Soil Biochemical Property Response to Drought Effects under Land-Use Change in the Context of Climate Change

ecological and socio-economic impacts ... Research framework ... Soil sampling locations at Phiem Ai Village, Dai Nghia Commune, Dai Loc District, Quang Nam Province ... Experiment setu[r]

VIETNAM NATIONAL UNIVERSITY, HANOI

VIETNAM JAPAN UNIVERSITY

BUI HANH MAI

SOIL BIOCHEMICAL PROPERTY RESPONSE TO DROUGHT EFFECTS UNDER LAND-USE CHANGE IN THE CONTEXT OF CLIMATE CHANGE

MASTER’S THESIS

VIETNAM NATIONAL UNIVERSITY, HANOI

VIETNAM JAPAN UNIVERSITY

BUI HANH MAI

SOIL BIOCHEMICAL PROPERTY RESPONSE TO DROUGHT EFFECTS UNDER LAND-USE CHANGE IN THE CONTEXT OF CLIMATE CHANGE

MAJOR: CLIMATE CHANGE AND DEVELOPMENT

CODE: 8900201.02QTD

RESEARCH SUPERVISOR:

Dr HOANG THI THU DUYEN

Hanoi, 2020

PLEDGE

I assure that this thesis is the result of my own research and has not been published The use of results of other research and other documents must comply with regulations The citations and references to documents, books, research papers, and websites must be in the list of references of the thesis

Author of the thesis

Bui Hanh Mai

TABLE OF CONTENT

LIST OF TABLES i

LIST OF FIGURES ii

LIST OF ABBREVIATIONS iii

ACKNOWLEDGMENT iv

CHAPTER 1: INTRODUCTION 1

1.1 Background and motivation of the study 1

1.2 Research framework 5

1.3 Drought in the world 6

1.4 Drought in Vietnam 8

1.5 Impact of drought and land use change on soil properties 10

1.5.1 Impacts of drought on soil microbial activities and biochemical properties 10

1.5.2 Impacts of land use change on soil microbial activities and biochemical properties 11

1.6 Objects and scope of the research 13

1.7 Research questions and hypothesis 17

1.7.1 Research questions 17

1.7.2 Hypothesis 17

CHAPTER 2 METHODOLOGY 18

2.1 Data collection 18

2.1.1 Meteorological data 18

2.1.2 Remote sensing data 18

2.2 Methods of identifying and calculating drought indicators 20

2.3 Soil sampling and processing 21

2.4 Experiment setup 22

2.5 Determination of MBC and MBN 24

2.6 Identification of microbial basal respiration 24

2.7 Statistical analysis 25

CHAPTER 3: RESULTS AND DISCUSSION 26

3.1 Results 26

3.1.1 Land use and land cover maps 26

3.1.2 Drought progress characteristic 27

3.1.3 Basic soil properties 30

3.1.4 Microbial activities 31

3.2 Discussion 37

3.2.1 Land use and land cover maps 37

3.2.2 Drought progress characteristics 37

3.2.3 Soil properties and microbial activities 37

CHAPTER 4 CONCLUSIONS AND RECOMMENDATIONS 42

4.1 Conclusions 42

4.2 Recommendations for future research 43

REFERENCES 45

APPENDIX 53

i

LIST OF TABLES

Table 2.1 Land cover types description 189

Table 2.2 Classification used for K indices 21

Table 2.3 Methodologies to analyze soil physic-chemical properties 22

Table 3.1 The basic properties of forest soil and pineapple soil 30

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LIST OF FIGURES

Figure 1.1 Drought concept relevant to climate change Drought releases

ecological and socio-economic impacts 2

Figure 1.2 Research framework 6

Figure 1.3 Average monthly sunshine hours (2000 - 2019) in Quang Nam 14

Figure 1.4 Average monthly temperature (2000 - 2019) in Quang Nam 15

Figure 1.5 Average monthly precipitation (2000 - 2019) in Quang Nam 16

Figure 1.6 Average monthly evaporation (2000 - 2019) in Quang Nam 16

Figure 2.1 Soil sampling locations at Phiem Ai Village, Dai Nghia Commune, Dai Loc District, Quang Nam Province 231

Figure 2.2 Experiment setup for drought condition 23

Figure 2.3 Design experiment to analyze soil respiration 24

Figure 3.1 Land-use and land cover maps in Quang Nam (2003 – 2018) 26

Figure 3.2 The total area of each type of land use and land cover in Quang Nam 2003 – 2018 27

