat*Stage 4 0.3919 0.0980 17.6303 <.0001 Species*Treat*Stage 4 0.0888 0.0222 3.9939 0.0046

179

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 7. Analysis of variance for aerial biomass production of BG, ST, KL and WB species evaluated during the 2016 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 35 23.0714 0.6592 54.5144 <.0001 Error 216 2.6119 0.0121 C. Total 251 25.6833 Interactions Species 3 18.3653 6.1218 506.2680 <.0001* Treat 2 0.8089 0.4045 33.4480 <.0001* Species*Treat 6 0.3456 0.0576 4.7638 0.0001* Stage 2 2.0751 1.0376 85.8062 <.0001* Species*Stage 6 0.2332 0.0389 3.2149 0.0048* Treat*Stage 4 0.8509 0.2127 17.5932 <.0001* Species*Treat*Stage 12 0.3923 0.0327 2.7038 0.002*

180

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 8. Analysis of variance for crown biomass production of BG, ST, KL and WB species evaluated during the 2016 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 35 21.8445 0.6241 43.2732 <.0001 Error 216 3.1154 0.0144 C. Total 251 24.9598 Interactions Species 3 17.0739 5.6913 394.6015 <.0001 Treat 2 1.7552 0.8776 60.8460 <.0001 Species*Treat 6 0.2938 0.0490 3.3952 0.0032 Stage 2 1.9013 0.9506 65.9121 <.0001 Species*Stage 6 0.2369 0.0395 2.7372 0.0139 Treat*Stage 4 0.2602 0.0651 4.5103 0.0016 Species*Treat*Stage 12 0.3232 0.0269 1.8673 0.0397

181

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 9. Analysis of variance for root production of BG, ST, KL and WB species evaluated during the 2016 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 35 17.2297 0.4923 35.0132 <.0001 Error 216 3.0369 0.0141 C. Total 251 20.2666 Interactions Species 3 14.4182 4.8061 341.8312 <.0001 Treat 2 0.3247 0.1624 11.5474 <.0001 Species*Treat 6 0.4903 0.0817 5.8119 <.0001 Stage 2 1.4307 0.7154 50.8803 <.0001 Species*Stage 6 0.1124 0.0187 1.3320 0.244 Treat*Stage 4 0.2269 0.0567 4.0344 0.0036 Species*Treat*Stage 12 0.2266 0.0189 1.3428 0.196

182

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 10. Analysis of variance for total biomass production of BG, ST, KL and WB species evaluated during the 2016 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 35 18.9117 0.5403 55.6031 <.0001 Error 216 2.0990 0.0097 C. Total 251 21.0107 Interactions Species 3 15.2824 5.0941 524.2126 <.0001 Treat 2 0.7247 0.3624 37.2877 <.0001 Species*Treat 6 0.2228 0.0371 3.8214 0.0012 Stage 2 1.8643 0.9321 95.9217 <.0001 Species*Stage 6 0.1498 0.0250 2.5686 0.0201 Treat*Stage 4 0.4568 0.1142 11.7507 <.0001 Species*Treat*Stage 12 0.2110 0.0176 1.8091 0.0481

183

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 11. Analysis of variance for aboveground to belowground biomass ratio of BG, ST, KL and WB species evaluated during the 2016 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 35 12.1595 0.3474 47.3270 <.0001 Error 216 1.5856 0.0073 C. Total 251 13.7451 Interactions Species 3 10.6013 3.5338 481.3935 <.0001 Treat 2 0.2643 0.1321 18.0023 <.0001 Species*Treat 6 0.1291 0.0215 2.9315 0.009 Stage 2 0.2800 0.1400 19.0714 <.0001 Species*Stage 6 0.2206 0.0368 5.0083 <.0001 Treat*Stage 4 0.3643 0.0911 12.4079 <.0001 Species*Treat*Stage 12 0.2998 0.0250 3.4038 0.0001

184

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table A 12. Analysis of variance for WUE of BG, ST, KL and WB species evaluated during the 2016 growing season. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 35 14.8758 0.4250 43.7369 <.0001 Error 216 2.0990 0.0097 C. Total 251 16.9748 Interactions Species 3 13.1218 4.3739 450.1006 <.0001 Treat 2 0.3359 0.1680 17.2835 <.0001 Species*Treat 6 0.2633 0.0439 4.5158 0.0002 Stage 2 0.4414 0.2207 22.7110 <.0001 Species*Stage 6 0.1939 0.0323 3.3257 0.0037 Treat*Stage 4 0.2262 0.0565 5.8186 0.0002 Species*Treat*Stage 12 0.2933 0.0244 2.5148 0.0041

185

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table C. 1. Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during July, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 5 0.5330322 0.106606 1.1327 0.3495* Error 84 7.90604 0.09412 C. Total 89 8.4390722

Table C. 2. Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during August, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 5 6.647571 1.32951 12.9463 <.0001** Error 84 8.626332 0.10269 C. Total 89 15.273903

Table C. 3. Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during September, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 5 9.4507 1.89014 26.3788 <.0001** Error 84 6.018904 0.07165 C. Total 89 15.469605

186

Texas Tech University, Leobardo Richarte-Delgado, August 2018

Table C. 4 Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during October, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 5 19.86304 3.97261 51.9036 <.0001** Error 84 6.429208 0.07654 C. Total 89 26.292248

Table C. 5 Analysis of variance for Means Stage Count (MSC) of Alamo (AL), Kanlow (KL), cultivar I (CI), cultivar II (CII), blue grama (BG) and sideoats grama (ST) evaluated during November, during the 2015 growing season under greenhouse conditions, Lubbock TX, USA. Source DF Sum of Squares Mean Square F Ratio Prob > F Model 5 39.745164 7.94903 85.9839 <.0001** Error 84 7.765622 0.09245 C. Total 89 47.510786

187