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ProQuest Information and beaming 300 North Zeeb Road, Ann Arbor, Ml 48106-1346 USA 800-521-0000
IMI’
EROSION AND LAND USE EFFECTS ON SOIL QUALITY AND CROP YIELD ON SLOPING LANDS IN SOLOMON ISLANDS
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate
School of The Ohio State University
By
Morgan M. Wairiu, B.S., M. S.
*****
The Ohio State University
2001
Dissertation committee: Approved by
Dr. R. Lai (Adviser)
Dr. F. Calhoun f /« Adviser Dr. A. Ward Soil Science Graduate Program UMl Number: 3011157
UMl
UNtI Microform 3011157 Copyright 2001 by Bell & Howell Information and Learning Company. All rights reservecd. This microform edition is protected against unauthorized copying under Title 17, United States Code.
Bell & Howell Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, Ml 48106-1346 ABSTRACT
Soil properties were evaluated under three land use practices on sloping land on
Kolombangara in Solomon Islands (lat. 5-12 ° S and long. 155-170 ° W). The land use
practices include: (1) natural forest (NF), (2) current farmers shifting cultivation practice
(FP), and (3) current farmers practice with topsoil removed or scalped (SC). Saturated
hydraulic conductivity, bulk density, texture, and aggregation were significantly impacted
by cultivation and topsoil removal. Soil organic carbon content (SOC) was significantly
low under the FP and SC treatments compared to NF treatment. The NF treatment had
2.8 times more SOC than FP treatment and 9.6 times more than SC treatment in the top
15cm depth. In the 15-30 cm depth, the SOC content in NF was 1.7 times more than FP
and 6 times more than SC. High SOC content was only found in the topsoil (0-15 cm
depth) and decreases abruptly with depth among all three treatments.
The data also showed that the changes in the soil chemical properties had
significant effect on the sweet potato yield compared to soil physical properties. Sweet potato yield was low for the SC treatment, which had significant reductions in SOC, N, P,
K and CEC. After two sweet potato crops under the current farmers practice, yield was drastically reduced along with changes in soil chemical properties. Changes in soil properties impacts soil quality which made the current farmers practice unsustainable without high input. Three types of vegetative barriers were evaluated against traditional farmer’s practice (FP) for their potential to reduce runoff on a 35 percent slope from February
1999 to April 2000. Rxmoff amount was strongly correlated with daily rainfall amount
(r^ = 0.76,) and occurred in daily rainfall events exceeding 20mm. There was no significant difference in runoff between different vegetative barriers and FP which, suggest vegetative barriers used had little effect on runoff. Total runoff amount during the
15 month period for the four different treatments were 67.6 mm for FP, and 82.7 mm,
97.2mm, 76.2mm for banana (Musa nana)/heliconia (Heliconia bihai ), pineapple
Ananas comosis and western cabbage(/*o/yc/ Ill Dedicated to my son, Moqon IV ACKNOWLEDGMENTS By Gods grace and guidance I was able to successfully complete this arduous task. For this, I thank the almighty. I am thankful to Dr. Rattan Lai, my adviser for his inspiring guidance, encouragement and constructive criticism during the entire course of my study. Deep gratitude is expressed to Drs. Frank Calhoun and Andy Ward, members of my graduate committee, who helped in making constructive suggestions and for reviewing the dissertation. Colleagues in the department. Dr. R. Bajracharya, Dr. V. Akala, A. Lantz, T. Houser, B. Baker, L. Mulumba, and J. Hao. Your company and support is greatly acknowledged. I would also like to thank my fiiend and colleague Dr. Chanwoo Ahn for both academic and social support we share with each other. Financial support for this study came from the US department of state through the Fulbright Scholarship program and The Ohio State University Graduate school. I extend my appreciation for this. It is my pleasure to thank Solomon Islands Government’s MAL and IBSRAM/PACIFICLAND project for granting me permission for use of their experimental site at Ringgi FES on Kolombangara. I would like to thank A.T. Bero, J. Honiseu, R.Vaketo, R. Sembala and P. Honiseu at Ringgi FES and C. Wate from Taro Beetle Project at Dodo Creek Research Station for help with fieldwork. Also extend my appreciation to R. Pauku, D. Poa, F. Vaghi and S. Vave of KFPL Ringgi for field research and logistical support. Many firiends whose help and encouragement cannot be forgotten have made my stay at The Ohio State University a pleasant experience. I owe a lot to Dr M. Ahmadi and wife Dr. L. Ahmadi, Tom and Terapa Pyatt, Ubaldo Soto and family at Columbus. I would also Like to extend my sincere thanks to Jerry and Joyce Manele, Rex and Mary Horoi, Peter Jr. and Vanessa Kenilorea, Jimi and Elenisi Ovia for the wonderful hospitality during my numerous visits to New York and Ruby and Charity Titiulu in Washington DC. Finally, I gratefully acknowledge the loving sacrifices made by my wife Ellen, daughter Ellah and son Moijon for bearing with me the ordeals of my long absence fi-om home. Thank you Ellen for taking care of our two lovely children. VI VITA February 23, 1963...... Bom — Honiara, Solomon Islands 1987 ...... Bachelor of Agriculture, University of PNG 1987 — 1989 ...... Research Officer MAL, Solomon Islands 1990 — 1991...... Master of Science, Aberdeen University, Scotland 1992 — 1994...... Senior Research Officer MAL, Solomon Islands 1995 -1996...... Technical Services Manager Kolombangara Forest Products Limited 1996 -1997...... Technical Manager Solomon Islands Landscaping and Garden Center 1997 — Present...... Graduate Research Associate The Ohio State University PUBLICATIONS Research Publication 1. M. Wairiu, “Shifting cultivation practices on steeplands in Solomon Islands.” In Proceedings of workshop on sustainable agriculture in South — East Asia, IIRR, Cavite, Sept. 8-12, (1988). 2. M. Wairiu, “Traditional knowledge about the use of soils in the Solomon Islands”. In Proceedings of soil management and smallholder development in the Pacific Islands. IBSRAM proceeding No. 8. IBSRAM Inc. Bangkok, Thailand, (1989). v ii 3. M. Wairiu, C.E Mullins, and C.D. Campbell, “Soil physical properties affecting the growth of sycamore (Acer pseudoplatanus L.) in a silvopastoral system on a stony upland soil in Northeast Scotland.” AgroSys. 24: (3), 295-306, (1993). 4. R.N. Deka, M. Wairiu, P.W. Mtakwa, C.E. Mullins, E.M. Veenendaal, J. Townend, “ Use and accuracy of the filter-paper technique for measurement of soil matric potential.” European JS o il ScL, 46: (2), 233-238, (1995) FIELDS OF STUDY Major Field: Soil Science vm TABLE OF CONTENTS Pass Abstract ...... ii Dedication...... iv Acknowledgments ...... v Vita...... vii List of Tables ...... xii List of Figures...... xv List of Plates...... xvii Chapters: 1 Introduction and literature review...... 1 1.1 Location...... 1 1.2 Climate...... 3 1.3 Geology and landform...... 3 1.4 Population...... 4 1.5 Agriculture 4 1.6 Soil erosion on sloping lands in SI and the South Pacific 5 1.7 Decline in SOC and changes in soil properties...... 10 1.8 Soil quality and crop productivity...... 14 1.9 Location of Experimental site and Physical Environment 16 1.9.1 Physiography...... 16 1.9.2 Climate...... 18 1.9.3 Vegetation and soil...... 20 1.9.4 Land use...... 24 2 Impact of cultivation and topsoil losson soil organic carbon (SOC) content on sloping lands in Solomon Islands...... 31 2.1 Introduction...... 31 ix 2.2 Materials and method...... 33 2.2.1 Site and soil description...... 33 2.2.2 Experimental design and soil sampling...... 34 2.2.3 Soil Preparation for SOC analysis...... 39 2.2.4 SOC analyses...... 39 2.2.5 Data analyses...... 39 2.3 Results and Discussion...... 40 2.3.1 The SOC content in the whole soil...... 40 2.3.2 Effect of land use on soil SOC...... 42 2.3.3 Aggregate size distribution...... 43 2.4 Contusion...... 50 3. Changes in soil properties and crop yield due to cultivation and topsoil removal on sloping lands in Solomon Islands...... 56 3.1 Introduction...... 56 3.2 Materials and methods...... 58 3.2.1 Site and soil description...... 58 3.2.2 Experimental design and soil sampling...... 58 3.2.3 Measurement of soil physical properties...... 59 3.2.3.1 Soil water retention...... 59 3.2.3.2 Strength Properties...... 59 3.2.3.3 Mechanical Properties...... 60 3.2.3.4 Hydrologie properties...... 62 3.2.4 Soil chemical properties...... 65 3.2.5 Crop growth and yield assessment...... 66 3.2.6 Soil-and crop yield relationship...... 67 3.2.7 Development of soil quality index...... 67 3.3 Results and Discussion...... 68 3.3.1 Physical Properties...... 68 3.3.1.1 Soil water retention characteristics...... 68 3.3.1.2 Mechanical Properties...... 71 3.3.1.3 Strength Properties...... 74 3.3.1.4 Hydrologie properties...... 76 3.3.2 Soil chemical properties...... 81 3.3.3 Sweet potato growth and yield...... 83 3.3.3.1 Canopy cover and vine length...... 84 3.3.3.2 Crop yield...... 84 3.3.4 Relationship between soil properties and crop yield 88 3.3.5 Cumulative soil quality index...... 93 3.4 Conclusion...... 95 4. Evaluation of porosity and pore size distribution under different long — term tillage treatments and land use practices in soils at Ohio, USA and Solomon Islands...... 101 4.1 Introduction...... 101 4.2 Materials and Methods...... 103 4.2.1 Site Description...... 103 4.2.2 Experimental Design...... 105 4.2.3 Soil Sampling...... 105 4.2.4 Determination of porosity and pore size distribution 106 4.3 Results and discussion...... 110 4.4 Conclusion...... 120 5. Evaluation of the potential of three different vegetative barriers to reduce runoff on a 35 percent slope on Kolombangara in Solomon Islands...... 123 5.1 Introduction...... 123 5.2 Materials and Methods...... 125 5.2.1 Site Description...... 125 5.2.2 Experimental Design...... 127 5.2.3 Plot Layout and Construction...... 127 5.2.4 Instrumentation...... 129 5.2.5 Measurement of runoff...... 131 5.3 Results and discussion...... 131 5.3.1 Rainfall characteristics...... 131 5.3.2 Rainfall amount and distribution ...... 132 5.3.3 Runoff...... 137 5.3.4 Runoff and Infiltration...... 143 5.3.5 Runoff and soil loss...... 145 5.4 Conclusion...... 147 6. Summary and Conclusion...... 151 Bibliography...... 155 Appendices Appendix A: Soil physical properties 167 Appendix B: Soil Chemical properties 172 Appendix C: Runoff amoimt...... 175 XI LIST OF TABLES Table Page 1.1 Soil loss rates from South Pacific countries...... 8 1.2 Soil loss under Farmers Practice in countries participating in the PACIFICLAND soil erosion network. 9 1.3 Ringgi land system classification and description on Kolombangara Island ...... 21 2.1 The SOC content in two soil profiles located at mid and lower slope at the experimental site...... 40 2.2 Distribution of SOC along different slopes at the experimental site...... 41 2.3 The SOC content and SOC pool in the soil under NF, FP and SC treatments...... 42 2.4 Distribution of water stable aggregates for NF, FP and SC treatments for 0-15 cm and 15-3 0cm depths...... 44 2.5 Bulk density, WSA, and MWD under three land use practices...... 45 2.6 The SOC content in different aggregate size fractions 48 3.1 Sand, silt and clay distributions within 0-30 cm depth under the three land use practices...... 72 3.2 The percent WSA and GMD, MWD under the three land use practices within 0-30 cm depth...... 73 3.3 Total porosity and air-filled porosity under the three land use practices within 0-15 cm depth...... 74 xii 3.4 Treatment eÊfect on bulk density and particle density at 0-30 cm depth...... 75 3.5 Treatment effect on penetration resistance within 0-30 cm depth...... 75 3.6 Cumulative infiltration (I), infiltration rate (i), sorptivity (S) and transmissivity (A) of Philip’s model and empirical constants a and b in Kostiakov model ...... 79 3.7 Saturated hydraulic conductivity under three land use practices within 0-30 cm depth...... 80 3.8 Treatment effect on soil chemical properties...... 83 3.9 Comparison of growth characteristics of sweet potato between FP and SC treatments ...... 84 3.10 Nutrient uptake by (a) vegetative biomass and (b) tuber for FP and SC treatments for the first crop...... 86 3.11 Nutrient uptake by (a) vegetative biomass and (b) tuber for FP and SC treatments for the second crop...... 87 3.12 Nutrient content in sweet potato tubers harvested during the first crop...... 86 3.13 Linear relationship between soil properties and sweet potato yield...... 92 3.14 Cumulative rating index developed for the three land use practices...... 93 4.1 Sample of data reduction output from the Autoscan porosimeter...... 108 4.2 Median pore radius under different treatments (a) at Wooster and South Charleston and (b) at Kolombangara.. 111 4.3 Peak or maximum pore radius under different treatments (a) at Wooster and South Charleston and (b) at Kolombangara ...... 112 Xlll 4.4 Site effect on mean volume of transmission pores (TP), storage pores (SP) and residual pores for Wooster and South Charleston...... 116 4.5 Pore radius range and porosity in soil aggregates at (a) Wooster and South Charleston and (b) Kolombangara 119 5.1 Runoff amount at Ringgi site between four treatments (a) wet season (b) dry season and (c) for wet and dry seasons 138 5.2 Rainfall and infiltration at Ringgi during (a) wet season, (b) dry season, (c) both wet and dry seasons ...... 144 5.3 Comparison of under different vegetative barriers from PNG and Western Samoa and Solomon Islands...... 146 XIV LIST OF FIGURES Figure Page 1.1 Map of Solomon Islands with Kolombangara (157W and 8S) located in the New Georgia group ...... 2 1.2 Average annual rainfall at Ringgi Cove and Vanga Point on Kolombangara ...... 19 1.3 Different facets and distribution of the Ringgi land system on Kolombangara Island ...... 22 2.1 Bulk density versus SOC content in NF, FP and SC treatments for 0-15 cm depth 46 3.1 Logarithm transformation of cumulative infiltration vs time to determine constants “a” and “b” in Kostiakov model ...... 63 3.2 Infiltration vs time to determine S and A using Philip’s model.. 64 3.3 Volumetric water content between 0.003 to 0.05 MPa suctions under the three land use practices within top 15 cm depth...... 69 3.4 Volumetric water content between 0.1 to 1.5 MPa suctions under the three land use practices within top 15 cm depth...... 70 3.5 Penetration resistance under three land use practices within 0-100 cm depth...... 76 3.6 Treatment effect on cumulative infiltration over three hours time period...... 78 3.7 Linear relationship between crop yield and SOC content...... 89 3.8 Linear relationship between crop yield and total N ...... 90 3.9 Linear relationship between crop yield and available P...... 91 XV 3.10 Linear relationship between weighting factors (soil quality) and crop yield...... 94 4.1 Location of experimental sites at Wooster and South Charleston, 104 Ohio...... 4.2 Graph showing the peak pore radius...... 109 4.3 Tillage effect on mean volume of transmission pores (TP), storage pores (SP) and residual pores, as mean values for Wooster and South Charleston...... 114 4.4 Land use effect on mean volume of transmission pores (TP), storage pores (SP) and residual pores for Kolombangara...... 115 5.1 Map of experimental site showing the contours at 10 m interval with runoff plots (not to scale) marked as rectangles...... 126 5.2 Monthly rainfall totals and average runoff firom all treatments from February 1999 to April 2000...... 132 5.3 Daily rainfall distribution at Ringgi from February 1999 to April 2000...... 134 5.4 Rainfall intensity distribution at Ringgi experimental site...... 135 5.5 Effect of degree of ground cover on runoff during sweet potato different growth stages...... 141 5.6 Runoff during months with no ground cover...... 142 5.7 Relationship between rainfall and runoff ...... 143 XVI LIST OF PLATES Plate Page 1.1 Kolombangara Island with Mt. Veve the highest peak and the crater rim ...... 17 2.1 Natural forest (NF) treatment...... 35 2.2 Framers practice (FP) treatment with sweet potato growth at 3 months after planting...... 36 2.3 Scalped (SC) treatment with sweet potato growth at 3 months after planting...... 37 5.1 The runoff collection setup showing concrete trough, manifold and tipping bucket...... 128 5.2 The AWS at the experimental site at Ringgi...... 130 XVll CHAPTER 1 INTRODUCTION AND LITERATURE REVIEW This study describes an experiment conducted on Kolombangara in Solomon Islands during June 1999 to May 2000. It was part of PACIFICLAND, an ongoing soil management research on sloping land network in the South Pacific region. PACIFICLAND was initiated in 1990 with the goal to quantify soil erosion rates and develop sustainable cropping systems for sloping lands in the South Pacific countries. This study was specifically set up to assess the impact of sloping land cultivation and soil erosion impact on soil properties and crop productivity. 1.1 Location Solomon Islands lies between 155 30' and 170 30'W longitude and between 5 10' and 12 45'S latitude. It stretches in a southeasterly direction firom the southern tip of Papua New Guinea to northern end of Vanuatu, forming a scattered archipelago of mountainous islands and low-lying coral atolls. The six biggest islands are Choiseul, New Georgia, Santa Isabel, Guadalcanal, Malaita and Makira (Figure 1.1). They are characterized by thickly-forested mountain ranges intersected by deep, narrow valleys. 155W ;158W: 160W I62W ISABEL. SOLOMON ISLANDS OUADALCAHAL. SAN CMSTOBAL2 REHNEL wBELkOHA kilometers Figure 1.1 Map of Solomon Islands with Kolombangara ( black 157W and 8S) located in the New Georgia group. 1.2 Climate The climate is tropical, though temperatures are rarely extreme due to cooling winds blowing off the surrounding seas. Daytime temperatures fluctuate between 25 to 32 ° C falling about 3 to 5 ° C at night. The rainy season occurs between November to March and two short dry seasons are from April to June and September to October during the year. There is sufficient rainfall all year round to support plant growth. Most islands have a mean armual rainfall of 3,000 to 5,500 mm with two-peak rainfall periods during the year, (July to August and December to March). The highest rainfall recorded in Solomon Islands is an annual average of 8,304 mm at 430 m above sea level at Koloula on Guadalcanal (Hansell and Wall, 1970). Daily rainfall of over 250 mm are normal and may occur at sometimes in a year, for example 15 daily totals of more than 200 mm were recorded in the past 25 years by the Solomon Islands Meteorological Services. The heaviest recorded prolonged rainy spell which lasted for 18 consercative days was recorded at the Koloula river catchment on Guadalcanal Island with an average of 209 mm per day (Aldrick, 1993). 1.3 Geology and landform The Solomon Islands (excluding the Santa Cruz group) are divided into three geological provinces: a pacific province, a central province and a volcanic province (Falvey et al., 1991). The volcanic geological province includes the New Georgia group of islands where Kolombangara (experimental site) is located. Other islands with recent extinct volcano are also found in this province which included the north western tip of Guadalcanal, the Russell Islands, Shortlands and Savo. The volcanic geological province 3 is much younger and consists of Late Miocene to Holocene volcanics, which are only five to six million years old. The larger islands of the New Georgia group are almost entirely of volcanic origin. 1.4 Population The current population according to year 2000 estimates is around 466,194 with a population growth rate o f 3.4 percent. Almost half of the population (44 %) is between the age of 0 to 14 years old while 53 percent are between 15 to 64 years. Most people are in the active reproductive age group. Only 3 percent are in the age group greater than 64 years. (World Bank, 2000). This means the population is growing rapidly and thus food production must also increase to meet their food requirement. About 85 percent of the 446, 194 people live in the rural areas and meet their daily food requirements through subsistence farming. Agriculture is therefore the most important occupation of the people. 1.5 Agriculture The Solomon Islands economy is predominantly agriculturally based. Like most of its South Pacific island countries, the agricultural sector account on average for 30 percent of GDP, 50 percent of export revenue and over 60 percent of employment (paid and subsistence) (Rogers and Thorpe, 1996). The range of crops grown at subsistence level includes root and tuber crops, coconuts and range of fruits and vegetables. Most of the food crops are grown on steep or sloping lands. About 63% of the total land area (270001 oki ^) comprise steep lands (> 20 percent slope) which are used for shifting cultivation by smallholders. In areas of low population density, shifting cultivation maintains soil fertility fcy means of long fallow (10-15 years). This mechanism however breaks down in areas o f high population densities in excess of 10 person per km^ (Mackay, 1988). Shortage of suitable arable lowlands due to a combination of increased population, land tenure issues, and the introduction of tree cash crops, has increased pressure on marginal and sloping lands that are now being cultivated. Cultivation of marginal sloping lands is unsustainable and is responsible for widespread soil erosion, loss of soil fertilit>% decline in crop yield, and widespread land degradation. There are few if any quantitative data on soil erosion rate, extent and severity of land degradation, decline in soil fertility and sustainability of current cropping systems in Solomon Islands. These problems are only experienced through continuous decline in crop yield. The continuous decline in crop yield is a result of a combination o f several factors including: (1) loss of topsoil or reduction o f topsoil depth, (2) decline in soil organic carbon (SOC) and plant nutrients through soil erosion, (3) plant nutrient leaching through the soil profile and (4) nutrient uptake by crop growth. This study focused mainly on factor’s (1) and (2), which are greatly affected by soil erosion. 