Figure 3.3 Drought frequency month during 2000 – 2019 28

Figure 3.4 K indices of mean drought months in dry season 28

Figure 3.5 K indices of drought months during dry season (2000 – 2019) 29

Figure 3.6 MBC of forest soil and pineapple soil 31

Figure 3.7 MBN of forest soil and pineapple soil 32

Figure 3.8 MBC:MBN ratio of two soil types and three treatments 33

Figure 3.9 The ratios of MBC to SOC and MBN to TN of both soils 33

Figure 3.10 The microbial basal respiration in the difference soil moistures of both soil 35

Figure 3.11 The amount of CO2 after three periods incubators at three treatments 35

Figure 3.12 The correlation between MBN and soil respiration of forest soil in incubated with 10% WHC 36

MBC Microbial biomass carbon

MBN Microbial biomass nitrogen

MODIS Moderate Resolution Imaging Spectroradiometer

SOC Soil organic carbon

SOM Soil organic matter

WHC Water holding capacity

iv

ACKNOWLEDGMENT

To complete this thesis, I would like to express my sincere thanks to the lecturers and staff of Program of Climate Change and Development, Vietnam Japan University, Vietnam National University, Hanoi, and other lecturers and students of Soil Sciences Department of Vietnam National University of who guided and facilitated me to complete my thesis on time

I would like to express my deepest and most sincere thanks to my supervisor -

Dr Hoang Thi Thu Duyen, advisor - Dr Kotera Akihiko, Prof Phan Van Tan and Dr Nguyen Van Quang - Lecturers of Climate Change and Development program, Vietnam Japan University, VNU for their dedication and valuable comments on thesis

In addition, the research has also received support and help from leaders and staff of Quang Nam Crop Production and Plant Protection Subdepartment and Department of Agriculture and Rural Development Dai Loc District so that I could collect information related to the thesis

Last but not least, the author also appreciates financial support of VNU project (code QG.20.63, No 1086/QĐ-ĐHQGHN), without this support the implementation is impossible

Finally, I would like to dedicate this thesis to my parents and friends as a gesture of my thanks for their constant support and belief in me

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CHAPTER 1 INTRODUCTION 1.1 Background and motivation of the study

Climate change is a natural process but it is boosted by anthropogenic activities (IPCC, 2012) and the rapid increases in CO2 concentrations over the last few centuries, which leads to a series of unpredictable weather events Drought/severe drought is one of the consequences of climate change, which

is projected to increase unprecedentedly in prone areas (IPCC, 2019) The world temperature is supposed to increase over 1.5 to 2oC in the period of

2081 to 2100 (Collins et al., 2013) Each increase of atmospheric temperature results in 7% increase of atmospheric moisture holding capacity (Sun et al., 1996) Therefore, precipitation becomes more condensed, and hence, prolonged dry season over a year In drought-sensitive areas, such as the Mediterranean, north-eastern Asia, West Asia, many regions of South America and the majority of Africa (IPCC, 2019), global warming exacerbates drought severity by accelerating evaporation, enhancing shortage

of soil moisture (Figure 1.1)

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Figure 1.1 Drought concept relevant to climate change Drought releases

ecological and socio-economic impacts (Wilhite, 2000)

Excessive extraction of surface and underground water under drought context for agricultural production will proceed desertification in cultivated areas As

a consequence, land-use change occurs in response to the high demand for expanded cropland due to population growth, and the reduction of soil moisture and quality During 1990 – 2005, 13 million hectares forest destroyed per year (FAO, 2006) to convert from forest land to cropland, which reduces soil C sequestration and a rapid biomass C loss, releasing up to

180 – 200 Pg (pentagrams) C emissions in the last two centuries (Ramesh et al., 2019)