1.6 Soil erosion on sloping lands in Solomon Islands and the South Pacific region Soil erosion is one of the major causes of declining crop yield on sloping lands in the South Pacific region (Howllet, 1996). Principle processes that leads to decline in crop yield due to erosion include: (1) reduction in effective rooting depth (loss of topsoil), (2) loss of plant nutrients and soil organic carbon (SOC), (3) loss of plant available water and available water capacity, (4) loss of land area, and (5) damage to seedlings (Lai, 1998). Despite the large volume of literature on soil erosion on a global basis (Lai 1998), there is hardly any data on soil erosion and its impact on soil quality and crop productivity in Solomon Islands. The only report on soil erosion were those by Hansell and Wall (1970), Webb (1974), Wall et al. (1979), Stephens et al. (1986) and Eyles (1987). All these reports are however qualitative, for example, in an analysis of the agricultural potential areas on Guadalcanal Island, Hansell and Wall (1970) reported that largely mountainous Kaichui and Itiri land regions are subject to moderate to severe erosion. Paru land region experiences landslides and undergoes gully erosion. Webb (1974) reported that in excess of 15 percent of land had been significantly damaged by machine logging operations on the island of Kolombangara and pointed out that steep portions of these logged areas can be very prone to soil erosion. This observation was later supported by Eyles (1987) who reported that logging on steep lands significantly increases the sediment runoff for 1 to 2 years before complete establishment of ground cover on Kolombangara Island. Wall et al. (1979) consider that surface runoff is the most prevalent form of erosion and when occur on bare slopes steeper than 27 percent it can be severe. Gully erosion is also common especially on residual or sedimentary landscapes on all islands. During cyclonic rainfall events, mountain regions can be susceptible to landslide erosion as observed during cyclone Namu in 1986 on Guadalcanal (Stephens et al., 1986). Solomon Islands share similar aggressive climate, rugged topography, and agricultural activities such as shifting cultivation and land clearing for plantations with 6 other South PaciJBc countries including, Fiji, Papua New Guinea, and Vanuatu. Erosion studies in these countries confirmed that soil erosion is high, thus it is therefore more likely that soil loss on sloping lands under shifting cultivation in Solomon Islands would be similar in magnitude to those observed in these countries. Published reports on soil erosion in the South Pacific include those by Morrison (1981), Liedtke (1984), Clarke and Morrison (1987), and Liedtke (1988) in Fiji, Williams et al. (1981), Wood (1984), Humphreys (1984), Oldfield et al. (1985), Carman (1989), Humphreys and Wayi (1990), Sillitoe (1993), and Konabe (1996) in Papua New Guinea (PNG), and Pratap (1994) in Western Samoa. Reported soil erosion rates in these studies range from 10 to 300 Mg ha' *yr'^ as shown in Table 1.1 Location Slope Time Soil loss rate Reference (percent) (months) (Mg ha' Fiji (Waibau) - 1.1 59-65 Liedtke (1988) Fiji (Waibau) - 1.1 60-66 Liedtke (1988) Fiji (Seaqaqa) 9-14 - 300 Clarke & Morrison (1987) Fiji (Nadi) 33-41 - 90 Clarke & Morrison (1987) Fiji (Lautoka) - - 24-80 Morrison & Clarke (1990) Fiji (Lautoka) 9-23 1 69-78 Liedtke (1984) Fiji (Nadi) 26 - 37 Morrison (1981) Fiji (Nausori) 26 - 86 Morrison (1981) PNG(Chimbu) - - 25 Silitoe (1993) PNG(Chimbu) 40-45 7-15 40-80 Humphreys & Wayi(1990) PNG(Chimbu) 45 7-15 10 Humphreys& Wayi (1990) PNG (Rabaul) - - 38.2 Carman (1989) PNG(Chimbu) - 15-18 80 Humphreys (1984) PNG (Tari) - 1.3 13.6 Wood (1984) PNG (Bubia) - 3 10-12 Williams et al. (1981) Tahiti - - 15 Eyles (1987) PNG = Papua New Guinea Table 1.1 Soil loss rates from South Pacific countries Most of the soil erosion rates reported here have been based on the Universal Soil Loss Equation (USLE) without any calibration for the South Pacific region. They cannot therefore be considered to be truly quantitative, however they do indicate the potential risk of soil erosion. The only quantitative data on soil erosion came from runoff plot studies that included those by Liedtke (1988), in Fiji, and Humphreys and Wayi (1990) in Papua New Guinea. More recently the PACIFICLAND soil management network set up soil erosion studies using runoff plots to quantify soil loss from sloping lands under the current 8 farmers practices in the South Pacific region. The soil loss amoumnt obtained through this study is shown in Table 1.2. Soil loss range firom 7.2 to 36.11 Mg ha The site at Western Samoa recorded unusually low amount of just 0.2 Mg hai Country Location Rainfall Slope Time ; Soil loss (mm) (%) (months) C M gha't) Fiji Waibau 4000 27-32 41 10.0 Papua New Guinea Aiyura 2500 18-36 12 28.0 Vanuatu Lakura 1962 18-36 32 36.1 Vanuatu Sara 3486 34-45 20 7.2 Western Samoa Tapatapao 4500 36-47 13 0.2 Table 1.2: Soil loss under Farmers Practice in countries: participating in the PACIFICLAND soil erosion network, after Howllet (1995) There is little data on the impact of erosion on soil propenties, soil quality and productivity. It is important to know whether the rate of soil loss in this region is having any direct effect on soil properties such as reduction in topsoil degjth, soil organic carbon (SOC) and changes in soil physical and chemical properties. Changes in these soil properties can affect soil quality and crop productivity. 1.7 Decline La SOC and changes in soil properties on sloping lands Decline in SOC was observed under land use practices and cropping systems that do not return residue to the soil (Lai 1986, Lai et al., 1995). An example is subsistence agriculture using shifting cultivation, especially when done with the reduction of the fallow period, removal of crop residue, and indiscriminate burning (Lai, 1974). Cultivation leads to SOC loss through processes such as: (1) increase decomposition and mineralization of biomass due to increase aeration and mixing of plant residues into the soil, and (2) removal by accelerated soil erosion (Lai, 1984; Lai, 1989; Tisdall, 1996) particularly on sloping lands. Accelerated erosion has greater impact on SOC levels in eroded landscapes (Mitchell et al., 1998; Gregorich et al., 1998). Mokma and Sietz (1992) observed a significant reduction in surface SOC due to erosion particularly under cultivation than grassland ecosystem. Tagwira (1992) reported SOC loss of 534 kg ha'^ under traditional farmland in Zimbabwe when soil erosion was 24.6 Mg ha"\ In Thailand, Phommasack et al. (1997) observed 3 g kg"' of soil organic matter (SOM) was lost under farmer’s practice on sloping land when soil erosion amount was 5.2 Mg ha'L The SOC loss is associated with soil erosion because the eroded sediments are generally enriched in SOC due to selective removal of fine soil fractions with higher amounts of associated SOC (Bajracharya and Lai, 1992). Accelerated soil erosion is responsible for topsoil removal, which in turn leads to loss o f SOC and plant nutrients and subsequently a reduction in crop productivity (El- Swaify and Dangler, 1982). Lai (1998) reported that loss of topsoil could cause primary productivity reductions of 50 percent or more in severely impacted regions. Sutherland et al. (1996) observed that both wash and splash erosion components transported <63 pm 10 aggregates and splash erosion preferentially transported 500-1000pm aggregates on less than 18 percent slope. As soil is transported from eroded to depositional positions across watersheds, aggregate breakdown exposes physically protected SOC to oxidation (Lai, 1995b). While SOC can be found in the whole soil, it is mostly retained in the soil aggregates and its presence improves aggregation (Dexter, 1988; Elliot et al., 1993). Aggregates exist in different sizes as reported by Tisdall (1996) and are divided into two categories based on size: 1. Aggregate >250pm diameter 2. Micro aggregate <250pm diameter The micro aggregates are further subdivided into three classes: 1. Microaggregates < 2pm diameter 2. Microaggregates 2 to 20pm diameter 3. Microaggregates 20 to 250pm diameter The SOC can be estimated from aggregate fractions recovered as 50-250pm size aggregates by sieving (Elliot 1993). Using this method, Bajracharya et al. (1998) observed a 30-50 percent increase in SOC within the Ap horizon under no-till plots (NT) compared to conventional till (CT) plots in a long-term tillage experiment in Ohio. They reported similar values for SOC in different aggregate fractions, which suggest that much of SOC is concentrated within the macroaggregates particularly under reduced tillage systems. Beare et al. (1994) also observed similar results. They found that in surface samples of both tillage treatments (no-till & conventional tillage). Particulate organic matter (POM) in aggregate size range 106 to 250pm was highest in NT than CT. Paustian et al.(1997) reported that on relative basis, most sites showed 5-20 percent 11 increases in SOC under NT vs. CT but pointed out that this could be a underestimate if sampling is restricted to the mineral soil because it does not account for the surface mulch which build up on the NT soils. In all these studies SOC was only found to be higher in the topsoil. Two major on-site effects of accelerated soil erosion on crop productivity are decline in soil physical properties and loss of plant nutrients (Lai 1999). The soil physical properties included structure, texture, bulk density, infiltration rate, available water holding capacity and favorable rooting depth (Frye et al., 1982; El- Swaify, 1993; Ebeid et al., 1995; Olson et al., 1999). While other factors such as weather and genetic potential can control the overall production of crops in a geographical area, Olson et al. (1999) pointed out that the soil system remains the major determinant of yields because o f the environment it provide for root growth. Artificial topsoil removal is one of the field methods used to assess the on-site effects o f soil erosion on soil properties and crop productivity. In this technique, soil erosion is simulated by varying the topsoil depth (TSD) through removal or addition of topsoil to the existing soil surface (Lai, 1998). Greb and Smika (1985) reported that removing the topsoil alters soil physical and chemical properties of the site and thus changes the soil quality and subsequently crop productivity. This method has been, widely used in North America which included studies by Ives and Shaykewich (1987), Lamey et al. (1995) in Canada, Henning and Khalaf (1985), Tanaka (1995), and Changere and Lai (1995) in USA. In USA, it was used as far back in the 1930’s and 1940’s (Meyer et al. 1985) where topsoil removal was found to have resulted in increased runoff and erosion and consistent yield reduction mainly in grain crops like com {Zea mays), wheat 12 {Triticum aestivum) and oats {Aneva sativa). Use of the topsoil removal technique in the tropics include studies by Lai (1976) in Nigeria, El-Swaify and Dangler (1982) in Hawaii, and Rose and Dalai (1988) for semiarid regions of Australia. The studies were restricted to assessment of yield of grain crops such as maize, and wheat. There was little or no study on root or tuber crops like sweet potato (Jpomoea batatas). Although the impact on topsoil removal through accelerated soil erosion on soil properties and crop productivity are well documented for temperate regions, the data are still fragmented, and therefore it is difficult to make conclusive management decisions based on the available data (Wolman, 1985). There is hardly any for the South Pacific including Solomon Islands. The only topsoil removal studies in the Pacific region are those by El-Swaify and Cooley (1981) and El-Swaify & Dangler (1982) in Hawaii. El-Swaify and Cooley (1981) reported that a major factor that can cause reduced productivity is the physical degradation of the soil within the rooting zone. They monitored soil deposition as a result of erosion in Hawaii and found that aggregates less than 2mm size and soil particles were mainly transported in the fast flowing water and re-deposited on flat areas. The detachment and transport of the soil aggregates from steeper slopes resulted in reduced topsoil depth and caused reduction in infiltration rate to 1.23 cm hr'* on the slopes. El- Swaify & Dangler (1982) observed that soil erosion was associated with top soil removal and led to loss of organic matter and soil nutrients and subsequently a reduction in productivity. In other tropical regions, Lai (1976) reported 50 percent decline in yield of maize and cowpea when topsoil was removed artificially to depths of 12 or 13 cm on an Alfisol 13 in Nigeria. The decline in yield were attributed to losses in organic matter, nitrogen, moisture retention, and infiltration. Comia et al. (1994) reported low saturated hydraulic conductivity and air permeability in both the 0-5cm and 7-12 cm depths under the farmers practice where erosion was higher in Philippines. Total porosity and volume of pores with equivalent diameter >30 pm in the 0-5 cm depth were significantly greater while soil bulk density in the mulched alley cropping system when compared to farmers practice was low. The mulch alley cropping system provided the lowest annual soil nutrient loss. 1.8 Soil quality and crop productivity It is useful to know the amount o f soil loss but what is more important is the depth of topsoil that remains on the eroded site. The amount of soil loss or topsoil removed with its plant nutrient content may be known through quantification of soil loss but if they cannot be replaced then it is no use for crop growth. It is therefore important to know the condition or the quality of the soil that remains behind. It is the quality of the remaining soil that affects crop productivity. Therefore, assessment of the soil quality is important to planning strategies for sustainable land use. Soil quality is broadly defined in terms of soils physical, chemical, and biological properties that (1) provide a medium for plant growth and biological activity, (2) regulate and partition water flow and storage in the environment, and (3) serve as an environmental buffer in the formation and destruction of environmentally hazardous compounds (Pierce and Larson, 1993). Similarly, Karlen et al. (1997) defined soil quality as the capacity of a specific kind of soil to function, within natural or managed ecosystem 14 boundaries, to sustain plant and animal productivity, maintain or enhance water and air quality, and support human health and habitation. (Lai, 1996) simply referred to soil quality as the productivity and environmental moderation capacity of soil and can change over time due to natural events or human use (Doran et al., 1999). In order for the soil to meet its capacity to function, in this case improve and sustain crop yield, it must have certain qualities. Lai (1999) divided soil quality into three divisions: soil physical quality, soil chemical quality and soil biological quality and stressed that all the three aspects of soil quality are adversely affected by soil erosion. The on site impact of soil erosion on soil physical quality can be observed through loss of effective rooting depth, decline in or deterioration of soil structure, imbalance in soil water regime and loss of available water capacity. Erosion impact on soil chemical and biological quality can also be realized through decline in soil fertility and decline in all three soil quality aspects impacts on crop productivity (El- Swaify, 1993; Lai, 1999). El-Swaify (1993) reported that erosion impacts on crop productivity of highly weathered tropical soils are more severe than for temperate soils. According to Lai (1995a), one of the reasons why there has not been enough work in this area even in other eco-regions of the world is that it is very difficult to conduct experiments that assess soil quality and directly relate it to crop productivity. The difficulty is due to the fact that productivity or yield is not a function of soil quality alone but other factors such as prevalent climate, incidence of pest and diseases, cultural practices and past and current erosion also interact and affect productivity. 15 Crop productivity is defined as the biophysical production or output (biomass or grain yield) per hectare and this may change due to change in soil properties over time (erosion, compaction, salinization, waterlogging, etc), introduction of new cultivars, and change in input used (Lai, 1598). The objectives o f this study therefore were to: (1) assess cultivation and topsoil loss impact on soil properties (2) develop a relationship between changes in soil properties and crop yield, and (3) evaluate potential vegetative barriers to reduce runoff and soil erosion 1.9 Location of Experimental site and Physical Environment The experimental site is located at Ringgi Cove on Kolombangara Island (lat. 8° S and long. 157° W). It is located within the New Georgia group of islands and they lie at the northwestern extreme to the south of the main limb that forms the long chain of islands forming the Solomon Islands archipelago (Figurel.l). 1.9.1 Physiography Hansell and Wall (I9T5) described Kolombangara Island as a classic example of a cone-shaped volcano with a total area of 685 km^. It has almost circular plan with 30km diameter and rises from narrow coastal plain through broad, flat-topped ridges and increasingly narrow ridges with steep sides to a rugged crater rim. Inside the crater rim are steep-sided ridges descending to 760m with a centripetal drainage system while on the outside of the rim is a v/ell-developed radial drainage system. The highest peak known as Mt. Veve is 1760 m high. The Vila River, the biggest on the island drains the crater through a major break iit the rim on the south eastern side. To the Southwest is an area of deeply eroded volcanic ridges (Plate 1.1). 16 ^ ,4- _ Plate 1.1 Kolombangara Island with Mt. Veve the highest peak and the crater rim. 17 1.9.2 Climate Kolombangara’s climate is similar to all other islands in Solomon Islands as described in section 1.2. The rainfall is well distributed with an annual mean of 3500 mm. The wettest period is between December and March. Mean monthly minimum temperatures at sea level are between 22 and 23 ° C and maximum temperatures between 30 and 31 ° C. In the interior of the island specially on the mountain areas temperatures can fall to about 13 to 15 ° C at night. Relative humidity normally fluctuates rapidly during the day depending on temperature, rainfall and cloud cover. It may fall to 60 percent on clear sunny days and rise to 85 percent on cloudy days. The monthly rainfall recorded at Vanga Point from 1972 to 1994 and at Ringgi from 1994 to 1997 are shown in Figure 1.2. The rainfall pattern shows the wet season (December to March) very clearly. 18 450 4 0 0 - ■ Ringgi □ Vanga 350 - 300 - 25 0 - 'S 2 0 0 - 150 - 100 - 50 - 0 JFMAMJJASOND Month Figure 1.2 Average annual rainfall at Ringgi Cove and Vanga Point on Kolombangara (Source: Kolombangara Forest Products Limited and SI Met. Services, 2000) 19 1.9.3 Vegetation and Soil Secondary forest is generally confined to the belt between 40 and 400m contours. This results from selective logging of primary lowland forest by Levers Pacific Timbers Ltd (LPTL) in the I960’s and 70’s. Beyond the 400m contour there is primary forest leading to montane forest. Coastal vegetation is more under human influence, there are large areas of coconut grooves and food gardens as well as brackish swamps. The experimental site has secondary forest but there are remnant patches of lowland primary forest especially on steep slopes next to very narrow valley floors. The species composition is dominated by native flora but elements of naturalized and recently introduced species were also present including both woody and herbaceous species. The lower part of the forest canopy is invaded by small trees and herbaceous plants but denser in most areas than others. Their distribution is influenced by competition for light, soil nutrients, slopes and floristics. The soils on Kolombangara Island are well documented compared to other islands in the Solomon group. They are classified as Haplorthox, belonging to the soil order Oxisol according to the US soil taxonomy classifcation system (Hansell and Wall 1975). The soil belongs to a land unit identified as the Ringgi land system. This land system is a local nomenclature proposed by Hansell and Wall (1975). It is defined as a tract of land with similar or re-occurring parent material, landform, vegetation and rainfall. It is the dominant land system on Kolombangara and encircles the entire Island (Figure 1.3). Description of different land facets or landforms found on the Ringgi land system is given in Table 1.3. Generally the Ringgi land system include ridge crests that are narrow to wide, upper hill slopes (5-14 percent) are very short to short, straight or convex and 20 moderately steep. The lower hill slopes (14—24 percent) and gullies are ultra-short, straight to concave and steep. Valleys are narrow less than 30 m wide with intermittent small streams. Land Area Landform Soil Facet (km^) 1 149 Ridge crests: narrow to very Deep, yellowish red or 56% broad, crestal slope almost flat to reddish brown clay with a gently sloping deep, dark brown or dark 2 74 Hill slopes: very short to short, reddish brown topsoil 28% straight or convex, moderate to (Haplorthox) moderately steep (18-47%) Deep, brown to dark brown clay 3 27 Gullies and lower hill slopes: Moderately deep, strong 10% ultra-short to very short slopes, brown clay with few straight to concave, steep (47- weathered rock fragments 100%) 4 10 Coastal margins: gentle,even Moderately deep to deep, 4% crestal slope with moderate to yellowish red clay overlying moderately steep valley sides; coral (Tropudalfs) limestone outcrops in places Shallow, brown to dark brown clay overlying coral (Lithic Rendolls) 5 5 Valleys: commonly incised, less Shallow to deep, dark sands 2% than 30 m wide with intermittent and loams with stony small streams subsoils (Tropepts, Fluvents) Table 1.3 Ringgi land system classification and description on Kolombangara Island, after Hansell and Wall, (1975) 21 Figure 1.3 Different facets and distribution of the Ringgi land system on Kolombangara Island, after Hansell and Wall, (1975) 22 The soil of Ringgi land system developed over andesitic and basaltic lava. Stones are rarely found in the soil but decomposing rocks usually occurs at depth. Mineralogical examination showed that many clays are rich in bauxite. Under natural forest the topsoil is generally rich in humus and appears to be well drained on the ridges. Hansell and Wall (1975) and Chase et al. (1986) reported that the soil is highly weathered, brownish to red clays, acidic with pH commonly below 5, (pH was measured in 1:2.5 soil-water ratio), very low available and reserve nutrients, low cation exchange capacity ranging from 6 cmol kg'* of soil in the 0-5 cm to 1.3 cmol kg'* of soil at 100 cm depth and very low base saturation percentages. Percentage base saturation decreases with depth, from 37 percent in top 5 cm depth to as low as 1 percent at 100 cm depth. Available phosphorus (determined using Bray method for soils with pH <7) and total nitrogen are also low with average of 2.1 mg kg '* and 0.34 percent in the topsoil and 0.6 mg kg '* and 0.16 percent in subsoil, respectively. Organic carbon is high only in the top 15 cm depth due to the presence of thin (0-4 cm depth) layer of undecomposed organic material covering the top soil especially on the ridges and slopes. It decreases abruptly with depth. The slopes also affect the distribution of organic carbon. Physically the soil is deep, well drained and aggregated despite low organic matter content beneath the top soil layer. The aggregation is due to presence of high amounts of iron and aluminum oxides which gives the soil it’s brownish to reddish color. It is susceptible to erosion when disturbed by logging activities. 23 1.9.4 Land use About 75 percent of the total land area (685 km^) is designated as alienated land (land title held by SI government) and has been logged by Levers Pacific Timbers Ltd in the 1960’s and 70’s. Kolombangara Forest Products Ltd (KFPL) a reforestation joint venture company between Commonwealth Development Corporation (CDC) of United Kingdom and Solomon Islands Government was granted a 75 years lease over the logged over area. By year 2000 the company had established a total area of 16000 ha of forest plantation. The company also left the area beyond the 400m contour untouched and still remains a primary forest leading to montane forest. Coastal vegetation is more under human influence through establishment of large areas of coconut grooves by colonial traders and food gardens. The coconut plantations are now owned and managed by local communities. The current population is estimated at 6000 comprising 25 percent of hired labour from other islands who work on the KFPL plantation. Almost all local residents live in small villages on or near the coast and are involved in subsistence farming and to some degree cultivation of cash crops mainly coconut and cocoa. The recent introduction of the contract system by KFPL attracted a good number of local groups to work on forest operations. Some smallholders are currently engaged in establishment o f small forest plantation on their customary land. About 75% of rural population are involved in one way or the other in sale of their garden produce at nearby markets outlets at both KFPL administration stations Ringgi and Poitete and nearby towns at Gizo and Noro. 24 REFERENCES Aldrick, J.M. 1993. The susceptibility o f lands to deterioration in the Solomon Islands. Project working paper no. 12. Australian International Development Assistance Bureau / Ministry of Natural Resources, Honiara. 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Spring wheat straw production and composition as influenced by topsoil removal. Soil Sci. Soc. Am. J. 59:649-654. Tisdall, J. M. 1996. Formation of soil aggregates and accumulation o f soil organic matter. p57-96. In M. R. Carter and B. A Stewart (ed.) Structure and Organic Matter Storage in Agricultural Soils. Adv. Soil Sci.. CRC Lewis Publishers. New York. Wall, J. R. D., Hansell, J. R. D., Catt, J. A., Ormerod, E. C., Varley, J. A. and Webb, I. S. 1979. The soils of Solomon Islands Vol. 1. Technical Bulletin 4, Land Resources Development Centre, Ministry of Overseas Development, Surrey, England. Webb, I. S. 1974. The effect of tractor logging on some soil properties on the growth of tree crops. Unpublished report. Ministry of Agriculture and Rural Economy, Solomon Islands. Williams, A. R., Fairclough, T. J. and Nianfop, M.P. 1981. A report on the present soil erosion research programme of the Department of Agriculture, University of Papua New Guinea. Port Moresby Wood, A.W. 1984. Land for tomorrow. Subsistence agriculture, soil fertility and economic stability in the New Guinea Highlands. Unpublished Ph.D. thesis. University of Papua New Guinea. World Bank, 2000. www.worldbank.org 30 CHAPTER 2 IMPACT OF CULTIVATION AND TOPSOIL LOSS ON SOIL ORGANIC CARBON (SOC) CONTENT ON SLOPING LANDS IN SOLOMON ISLANDS 2.1 Introduction The adverse impacts of land clearing, cultivation and soil erosion on SOC content are widely recognized (Tisdall and Cades, 1982; Gregorich and Anderson, 1985; Camberdella and Elliot, 1993; Changere and Lai, 1995; Lai, 1998). Chan (1997) reported that conversion of land under pasture to cropland on a Vertisol in Australia significantly reduced SOC content. Lai (1986) pointed out that land use practices and cropping systems that do not return residue to the soil can cause a significant decline in SOC content. An example is subsistence agriculture using slash and bum method, especially when done with the reduction of fallow period, removal of crop residue, and indiscriminate burning (Lai, 1974). When the soil is brought under cultivation it causes SOC loss through several processes leading to increase in: (1) decomposition and mineralization of biomass due to increase in aeration and mixing of plant residues into the soil and high biological activity due to high soil temperature, and (2) accelerated soil erosion and preferential removal of 31 s o c by erosional processes (Lai, 1984; Lai, 1989; Tisdall, 1996). The primary cause of depletion of SOC content on sloping lands is accelerated soil erosion. For example, Mokma and Sietz (1992) reported a significant reduction in surface SOC content due to erosion particularly under cultivation than grassland ecosystem. This is so because the eroded sediments are generally enriched in SOC due to selective removal of fine soil firactions with high amounts of associated SOC (Bajracharya and Lai, 1992). Depletion of SOC content can result in reduction in aggregation and decline in soil structure. Often, this leads to processes such as soil crusting and hardsetting, compaction, accelerated soil erosion, excessive wetness and anaerobiosis, drought and salt imbalance (Lai, 1991; Faustian et al., 1997; Grace et al., 1998). These processes can have adverse impact on soil quality and crop productivity. The SOC content is, therefore, important factor in the maintenance of high soil productivity and reduction of adverse environmental and agronomic effects of accelerated soil erosion (Oades, 1984; Lai, 1986). Being and important component of the global C cycle, SOC dynamic is also related to the accelerated greenhouse effect (Lai et al., 1995; Lai, 1998). Soil aggregation is an important process affecting retention of SOC in the soil. Because of its favorable impact on soil aggregation, understanding of the relationship between SOC and aggregation is very important (Dexter, 1988; Elliot et al., 1993). Research in both the tropical and temperate regions has indicated that a greater proportion of SOC may be held in the 0.5 to 2 mm and larger aggregate fi-actions under natural vegetation compared to that in cultivated land (Elliot et al., 1993). The cultivated soil may have large proportion of SOC in the fine aggregates and particle size firactions 32 indicating susceptibility of macroaggregates to disruptive forces of agricultural activities and exposure to climatic elements (Angers et al., 1993). The objective of this study was to determine the changes o f SOC content as influence by shifting cultivation and loss of topsoil on sloping land under tropical ecosystem, and evaluate the importance of aggregation in soil carbon sequestration. The hypotheses tested in this study are as follows: 1. The SOC content in the whole soil and macroaggregate fraction is decreased by cultivation and loss of topsoil 2. Decrease in SOC content have adverse impact on aggregation and soil structure 2.2 Materials and methods 2.2.1 Site and soil description The experimental site, with gross area of about 8.7 ha is located about 2 km northwest of Ringgi township at 160 m elevation. Hansell and Wall (1975) described the upper hills at the site as short, straight or convex, and moderately steep with slope gradient of 11 to 28 percent and lower hill slopes and gullies are short, straight to concave and steep with slope gradient 28 to 50 percent. At the end of the slopes is a narrow valley that is less than 30m wide with small intermittent stream running in the north/south direction. Slopes appear uniform but are affected by logging roads. The west slope appears ‘smoother’ however it is traversed by an incised old logging track. The area was logged during 1970’s by Levers Pacific Timber limited (LPTL), and was under secondary forest regrowth when the trial was established. Soil of the experimental site is described in detail in section 1.9.3 of chapter 1. 33 2.2.2 Experimental design and soil sampling The trial consisted of three treatments with three replications organized in a randomized complete block design. The treatments are: (1) Undisturbed soil under natural forest (NF) with no visible signs o f soil erosion (Plate 2.1), (2) Farmers Practice (FP) where the cropping system used was farmers practice with two sweet potato (Ipomoea batatas) crops followed by one year fallow. The sweet potato was planted up and down slope on mounds at 1 m intervals after the vegetation was slashed and burnt, and (Plate 2.2) (3) Scalp (SC) where topsoil (0-15 cm depth) was de-surfaced followed by cultivation of two sweet potato crops and one year fallow. The topsoil was manually removed after vegetation was slashed and burnt. The sweet potato was planted up and down slope on mounds at Im intervals (Plate 2.3). 34 Plate 2.1 Natural forest (NF) treatment 35 Plate 2.2: Framers practice (FP) treatment with sweet potato growth at 3 months after planting 36 % Plate 2.3 Scalped (SC) treatment with sweet potato growth at 3 months after planting 37 The FP and SC treatments were replicated three times while NF did not have any replication but samples or measurements were obtained in triplicate to determine the average value of the soil parameter under investigation. The trial consisted of 6 plots each measuring 20 m by 10 m in size. The FP and SC treatments were planted to sweet potato on mounds with center to center spacing of 1 m. Mounds were made from the topsoil using a 1-m^ frame. A total o f four sweet potato vines, with 30cm length, were planted in each mound. During the cropping period the FP had lost 1.5 Mg ha*^ soil as bedload. The bedload was collected from the bedload collection trough located at the lower end of the plot. Soil was sampled during year 2000 immediately after the crop harvest. Composite soil samples were obtained from each plot at 0-15 and 15-30 cm depths using a soil auger. Soil samples from the adjacent natural forest were obtained at the same time both within the designated plot area and along the catena. Soil profile samples were also collected for each horizon to determine the SOC content. The soil was air-dried before transportation for laboratory analysis. Soil bulk density ( p^) was determined by the core method (Blake and Hartge, 1986), with core dimensions of 50 mm in diameter by 50 mm height. Core samples were taken from 0-15cm and 15-30 cm depths at the same time when composite soil samples were also collected. The bulk density data were used to compute the SOC pool for each soil depth on a hactare basis. 38 2.2.3 Soil Preparation for SOC analysis The air — dried soil was sieved to obtain aggregates within size range 5 to 8 mm diameters. The aggregates were sieved using the wet sieving technique (Yoder, 1936; Kemper and Rosenau, 1986). Fifty grams of soil aggregates (5-8 mm diameter) were placed on a set of nested sieves (5, 2, 1, 0.5 and 0.25 mm), and were sieved for 30 minutes. After wet sieving, samples were transferred to a set of pre-weighed beakers and oven dried at 60 ° C until water had evaporated, and were weighed. After weighing to determine percent water stable aggregates (% WSA) (Yoder 1936), and the mean weight diameter (MWD) (Van Bavel, 1949; Youker and McGuiness, 1956), sub-samples of each aggregate size were retained for SOC analysis to determine the SOC content in different size fractions. An average sample amount of 0.4 to 0.5 g was retained for SOC analysis. The whole soil samples (< 2mm) were gently ground, passed through 100 microns sieve, and tested for presence of carbonates prior to analysis for SOC content. 2.2.4 SOC analyses The whole soil (< 2 mm) and aggregates were analyzed for SOC content using dry combustion (Soil Survey Methods Manual, 1996) at 900 ° C for 4 min. About 80 to 120 mg of sample was used for the analysis. 2.2.5 Data analyses To test for the first hypothesis, one way analysis of variance (ANOVA) table, according to randomized complete block design, was used to statistically analyze the 39 s o c content in the whole soil and six different aggregate sizes using “MSTAT’ version 2.0 statistical computer package (Fred, 1991). Statistical significance was calculated using Fisher’s least significant difference (LSD) at p < 0.05 level. Regression analyses was also used to establish any relationship among soil properties and SOC content. The percent water stable aggregates (WSA), mean weight diameter (MWD) among the three landuse use treatments were used to evaluate the treatment effect on soil structure. 2.3 Results and Discussion 2.3.1. The SOC content in the whole soil The topsoil is generally rich in SOC content under the natural forest, especially in the top 15cm depth. High SOC content in the topsoil is due to the presence of a thin (0-4 cm depth) layer of un-decomposed organic material covering the topsoil especially on the slopes and ridge tops. However, the SOC content decreases abmptly with depth, as is shown in Table 2.1. Mid slope Profile Lower slope profile Horizon Depth SOC Depth SOC Content Content (cm) (g kg ‘‘) (cm) (g kg -') Ao 0-7 62 0-5 102 A 7-18 21 5-14 38 B 18-59 7 14-60 9 C 59-130 2 60-120 3 Cr >130 1 >120 1 Ao = A horizon with organic layer Cr = C horizon with soft rotten rock fragments Table 2.1. The SOC content in two soil profiles located at mid and lower slope at the experimental site 40 The slope also affects the distribution of SOC. There was a significantly higher SOC content in lower slopes than mid slopes and ridge tops in the top 15cm layer. There was however no significant difference in SOC content between NF, FP and SC treatments at 15-30 cm depth (Table 2.2.) Slope class SOC content (g kg "‘) A.0-15 cm depth Ridge top 52 Mid slope 63 Lower slope 74 LSD (0.05) 8 B. 15-30 cm depth Ridge top 43 M id slope 45 Lower slope 48 LSD (0.05) 6 Table 2.2: Distribution of SOC along different slopes at the experimental site The distribution of SOC content along different slopes suggest that the SOC may be redistributed from upper slopes to lower slopes through internal drainage. The SOC are accumulated at lower slope where more moisture is present and thus less oxidation. It may be also due sediment movement from the upper slopes to lower slopes. Even there was no obvious signs of soil erosion under the forest, the steep slopes (35-46 percent) and the high rainfall regime (3500 mm per annum) at the site may have contributed to some 41 level of sediment movement. As Bajracharya and Lai (1992) reported, the eroded sediments are generally enriched in SOC and due to selective removal of fine soil firactions with higher amounts of associated SOC may explain why lower slopes are high in SOC content. 2.3.2 Effect of land clearing, cultivation and topsoil loss on whole soil SOC There were marked differences in SOC content in whole soil because of differences in land clearing, cultivation, and topsoil loss for 0-15 and 15-30 cm depths. The SOC content and SOC pool followed the order NF>FP>SC (Table 2.3). The natural forest soil had 2.8 times more SOC than FP and 9.6 times more than SC in the top 15cm depth. In the 15—30 cm depth, the SOC content in NF was 1.7 times more than FP and 6 times more than SC. The same trend was observed for the SOC pool (Table 2.3). Whole soil Land use SOC SOC Pool (gkg ‘‘) (Mg ha') A.0-15 cm depth Natural Forest 67 66.3 Farmers Practice 24 27.0 Scalp 7 9.0 LSD (0.05) 3 22.8 B. 15-30 cm depth Natural Forest 48 48.2 Farmers Practice 28 35.3 Scalp 8 10.7 LSD (0.05) 3 5.1 Table 2.3. The SOC content and SOC pool in the soil under NF, FP and SC treatments. 42 The data in Table 2.3 suggest that land clearing, cultivation and topsoil loss had significant impact on both SOC content and pool. The significant decline in SOC content managed soils was due to the fact that SOC is concentrated in the topsoil (0-5 cm) layer. Once this soil layer is disturbed through clearing and cultivation, SOC content is adversely affected. Removal of vegetative biomass through burning and subsequent cultivation adversely affects soil aggregates, accentuating SOC mineralization especially under high soil temperature regimes in the humid tropics. The SC treatment had only 7 percent of the SOC content of the original topsoil. There are some soils in Solomon Islands that have completely lost topsoil due to frequent cultivation and accelerated soil erosion. The startling evidence of land degradation was brought into focus by rural farmers seeking help in the northern part of the island o f Malaita. In the district of Fouia, farmers are basically cultivating the sub-soil because topsoil has long been eroded away (Cheatle, 1988). 2.3.3. Aggregate size distribution under the different land use The distribution of the water stable aggregates (WSA) in the top 15 cm depth indicated that NF had significantly higher concentrations of WSA(5-8 mm) at both depths than FP and SC treatments. The FP treatment had highest concentration of 2-5mm size aggregates in the topsoil, and 0.5-lmm size aggregates in the subsoil. The SC treatment on the other hand, had significantly higher concentration of 0-0.25 mm size aggregates for both depths than NF and FP treatments (Table 2.4). The lower concentration of 5-8 mm size aggregate observed under the FP and SC treatments could have been due to loss of stmcture through reduction in SOC content and physical breakage through cultivation. 43 In the case of SC treatment, most of the large and water stable aggregates were lost in the topsoil when it was removed. Only the microaggregates remained in the plots. Land use Aggregate Size (mm) 5-8 2-5 1-2 0.5-1 0.25-0.5 0-0.25 A. 0-15 cm depth ------—------%^A^SA------Natural Forest 60.6a 18.7c 4.4c 2.0c 1.0b 13.3b Farmers Practice 21.7b 45.7a 14.7a 5.4b 2.1b 10.3c Scalped 4.4c 24.7b 10.4b 9.3a 10.3a 41.0a LSD (0.05) 1.9 4.7 1.1 0.4 10.3 0.6 B. 15-30 cm depth Natural Forest 72.3a 12.6b 3.9c 2.1c 1.1c 7.9b Farmers Practice 19.6b 13.5b 13.6b 31.4a 14.3a 7.7b Scalped 9.1c 25.7a 14.4a 9.5b 7.7b 33.8a LSD (0.05) 3.2 1.3 0.4 0.7 1.1 0.8 Means followed by the same letter are not significantly different Table 2.4: Distribution of water stable aggregates for NF, FP and SC treatments for 0-15 cm and 15-30cm depths. Soil bulk density decreased with increase in SOC content in all treatments, but the decrease was significant only in the top 0-15 cm layer (Table 2.5, Figure 2.1). The water stable aggregates (WSA) were not significantly among NF and FP treatments, but both had significantly higher WSA than SC treatment for both depths. The mean weight diameter (MWD) showed the same trend as that of the WSA in the top 15cm depth. 44 However MWD under NF treatment was significantly higher than that in FP and SC treatments in the 15-30 cm depth. Whole soil Bulk Land use SOC Density WSA MWD (g k g '‘) (Mg m'3) (%) (mm) A. 0-15 cm depth Natural Forest 67 0.66 89.7 5.5 Farmers Practice 24 0.75 86.7 4.8 Scalp 7 0.86 59.0 3.5 LSD (0.05) 3 NS 10.1 0.8 B. 15-30 cm depth Natural Forest 48 0.67 92.3 4.7 Farmers Practice 28 0.84 92.1 2.4 Scalp 8 0.89 66.2 1.9 LSD (0.05) 3 0.18 1.5 0.8 SOC = soil organic carbon, WSA = water stable aggregates, MWD = mean weight diameter Table 2.5 Bulk density, WSA, and MWD under three land use practices 45 Y= -0.03X4-0.85, R^= 0.40 NS 1.0 T ♦ Bulk density ■— Predicted bulk density 0.9 0.8 r<~' 0.7 -- B ^ 0.6 + ■I 0.5 + 3 0.4 + m 0.3 - 0.2 - 0.1 0.0 0 SOC (gkg') Figure 2.1: Bulk density versus SOC content in NF, FP and SC treatments for 0-15 cm depth 46 The soil organic matter (SOM) has pronounced effect on many soil physical characteristics including soil bulk density (Arvidsson, 1998). Lantz (2000) observed that soil bulk density significantly decreased with increase in SOC content in the top 0-5 cm depth. The lack of significant increase in bulk density with decline in SOC content between NF, FP and SC treatments in the topsoil may be due to high soil porosity (>60%) and low particle density of 2.4 Mg m'^ of the soil. The soils of the experimental site are of volcanic origin (Andosols) but have become heavily weathered into Oxisols (Hansell and Wall, 1975). Humphrey (1991) observed similar results for the same soil type in Papua New Guinea. Soil bulk density was less than 0.85 Mg m'^ with a porosity of 70 to 80 percent and particle density of 2.4 Mg m'^. The conversion of forest to cropland significantly reduced the SOC content and had drastic impact on soil structure causing a significant decline in both WSA and MWD in FP and SC treatments. Decline in soil structure may be due to the effect of cultivation, which can break larger aggregates into smaller aggregates (Jastrow and Miller, 1998). 