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Land-use change, as well as drought, have an impact on the biochemical properties of the soil Increasing frequency, intensity and timing of drought is predicted to lead to reduce the functions of microorganism, which is essential

of ecosystem sustainability (McHugh et al., 2017) Moreover, the structure of the soil microorganisms is greatly influenced by land use, land cover, and agricultural activities Those factors impact on SOM and lead to regulating the microbial structure appropriately (Moon et al., 2016; Bissett et al., 2011) Thus, it could impact on soil microbial biomass and the usage C efficiency of microorganism (Bauhus et al., 1998) Terrestrial plants are the main sources

of soil organic matter (SOM) which retains moisture in different soil horizons However, during 20 years (1980 – 2000), more than 80% of newly cultivated land came from the intact and disturbed forests (Gibbs et al., 2010) Land conversion from forest to cultivated land reduces SOM content, leading to a decline in soil moisture content and lowering resistance and resilience capacity of the terrestrial ecosystem to drought impacts (de Vries et al., 2012) This land-use change also triggers potential drought events as the soil is over-exploited for intensive agricultural production, which causes exhaustion in soil nutrients, bio-balance and hence soil WHC

In tropical dry land ecosystems, studies in land-use change under drought are still restricted when compared with the total coverage of wet ecosystems around the world (Ramesh et al., 2019) Therefore, the study “Soil biochemical property response to drought effects under the land-use change in the context of climate change” is conducted in Quang Nam, Vietnam to elucidate the relationship between abiotic factor (soil moisture) and biotic factor (microbial biomass and activity)

During the period 1999 – 2018, Vietnam ranks 6th among 10 countries most affected by the extreme weather events in the table of Long-term Climate

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Risk Indices (CRI) (Eckstein et al., 2019), especially the increase of drought frequency causes negative impacts on the production activities of local people Quang Nam, where is located in the South Central region with diverse terrain conditions and harsh climate, severely impacted by drought Due to drought in the Southern sub-regions and South Central are highly sensitive to ENSO (Le et al., 2018) According to the People's Committee of Quang Nam province (2010) and IMHEN (2009), the prolonged drought damaged, 4,841/44,500 hectares of summer-autumn rice in plain districts; 660 hectares

of rice were lost due to saline intrusion In addition, there are over 3,000 hectares of rice that cannot be sown due to aridity, along with 5,000 hectares

of crops lacking irrigation water and nearly 5,000 people suffer from water shortages in the midland and mountainous districts of Quang Nam From the beginning of the Summer-Autumn season in 2019, the weather was abnormal and the hot and sunny situation happened continuously and lasted for many days The storage capacity in many irrigation and hydropower reservoirs is only about 20 – 60% of the designed capacity, lower than the average many years Many small reservoirs have dried up (EVN, 2019)

This study was conducted to provide a general overview of the biochemical and microbiological activity of two different land-use types, namely forest and pineapple land in Quang Nam, under drought conditions The findings will provide stakeholders in Quang Nam with scientific background for adaptation strategy to climate change while maintaining soil health Moreover, in order to mitigate the effect of climate change, the identification

of management practices and appropriate land-use in each location is one of the necessary methods Thus, this study performs with three main objectives:

1 To define areas under drought impacts in Quang Nam in recent years

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2 To demonstrate the effect of drought on microbial activities including microbial biomass C and N (MBC and MBN) and microbial community composition in different land-use

3 To evaluate nutrient mineralization under drought impacts in different land-use

1.2 Research framework

Thesis is built around three main research objectives and follows an interdisciplinary approach using remote sensing, field methods, laboratory methods, and comprehensive analysis of collected data (Figure 1.2) The three main factors (drought, land-use change, soil microorganism activities) are closely intertwined The first objective uses MODIS data, field-survey and drought indicess to estimate the change of land-use, especially forest land and cropland, as a basis for drought area, frequency, and severity drought identification The second and third objective involves laboratory methods to estimate microbial biomass and microbial respiration based on a commonly-applied approach used in global studies and their interaction with the changing of climate in Quang Nam

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Figure 1.2 Research framework

1.3 Drought in the world

As mention above, drought directly affects agriculture Droughts often cause loss of agricultural land, crop structure changes and crop yields decline That impacts the lives of people and national food security Besides, drought also affects forest resources Increased temperature and evaporation cause prolonged drought, which will affect the growth ability of forest plants and animals Some regions in the world have occurred a trend to more longer and

Solutions Impact

Interaction

60 years were in 1965, 1972, and 2002 with more than 35% area under severe drought for the 12-month time-scale (Aadhar and Mishra, 2018) Since the late 1990s in China, extreme droughts have become more regular In the past five decades, the drought areas were reported to increase by around 3.72% per decade (Yu et al., 2014) Zou et al (2005) also indicated that since the 1990s drought in northern China has been on an upward trend, in particular, some areas occurred drought lasting 4 – 5 years from 1997 to 2003 In fact, in 1997, severe drought in northern China caused nearly 226 days of continuous zero flow in the Yellow River (Cong et al., 2009) Thus, besides the increased drought frequency and severity, the duration of drought periods has also significantly increased Drought events can last months to years in many countries

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In addition to using observational meteorological data to study drought, drought estimates by simulation results of climate factors from dynamic models have also been strongly developed in many countries In warmer future climates, most atmospheric circulation models anticipate increased summer drought and winter wetness in most of the medium latitudes and high latitudes in the north It is the summer drought that will lead to a greater drought disaster, especially in areas where rainfall decreases (IPCC, 2007) Kim and Byun (2009) estimated the effects of global warming on drought conditions in Asia in the late 21st century under the A1B scenario The results indicate that rainfall rates decrease the highest in North Asia in all seasons, in West Asia average rainfall plummets from winter to summer, leading to future droughts in these two areas have more frequency, stronger intensity, longer drought cycle than in the past, especially in summer The severity of drought in India is projected to increase under wetter and warmer future climate (Aadhar and Mishra, 2018) Due to there is an increase in precipitation, and more than 2 degree rise in temperature leads to more atmospheric water demand and an increase in drought severity by the end of the 21st century Under the RCP 8.5, almost all of India shows high-frequency

of severe drought events in the end period, more than three severe events per decades The area affected by severe drought is predicted to increase by 150% with warming by the end of the 21st century

1.4 Drought in Vietnam

The trends of drought in Vietnam had changed recently According to Le et

al (2019), the historical trends of drought, during 1980 – 2014, changed between sub-regions In northern sub-regions, drought trend to decrease of seasonal, except during summer months By contrast, in the central coastal, drought increases In other sub-regions, drought impact was not significant In

In addition to studies on Vietnam's drought history, there have been studies on drought prediction in Vietnam based on scenarios A1B and A2 According to Ngo Thi Thanh Huong (2011), the results of drought estimates under the A1B scenario for climatic regions in Vietnam showed that droughts are more likely

to occur in the future, especially in the period 2011 – 2030 in the Northwest climatic region and the period 2031 – 2050 in the three climatic regions of the South Central, Central Highlands and Southern regions Future lighter drought occurs in the Northeast and North Central regions

The estimated results of drought over time through Ped indicator under A2 scenario show that the drought trend in the period 2011-2030 decreased in the Northwest, Northeast climate regions and almost no change in the North Central climate region but increased significantly during the period 2031 –

2050 In the remaining climate regions, drought increased markedly in both periods, especially the Central Highlands and the South

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1.5 Impact of drought and land use change on soil properties

1.5.1 Impacts of drought on soil microbial activities and biochemical properties

IPCC (2019) emphasized that "Climate change, including increases in frequency and intensity of extremes, has adversely impacted food security and terrestrial ecosystems as well as contributed to desertification and land degradation in many regions" In the fact, extremes of arid conditions reduce the growth of most plants and microbial decomposition Moreover, microbial functions are important for ecosystem sustainability McHugh et al (2017) stated that increasing drought prediction lead to decline in microbial functions When soil drier, less SOC in the soil is decomposed and respired to

CO2, due to in soil pores have less water, thus resources in the soil cannot link together (Schimmel, 2018) In addition, these factors interact with the reduction loss of C through suppressed respiration (Heimann and Reichstein, 2008) In grassland ecosystems, the soil micro-biome can be impacted long-lasting by drought, due to the dominance of drought-tolerant plant species cause the changes in vegetation and root microorganisms also change (de Vries et al., 2018)

Also, in the soil pores, the microbial distribution becomes more restricted when soil becomes drier (Carson et al., 2010 and Dechesne et al., 2010) Besides, the dry situation kills many microbes However, many microbial species tolerate dryness due to they developed resistant strains or entered into

an inert stage The reason disruption of soil C and N cycling is the recovery of microbial communities that could not occur immediately after drought (Sheik

et al., 2011) However, fungi potentially maintain C and N cycling when water in the soil become scarce (Treseder et al., 2018) because fungal hyphae could link spatially discrete resources in the soil (Guhr et al., 2015)

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Conditions that favor microorganism growth will favor fast decomposition rates The product of complete decomposition are CO2, NH4