2.3.3. SOC content of aggregate size fractions The six aggregate size fractions exhibited a trend similar to the whole soil SOC content in the top 15cm layer. There was a significantly higher SOC content in large (>lmm) aggregate size fractions under NF than FP and SC treatments. However, no significant difference in SOC content in <1 mm aggregate size fractions among NF and FP treatments. The SOC content in the SC treatment remained significantly low except in the <0.25 mm aggregate size fraction. In fact there was no difference in the SOC content 47 in the <0.25 mm aggregate size among all three land use practices (NF, FP and SC). The SOC content <0.25 mm size fiaction was also high, almost similar in magnitude to SOC content in >lmm aggregate size (Table 2.6). On the whole the macroaggregates (> 0.25 mm) contained more SOC content than microaggregates (<0.25 mm). The macroaggregates contained 82 percent, 80 percent, and 60 percent more SOC than microaggregates in three land use treatments, respectively. The SOC content in the 15-30 cm depth was different to that o f the trend observed in the top 15 cm depth. Although the SOC content in the whole soil was significantly higher under NF than FP and SC treatments, the SOC content in different aggregate size fractions in the NF soil was significantly lower than that in FP treatment and not significantly different than that in the SC treatment. 48 Landuse Whole soil Aggregate size — fractions (mm) SOC 5-8 2-5 1-2 0.5-1 0.25-0.5 0-0.25 (g kg') A.0-15 cm depth Natural Forest 67a 45a 38a 27a 15b 18a 31a Farmers Practice 24b 37b 28b 24a 20a 15a 30a Scalp 7c 15c 13c 12b 8c 8b 38a LSD (0.05) 3 6 7 3 6 6 8 B. 15-30 cm depth Natural Forest 48a 35a 27b 16b 7b 7b 7b Farmers Practice 28b 29a 33a 22a 17a 14a 18a Scalp 8c 15b 13c 12b 8c 7b 8b LSD (0.05) 3 10 2 4 3 4 4 Means followed by the same letter are not significantly different. Table 2.6: The SOC content in different aggregate size fractions These data suggest that much of the SOC is concentrated within the water stable macroaggregates, particularly under the forest soils or uncultivated soils. These results are similar to the findings of other researches (Beare et al., 1994; Elliot et al., 1993; Bajracharya et al., 1998). Camberdella and Elliot (1993) reported that the macroaggregates may comprise of SOC-rich microaggregates which tend to be stable to physical disruption than are macroaggregates. Besnard et al.(1996) suggested several mechanisms in which the SOC is held within the microaggregates. Important among these are physical protection within the microaggregate and microbial bioproducts (e.g., carbohydrate threads and glues) reaching the mineral components. The microbial biomass is also held in the aggregates through covalent bonding, ion exchange, van der vaals 49 forces and electrostatic attractions between the organic matter and clay particles. Oades and Waters (1991) observed cores of plant debris and encrustation of plant fiagments by the mineral particles in many microaggregates of 100-200pm diameter. They therefore proposed that the mineral particles are possibly held together by the recalcitrant plant debris and fragments into microaggregates. Foster (1982) observed, through electron microspcopy, that most extracellular polysaccharides in the rhizosphere were negatively charged. Tisdall (1996) reported that such negatively charged polysaccharides or highly aromatic humic material are adsorbed on to surfaces of clays by polyvalent cations such ca^% Fe^^ and Al^^, aluminosilicates and hydroxyaluminium. Some uncharged organic molecules such as aliphatic groups in polysaccharides may also form H-bonds with water molecules in the H-shell of the exhangeable cation. Each individual bond is weak but when they are added together to form a long flexible molecule with many hydroxyl groups, the many H-bonds may be bound strongly to the surface of the clay particle. Although it may appear that aggregate formation may start in this way it has not yet been proven and can only be regarded as hypothesis. There is still a need to conduct further research in this area. 2.4 Conclusions The following conclusions can be made from the data obtained through this study: 1. The SOC content was high under forest soil but only in the topsoil (0-15 cm) layer. It decreased abruptly with increase in depth. Further SOC content was high in the lower slopes compared to upper slopes and ridge top positions. 2. Subsistence agriculture on sloping lands had significant adverse impact on SOC content. There was significantly lower SOC content under FP and SC compared to 50 NF treatment which Macroaggregates (>0.25mm) had more SOC content compared to the microaggregates (<0.25mm). 3. Loss in SOC can significantly and adversely affect soil structure including WSA and MWD parameters. 4. 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Soil Sci. 83:291-294. 55 CHAPTERS LAND USE EFFECT ON SOIL PROPERTIES AND CROP YIELD ON SLOPING LANDS IN SOLOMON ISLANDS 3.1 Introduction Cultivation and topsoil loss through accelerated soil erosion can have major effect on soil properties. Two major on-site effects of cultivation and accelerated soil erosion on crop productivity are decline in soil physical properties and loss of plant nutrients (Lai 1979a). Soil physical properties included structure, texture, bulk density, infiltration rate, available water holding capacity and favorable rooting depth (Frye et al., 1982; El-Swaify, 1993; Ebeid et al., 1995; Olson et al., 1999). Soil chemical properties include soil pH, soil organic carbon, and major plant nutrients (e.g. N, P, K and Mg). While other factors (e.g. weather and genetic potential) can also control the overall production of crops in a geographical area, Olson et al. (1999) pointed out that the soil system remains the major determinant of yields because of the environment it provides for root growth. Lai (1998) reported different experimental techniques used in studying the on-site effects of soil erosion on soil properties and crop yield. Thein situ field methods includes: (1) removing topsoil, (2) creating different levels of accelerated soil erosion, (3) topsoil depth, (4) choosing soils with different depth to root restrictive layer, (5) defining soil erosion class, and (6) having depth with different past management history and soil 56 quality. The topsoil removal method was used in this study. In this method, soil erosion is simulated by varying the topsoil depth (TSD) through removal or addition of topsoil to the existing soil surface (Lai, 1998). Greb and Smika (1985) reported that removing the topsoil alters soil physical and chemical properties of the site and thus changes the soil quality and subsequently crop productivity. The impact on topsoil removal through accelerated soil erosion on soil properties and crop productivity are well documented for temperate regions but the data are still fragmented, and therefore it is difficult to make conclusive management decisions based on the available data (Wolman, 1985). In the tropics, the data are not only fragmented but also scarce and there is hardly any information available for the South Pacific region including Solomon Islands. The only studies in the Pacific region are those by El-Swaify and Cooley (1981) and El-Swaify and Dangler (1982) in Hawaii. El-Swaify and Dangler (1982) reported that soil erosion caused the loss of topsoil and led to depletion of organic matter and soil nutrients, and reduction in productivity. The objective of this study was to evaluate the effect of cultivation and topsoil loss on soil properties, and develop a relationship between soil properties and crop yield on sloping lands in Solomon Islands. 57 3.2 Materials and method 3.2.1 Site and soil description Detail description of the experimental site is given in section. 2.3 of chapter 2. The soil is also described in detail in section 1.9.3 of chapter 1. Physically the soil is deep, well drained and strongly aggregated despite low organic matter content. The aggregation is due to presence of high amounts o f iron and aluminum oxides which gives the soil its brownish to reddish color. It is susceptible to erosion when disturbed by logging activities (Hansell and Wall, 1975). The soil is highly weathered, acidic with pH commonly below 5, very low available and reserve nutrients, low cation exchange capacity (CEC) ranging from 6 cmol kg'* in the 0-5 cm to 1.3 cmol kg'* at 100 cm depth and very low base saturation percentages (Chase et al., 1986). Generally it is chemically infertile soil especially on upper and mid slopes. 3.2.2 Experimental design and soil sampling The experimental design is described in detail in section 2.3.2 of chapter 2. The experiment consisted of three treatments with three replications arranged in a randomized complete block design. The treatments are: (1) imdisturbed soil under natural forest (NF) with no visible signs of soil erosion, (2) farmers practice (FP) with two sweet potato (Jpomoea batatas) crops followed by one year fallow. The sweet potato was planted up and down slope on mounds at 1-m intervals after the vegetation was slashed and burnt, and (3). scalped (SC) where the topsoil (0-15 cm depth) was de-surfâced with two sweet potato crops followed by one-year fallow. The topsoil was manually removed after 58 vegetation was manually cleared. The sweet potato was planted up and down slope on mounds 1-m intervals. The mounds were made using hoes and mattocks to turn the soil. 3.2.3 Measurement of soil physical properties The soil physical properties were determined or assessed bothin situ and in the laboratory. The measured properties are discussed in detail in the subsequent paragraphs. 3.2.3.1 Soil water retention The soil water retention was measured by a combination of a tension table and pressure plate extractors at different tensions ranging from saturation to 1.5 mPa. Undisturbed soil cores obtained from 0-15 cm depth were used from the replicate plots for three land use practices. The plant —available water capacity was evaluated as the difference in the volumetric water content held at 0.03 mPa and 1.5 mPa tension corresponding to field capacity and permanent wilting point respectively. 3.2.3.2 Strength Properties Bulk density ( p&) and particle density (p^) were determined by the core and pycnometer methods (Blake and Hartge, 1986). The core dimensions were 50 mm in diameter by 50 mm in height. Core samples were taken from the middle 0-15cm and 15- 30 cm depths. The particle density was determined by evaluating the proportion of mineral and organic fractions through their specific gravity. Penetration resistance was measured in the field using a Bush Recording Penetrometer when the soil was at field moisture capacity. Penetration resistance was measured in kpa across all three treatments for 0, 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 cm depths. 59 3.2.3.3 Mechanical Properties Soil texture was determined by the hydrometer method (Gee and Bander, 1986), using sodium hexametaphosphate as dispersion agent and the destruction of soil aggregates into discrete units by mechanical means. Aggregate size distribution and stability were determined using the standard procedure for the wet sieving technique (Yoder, 1936). Pre-weighed where 50 g of soil aggregates (5-8 mm) were placed on a set of nested sieves (5,2, 1, 0.5 and 0.25 mm), and were sieved under water for 30 minutes. Oven dry weight of aggregates remaining on each sieve size was determined. Correction for the sand fraction was made by dispersing the aggregates using sodium hexametaphosphate solution of a concentration of 37.5g 1'^ and re-sieved through their respective sieve sizes. Results were expressed as the mean weight diameter (MWD) in mm (Van Bavel, 1949; Youker and McGuiness, 1956) and geometric mean diameter (GMD) in mm (Mazurak, 1950) using the equations 3.1 and 3.2: MWD = Z Xj Wj...... (eq. 3.1) J = l Where, MWD is the mean weight diameter, n is the number of aggregate size ranges (mm), Xj is the mean weight diameter o f any particle size range o f aggregates separated by sieving, and wj is weight of the aggregates of that size range as a fraction of the total dry weight o f sample analysed. 60 E Wi log Xi GMD = exp...... (eq. 3.2) n E Wi i= i Where, GMD is geometric mean diameter w, is the weight of the aggregates in a size class of average diameter, Xi is size class of average diameter. Aggregate size distribution is a useful index for relating to other soil properties and processes mth MWD and GMD. Aggregate stability measures the degree of resistance of aggregates to breakdown when they are subjected to disruptive forces of water. Aggregate stability is evaluated by determining the proportion of the original sample that resisted the disruptive forces (Kemper and Roseneau, 1986). (weight retained) — (weight of sand (gravel)) % WSA = ------xlOO (eq. 3.3) (total weight of sample) — (weight of gravel) Total porosity (f) and air filled porosity (fa) were determined from the moisture release curve determined in section 3.2.3.1. Total porosity was calculated by determining volumetric water content using the data on water content on weight basis at saturation and bulk density (Danielson and Sutherland, 1986). f= ( P&) * ( 0w) at saturation ...... (eq.3.4) Air-filled porosity was determined by subtracting the volumetric water content at each suction or moisture potential from total porosity. 61 3.2.3.4 Hydrologie properties Infiltration rate was measured by conducting infiltration tests in each plot using double ring infiltrometer (Bouwer, 1986). The diameters of the outer and inner rings were 40 cm and 30 cm respectively. Since measurements were conducted on slopes a portion of the topsoil was removed to create a flat surface on which the measurement was made. This caused some degree of disturbance. Both the outer and inner rings were driven into the soil to a depth of 15 cm. Water was applied to both rings. The cummulative infiltration was recorded at time intervals of 1, 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170 and 180 minutes. Using the field data the cumulative infiltration was calculated and plotted against time. The data were then analyzed according to the following models: Philip’s (1957) model: I = St'^+At...... (eq. 3.5) Where, I is cumulative infiltration (cm), S is soil water sorptivity (cm min''^), A is transmissivity (cm min ^), and t is time. The infiltration rate i (cm hr'^) was calculated using the formula: i = dl/dt = S/2*f^^ + A ...... (eq.3.6) The Kostiakov (1932) model was used in relating cumulative infiltration (I) and infiltration rate as a function of empirically determined constants. I = at^...... (eq.3.7) Where, I is cumulative infiltration (cm), t is time (min) and a and b are empirically determined constants. Figures 3.1 and 3.2 show use of Kostiakov (1932) and Philip’s (1957) models to determine soil water sorptivity (S), transmisivity (A) and impirical constants a and b . The NF treatment data is included in figures 3.1 and 3.2. 62 10 o LogI(cm) PredictedLogI(cm) 1 -J Kostiakov model R^=0.99 Y=0.71 x+0.70 0.1 0.1 1 10 Log t (min) Figure 3.1; Logarithm transformation of cumulative infiltration vs time to determine constants “a” and “b” in Kostiakov model. 63 4.5 0 A ± B l infîltrHtÎQarale Recficted infiltration rate 3.5 2 c o 2 MipsMxM I^=0.77 Y=3.73x+0.46 0.5 0 0 2 0.4 0.6 0.8 1 12 Figure 3.2: Infiltration vs time to determine S and A using Philip’s model. Saturated hydraulic conductivity of soil cores was measured under steady state conditions in the laboratory using the constant head method (Klute and Dirksen, 1986). According to Darcy’s law for saturated flow, hydraulic conductivity is expressed as a ratio of the water flux (LT') to hydraulic gradient (LL'*), or the slope of the flux versus gradient curve. The saturated hydraulic conductivity was calculated using the following formula: 64 Ks =Q/At*L/H ...... (eq.3.8) Where, Ks is proportionality factor (cm hur'‘), Q is total volume (cm^), A is cross sectional area of soil core (cm^), t is interval (30 minutes), L is length o f sample (cm), H is hydraulic head (cm) 3.2.4 Soil chemical properties Soil was sampled immediately after crop harvest during the year 2000. Composite soil samples were obtained from each plot at 0-15 and 15-30 cm depths using soil auger. Soil samples from the adjacent natural forest were obtained at the same time both within the designated plot area and along the catena. The soil was air-dried, grind and sieved before transportation for analysis. The following chemical properties were analyzed following the standard analysis procedures: pH, SOC, Total N, available P, Exchangeable K, Ca, and Mg. The soil pH was determined in 1:1 soil-water ratio (Thomas, 1996). The SOC was determined by dry combustion at 900 ° C (Soil Survey Methods Manual, 1996). Total Nitrogen was analysed by the kjeldahl digestion method with potassium sulfate catalyst followed by titration with sulfuric acid (Bremner and Mulvaney, 1982). The available P was determine using Bray PI extraction method (Olsen and Dean, 1996). The Bray PI method was used since the soil pH was below pH 7 and thus acid extractants are more appropriate for acid soils. The exchangeable cations (K \ Ca^% Mg^^ were analysed by Soil Mehlich 3 Extraction (Wamcke and Brown, 1998). The CEC of the soil was calculated as summation of the exchangeable cations, it was calculated using equation 3.9 65 CEC= Ca + Mg + K (in cmol kg "^) +1.2(70 - LTI) ...... (eq. 3.9) Where LTI is Lime Test Index which is a measure of the buffering capacity of the soil. Exchangeable Fe was determined by atomic absorption spectrometry using diethylenetriaminepentaacetic (DTPA) as extracting solution (Olson and Ellis, 1982) and exchangeable A1 was determined by extracting technique using unbuffered salt solution of potassium chloride (Bertsch and Bloom, 1996). 3.2.5 Crop growth and yield assessment Two sweet potato crops were grown between September 1999 to May 2000 in the FP and SC treatments. The first crop was planted in August and harvested in December while the second crop was planted in January and harvested in May. Assessment of vegetative crop growth was made on weekly basis until harvest. The following parameters were assessed: percentage canopy cover, number of growing vines, vine length, inter-node length, leaf and vein size, and leaf color. Leaf and vine samples were obtained two months after planting for plant nutrient determination. Another set of leaf and vine samples was obtained during harvest in December 1999. The same frequency of sampling was carried out during the second crop. Both vegetative and tuber yield were determined at both harvests. Mineral Analysis by inductive coupled plasma ( ICP) after dry ash and acid dissolution was carried out for major elements including P, K, Ca, Mg, Al, and Na (Perviz et al., 1982) on both vegetative and tuber samples . 6 6 3.2.6 Soil-and crop yield relationship The effect of changes in soil properties on the yield of sweet potato was established through running a set of linear regression analysis. Sweet potato yield being the dependent variable was regressed against a set of soil properties to see if there is any relationship between the soil properties and yield. The linear regression analysis was carried out using the following soil properties: SOC, MWD, bulk density, clay content, porosity, available water capacity, cumulative infiltration, soil pH, N, P, K and CEC. 3.2.7 Development of soil quality index The soil quality indicators or properties quantified under each treatment were combined to develop a cumulative rating index using the methodology proposed by Lai (1994). The soil quality indicators are listed in table 3. 23 with their respective weighting factors. Lai (1994) allocated each soil indicator of soil quality weighting factors ranging from 1 to 5 with 1 as no limitation, 2 as slight, 3 as moderate, 4 as severe and 5 as extreme. The data on soil quality indicators obtained were combined into an index to assess sustainable use of soil resource. This involved combining weighting factors for the relevant indicators to obtain the cumulative index. A relationship was established between the cumulative soil quality index and sustainability of each land use. 67 3.3 Results and Discussion 3.3.1 Physical Properties 3.3.1.1 Water retention characteristics The data on moisture release characteristics are shown in figures 3.3 and 3.4. It is apparent that the treatments did not have any significant effect on the volumetric water content and fraction of pore space occupied by water. In general, however, SC treatment had lower volumetric water content at different suctions compared to NF and FP treatments. The lower moisture retention in SC treatment may be due to the high sand and low silt and clay fiactions observed under SC at 0-15 cm depth. The NF and FP treatments had significantly high clay content than SC. The capacity of the soil to transmit and retain plant available water depends on its physical conditions. Processes such as topsoil loss through erosion can impact soil physical conditions through alteration of texture and structure. 6 8 055 SC n,G 05- i 04 0 001 002 oœ 005 006 Suctkxi(ml^) Figure 3.3: Volumetric water content between 0.003 to 0.05 mPa suctions under the three land use practices within top 15 cm depth 69 Q5D 9C 035 030 0 02 04 06 08 1 12 14 L6 SLctknCmfô) Figure 3.4: Volumetric water content between 0.1 to 1.5 mPa suctions under the three land use practices within top 15 cm depth There was also no significant difference in the available water capacity between the treatments. The volumetric water content between field capacity and wilting point was low, 0.03, 0.04 and 0.04 for NF, FP and SC respectively. About 64 percent of the soils volumetric water content drained off at lower suctions than field capacity for both 70 NF and FP treatments and 45 percent for the SC treatment. This showed that most of the soil water drained at low suctions and this may be due to the soil high porosity. Lai (1979b) also reported that moisture retention of predominantly coarse-textured soils with kaolin and iron oxide clay minerals in the tropics is generally low. The soil at the experimental site has clay loam texture with kaolin and iron oxide clay minerals. Lai (1979b) also pointed out that field capacity of the soils of the tropics occur around 0.01 mPa suction. 3.3.1.2 Mechanical Properties The data in table 3.1 show that topsoil removal or scalping (SC) had a significant effect on sand, silt and clay contents in the 0-15 cm depth. The SC had significantly higher sand and lower silt and clay contents than FP and NF treatments. The FP treatment also had significantly higher sand than NF but there was no significant difference in the silt and clay fractions. Within 15-30 cm depth, the clay content under SC increased significantly but still had low silt content. There was no significant difference in sand and silt fractions, except for the clay content between FP and NF treatments. The significantly low clay and silt and high sand content under the SC suggest that the bulk of the clay and silt fractions were removed in the topsoil. Land clearing and cultivation in FP did not have any significant effect on the silt and clay fractions. 