+, NO3

, SO4 2-,

-H2PO4

-, H2O resistant residues, and multiple other necessary nutrient elements for plants in smaller quantities Chemical soil degradation is likely nutrient decreased because of the imbalance of nutrient extraction resulting from harvested products and fertilization Excessive N fertilization and export in harvested biomass increase acidification in croplands because of the depletion

of cation like calcium, magnesium or potassium in the soil (Guo et al., 2010)

In the context of climate change, the depletion of organic matter pool causes soil chemical degradation processes Tillage and the belowground plant biomass inputs reduction cause the increase of respiration rates, which reduced organic matter in agricultural soils The warming directly impacts on the decline of SOM pools in both under natural vegetation and cultivated land (Bond-Lamberty et al., 2018) Creating energy from harvesting residues also could lead to reducing organic matter in the forest (Achat et al., 2015) A

“hub” of degradation processes could be SOM, which also is an important connection with the climate system (Minasny et al., 2017) Zhao et al (2017) stated that interaction between temperature and precipitation influences not only terrestrial ecosystem productivity but also the decomposition rate of SOC That is the reason why those environmental factors are the most affecting soil CO2 efflux rates

1.5.2 Impacts of land use change on soil microbial activities and biochemical properties

Land-use change contributes to global warming because the land-use change affects CO2 emission to the atmosphere (Ramesh et al., 2019) Moreover, the soil is one of the global C sinks Soil stores C higher than atmosphere and vegetation, about two times and three times, respectively (Zomer et al., 2002)

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The processes, namely the oxidation of superficial soil C stocks, enhancing gas emissions (COz and other gases) to the atmosphere, are markedly impacted by the changes from forest to agriculture and grassland (IPCC, 1992) That conversion also causes soil organic C loss (Kasel and Bennett, 2007; Guo and Gifford, 2002) According to IPCC (1992), land-use change and deforestation emitted about 55±30 Gt CO2

In the tropical land, the land conversion from forest land to other lands caused big SOC losses in the soil, such as 25% SOC losses in cropland, 30% SOC losses in perennial crops and 12% SOC losses in grasslands (Don et al., 2011) The land-use change causes loss SOC not only in the surface soils but also in the sub-surface soils Deforestation and change to agriculture caused rapidly SOC initial decreased, which lead to the active SOC pool loss or the labile C pool loss (Motavalli et al., 2000) Besides, land clearing also makes the loss of SOC The losses SOC could lead to soil erosion, increased rate of SOM decomposition, and alteration of the components of plant residue (Feller and Beare, 1997) Tillage, such as aerating the soil, disturbing soil aggregates, concealing surface residues, and revealing new surfaces for microbial pervaded, make the SOM decomposition rate increased (Indoria et al., 2017) According to Ramesh et al (2019), declining CO2 emission to the atmosphere and increasing SOC sequestration is the best way to mitigate global warming The rapid decomposition activities of microorganisms intensify the rate of

CO2 emission to the atmosphere The accumulation rate of organic C in soil depends on many factors in specific places, including plant species, soil properties, and climate Perennial vegetation or forests, which are converted from vegetation on barren, abandoned agriculture, or degraded lands, could improve C storage capacity in the soil (Choudhury et al., 2014) In addition,

of cover crops, and no-tillage However, the organic manure application and residues enhance CO2 emission to the atmosphere Thus, the utmost crucial factor to mitigate the changing of climate is C sequestration in soil from identification appropriate management practices and land-use

1.6 Objects and scope of the research

- Study site: Quang Nam province

Quang Nam is located in the central region of Vietnam, is a region with relatively complex topography, lower from the West to the East, forming three ecological regions: high mountains, midlands, and coastal plains The province is divided by the Vu Gia and Thu Bon river basins

Quang Nam is located in the typical tropical climate region, with only two seasons: the dry season (from January to August) and the rainy season (from September to December) However, there still influence by the cold winter in the North

At present, there are two meteorological stations in the province, which fully observe meteorological factors for a long time (starting from 1976), namely Tam Ky and Tra My stations Tam Ky station located in Hoa Thuan Ward, Tam Ky City The meteorology data was collected in Tam Ky station is used

to calculate the relevant meteorological factors for the eastern delta of the province Tra My station located in Tra My town, Bac Tra My district The

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meteorology data was collected in Tra My station is used to calculate the relevant meteorological factors for the western mountainous region of the province