71 Land use Sand Silt Clay A. 0-15 cm depth % - Natural Forest 28.2 13.6 58.2 Farmers Practice 30.2 13.2 56.6 Scalped 36.6 8.9 54.6 LSD (0.05) 1.1 0.3 1.6 B. 15-30 cm depth Natural Forest 18.2 27.6 54.2 Farmers Practice 20.2 27.2 52.6 Scalped 32.6 10.8 56.6 LSD (0.05) 1.8 1.3 1.2 Table 3.1: Sand, silt and clay distributions within 0-30 cm depth under the three land use practices The percentage water stable aggregates range from 89.7 percent to 92.3 percent under NF treatment for both depths respectively. Aggregation decreased slightly under FP treatment, but a significant decrease was observed under SC treatment at both depths. Aggregation in SC treatment decreased by 34 percent and 28 percent for both depths compared to NF treatment. There was no significant difference in GMD and MWD between NF and FP treatments but they were significantly lower under SC treatment in the 0-15 cm depth. The same trend was observed for the 15-30 cm depth, except GMD, which was significantly high under FP treatment, and MWD which was high under NF treatment (Table 3.2). Removal of the topsoil resulted in decrease in carbon and stable 72 aggregates and increase in sand fractions. The high sand and low silt and clay contents under SC treatment resulted in low water stable aggregation, MWD and GMD. Land use WSAGMD MWD (%) (mm) (mm) A. 0-15 cm depth Natural Forest 89.7 1.6 5.5 Farmers Practice 86.7 1.8 4.8 Scalp 59.0 0.9 3.5 LSD (0.05) 10.1 0.1 0.8 B. 15-30 cm depth Natural Forest 92.3 1.2 4.7 Farmers Practice 92.1 1.8 2.4 Scalp 66.2 1.0 1.9 LSD (0.05) 1.5 0.1 0.8 WSA = Water stable aggregates, GMD = Geometric mean diameter, MWD = Mean weight diameter Table 3.2: The percent WSA and GMD, MWD under the three land use practices within 0-30 cm depth. The data for total porosity and air-filled porosity are shown in table 3.3. Total porosity was not significantly different between the three land use practices. There was also no significant difference in the fraction of pores occupied by air or the air-filled porosity at 0.003 to 1.5 mPa suction. Both total porosity and air-filled porosity were generally low under SC than FP and NF treatments. The decrease in total porosity for SC treatment may be attributed to removal of topsoil and thus discontinuity of the pores. 73 Suction :mPa) Land use / 0.003 0.01 0.01 0.03 0.05 0.1 0.3 0.5 1.5 /a 0-15 cm depth Natural Forest 0.63 0.15 0.19 0.21 0.22 0.23 0.23 0.24 0.25 0.25 Farmers Practice 0.66 0.14 0.18 0.20 0.21 0.22 0.22 0.24 0.24 0.25 Scalp 0.56 0.16 0.19 0.20 0.21 0.22 0.22 0.23 0.24 0.24 LSD (0.05) NS NS NS NS NS NS NS NSNSNS / = Total porosity /a = Air filled porosity Table 3.3: Total porosity and air-filled porosity under the three land use practices within 0-15 cm depth. 3.3.1.3 Strength Properties Data on bulk density, particle density are shown in table 3.4 There was no significant difference in bulk density between the three land use practices in the 0-15 cm depth, but was in the order SC > FP > NF. In the 15-30 cm depth, SC treatment had significantly higher bulk density than other treatments. Particle density was significantly higher under SC than NF and FP treatments at both depths. The particle density were low imder all three land use practices (highest 2.52 Mg m'^ under SC), compared to a value of 2.70 Mg m‘^ for most mineral soils. The low bulk and particle densities in this soil may be due to volcanic origin (Andosols) of the heavily-weathered Oxisols. The soil is also well drained and aggregated due to presence of iron oxides (Hansell and Wall, 1975). 74 p6 (Mg m'^) p^ (Mg m'^) Land use A. 0-15 cm depth Natural Forest 0.66 2.44 Farmers Practice 0.75 2.37 Scalp 0.86 2.52 LSD (0.05) Ns 0.07 B. 15-30 cm depth Natural Forest 0.67 2.43 Farmers Practice 0.84 2.37 Scalp 0.89 2.50 LSD (0.05) 0.18 0.07 p6 = Bulk density p^=Particle density Table 3.4: Treatment effect on bulk density and particle density at 0-30 cm depth. There was no significant difference in penetration resistance between the treatments within the top 30 cm depth (Table 3.5) but penetration resistance was high under SC below 30 cm depth. The penetration resistance in SC below 50 cm depth was about 50 percent more than that in the NF treatment (Figure 3.5). Land use (mPa) 0-30 cm depth Natural Forest 0.24 Farmers Practice 0.29 Scalp 0.30 LSD (0.05) NS Table 3.5: Treatment effect on penetration resistance within 0-30 cm depth. 75 1.2 NFFP SC cu ■ Û 0.6 - 0-4 - cuO.2 - 0 20 40 6080 100 120 Depth (cm) Figure 3.5 Penetration resistance under three land use practices within 0-100 cm depth 3.3.1.4.Hydrologic properties The cumulative infiltration and infiltration rates o f the soil on the 35 percent slope measured during the low rainfall season in 2000 are shown in Figures 3.6 and 3.7. The effect of treatments were neither significant for cumulative infiltration nor for infiltration rates. The total cumulative infiltration over the three-hour period was 170.2 cm, 168.4 cm, and 152. 8 cm depth for NF, FP and SC treatments respectively. Although the cumulative infiltration rate was not statistically different between the three treatments, it was lowest under SC. The average infiltration rates were 78.3cm hr"% 72.4cm hr'\ and 76 68.1cm hr * for NF, FP and SC treatments respectively. The infiltration rate after three hours in SC treatment was 7.8 cm hr'* compared to 10.8 cm hr'* for NF and 9.6 cm hr'* FP treatment. The initial rate was 216.0 cm hr'* for SC, 240.0 cm hr'* for FP and 217.0 cm hr'* for NF treatment. The SC treatment had lower cumulative infiltration and infiltration rate compared to NF and FP, which may be attributed to low aggregation, porosity and bulk density in the top 15 cm depth. In terms of porosity, there may be a possible increase in storage pores and decrease in transmission pores. 77 180 160 'B o 140 c O 120 % 100 ü > 80 ' i 60 I 40 20 0 0 20 40 60 80 100 120 140 160 180 Time (min) Figure 3.6: Treatment effect on cumulative infiltration over three hours time period 78 Philip's Kostiakov model model Land use Cum. Infilt. Infiltration Rate S A a b (cm) (cm hr ~^) (cm hr (cm hr'^) Natural Forest 170.2 78.3 243 35.4 4.6 6.0 Farmers Practice 168.4 72.4 186 30.6 4.2 5.7 Scalped 152.8 68.1 153 21.6 3.4 4.9 LSD(O.OS) NS NS 43.5 4.2 0.6 NS Table 3.6: Cumulative infiltration (I), infiltration rate (i), sorptivity (S) and transmissivity (A) of Philip’s model and empirical constants a and b in Kostiakov model. The sorptivity (S) value in the Philip’s (1957) model (I = St‘^ + At) is a measure of the soils capacity to absorb water thus the initial infiltration rate is controlled by the sorptivity of the soil. Table 3.6 shows that there was significant difference in sorptivity between the three treatments. The SC treatment had significantly low sorptivity compared to NF treatment but not significantly different from that of FP treatment. The low initial infiltration for SC by 4.2 percent and 13.8 percent compared with that of NF and FP treatments may due to low sorptivity. Although the land use practices did not significantly impact infiltration rate, the general trend showed that SC treatment had lower infiltration rate compared to FP and NF treatments. When “t” increases in magnitude, the second term (At) in the model becomes the dominant factor controlling infiltration rate, which means that the final infiltration rate is governed by soil water transmissivity (A). The SC treatment had significantly low transmissivity compared to 79 NF and FP treatments. Again this result is reflected in the infiltration rate recorded at the end of the three-hour period in which SC had lower infiltration rate than NF and FP treatments. Computation of empirical constants “a” and “b” based on the Kostiakov model (I = at**) for cumulative infiltration, it was found that there was no significant difference in “b” but ”a” was significantly low for SC treatment. The constant “a” value for SC was lower by 26 and 19 percent than NF and FP treatments, respectively. According to saturated hydraulic conductivity classes by the Soil Survey Staff (1993), the hydraulic conductivity values obtained in this study were classified as high for all three land use practices. However, the NF treatment had significantly higher ks than FP and SC treatments for both depths (Table 3.7). Since the water movement within the soil profile is high, it was reflected in the cumulative infiltration data. Land use Saturated hydraulic Conductivity A. 0-15 cm depth Cm h r-' Natural Forest 15.90 Farmers Practice 3.70 Scalp 2.20 LSD (0.05) 5.68 B. 15-30 cm depth Natural Forest 12.1 Farmers Practice 3.1 Scalp 1.9 LSD (0-05) 0.18 Table 3.7: Saturated hydraulic conductivity under three land use practices within 0-30 cm depth. 80 Saturated hydraulic conductivity is a measure of the ability of a soil to permit water flow. It is influenced by pore volume, size distribution and geometry, and the fluid density and viscocity. High hydrauhc conductivity in all treatments was due to high porosity of the soil. 3.3.2 Chemical properties The data on soil chemical properties are shown in table 3.8. Soil pH remain between 4 and 5 among all treatments, but was significantly higher in the SC treatment after crop harvest compared to NF treatment. There was also an increase in soil pH for FP but was not significantly different firom the NF treatment. The soil at the site is highly weathered, brownish to red clays, acidic with pH commonly below 5. There were marked differences in SOC content in whole soil because of differences in land clearing, cultivation, and topsoil loss for 0-15 cm depth. The SOC content followed the order NF>FP>SC (Table 3.8). The natural forest soil had 2.8 times more SOC than FP and 9.6 times more than SC in the top 15cm depth. Soil cultivation and cropping resulted in 50 percent decrease in the SOC content under FP treatment. There was also a 12 percent decrease for SC after cropping. The reduction of SOC content under both FP and SC treatments may be due to the impact of cultivation and topsoil loss through exposure of aggregates and removal of aggregates and clay with the within the topsoil. The N content was significantly lower for SC than FP and NF treatments both before and after cropping. Cropping did not have any effect on the N content. The C/N ratio was significantly low for FP and SC both before and after 81 cropping. This is due to the significant reduction in the SOC content in the soil between treatments and after cropping. Available P was significantly high under FP followed by SC but decreased after cropping. The high amount of available P obtained for FP may be due to the burning of biomass during land preparation (Chase, 1981). The same is also true for exchangeable K, with significant level for FP treatment compared to NF and SC. The soil naturally has low exchangeable cations and low CEC in the range 13-22 cmol kg'*. There were significant changes in both exchangeable cations and CEC among treatments with lowest values for SC. Cropping also reduced the level of both exchangeable cations and CEC. On another study at the site. Chase et al. (1986) observed reduction in CEC with depth, firom 16 cmol kg'' in the 0-5 cm depth to 1.3 cmol kg'' at 100 cm depth and there was also low base saturation percentages. Percentage base saturation decreased with depth, firom 37 percent in top 5 cm depth to as low as I percent at 100 cm depth. Available phosphorus and total nitrogen were also low with average values of 2.1 mg kg ' of P and 0.34 percent of N in the 0-15 cm layer, and 0.6 mg kg'' and 0.16 percent in the 15-30 cm depth. Soil organic carbon was high in the 0-15 cm depth only. The soil in its natural form is chemically infertile especially on upper and mid slopes (Hansell and Wall, 1975; Chase, 1981). These are the slopes commonly cultivated by farmers who often harvest low crop yield. The data obtained in this study showed significant adverse changes in the chemical status of the soil among cropping treatment, which can have adverse effect on crop yield. 82 Land use K Ca Mg CEC Fe (DPTA) KCl Ext. A1 ( cmol kg'^) Natural Forest 0.1 0.3 0.4 21 0.3 0.1 Farmers Practice 0.2 3.2 0.8 20 0.2 0.3 Scalped 0.1 1.8 0.3 13 0.7 0.2 LSD (0.05) 0.01 0.4 0.1 3 0-1 0.01 (a) Land use pH SOCNC/N P (HlinHzO) (gkg-‘) (gkg-') (mgkg'^) Natural Forest 4.3 67 4 17 8 Farmers Practice 4.9 24 4 6 12 Scalped 5.1 7 3 2 8 LSD (0.05) 0.6 3 0.06 0.9 2 (b) Table 3.8: Treatment effect on soil chemical properties (a) exchangeable cations and (b) pH, SOC and other major nutrients 3.3.3 Sweet potato growth and yield The rainfall during February and March 2000 w as unusually low and the second sweet potato crop suffered from drought stress. Furthermore, the damage caused by birds to sweet potato vines during the first month after plamting was also another factor affecting growth. It was observed that about 35 percent of sweet potato vines planted were either pulled out of the mounds or eaten by birds. The effect of changes in soil properties were therefore confounded with the effect o f drought and crop damage especially for the second crop. In general, crop growthi and vigor were best for FP treatment compared to SC treatment. It was observed that vines under the SC treatment 83 had stunted growth, short inter-nodes with small leaves and veins. Almost all cuttings failed to creep, they were still standing even a harvest stage. Leaves showed pink color with reddening of mid veins. 3.3.3.1 Canopy cover and vine length The data in table 3.9 show sweet potato growth characteristics between FP and SC treatments. Growth Parameter FP SC Ground Cover (%) - at 3 months 75-100 5 - at Harvest 100 10 Mean no. of vines/mound at 4 2 harvest Mean vine length at 3 months 2 m 0.5 m Mean inter-node length at 3 0.2m 0.05m months Vein color Green Pink/red Table 3.9: Comparison of growth characteristics of sweet potato between FP and SC treatments 3.3.3.2 Crop yield Tuber yield and vegetative biomass were significantly higher under FP than SC treatment for both crops (Table 3.10 emd Table 3.11). Both tuber yield and vegetative biomass were 96 percent lower for SC treatment compared to FP treatment in the first 84 crop. In the second crop, tuber yield was 80 percent and vegetative biomass was 67 percent lower for SC than FP treatment. Tuber yield under SC treatment was significantly low at 0.1 Mg ha'* compared to 2.6 Mg ha'* under FP treatment for the first crop and 0.04 Mg ha'* compared to 1.2 Mg ha'* for the second crop. These yields represent a loss of 60 percent tuber production. Although the vegetative growth and tuber yield under FP was significantly higher than SC there was also a drastic decline in tuber yield between the two crops from 2.6 Mg ha * to 1.2 Mg ha'*, a yield reduction of more than 50 percent. Average yield on FP plots was around 4.7 Mg ha * in Solomon Islands and in the South Pacific region (O’Sullivan et al. 1997). The yield from the first crop is usually around 4 - 6 Mg ha'* but continue to decline thereafter. In PNG, Humphrey (1991) reported yield reduction after three successive crops under farmers practice to be 6.7 Mg ha'*, 3.4 Mg ha'* and 3.0 Mg ha'* respectively. Although there was reduction in yield the rate of yield decline was not as drastic as obtained in this study. While changes in both physical and chemical properties could have contributed to the observed drastic yield reductions, two possible factors that may also have contributed to the lower yield were the low rainfall during February and March 2000 and the damage caused by birds to the planted vines at planting stage. It was observed that about 35 percent of sweet potato vines were either pulled out of the mounds or eaten by birds. This may have confounded the effect from changes in the soil properties especially the FP treatment. The significant yield differences observed between FP and SC especially during the first crop was due to differences in soil properties between FP and SC treatments. Removal of the top 15 cm of soil resulted in 80 to 90 percent decline in yield of the sweet potato during two cropping seasons. 85 Sub-samples of vegetative and tuber biomass were analyzed for their nutrient content (Table 3.12) from which and the nutrient uptake by the crop was determined. Results are shown in table 3.10 and 3.11. There was significant difference in nutrient uptake between FP and SC treatments in both the biomass and tubers for both cropping seasons. The FP treatment had considerable high level of nutrients than SC treatment and this was reflected in both the crop growth and yield. Low plant nutrient levels obtained was due to the drastic reduction in the nutrient level in the soil after the topsoil was removed. A considerable amount of N, K and Ca were taken up in the vegetative biomass particularly under FP treatment and as well as small quantities of P and Mg. The removal of tubers during harvest resulted in removal of N and K from the soil and these needs to be replaced by fertilizer and amendments to sustain crop growth and yield. Treatment Vegetative Nutrient uptake Biomass N PK Ca Mg Na -1____ -kg ha ------— Farmers Practice 4600 155.7 7.8 141.3 37.5 19.7 5.9 Scalped 200 5.5 0.3 6.3 1.3 0.5 0.8 LSD (0.05) 248.4 14.7 1.1 99.3 6.7 10.3 1.4 (a) Treatment Tuber Nutrient uptake N P K Ca Mg Na -kg ha Farmers Practice 2600 18.3 1.6 21 2.3 1.5 0.7 Scalped 100 0.4 0.1 0.8 0.1 0.05 0.1 LSD (0.05) 470.2 1.2 0.4 2.6 0.6 0.5 0.5 (b) Table 3.10: Nutrient uptake by (a) vegetative biomass and (b) tuber for FP and SC treatments for the first crop. 86 Treatment Vegetative Nutrient uptake Biomass N P K Ca Mg Na —kg ha'^— —------Farmers Practice 1200 32.8 1.6 16.2 7.1 3.6 20.9 Scalped 400 10.3 0.4 10.1 1.9 0.7 11.6 LSD (0.05) 430.3 4 0.3 NS 1.7 0.7 1.7 (a) Treatment Tuber Nutrient uptake N P K Ca Mg Na -Kg na Farmers Practice 200 1.2 0.9 7.8 1.6 0.9 0.3 Scalped 40 0.3 0 0.5 0.1 0 0.01 LSD (0.05) 74.5 0.2 0.3 0.7 0.3 0.2 NS (b) Table 3.11: Nutrient uptake by (a) vegetative biomass and (b) tuber for FP and SC treatments for the second crop. Treatment Nutrient content NK Ca Mg g kg q- Farmers Practice 7.1 0.6 8.1 0.9 0.6 Scalped 4.0 0.4 7.9 0.7 0.5 LSD(O.OS) 0.3 0.1 1.0 0.1 NS Table 3.12: Nutrient content in sweet potato tubers harvested during the first crop 87 3.3.4 Relationship between soil properties and crop yield The relationship was established through regression analysis between selected soil properties as independent variables and crop yield as dependent variable. Figures 3.7 to 3.9 showed the relationship between crop yield and SOC content, total N and available P. Table 3.12 showed other linear relationships between soil properties and crop yield. There was no significant relationship between soil physical properties and crop yield, except that with total porosity. In contrast, there was significant relationship between soil chemical properties and crop yield. 88 R^ = 0.70* Y =-1.06+ 0.13 (SOC) 3.0 2.5 -- o Actual Yield ■ Predicted Yield 2.0 -- es 00 s 1.5 -f 1.0 -- 0.5 -- o o 0.0 -og±P 10 20 30 SOC Content (g kg '^) Figure 3.7: linear relationship between crop yield and SOC content 89 R^ = 0.76* Y = -2.4 -1- 0.97 (N) o Actual Yield o ■ Predicted Yield o 2.5 -- o 2 -- ■ Æes ■ CJO ■ ê 1-5 2 / o :1 1 0 1 2 3 4 5 - 1, Total N (g kg ) Figure 3.8: Linear relationship between crop yield and total N 90 =0.92* Y= -1.67+0.18 (P) o Aîtual'Vîeld 2.5 - ■ Predicted MeW 2 - * *-GCQ CO S 1.5 12o 0.5 A Ô o$o 10 15 20 25 30 -K Available P (tqg kg ) Figure 3.9: linear relationship between crop yield and available P 91 The decline in the sweet potato yield may be due to the depletion of SOC and reduction in plant nutrients (e.g. N, P, K) and CEC. Changes in soil physical properties did not have any significant effect on the sweet potato yield. Regression Equation RZ Y = -1.06+ 0.13 (SOC) 0.70* Y =-10.2+2.26(MWD) 0.58 NS Y = -2.36+ 109.3 (AWC) 0.16 NS Y = 9.10 - 9.56 (Bulk density) 0.41NS Y = 31.5-0.52 (Clay) 0.33NS Y = -9.96 + 18.8 (Porosity) 0.70* Y = -13.44 + 0.09 (Infiltration) 0.59 NS Y = 8.10- 1.33 (pH) 0.06NS Y = -1.67+ 0.18 (P) 0.92* Y = -2.4 + 0.97 (N) 0.76* Y = -2.64 +20.55 (K) 0.95* Y = -4.28 + 0.35 (CEC) 0.96* NS = Not Significant Significant at P = 0.05, SOC = Soil organic carbon, MWD = Mean weight diameter, AWC = Available water capacity, P = Phosphorus, N = Nitrogen, K = Potassium, CEC = Cation exchange capacity Table 3.12: Linear relationship between soil properties and sweet potato yield 92 3.3.5 Cumulative soil quality index Weighting factors for ten relevant soil quality indicators were combined into a cumulative soil quality index as shown in table 3.23. for all three treatments. The NF treatment showed the lowest cumulative index, followed by FP treatment and then SC treatment. The maximum value of the cumulative index based on ten factors is 50 and the lowest is 10 (Lai, 1994). The high value indicate that the soil quality is poor or have extremely severe limitations while the low value indicate good soil quality. The relationship between cumulative index and sustainability were then established according to procedure proposed by Lai (1994) which showed that the NF treatment was sustainable, FP treatment sustainable with high input and SC sustainable with another land use. Soil Properties Weighting factors NF FP SC NF FP SC Effective rooting depth (cm) >150 >150 >150 1 1 1 Soil bulk density (Mg m^) 0.66 0.75 0.86 1 1 1 Soil Structure - WSA (%) 89.7 86.7 59 1 1 2 Texture Clay Clay Clay 3 3 3 loam loam loam Available water capacity(v/v) 0.3 0.4 0.3 5 5 5 Nutrient status 3 4 5 Acidity (pH) 4.3 4.3 4.5 5 5 5 Exchangeable A1 (% of CEC) 0.6 0.6 2.4 1 1 1 Soil organic carbon (%) 6.6 4.3 0.8 1 2 4 Soil Erosion (Mg ha yr “') 0-5 10-20 >100 1 3 5 Cumulative rating index 22 26 32 Table 3.14: Cumulative rating index developed for the three land use practices. 93 The weighting factors for ten soil properties for both FP and SC treatments were regressed against the sweet potato yield to as shown in figure 3.10. A significant relationship exist between weighting factors or soil quality and crop yield for the SC treatment. Crop yield decreased as the weighting factors increased. Increase in weighting factors firom 1 to 5 indicate poor soil quality. r2 = 0.40* Y = 2.4- 0.5 (WF) 3 o o O Actual Yield 2.5 ■ Predicted Yield S 1.5 (L> 1 0.5 + 0 0 2 4 Weighting Factor (1-5) Figure 3.10: Linear relationship between weighting factors (soil quality) and crop yield 94 The result obtained from the cumulative rating index confirmed that the current farmer’s practice (FP) on sloping lands in Solomon Islands is currently unsustainable unless there is additional high input into the system. Identification of the appropriate, acceptable and affordable inputs are very important. Inputs such as use the crop vegetative biomass as mulch after harvest, vegetative hedgerows to reduce soil erosion and use of its vegetative material for mulch and nutrient cycling, inter-cropping and crop rotation with legumes and fertilizer use are some of the options. 3.4 Conclusions The data obtained in this study showed that cultivation and topsoil loss had significant effect on soil physical properties such as saturated hydraulic conductivity, bulk density, texture, and structure. It impacts texture and soil structure through changes in particle size fractions, percent water stable aggregates and MWD. Although other soil physical properties like available water capacity, infiltration rate, and porosity were not significantly affected the general trend was that the SC treatment in which the topsoil was removed showed low values for these soil physical parameters compared to NF and FP. Soil chemical properties (e.g., SOC, N, P, K, exchangeable cations and CEC) were all significantly affected by land use and management. The data also showed that the changes in soil chemical properties had more significant effect on the sweet potato yield compared to soil physical properties. The sweet potato yield was low for the SC treatment, which had significant reductions in S O C ,N ,P ,K and CEC. 95 After two sweet potato crops under the current farmers practice, yield was drastically reduced along with changes in soil chemical properties and physical properties. Such changes in soil properties impacts soil quality which made the current farmers practice unsustainable without high input. This highlights the need to identify cropping systems that are sustainable for sloping lands in Solomon islands. 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Follet, (ed.) Soil Erosion and Crop Productivity. Soil Sci. Soc. Am. WI, USA. Yoder, R E . 1936. A direct method of aggregate analysis and a study of the physical nature of erosion losses. J. Am. Soc. Agron. 28:337-351. Youker, R.E. and J.L. McGuiness. 1956. A short method of obtaining mean weight diameter values of aggregate analysis of soils. Soil Sci. 83:291-294. 100 CHAPTER 4 TILLAGE AND LANDUSE EFFECTS ON SOIL MICROPOROSITY IN OHIO, USA AND KOLOMBANGARA, SOLOMON ISLANDS 4.1 Introduction Porosity refers to the voids between particles and structural units of a soil. The size and distribution of these voids, particularly of those between particles or between structural units, are important to plant growth because they affect the storage and movement of water and gases, and root growth. Presence of transmission pores or elongated and continuous pores (pores ranging from 50-500 pm) is important in soil/plant relationship, because they indicate good soil structure (Pagliai et al., 1984). Quantitative information about the amount, size, configuration or distribution of the pore spaces is more important in characterizing the soil as medium for plant growth or other uses than the particle size distribution (Danielson and Sutherland, 1986). Soil structure is preferably defined in terms of its functional attributes comprising soil porosity and pore size distribution (Lawrence, 1977; Greenland, 1977). Ringrose-Voase and Bullock (1984) and Pagliai et al. (1984) also reported that porosity and pore size distribution are the best indicators of soil structure, because the size, shape and continuity of pores affect important soil processes. Thus adverse effects on soil structure can be recognized by 101 quantifying reduction in the proportion of transmission pores (Pagliai et al., 1995). The porosity and pore size distribution are easily influenced by practices such as cultivation or tillage , loss of topsoil through soil erosion, and crop residue management. Intensive tillage in some agricultural soils often results in deterioration of soil structure, and decrease in crop yields ( Cotching et al., 1979; Pagliai et al., 1995). Tillage-induced changes in soil structure affect porosity and pore size distribution (Lawrence, 1977; Ringrose-Voase & Bullock, 1984). Comparative effect of tillage methods on pore size distribution have been reported for some soils in Italy (Pagliai et al., 1983; 1984; 1995), New Zealand (Francis et al., 1987; Hermavan and Cameron, 1993), Australia (Chan, 1982), Canada (Shipitalo and Protz, 1987) and USA (Mahboubi et al., 1993; Lai et al., 1994). However soil-specific information is needed to assess sustainability of land use and soil management practices. Thus the objectives of this study were to evaluate the effects of land use change and tillage systems on soil stmcture through assessment of porosity and pore size distribution of soil aggregates using the mercury intrusion method. 102 4.2 Materials and Methods 4.2.1 Site Description This study was conducted on soil samples collected from long-term tillage experiments established on two predominant soils in central Ohio, USA. Tillage experiments are sited at Wooster (40.5° lat., 82° long.) and South Charleston (39.8° lat., 84° long.) (Figure 4.1). The soils and experimental layout at both sites have been described in detail by Dick et al. (1986), Mahboubi et al. (1993), Lai et al. (1994), and Bajracharya et al. (1997). The soil at Wooster site is classified as Wooster silt loam, (fine-loamy, mixed, mesic Typic Fragiudalf). The Wooster silt loam has a deep, well drained profile and is developed from glacial tilth. The soil at South Charleston site is a Crosby silt loam (a fine, mixed, mesic Aerie Orchraqualf). The surface layer 0-22 cm layer is greyish brown (10 YR 4/2) silt loam and is of weakly massive structure breaking up- into weak, coarse granular aggregates. The 22 to 28 cm layer is distinctly mottled silt loam with fine subangular blocky structure. The experimental site in Solomon Islands is located at Ringgi Cove on Kolombangara Island (lat. 8° lat., 157° long.). Kolombangara is located within the New Georgia group of islands and they lie at the north-western extreme to the south of the main limb that forms the long chain of islands forming the Solomon Islands archipelago (Figure I.l, Chapter I). The soil at Ringgi site is classified as Haplorthox, belonging to the soil order Oxisol. It was developed over andesitic and basaltic lava. Mineralogical examination showed that many clays are rich in bauxite. The soil texture is clay loam. Physically the 103 soil is deep, well drained and aggregated despite low organic matter content. Tine aggregation is due to presence of high amounts of iron and aluminum oxides which gives the soil it’s brownish to reddish color (Hansell and Wall, 1975). Wooster 0 South Charleston Figure 4.1 Location of experimental sites at Wooster and South Charleston, Ohio 104 4.2.2 Experimental Design There were three tillage treatments at both Wooster and South Charleston sites namely, no-till (NT), chisel plow (CP) and molboard plow (MP). The MP treatments at both sites involved complete soil inversion and residue incorporation to 20cm depth. The CP treatment involved chisel plowing to a depth o f about 30cm, while crops in NT were planted directly through the previous crop residue. All three treatments were replicated four times in a randomized block design. There were a total of 12 plots at each site. Plots at Wooster (Slopes 2.5-2.4 percent) were 8.4 by 37 m, and those at South Charleston (slope 1 percent) were 5 by 61 m. Soil samples were obtained from plots grown to continuous com (Zen mays) since 1958. Com is planted at a distance of 7 cm within rows. The experimental trial in Solomon Islands consists of three treatments with three replications in a randomized complete block design. The treatments are: (1) undisturbed soil under natural forest (NF) with no visible signs of soil erosion, (2) farmers practice (FP), with two sweet potato (Jpomoea batatas) crops followed by one year fallow. The sweet potato was planted up and down the slope on mounds at 1 m interval after the vegetation was slashed and bumt and (3) Scalped (SC) where topsoil (0-15 cm depth) was de-surfaced following which two sweet potato crops were grown followed by one year fallow. The topsoil was manually removed after vegetation was slashed and bumt. 4.2.3 Soil Sampling Bulk clod samples were collected from each plot at aU three sites and composited. Clod samples were obtained from 0-10 cm and 10-20 cm depths in all three treatments at Wooster and South Charleston. In the NT plots, clod samples were separately obtained 105 from the traffic zone (TZ) and row zone (R2^ at Wooster and South Charleston. Samples were obtained during spring 1997 just before com was sown. At Kolombangara, samples were obtained at 0-15 cm and 15 —30 cm depth in April 2000. Soil aggregates were obtained from the clods and were air dried before storage. The aggregates were oven dried prior to analyses for porosity and pore size distribution. 4.2.4 Determination of porosity and pore size distribution Oven dry aggregates of about 2 cm^ were used to monitor porosity and pore size distribution using the Autoscan Porosimeter. Only the microporosity in the aggregates were determined and not the total porosity of the whole soil. The Autoscan 500 mercury (Hg) porosimeter is manufactured and supplied by Quantachrome corporation, Florida USA . It operates on the principle that mercury is forced under pressure into a porous material or powdered sample placed in a sample cell. The applied pressure is increased in discrete steps and the volume of pores intmded between steps is obtained. This particular instrument is used mainly in the medical field of pharmaceutics to determine pores in powdered samples. It, however, can also be used to determine pores in any porous material. In this study, micro-porosity and pore size distributions within 2 cm ^ size aggregates were measured by forcing Hg into oven dry and evacuated soil aggregate placed in a sample cell. The micro-porosity and pore size distribution were determined from the range of pore radius obtained at different pressures. The range of pressure applied was around 13.8 kPa to 3450 kPa. The pore radius into which mercury was 106 intruded in a sample aggregate as a function of pressure was calculated using the Washburn Equation (Eq 4.1), (Quantachrome Corporation, 1996), P r = -2y cos © ------(eq. 4.1) where P is pressure (kPa), r is radius (pm), y is surface tension of mercury (erg cm*^), cos 0 is contact angle (degrees). The data were analysed using a factorial analysis for the two factors, treatment and site (location) using “MSTAT” version 2.0 statistical computer package (Fred, 1991). The Median pore radius for each soil aggregate was computed, corresponding to the radius at which about 50% of the pores are full of Hg. Table 4.1 show a typical data reduction output after each analysis. The values 0.7 (bold) shows the median pore radius at 51.48 percent. The peak pore radius or maximum pore radius was also determined from the data output. It is the pore radius at the point where the rate of change in volume of Hg intruded over the rate of change in pressure applied was at its maximum, as is shown in Figure 4.1. The volume of different pore categories were determined according to pore classification by Greenland (1977) which include transmission pores (50 —500 pm), storage pores (0.5-50 pm) and residual pores (0.5-0.005pm). 107 Pressure Pore Intruded Volume Pressure Pore Intruded Volume Radius Volume Intruded Radius Volume Intruded kPa |im cm^ % kPa lun cm^ g'l % 10.08 74.07 0.00 0.54 880.18 0.85 0.03 39.13 32.20 23.19 0.00 2.07 934.85 0.80 0.03 42.70 56.35 13.25 0.00 4.07 994.56 0.75 0.03 46.63 80.71 9.25 0.00 4.96 1072.89 0.70 0.04 $1.48 107.10 6.97 0.00 5.75 1153.11 0.65 0.04 56.16 134.89 5.54 0.00 6.39 1232.84 0.61 0.04 60.19 163.45 4.57 0.01 7.10 1311.73 0.57 0.05 63.69 192.15 3.89 0.01 7.60 1390.13 0.54 0.05 67.01 220.85 3.38 0.01 8.28 1472.80 0.51 0.05 69.90 249.34 2.99 0.01 8.85 1574.93 0.47 0.05 73.19 277.90 2.69 0.01 9.57 1675.94 0.45 0.05 75.97 306.46 2.44 0.01 10.21 1776.46 0.42 0.06 78.54 334.95 2.23 0.01 10.85 1883.91 0.40 0.06 80.90 363.51 2.05 0.01 11.64 2003.89 0.37 0.06 83.29 391.86 1.91 0.01 12.57 2121.07 0.35 0.06 85.40 420.35 1.78 0.01 13.39 2246.37 0.33 0.06 87.47 448.77 1.66 0.01 14.42 2378.81 0.31 0.06 89.40 488.88 1.53 0.01 16.07 2515.94 0.30 0.07 91.29 545.37 1.37 0.01 18.74 2657.83 0.28 0.07 93.07 602.07 1.24 0.02 21.78 2808.54 0.27 0.07 94.47 658.00 1.13 0.02 24.99 2967.09 0.25 0.07 96.04 714.14 1.05 0.02 27.95 3132.01 0.24 0.07 97.39 769.72 0.97 0.02 31.42 3303.93 0.23 0.07 99.00 824.95 0.91 0.03 35.24 3482.92 0.21 0.07 100.00 Table 4.1 Sample of data reduction output from the Autoscan porosimeter. 108 5.00E-04 4.50E-04 - 4.00E-04 £• 3.50E-04 I 3.00E-04 a.i -S 2.50E-04 I ^ 2.00E-04 = U 1.50E-04 l.OOE-04 5.00E-05 O.OOE+00 10 20 30 40 50 60 70 80 Pore radius (microns) Figure 4.2: Graph showing the peak pore radius 109 4.3 Results and Discussion There was a significant difference (P = 0.05) in median pore radius between NT and other treatments at Wooster but not at South Charleston (Table 4.2a). The median pore radius for the NT treatment at Wooster was significantly higher than other tillage treatments for both depths. This shows that the NT treatment had some beneficial effect on pore size distribution and soil structure on the fine silt loam soil at Wooster. At Kolombagara, the NF soil has significantly higher median pore radius (18.6 pm and 17.9pm) at both depths than the SC treatment but not significantly different fi-om that of FP. There was also no significant difference between FP and SC treatments (Table 4.2b). Cultivation and topsoil loss can therefore reduce the median pore radius, which is an indication of decline in soil structure. No significant difference among tillage treatments was observed in the peak pore radius (9.2 - 41.5 pm) (e.g., peak rate of change in volume over rate of change in pressure) in 0-20 cm depth at either of the two sites at Ohio (Table 4.3a). The peak pore radius was highest (16.4 - 41.5 pm) for MP treatment but the values are not statistically different from the other treatments. The NF has significantly higher peak pore radius at Kolombangara than the FP and SC treatments in the top 15 cm depth but not significantly different firom FP in the 15-30 cm depth (Table 4.3b). The SC was significantly lower than NF at both depths. The low median and peak pore radius observed under SC suggest that removal of the topsoil impacted soil structure especially in the subsoil. 110 Tillage method Wooster South Charleston 0-10cm 10-20cm 0-10cm 10-20cm Moldboard plow 0.7 0.7 0.8 0.5 Chisel plow 0.7 0.7 0.7 0.6 No-till (TZ) 1.4 1 1.6 0.8 No-till (RZ) 1.4 1.1 1.2 0.8 LSD (0.05) 0.24 0.22 NS NS (a) NS = not significant TZ = Tractor zone RZ = Row zone Land use Kolombangara 0-15cm 15-3 0cm Natural forest 18.6 17.9 Farmers Practice 14.0 13.6 Scalped 11.2 9.2 LSD (0.05) 5.4 5.9 (b) Table 4.2: Median pore radius under different treatments (a) at Wooster and South Charleston and (b) at Kolombangara. I ll Tillage method Wooster South Charleston 0-10cm 10-20cm 0-10cm 10-20cm Moldboard plow 20 16.4 41.5 22.5 Chisel plow 21.5 9.2 23.8 12.9 No-till (TZ) 14.3 20.5 14.3 17 No-till (RZ) 14.8 15.5 17.5 20.8 LSD (0.05) NS NS NSNS (a) NS = not significant TZ = Tractor zone RZ = Row zone Land use Kolombangara 0-15cm 15-30cm ------gm------Natural forest 27.3 19.7 Farmers Practice 18.3 20.7 Scalped 18.3 13 LSD (0.05) 4.1 4.9 (b) Table 4.3: Peak or maximum pore radius under different treatments (a) at Wooster and South Charleston and (b) at Kolombangara. 112 There was no significant difference (P = 0.05) among treatments in the volume of different pore categories at 0-20 cm depth. Although they were not statistically different, the volume of storage pores was highest (0.112 cm^ g'^ and 0.124 cm^ g'^ at both depths respectively) for the NT compared to other tillage treatments. There was higher concentration of storage pores in the soil aggregates and very small to almost zero volume of transmission and residual pores as shown in figure 4.3. The aggregates contained 95 and 94 percent storage pores at both depths respectively. Although there was no treatment effect on the volume of pore size distribution in this study, the NT treatment showed some effect on storage and residual pores at both sites. This showed that NT improved pore size distribution compared to plow-till (PT). There was also no significant difference among the land use treatments in the volume of different pore categories at Kolombangara. The SC treatment however had low volume of pore sizes in the top 15cm depth but higher volume of storage pores at the 15- 30 cm depth (Figure 4.4). It did not have any transmission pores at 15-30cm depth. The was almost even distribution of storage and residual pores within the aggregates which was different fi*om the result obtained for the soils at Ohio which had higher concentration of storage pores. The observed difference could be due to the difference of intensity in cultivation and soil texture. 113 C5Û "I QJ I B ~ 3 8 > B 0.001 - g 0.0001 I TP SP RP TP SP RP 0-10 cm 10-20cm Pore Categories Figure 4.3: Tillage effect on mean volume of transmission pores (TP), storage pores (SP) and residual pores, as mean values for Wooster and South Charleston. 114 1 0 .0 0 0 0 1.0000 00 0.1000 3 0.0100 - 0.0010 - 0.0001 TP TP 0-15 cm 15-30 cm Pore Categones NF = Natural Forest, FP = Farmers Practice, SC = Scalped Figure 4.4: Land use effect on mean volume of transmission pores (TP), storage pores (SP) and residual pores for Kolombangara. 115 There was a significant difference in volume of both storage and residual pores between the two sites for 0-10 cm depth (Table 4.4). Volume of both storage and residual pores were higher for Wooster than South Charleston soil. No significant difference was observed for 10-20 cm depth. The observed difference in the volume of storage and residual pores between the two sites may be due to differences in soil texture. South Charleston soil has silt loam texture, which is a weakly massive structure breaking up- into weak, coarse granular aggregates. Tillage 0-10cm 10-20cm Method TP SP RP TP SP RP -cm^ g*‘— Wooster 0.002 0.113 0.004 0.001 0.10 0.007 S.Charleston 0.001 0.073 0.002 0.001 0.06 0.002 LSD (0.05) NS * * NS NS NS Table 4.4: Site effect on mean volume of transmission pores (TP), storage pores (SP) and residual pores for Wooster and South Charleston. 116 The reduction in the volume of both storage and residual pores under long-term PT treatments may be an indication of degradation of soil structure and reduction in aggregate stability. In a similar study, Pagliai et al. (1984), reported that there was a reduction in number of transmission pores with regular shape in the PT treatments within 7-10 cm depth. Similarly, Naohiro et al. (1994) observed that the pore size range between 20 -110 pm was greatly reduced within a compacted soil layer at 30 cm under PT treatments. These data are contrary to those of Pagliai et al. (1995), who reported increase in transmission pores and no significant change in storage pores under minimum tillage (MT) than PT treatment. Differences due to tillage treatment may be due to difference in soil texture and in methods used to determine the pore size distribution. For a silty loam soil, Hermavan and Cameron ( 1993) found that the volume of transmission pores was greater in the PT than MT or NT plots particularly in the 5-20 cm depth. It is likely that tillage-induced changes in pore size distribution may occur more in heavy-textured than in light or medium- textured soils. In this study, the result showed that there was no significant difference in the volume of three pore categories between tillage treatments but there were significant difference in volume of storage and residual pores between the sites. This showed that soil texture may have influenced the pore size distribution. Soil texture is silt loam (fine-loamy) for Wooster soil which is developed firom glacial tilth. 117 Porosity within the soil aggregates was significantly higher under NT and MP treatments at Wooster in the 0-20 cm depth but not at South Charleston (Table 4.5). Pagliai et al. (1983) observed that porosity was significantly higher in aggregates sampled from PT treatment than those from NT plots, but a year later they found that the total porosity decreased in the PT treatment while no change occurred in the NT. This differential response suggest that PT treatment caused some significant impact on porosity. The result obtained from this study are in agreement with this report, and the effect was more evident for the Wooster soil which is fine silt and loamy in texture. The pore size range within the aggregates was the widest (0.2pm -100pm) in NT and nonwide under MP for 10-20 cm depth for the South Charleston soil There was no significant difference in porosity between the three land use practices at Kolombangara but both the porosity and pore radius range were highest in the topsoil under the Natural forest treatment (Table 4.5b). These data suggest that the soil is well structured under natural forest. Cultivation and topsoil removal led to decline in soil structure. 118 Wooster South Charleston Tillage 0-10cm 10-20cm 0-10cm 10-20cm Method Pore radius Pore radius Pore radius Pore radius Range / Range / Range / Range / pm pm pm pm MP 0.2-64 0.16 0.2-51 0.25 0.2-64 0.33 0.2-52 0.22 CP 0.2-62 0.13 0.2-47 0.20 0.2-56 0.26 0.2-59 0.37 No-till (TZ) 0.2-70 0.14 0.2-60 0.26 0.2-23 0.23 0.2-57 0.43 No-till (RZ) 0.2-95 0.14 0.2-49 0.24 0.2-38 0.36 0.2-100 0.30 LSD (0.05) 0.01 0.02 NS NS (a) NS = not significant TZ = Tractorzone RZ = Rowzone MP=Mcldboard plow CP=ChiseI plow / = Micro- porosity 0-15cm 15-3 0cm Land use Pore radius Pore radius Range / Range / pm pm NF 0.2-50 0.27 0.2-35 0.18 FP 0.2-36 0.26 0.2-32 0.13 SC 0.2-33 0.22 0.2-22 0.12 LSD (0.05) Ns Ns (b) NF=NaturaI forest FP=Farmers Practice SC=ScaIp Table 4.5: Pore radius range and micro-porosity in soil aggregates at (a) Wooster and South Charleston and (b) Kolombangara 119 4.4 Conclusions The intra-aggregate pore size ranged from 0.2 to 100 pm. No significant difference among tillage treatments was observed in the peak radius (9.2-41.5pm) of pores in 0-20 cm depth at either of the two sites. However the median pore radius was significantly (P = 0.05) larger in NT than other tillage treatments at Wooster but not at South Charleston. The NT treatment had median pore radius of 1.4 pm compared with 0.7pm in MP and CP treatments for the Wooster soil. There was also not a significant difference among tillage treatments in the volume of three pore size categories for 0-20 cm depth, but there a was significant difference in volume of both storage and residual pores in 0-10 cm depth between both sites. Total porosity within soil aggregates was significantly higher under NT and MP treatment at Wooster in the 0-20 cm depth but not at South Charleston. It can therefore be concluded that the NT treatment caused some beneficial effect on porosity, pore size distribution and soil structure in the fine loamy silt soil at Wooster than in the crosby silt soil at South Charleston. At Kolombangara, the NF treatment had significantly higher median pore radius, peak pore radius and total porosity. There was however no significant difference among treatments in the pore size distribution. Conversion of natural forest soil to cropland and subsequent topsoil loss especially on sloping lands had the potential to cause reduction in total porosity, an indication of loss of soil structure. 120 REFERENCES Bajracharya, R.M., R. Lai, and J.M. Kimble. 1997. Long-Term tillage effects on soil organic carbon distribution in aggregates and primary particle fractions of two Ohio soils. In R. Lai et al. (ed.) Management of Carbon Sequestration in Soil. CRC Press LLC. Chan K Y. 1982. Shrinkage characteristics of soil clods from a grey clay under intensive cultivation. Austr. J. Soil Res. 26:509-518. Cotching, W.E., R.F. Allbrookk and H.S. Gibbs. 1979. Influence of maize cropping on the stmcture of two soils in the Waikato district. New Zealand. New Zealand LAgric. Res. 22:431:438. Danielson, R.E; and P.L. Sutherland. 1986. Porosity. p443-460. In A. Klute (ed.) Method of Soil Analysis; Part 1. Physical and Mineralogical methods, 2nd Edition. Monograph no.9 ASA and SSSA, Madison, WI. Dick, W.A., D.M. Van Doren, Jr., G. B. Triplett, Jr., and J. E. Henry. 1986. Influence of long-term tillage and rotation combination on crop yields and selected parameters, n. Results obtained for a Typic Fragiudalf soil. Res. Bull. 1181. Ohio Agric. Res. Dev. Cent., Wooster, OH. Francis, G.S, K.C. Cameron and R.S.Swifr. 1987. Soil physical condition after six years of direct drilling or conventional cultivation on a silt loam soil in New Zealand. Austr. J. Soil Res. 26:637-649 Fred, R. F. 1991. Mstat microcomputer statistical program. Michigan State University. Greenland D. J. 1977. Soil management and soil degradation. J. Soil Sci.32: 301-322 Hansell, J. R. F., and Wall, J. R. D. 1975. Land resources of Solomon Islands, Vol. 4. New Georgia Group and the Russell Islands. Land Resources Study 18. Land Resources Division, Surrey, England Hermavan, B., and K.C.Cameron. 1993. Structural changes in a silt loam under long term conventional or minimum tillage. Soil Tillage & Res. 26:139-150 121 Lai, R., A.A. Mahboubi, and N.R. Faussey. 1994. Long-term tillage and rotation effects on properties of a central Ohio soil. Soil Sci. Soc. Amer. J. 58:517-522 Lawrence, G.P. 1977. Measurement of pore size in fine textured soils: A review of existing techniques. J. Soil Sci. 28:527-540 Mahboubi, A. A., Lai, R., NJR.. Faussey. 1993. Twenty-eight years o f tillage effects on two soils in Ohio. Soil Sci. Soc. Amer.J. 57:506-512 Naohiro, M., R. Msoni, and K. Kyuma. 1994. Changes in microstructure of surface soil through a slope. Soil Sci. & Plant Nutr., 40 (3): 457-470 Pagliai, M., M. La-Marca, and G. Lucamante. 1983. Micromorphometric and miromorphological investigations of a clay loam soil in viticulture under zero and conventional tillage. J. Soil Sci. 34:391-403 Pagliai, M., M. La-Marca, G. Lucamante, and L. Genovese. 1984. Effect of zero and conventional tillage on the length and irregularity of elongated pores in a clay loam soil under viticulture. Soil & Tillage Res. 4:433-444 Pagliai, M., M. Raglione, T. Panini, M. Maletta, and M.La-Marca. 1995. The stmcture of two alluvial soils in Italy after 10 years of conventional and minimum tillage. Soil & Tillage Res. 34:209-223 Quantachrome Corporation. 1996. Autoscan porosimeter data acquisition board and poro2pc data reduction software. Brynton Beach, FL. Ringrose-Voase, A. J., and P.Bullock. 1984. The automatic recognition and measurement of soil pore types by image analysis and computer programs. J. Soil Sci., 35:673- 684. Shipitalo, M. J., and R. Protz. 1987. Comparison of morphology and porosity of a soil under conventional and zero tillage. Can. J. Soil Sci., 67:445-456. 122 CHAPTER 5 EVALUATION OF THE POTENTIAL OF VEGETATIVE BARRIERS TO REDUCE RUNOFF ON SLOPING LANDS ON KOLOMBANGARA, SOLOMON ISLANDS 5.1 Introduction Despite the large global volume of literature on soil erosion (Lai 1998), there is hardly any data on soil erosion and its impact on soil quality and crop productivity for Solomon Islands. The only published reports on soil erosion were those by Hansell and Wall (1970), Webb (1974), Wall et al. (1979), Stephens et al. (1986) and Eyles (1987). Although these reports are qualitative, they highlighted the potential threat from soil erosion and land degradation on sloping lands in the coimtry. The startling evidence of land degradation was brought into focus by rural farmers seeking help in the northern part of the island of Malaita. In the district of Fouia, people farm in the realization that their hillsides are broken and soils laid open to waste (Cheatle, 1988). This and other communities need help in identifying appropriate soil conservation and sustainable cropping systems for their marginal sloping lands. Sloping or steeplands, with a slope gradient of 20 percent or more (Lai, 1990), comprise about 63 percent of the total land area (27000km^) of Solomon Islands. The widespread practice of slash-and-bum agriculture, with rapid encroachment on steeper 123 and forested lands, is unsustainable and the cause for widespread soil erosion, loss of soil fertility, and land degradation. Despite lack of quantitative data on soil erosion in Solomon Islands, erosion rates observed in neighboring South Pacific countries which share similar climate, soil and land use (section 1.7, chapter 1) are high. Reported soil erosion rates are in the range of 10 to 300 Mg ha'^ yr"' (Morrison, 1981; Liedtke, 1984; Clarke and Morrison, 1987; Liedtke, 1988; Williams et al., 1981; Wood, 1984; Humphreys, 1984; Carman, 1989; Humphreys and Wayi, 1990; Sillitoe, 1993; Konabe 1996; Pratap, 1994) in Fiji, Papua New Guinea (PNG), Vanuatu and Western Samoa. The impact of erosion on soil quality and crop productivity is therefore a major problem leading to food insecurity. Subsistence food production is the only means of livelihood of 85% of the country’s 400,000 inhabitants, and this calls for a need to practice some form of conservation measures while attempts to develop management practices to maintain crop yield on eroded sites continues. There is a need for emphasis upon investigations and development of conservation system, which will provide soil conservation of practical utility to resource poor farmers. In consideration of this, use of vegetative barriers as a means of controlling and reducing runoff and soil loss becomes appropriate. The rationale for undertaking this study is therefore to develop cropping practices utilizing vegetative barriers to control and reduce runoff and soil erosion on the steep slopes. The specific objective of the study is to evaluate the potential of different vegetative barriers in controlling runoff compared to the current farmers practice. The hypotheses are evaluated were: (l)current sloping land cultivation (farmers practice) contribute to high runoff volume leading to high soil loss, and (2) use of vegetative barriers reduces runoff amount. 124 5.2 Materials and Methods 5.2.1 Site Description Detail description of the experimental site is given in section 1.8 of Chapter 1. A detailed contour survey was carried out prior to establishment o f the runoff plots (Figure 5.1). Logging roads and former skid tracks are still visible on the ground surface. The area was logged about 30 years ago by Levers Pacific Timber limited (LPTL) and was under secondary forest when the trial was established. Due to uneven topography, both east and west slopes were used for the trial plots together with instrumentation measuring runoff. 125 | T , '|T J |T|. I Figure 5.1: Map of experimental site showing the contours at 10 m interval with runoff plots (not to scale) marked as rectangles 126 5.2.2 Experimental Design The experiment consisted of 12 runoff plots each measuring 20 x 10m, in a randomized complete block design with three replications. It was designed to quantify and compare surface runoff under three different vegetative barrier treatments and the traditional farmer practice (FP). The vegetative barriers used perceived to have the potential to control and reduce runoff and subsequently soil loss, maintain soil fertility and produce food and cash crop. Excess vegetative growth from the barriers were pruned on regular basis and added as mulch for nutrient cycling. The aim of the study was to test whether three different vegetative barriers or hedgerows can effectively control or reduce runoff amount, and better maintain soil fertility than the FP without vegetative barrier. Four treatments studied were: (1) The FP included growing two sweet potato (Ipomoea batatas) crops established on an eroded soil followed by one-year of fallow. The sweet potato was planted up and down slope on mound at 1-m interval after the vegetation was slashed and burnt in situ, (2) Banana {Musa nand) and Heliconia {Heliconia bihai ) vegetative hedgerows were planted at 9-m intervals and two crops in sweet potato were grown, (3) Pineapple Ananas( comosis ) hedgerows planted at 9-m intervals in double rows and sweet potato were grown in the alley space, and (4) Westem cabbage {Polycias gradiflora) hedgerow were planted at 9-m intervals in double rows, and sweet potato crop were grown in the alleys. 5.2.3 Plot Layout and Construction A total of 12 runoff plots were installed on both eastern and westem slopes. They were aligned so as to have as uniform slope and aspect as possible. The plot area was 127 inspected and mapped before plot construction. The plots had concrete runoff collecting trough that spanned the entire width towards the downstream side and kept in place with concrete slabs. The slabs provided support for the tipping bucket, steel manifold, and splitter sampler (Plate 5.1). Plate 5.1: The runoff collection setup showing concrete trough, manifold and tipping bucket. Vegetative hedgerows were established using three plant species, and the resulting alleyways were 9-m wide with an average slope of around 35 percent. Each plot was bordered on the top and sides with 0.1m high steel sheeting. Another open drain was 128 dug across the top of each plot above the border to divert runoff away from the plot. The sweet potato crop was planted on mounds with center to center spacing of 1-m. The mounds were made by scraping and heaping the top soil from the 1 m^ frame. A total of four sweet potato vines, each 30cm long, were planted on every mound. 5.2.4 Instrumentation Instruments comprised of an automatic weather station (AWS), runoff collecting troughs, tipping bucket, tipping bucket counter and suspended sediment sampler. The AWS was installed at the experimental site to measure daily rainfall amount and short- time intensity. It is manufactured by "Monitor Sensors" at Caboolture, Australia. In standard configuration, it is supplied with sensors for rainfall, air temperature and solar radiation. The station is powered by a lead-acid gel battery, which is charged by a solar panel. It uses Windows-based software for downloading and processing data (Plate 5.2). 129 ■ Plate 5.2: The AWS at the experimental site at Ringgi. The tipping buckets were assembled prior to installation, including fitting of counters and splitter samplers. They were constructed with a piece of thin metal with volumes of 9-litre per side to service a plot area of 200m^ (assuming a 0.9 coefficient of runoff and rainfall intensity of 300mm hr’'). They were fixed to the concrete mounting slab with screws and "rawl" plugs. A suitable shade structure made from steel roofing was constructed over the buckets to protect them from direct sunlight. The counters installed on the buckets offered a good compromise between cost and performance. 130 5.2.5 Measurement of runoff Runoff from the plots was measured by automatic tipping buckets. A slotted manifold at the middle of the collecting trough distributed the water to the buckets under flow conditions. Most of the steel manifolds were assembled and sealed. The buckets were individually calibrated in situ. Each bucket capacity was 9-liters. Once the bucket is filled with nm off it tips, and the munber of tips are recorded on the automatic counter. The volume of runoff in liters was then converted to depth in millimeters. 5.3 Results and discussion 5.3.1 Rainfall characteristics The rainfall on Kolombangara has a bimodal distribution. Thus, there are two wet seasons, one at beginning/end of the year from December to March and the other in middle of the year from July to August. There are two dry periods in between the wet seasons, April to May, and September to November (Figure 1.3, chapter 1). The rainfall records during the study period are shown in figure 5.2. Monthly rainfall totals are high except for the months of February and March 2000, which were very dry months with 60 and 29 mm of rainfall respectively. This is very unusual, in fact the rainfall received were the lowest in 35 years of record on Kolombangara Island. Months of February and March are normally very wet. Annual average rainfall at the site is about 3000 mm. 131 Rainfell Runoff S 300 - 10.0 - 8.0 f 200 / V s 150 Vi - 2.0 1^ 1* I FMAMJ JASONDJFMA Month Figure 5.2: Monthly rainfall totals and average runoff from all treatments from February 1999 to April 2000. 5.3.2 Rainfall amount and distribution Daily rainfall amount and intensity were used to compute the frequency distribution in order to identify the erosive rainfall events. The rainfall intensity data were not collected in the year 2000, since it was recorded by the AWS which was not operational then. 132 Daily rainfall records showed that 85 percent of rain fell in events of <20mm over the two year period, 15 percent fell at >20 mm (Figure 5.3). There were no records of daily rainfall amount equal to or greater than 100mm. No major storm occurred during the study period. Normally such storms are associated with high daily rainfall amount in the range of 100 to 200 mm. The observed rainfall trends are similar to rainfall records in the neighboring South Pacific countries in the PACIFICLAND soil management network (IBSRAM, 1997). Daily rainfall records from Keravat (PNG), Lakura (Vanuatu), and Waibau (Fji) showed that 75 percent of rains fell in events of < 20 mm and 25 percent at >20mm. The maximum daily rainfall amount recorded at three sites as of 1997 were: 178 mm at Keravat, 391 mm and at Lakura, and 134 mm at Waibau. The maximum daily rainfall amount recorded at Ringgi during the two year period was 93 mm (June 99) which was lower than the records for the three countries of the region. The data of rainfall intensity distribution show a pattern similar to that of the rainfall amount. Low intensities (<20 mm hr ’’) were observed in 75 percent of rain events, whereas high intensities (>20 mm hr '^) were observed in 25 percent o f events within the 20 month period (Figure 5.4). 133 01998 01999 = 2000 50-100 Daily rainfall amount (mm) >100 Figure 5.3 Daily rainfall distribution at Ringgi from February 1999 to April 2000 134 01998 #1999 çr 30 5-10 10-20 2CMW 40-80^ go-160 >160 Rainfall intensity (mmhf ) ;,^h„tion at Ringgi experimental site 5 . 4 BainfalUntensity distribut'™ Figure 135 Similar rainfall intensity patterns were reported in Fiji, PNG, and Vanuatu. Low intensities (<20 mm hr '^) were obtained in 85 percent of rainfall events, where as high (>20 mm hr '*) intensities were observed in only 3 percent of events at Lakura in Vanuatu and Waibau in Fiji, and in 15 percent of events at Keravat, Papua New Guinea (IBSRAM, 1997). Maximum 6-minute rainfall intensities recorded at the three sites as of 1997 were: 109 mm hr at Keravat, 77 mm hr at Lakura, and 63 mm hr at Waibau. The maximum rainfall intensity recorded at Ringgi during the two year period was 125 mm hr (May 99), which is higher than the records for the three countries in the region. At Lakura site in Vanuatu, where soil loss is better related to rainfall intensity (r = 0.72,) soil loss was initiated at rainfall intensities in the range of 20-30 mm hr”'. This represents 25 percent of the rainfall intensity recorded at the Ringgi site. The rainfall intensity threshold of 25mm hr ' as suggested by Hudson (1971), is therefore within the observed intensity range which indicated that there was definitely some soil loss on the 35 percent slope at Ringgi. Humphreys (1984) found that soil erosion in PNG was more for 25 mm hr*' intensity than the 12 mm hr ' intensity. The correlation however was not strong on plots with vegetative cover which is likely to be the case in this study. Humphreys (1994) further pointed out that since some factors vary between plots and treatments this type of general relationship should only be undertaken for individual plots. 136 5.3.3 RimoÊF Runoff recorded over the 15-month period (February1999 to April 2000) is shown in Table 5.1 subdivided according to wet and dry seasons. Runoff amounts recorded during the first wet season (December 1999 to March 2000) were three times higher than those recorded during the dry season. This was due to high amount of rainfall (1386 mm) and the length of the wet season (5 months). There were however no difference between the runoff during the second wet season and the dry seasons. The second wet season only last for two months and the rainfall amount (592 mm) was almost similar to the amount (840 mm and 551 mm respectively) during the two dry seasons that lasted 3 months (Table 5.1 ). There was no significant difference in runoff between FP and the three vegetative barrier treatments but the lowest runoff amount was observed under FP (67.6 mm) and the highest (97.2mm) under the pineapple vegetative barrier. The FP treatment had low runoff amount due to the complete ground cover from the sweet potato vines. Other vegetative barriers had gaps within the barrier stands that remain open and thus runoff could take place. The observed value of 67.6 mm for FP was low in contrast to 116 mm for FP in PNG, where the site is located on a 11-22 percent slope with total rainfall amount of 1338 mm over the 19-month period (Konabe, 1996). Without surface cover runoff could be high. For example, Lai (1979), observed high runoff in the range of 25.5 mm to 316.5 mm on 15 percent slope under bare fallow treatment in Nigeria. The low runoff amount recorded in the present study could be due to the surface crop cover and high infiltration because of well-structured and well-drained soil at the site. 137 Treatment Wet season Dec-March July-August Total —Runoff (ram)------Farmers Practice 33.4 13.8 47.2 Banana/Heliconia 46.4 15.3 61.8 Pineapple 55.7 18.1 73.9 Western Cabbage 40.7 14.9 55.7 LSD (0.05) NSNS NS Rainfall (mm) 1386 592 1978 (a) Treatment Dry season April-June Sept.-Nov. Total Runoff (ram) Farmers Practice 10.3 13.2 23.5 Banana/Heliconia 12.4 15.9 28.3 Pineapple 12.1 20.7 32.8 Western Cabbage 14.2 15.2 29.4 LSD (0.05) NS NS NS Rainfall (ram) 840 551 1391 (b) Treatment Runoff (ram) Farmers Practice 67.6 Banana/Heliconia 82.7 Pineapple 97.2 Western Cabbage 76.2 LSD (0.05) NS Rainfall (ram) 3369 (c) NS = not significant Table 5.1 Runoff amount at Ringgi site between four treatments (a) wet season (b) dry season and (c) for wet and dry seasons 138 Runoff peaked across all four treatments in August 1999 and January 2000 and was lowest in March during the same year (Figure 5.2), a trend that is influenced by the rainfall pattern with highest rainfall in August 1999 and lowest in March 2000. The highest runoff (14.9mm) that was recorded in January 2000 across all treatments occurred when the plots were almost bare without vegetative cover in the alleys. The first sweet potato crop was harvested in December 1999 and plots were left almost bare in January except for the vegetative biomass left within the alleys. The second peak runoff (9.3mm) was recorded in August 1999 for all four treatments when again the plots were bare, after the vegetative re-growth were removed in preparation for planting of the first sweet potato crop (Figure 5.5). The third peak runoff was recorded in March 1999 (7.5mm), which corresponded with the time when the vegetative hedgerows were just established and plots were still without a cover (Figure 5.6). As shown in figure 5.5, at 75 to 100 percent ground cover (GC75 percent-100 percent and GClOO percent) in December 2000, runoff was only 2.9 mm , despite high rainfall of 363 mm. Monthly rainfall amounts >300 mm were observed to have caused higher runoff (9.3 mm in Aug. 1999, 14.9 mm in Jan.2000) when there was no adequate ground cover. The low runoff amount obtained when the ground cover was 75 percent to 100 percent indicates that ground cover is very important for these slopes to minimize or control runoff. Usually there is always a period of one month during the active gardening stage when gardens remain bare and the vines are beginning to spread but don’t provide an effective cover. This is the critical stage of crop growth. Most farmers plant their crops during the rainy season to ensure adequate moisture for establishment of the crop but if soil surface is not adequately protected it can result in high runoff and soil loss. The low runoff observed under FP is probably due to 139 the complete vegetative cover of the entire plot during the cropping period. The FP treatment had no vegetative barriers, and those with vegetative barriers, had gaps in the stand. Shaxson (1999) reported that the percentage cover needed to ensure low risk of runoff and soil loss on a given soil type and cropping system increases with increasing slope gradient. He further reported that 75 percent ground cover was required to ensure low erosion risk on 20 percent to 60 percent slopes in El Salvador. The effectiveness of ground cover in erosion control is well documented in the literature (Lai 1990). On very steep slopes, low ground cover which has a high degree of contact with the soil surface (e.g. plant residues, stones and mulching materials hereafter referred to as “surface contact cover”) may be more effective in reducing runoff than aerial cover such as plant canopy which, only protect surface aggregates from particle detachment by direct impact of rain drops (Paningbatan et al., 1995; Shaxson, 1999). Lai (1979) observed that mulch significantly reduced on runoff on 1 to 15 percent slopes on an Alfisol in Nigeria. The sweet potato can be classified as surface contact cover because its vines spread on the soil surface maintaining close surface contact. Its is therefore effective in controlling runoff. 140 450 400 -- I I Rainfall Runoff -- 9 -- 8 350 -- -- 7 /g' 300 -- E -- 6 & 250 -- E -- 5 ‘I 2 0 0 -- -- 4 § *« c§ P i 150 -- -- 3 -- 100 -- 2 50 -- A-GCO-25% S-GC25-50% 0-GC50-100%N-GC75-100% D-GC-100% Sweet potato growth stages (Aug. 99-Dec.99) Figure 5.5; Effect of degree of ground cover on runoff during sweet potato different growth stages 141 300 I I Rainfall (m m ) Runoff (mm) 250 - -- 6 S 200 - 150 -- -- 4 fc - 3 5 100 - -- 2 50 -- MA M J J Months (No crop) Feb.99-Jul.99 Figure 5.6: Runoff during months with no ground cover Runoff is strongly correlated with daily rainfall (r = 0.76). This relationship suggest that runoff occurs in daily rainfall events >20mm which means that runoff is only likely to occur in 15 percent of rainfall events recorded over the 15 month period. Vegetative barriers had little effect in controlling runoff. Runoff occurred as long as the daily rainfall amount exceeded 20 mm. 142 6 T o Actual runoff Predicted runoff 5 T Rsq = 0.76* Y=0.04X-0.09 4 T E E o c 2 T oo 0 10 20 30 40 50 60 70 80 90 100 110 120 ISO Rainfall (mm) Figure 5.7 Relationship between rainfall and runoff 5.3.4 Runoff and Infiltration As shown in table 5.2, about 96 to 98 percent of rainfall amount over the 15- month period in which nmoff was recorded infiltrated into the soil in all four treatments. Infiltration was similarly high under both wet and dry seasons. Runoff was only 2 to 4 percent of total rainfall. 143 Wet season Trt. Dec-March July-August Rainfall Runoff Infiltration Infiltration Rainfall Runoff Infiltration Infiltration mm mm mm % Mm mm mm % FP 1387 33 1354 98 592 14 578 98 BH 1387 46 1341 97 592 15 577 97 P 1387 56 1331 96 592 18 574 97 WC 1387 41 1346 97 592 15 577 97 (a) Trt. Dry season April-June Sept.-Nov. Rainfall Runoff Infiltration Infiltration Rainfall Runoff Infiltration Infiltration mm mm mm % Mm mm mm % FP 682 10 672 98 551 13 538 98 BH 682 12 670 98 551 16 535 97 P 682 12 670 98 551 21 530 96 WC 682 14 668 98 551 15 536 97 (b) Trt. Rainfall Runoff Infiltration Infiltration mm mm mm % FP 3369 68 3301 98 BH 3369 83 3286 98 P 3369 97 3272 97 WC 3369 76 3293 98 (c) FP = Farmers Practice, BH = Banana/Heliconia, P = Pineapple, WC = Western Cabbage Table 5.2 Rainfall and infiltration at Ringgi during (a) wet season, (b) dry season, (c) both wet and dry seasons. 144 Similarly, runoff and infiltration records at Ayiura site in PNG and Tapatapao in Western Samoa showed that about 91 to 99 percent of total rainfall amount infiltrate while only 1-9 percent as runoff (Pratap, 1994; Konabe, 1996). There were no major storms with high rainfall amount and intensity recorded during the study period. Major storms normally caused high runoff and sediment loss as observed through rising water levels, flooding and high sediment concentration in the river systems close to the experimental site. Instead, some of the driest month or lowest rainfall were recorded during this time such as in February (60 mm) and March (29 mm) of year 2000 which are normally the wet season. Howlett (1996a) pointed out that low runoff and high infiltration could be due to the fact that soils are generally well structured clay loams and are well drained, and mostly of volcanic origin. High infiltration can have two important implications: first loss of nutrients through leaching; and, second the potential of soil slumping and land slides (Howlett, 1996b). Future land management studies in the region are needed to investigate these concerns. Thus an holistic or integrated land management studies are required to address the low crop yield currently obtained by the farmers in the South Pacific region. 5.3.5 Runoff and soil loss The type of vegetative barriers used had little effect on runoff amount. Runoff occurs on these slopes as long as the daily rainfall exceeds 20 mm. Similar observation was made on Lakura in Vanuatu and PNG (IBSRAM, 1997). Soil loss rates recorded at the PNG and Western Samoa PACIFICLAND sites are shown in Table 5.3. The PNG 145 site recorded the highest rates and Western Samoa the lowest. These figures could provide an indication of the likely level of soil loss that could occur at the Ringgi site. Annual Country Treatment Rainfall Runoff Soil loss (mm) (mm) (Mg h a -) PNG Farmers practice 1338 116 16.3 Vertiva strips 51 7 Leucaena 139 13.9 Coffee 97 8.9 W.Samoa Farmers practice 2722 33 0.06 Cover crop/mulch 36 0.06 Banana/pineapple 25 0.05 Flemingia/erythrina 25 0.03 Solomon Farmers practice 3369 68 1.5* Islands Banana/heliconia 83 2.0* Pineapple 97 2.1* Polyscias (Cabbage) 76 2.2* * Soil loss for Solomon Islands comprises only the bedload Table 5.3: Comparison of under different vegetative barriers from PNG and Western Samoa and Solomon Islands, after Howllet (1996) The soil loss data for Solomon Islands comprised only the bedload and not the total soil loss from the plots. The runoff samples were not analyzed for sediment concentration which is a major part of total soil loss. 146 5.4 Conclusions Runoff occurs with daily rainfall > 20 nun. The vegetative barriers selected and used are not effective in controlling runoff and probably soil loss. There is a need to identify and select different plant species that can provide effective control over runoff and soil loss. The sweet potato canopy cover was effective in controlling runoff especially during the later stages of growth when the vines completely spread on the soil surface. At this growth stage it provided 75 to 100% ground cover. Planting and early growth stages when the vines start to spread are very important in maintaining adequate cover because, this is the stage where runoff is high. Any soil conservation measure aim at controlling runoff should address this. Leaving the sweet potato vegetative biomass after harvest and addition of extra mulch are most practical options. 147 REFERENCES Carman, K.L. 1989. Soil loss and runoff from demonsfration gardens in Matalau village East New Britain Province. Dept, of Agriculture and livestock (PNG). Technical report 89/4. Port Moresby, PNG. Cheatle, R.J. 1988. Solomon Islands project proposal for IBSRAM soil management project. Dodo Creek Research Station, MAL, Honiara, Solomon Islands. Clarke, W.C., R. J. Morrison. 1987. Land mismanagement and the development imperative in Fiji, p i76-185. In H.C. Brookfield and M.P. Blaikie (ed.) Land Degradation and Society. London. Methuen. Eyles, G. O. 1987. Soil Erosion in the South Pacific, Institute of Natural Resources, USP, Suva, Fiji. Hansell, J. R. F., and Wall, J. R. D. 1970. Land resources of Solomon Islands, Vol. 2 Guadalcanal and Florida Islands. Land Resources Study 18. Land Resources Division, Surrey, England Howlett, D. 1995. The IBSRAM Pacificland network. In Pacific Regional Agricultural Programme. Project 1: Farming systems in the lowlands: Planning for on-farm research. PRAP Report no. 1, Suva, Fiji. Howlett, D. 1996a. The IBSRAM Pacificland network: Tackling land degradation in the South Pacific. In Agroforestry research and practices in the Pacific. Project 1 : Farming systems in the lowlands: PRAP Report no. 3, Suva, Fiji. Howlett, D. 1996b. Tackling land degradation in the South Pacific. In Interim final report of the first phase o f the PACIFICLAND network on the management of sloping lands for sustainable small holder agriculture in the South Pacific. IBSRAM Regional office, Suva, Fiji. Hudson, N. W. 1971. Soil conservation, 2^^ ed., London: Batsford and Co. Humphreys, G. S. 1984. The environment and soils of Chimbu Province, Papua New Guinea, with particular reference to soil erosion. Department of Primary Industry (PNG). Research Bulletin no. 35. Port Moresby, Papua New Guinea: Department of Primary Industry. 148 Humphreys, G. S. 1994. The interpretation of soil erosion measurements, pi 11-138.In The Management of Sloping lands in the South Pacific Islands (IBSRAM/PACIFICLAND). Network Document No. 10., Bangkok, Thailand. Humpreys, G. S. and Wayi, B. M. 1990. Measuring soil erosion on steeplands; the Chimbu experience. p243-269.In PACIFICLAND Workshop on the establishment of soil management experiments on sloping lands,. IBSRAM Technical notes no.4 Bangkok, Thailand. IBSRAM 1997. Highlights 1997. Bangkok, Thailand: IBSRAM, Konabe, B. 1996. Sloping land research in the highlands o f Papua New Guinea. p25-44. In The Management of Sloping lands in the South Pacific Islands (IBSRAM/PACIFICLAND). Network Document no. 19, Bangkok, Thailand Lai, R. 1979. Soil erosion problems on an Alfisol in Western Nigeria and their control. IITA Monograph no.l, Nigeria. Lai, R. 1990. Soil erosion in the tropics: Principles and Management. 580ff. New York, McGraw Hill Lai, R. 1998. Soil erosion impact on agronomic productivity and environment quality. Critical Reviews in Plant Sciences, 17 (4):319-464 Liedtke, H. 1984. Soil erosion and general denundation in North West Fiji. Bochum, Federal Republic of Germany, Unpublished report. Liedtke, H. 1988. Soil Erosion on the fields of indigenous Fijians in the area of Suva (Fiji). Fiji German Forestry Project Report. Mimeo. 5 Ip. Mackay E. 1988. Report on Farming Systems Survey in Solomon Islands. Unpublished report. MAL, Honiara, Solomon Islands. Morrison, R. J. 1981. Factors determining the extent of soil erosion in Fiji. MR Environmental Studies Report no.7, USP, Suva, Fiji. Morrison, R.J. and W.C. Clarke. 1990. Soil Erosion in Fiji — Problems and Perspectives. J.Erosion Control Engineering Society of Japan, 43:54-59 Paningbatan, E.P., C.A. Ciesiolka, K.J. Coughlan, and C.W. Rose. 1995. Alley croping for managing soil erosion of hilly lands in the Philippines. Soil Tech. 8:193-204. Pratap, V. 1994. Country report for Western Samoa. p81-91.In The Management of Sloping lands in the South Pacific Islands (IBSRAM/PACIFICLAND). Network Document no. 10., Bangkok, Thailand. 149 Shaxson, F. 1999. New concepts and approaches to land management in the tropics with emphasis on steeplands. FAO Soils Bulletin no.75, Rome. Sillitoe, P. 1993. Losing ground? Soil loss and erosion in the highlands of Papua New Guinea. Land Degradation and Rehabilitation. 4:143-166. Stephens, P R, Trustrum N A, and Fletcher J R. 1986. Reconnaissance of the physical impact of cyclone Namu Guadalcanal and Malaita, Solomon Islands. Consultant report to Ministry of Foreign Affairs, Wellington, N ew Zealand. Wall, J. R. D., Hansell, J. R. D., Catt, J. A., Ormerod, E. C., Varley, J. A. and Webb, I. S. 1979. The soils of Solomon Islands Vol. 1. Technical Bulletin 4, Land Resources Development Centre, Ministry of Overseas Development, Surrey, England. Webb, I. S. 1974. The effect of tractor logging on some soil properties on the growth of tree crops. Unpublished report. Ministry of Agriculture and Rural Economy, Solomon Islands. Williams, A. R., Fairclough, T. J. and Nianfop, M.P. 1981. A report on the present soil erosion research programme of the Department of Agriculture, University of Papua New Guinea. Port Moresby Wood, A.W. 1984. Land for tomorrow. Subsistence agriculture, soil fertility and economic stability in the New Guinea Highlands. Unpublished Ph.D. thesis. University of Papua New Guinea. 150 CHAPTER 6 SUMMARY AND CONCLUSIONS Soil properties were evaluated under three land use practices on sloping land on Kolombangara in Solomon Islands (lat. 5-12 ° S and long. 155-170 ° W). The land use practices include: (1) natural forest (NF), (2) current farmers traditional cultivation practice (FP), and (3) current farmers practice with topsoil removed or scalped (SC). Soil physical properties include: water retention characteristics, soil texture and water stable aggregates, bulk density, particle density, penetration resistance, porosity, infiltration and saturated hydraulic conductivity. Soil biological and chemical properties included: Soil organic carbon content (SOC), pH, N, P, exchangeable cations (K, Mg, Ca,) CEC, and C/N ratio. Saturated hydraulic conductivity, bulk density, texture, and aggregation were significantly impacted by cultivation and topsoil removal. The changes in soil texture and structure were evident through changes in particle size firactions, percent water stable aggregates and MWD. Although other soil physical properties like available water capacity, infiltration rate, and porosity were not significantly affected the general trend was that the SC treatment had low values for these soil physical parameters compared to NF and FP treatments. In terms of soil biological and chemical properties, SOC, N, P, K, 151 exchangeable cations and CEC were all significantly affected by land use change. Porosity and pore size distribution were using the mecury (Hg) intrusion method on 2 cm^ aggregate sizes. The data was compared to porosity and pore size distribution in aggregates from long term-tillage experiments for Wooster silt loam at Wooster (40.5° lat. 82° long.) and crosby soil at South Charleston 39.8° lat., 84° long.) in Ohio, USA. Tillage treatments at Wooster and South Charleston included: moldboard plowing (MP), Chisel plowing (CP), and no-till (NT) with continuous com. Porosity and pore size measured in the aggregates ranged from 0.2 to 100 pm. There was significant effect of NT on pore size distribution for Wooster silt loam. No significant difference among tillage treatments was observed in the peak radius (14-20 pm) of the pore in 0-20 cm depth for either of the two soils. However the median pore radius was significantly (P = 0.05) larger under NT than other tillage treatments for Wooster silt loam but not for the Crosby soil. The median pore radius was 1.4 pm in NT compared with 0.7 pm in MP and CP treatments for the Wooster silt loam soil. Tillage treatments did not affect transmission and storage pores within the top 10 cm depth but there was a significant difference in the volume of both transmission and residual pores for both soils. Soil organic carbon content (SOC)was significantly low under the FP and SC treatments compared to NF treatment. The NF treatment had 2.8 times more SOC than FP treatment and 9.6 times more than SC treatment in the top 15cm depth. In the 15-30 cm depth, the SOC content in NF was 1.7 times more than FP and 6 times more than SC. The same trend was observed for the SOC pool. High SOC content was only found in the topsoil (0-15 cm depth) and decreases abruptly with depth across all three treatments. The reduced SOC under FP and SC treatments had some effect on the water stable aggregates 152 and the mean weight diameter. The macroaggregates under NF had significantly higher SOC than SC but not FP. This result suggests that much of tJie SOC is concentrated within the stable macroaggregates, particularly under the forest soil. The data also showed that the changes in the soil chemical properties had significant effect on the sweet potato yield compared to soil physical properties. The sweet potato yield was low for the SC treatment, which had significant reductions in SOC, N, P, K and CEC. After two sweet potato crops under the current farmers practice, yield was drastically reduced along with changes in soil chemical properties and physical properties. Such changes in soil properties impacts soil quality which made the current farmers practice unsustainable without high input. This highlight the need to identify cropping systems that are sustainable for sloping lands in Solomon Islands. Any future soil management study should take a holistic approach in assessment soil properties due to soil loss and loss of nutrients through leaching while at the same time develop and identify cropping systems that can control soil loss and replenish nutrient loss. Three types of vegetative barriers were therefore evaluated against traditional farmer’s practice (FP) for their potential to reduce runoff on a 35 percent slope from February 1999 to April 2000. Runoff amount was strongly correlated with daily rainfall amount (r^ = 0.76,) and occured in daily rainfall events exceeding 20mm. There was no significant difference in runoff between different vegetative barriers and FP which, suggest vegetative barriers used had little effect on runoff. Total runoff amount during the 15 month period for the four different treatments were 67.6 mm for FP, and 82.7 mm, 97.2mm, 76.2mm for banana (Musa Ma/za)/heliconia {Heliconia bihai ), pineapple 153 Ananas comosis and western czibhz%c(Polycias gradiflora) vegetative barriers respectively. Since the runoff amounts were low, infiltration was high which can result in high nutrient leaching. Ground cover firom the sweet potato vines was had a positive effect in controlling runoff especially around 2 to 3 months after planting when the ground cover was 75 to 100 percent. 154 BIBLIOGRAPHY Aldrick, J.M. 1993. The susceptibility of lands to deterioration in the Solomon Islands. Project working paper no. 12. Austrahan International Development Assistance Bureau / Ministry of Natural Resources, Honiara. Arvidsson. J. 1998. Influence o f soil texture and organic matter content on bulk density, air content, compression index and crop yield in field and laboratory compression experiments. 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Soil Sci. 83:291-294. 166 APPENDIX A: SOIL PHYSICAL PROPERTIES Bulk Density 0-15cm Depth NF FP SC ------■(Mg m'^)— RI 0.81 0.71 0.83 R2 0.65 0.66 0.94 R3 0.52 0.84 0.81 Mean 0.66 0.74 0.86 15-3 0cm depth NF FP SC ------(Mg m'^)— Rl 0.81 0.87 0.92 R2 0.52 0.83 0.89 R3 0.68 0.82 0.87 Mean 0.67 0.84 0.89 Table A.I: Bulk density 167 Particle Density 0-15cm Depth NFFP SC ------(M g m'^)- — ------— Rl 2.47 2.43 2.51 R2 2.39 2.32 2.53 R3 2.47 2.37 2.51 Mean 2.44 2.37 2.52 15-3 0cm depth NFFP SC -(Mg m'^)- Rl 2.44 2.36 2.49 R2 2.38 2.38 2.52 R3 2.46 2.36 2.5 Mean 2.43 2.37 2.5 Table A.2: Particle density 168 Water stable aggregates 0-15cm Depth NF FP SC —— — Rl 88.8 88.1 62.61 R2 87.9 92.2 57.6 R3 89.7 84.3 67.5 Mean 88.8 88.2 62.6 15-30cm depth NF FP SC — ------Rl 83.9 95.1 56.1 R2 82.7 94.6 55.8 R3 81.3 94.9 55.7 Mean 82.6 94.9 55.9 Table A.3: Water stable aggregates 169 GMD 0-15cm Depth NFFP SC — (mm)- Rl 1.64 1.9 0.96 R2 1.59 1.86 0.79 EG 1.64 1.75 0.84 Mean 1.6 1.8 0.9 15-30cm depth NFFP SC —(mm)—------Rl 1.24 1.83 1.09 R2 1.18 1.75 0.84 EG 1.13 1.78 0.96 Mean 1.2 1.8 1 MWD 0-15cm Depth NFFP SC —(mm)— Rl 4 5.9 4.9 EG 3.1 5.2 5.2 EG 3.5 5.3 4.4 Mean 3.5 5.5 4.8 15-3 0cm depth NF FP SC ------— —(mm)— Rl 2.8 4.8 2.1 EG 2.1 5.2 1.89 EG 2.2 4.2 1.82 Mean 2.4 4.7 1.9 Table A. 4 Geometric mean diameter (GMD) and mean weight diameter (MWD) 170 Hydraulic conductivity 0-15cm Depth NF FP SC ------—(cm hr — Rl 15 4.5 1.1 R2 20 3.2 2.1 R3 12.7 3.3 3.4 Mean 15.9 3.7 2.2 15-30cm depth NF FP SC ------■—(cm hr )— ------Rl 13.1 3.4 2.2 R2 12.1 2.9 1.6 R3 11 2.9 1.9 Mean 12.1 3.1 1.9 Table A.5: Hydraulic Conductivity 171 APPENDIX B: SOIL CHEMICAL PROPERTIES I. pH Teatment/Rep. NF FP SC ------— pH in 1:1 H20------R l 4.1 5.1 5.3 R2 4.4 4.6 4.7 R3 4.3 5.0 5.2 Mean 4.3 4.9 5.1 2. CEC NF FP SC — ------“ (cmol kg "') Rl 24 22 12 R2 21 19 14 R3 21 20 13 Mean 22 20 13 Exch. Iron (Fe) NF FP SC ------(cmol kg ------Rl 0.3 0.3 0.09 R2 0.4 0.25 0.06 R3 0.29 0.26 0.07 Mean 0.33 0.27 0.07 Exch. Aluminium (AI) NF FP SC ------(cmol k g -1) ------RI 0.13 0.17 0.18 R2 0.12 0.15 0.14 R3 0.13 0.16 0.16 Mean 0.13 0.16 0.16 Table B.I: Soil pH, CEC, Fe, and A1 for NF, FP and SC treatments 172 Available P NF FP SC — ------—(mg kg *^)~- Rl 9 12 8 R2 8 13 7 R3 8 11 8 Mean 8 12 8 SOC NF FP SC - -Ig x g J Rl 67 25 7 R2 68 23 7 R3 65 24 8 Mean 67 24 7 Total N NF FP SC “ v g X g ) — Rl 3.8 3.7 2.8 R2 4.0 3.5 2.7 R3 3.9 3.8 2.6 Mean 3.9 3.7 2.7 C/N ratio NF FP SC Rl 17.6 6.9 2.5 R2 17.0 6.7 2.5 R3 16.7 6.4 3.2 Mean 17.0 7.0 3.0 Exch. Ca NF FP SC -(cmol kg '^)— Rl 0.26 3.5 1.8 R2 0.3 3.2 1.9 R3 0.24 2.8 1.7 Mean 0.26 3.17 1.8 Table B.2: Available P, SOC, N, C/N and exch. Ca for NF, FP and SC treatments 173 Exch. magnesium (Mg) NF FP SC ------(cmol kg "')------RI 0.4 0.89 0.3 R2 0.33 0.83 0.26 R3 0.38 0.78 0.28 Mean 0.37 0.83 0.28 Exch. Potassium (K) NF FP SC -(cmol kg ‘^)------RI 0.19 0.29 0.16 R2 0.16 0.23 0.14 R3 0.18 0.26 0.12 Mean 0.18 0.26 0.14 Exch. sodium (Na) NF FP SC ------(cmol kg '^)- Rl 0.1 0.09 0.05 R2 0.09 0.08 0.06 R3 0.08 0.07 0.05 Mean 0.09 0.08 0.05 Table B.3: Exchangeable Mg, K, and Na for NF, FP and SC treatments 174 APPENDIX C: RUNOFF AMOUNT UNDER FARMERS PRACTICE AND THREE VEGETATIVE BARRIERS T l= Farmers practice T2 = Banana/Heliconia, T3 = Pineapple, T4 = Cabbage Treat/Rep TI T2 T3 T4 ----Runoff (mm)—— ------— R l 65.4 97.9 136.1 54.5 R2 73.9 72.3 76.3 92.0 R3______63.6 77.8 79.2 82.1 Mean______67.6 82.7 97.2 76.2 RimofT during wet season 1 during months (Dec, Jan, Feb, Mar, Apr) Treatment TÎ T2 T3 T4 -Runoff (mm)- R1 28.7 63.3 76.1 30.7 R2 33.2 42.2 45.8 53.8 R3______38.1 33.8 45.3 37.7 Mean______33.4 46.4 55.7 40.7 -———Runoff (mm)—------— Runoff wet season 2 (Jul, Aug) Treatment TI T2 T3 T4 ------Runoff (mm)----- — ------R l 13.2 15.7 23.7 10.4 R2 15.7 15.0 14.6 18.5 R3 12.6 15.3 16.1 15.9 Mean 13.8 15.3 18.1 14.9 Table C. 1: Total runoff and wet season runoff for four treatments 175 Runoff Dry season 2 (Sep, Oct, Nov) Treatment TI T2 T3 T4 —— ------Runoff (mm)---- Rl 11.8 17.4 32.0 11.7 R2 15.1 14.4 14.3 17.7 R3 12.7 16.0 15.6 16.1 Mean 13.2 15.9 20.7 15.2 Total Runoff 2 Dry seasons (May, Jun, Sept, Oct, Nov) Treatment TI T2 T3 T4 -Runoff (mm)---- R l 23.5 30.2 45.8 20.6 R2 25.1 26.0 24.8 39.1 R3 22.0 28.8 27.8 28.5 Mean 23.5 28.3 32.8 29.4 Table C.2: Runoff during dry season under the four treatments 176