In general, the number of sunshine hours in Quang Nam was quite high (Figure 1.3) The mean sunshine hours (2000 – 2019) of Quang Nam province were 1850 hours in mountainous area and 2000 hours in coastal plain In May, the highest number of sunshine hours was from 227 to 242 hours December was the least sunshine hours in a year, from 55 – 68 hours

Figure 1.3 Average monthly sunshine hours (2000 – 2019) in Quang Nam

Temperature: The annual mean temperature in Quang Nam area was quite high, about 25.4oC in mountainous and 26.6oC in coastal plain The mean temperature of the months in winter has not exceeded the 20oC The coldest month was January with a mean temperature of 21.3oC (mountainous) and

22oC (coastal plain) The hottest month was June, with a mean temperature of about 29.5 – 31.5oC (Figure 1.4) The minimum temperature in Quang Nam was 12oC (mountainous) – 13.6oC (coastal plain) and the highest can be over 40.1oC (mountainous) – 41oC (coastal plain)

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Figure 1.4 Average monthly temperature (2000 – 2019) in Quang Nam Rainfall: Rain was not evenly distributed according to space, rainfall in mountainous areas was more than plain Mountainous was the center of heavy rainfall in Quang Nam, the total annual rainfall during 2000 – 2019 reaches

4311 mm, while the average annual rainfall measured at coastal plain station

is 2840 mm (Figure 1.5) The rainy months were from September to the end

of December, the peak was October to November with rainfall of about 899 – 1058mm (mountainous), 601 – 693mm (coastal plain), and accounting for 45.6 – 54.5% of the total mean rainfall of 19 years The lowest rainfall a year was from February to April, accounting for only about 5.7 – 7% of the total mean rainfall of 19 years

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Figure 1.5 Average monthly precipitation (2000 – 2019) in Quang Nam Evaporation: The average evaporation in many years in Quang Nam was 568 – 825 mm in both monitoring stations In the dry season, due to the high air temperature, low humidity, high winds, the evaporation in the dry months can

be twice compared with the rainy months It can be seen from Figure 1.6, the amount of evaporation in April – August was the most, while the rainfall was low

Figure 1.6 Average monthly evaporation (2000 – 2019) in Quang Nam Humidity: The annual average humidity was 85.6% in the lowlands (coastal plain) and 88% in the mountains (mountainous) However, there was a

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fluctuation between the months of dry and rainy seasons, the month with the lowest humidity was June (78 – 84%), and the highest humidity was December from 91 – 93%

- Time performed the research: From January to end of May, 2020

- Objects of the research: Forest soil and pineapple soil have the same topographic characteristics and soil types

1.7 Research questions and hypothesis

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CHAPTER 2 METHODOLOGY 2.1 Data collection

2.1.1 Meteorological data

To assess the drought conditions of Quang Nam province, daily meteorological data of Mountainous and Coastal plain meteorological stations from 2000 to 2019 were collected from Vietnam Institute of Meteorology, Hydrology and Climate Change (IMHEN), including average air temperature, maximum air temperature, minimum air temperature, average air humidity, number of sunshine hours, amount of evaporation, rainfall, wind direction and wind speed

2.1.2 Remote sensing data

The MODIS image data used in this study is the MODIS Land Cover Type Product (MCD12Q1) From 2001 until now, MCD12Q1 provides the annual map of global land cover at 500 meters spatial resolution with six different land cover legends This study was used Classification schemes of The International Geosphere-Biosphere Programme (IGBP) Type 1 land cover scheme identifies was chosen with 17 land cover classes (0 – 16), which include 11 natural vegetation classes, 3 developed and mosaicked land classes and three non-vegetated land classes (Sulla-Menashe and Friedl, 2018) Information about all of the data layers, including Quality Control is shown in Table 2.1 The image MODIS is analyzed to create land use and land cover maps in Quang Nam province from classifications of spectro-temporal features derived of data during 2003, 2008, 2013, 2018 by QGIS 3.4.6 software

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Table 2.1 Land cover types description (Sulla-Menashe and Friedl, 2018)

Closed Shrublands 6 Dominated by woody perennials (1-2m

height) >60% cover

Open Shrublands 7 Dominated by woody perennials (1-2m

height) 10-60% cover

Woody Savannas 8 Tree cover 30-60% (canopy >2m)

Savannas 9 Tree cover 10-30% (canopy >2m)

Grasslands 10 Dominated by herbaceous annuals (<2m) Permanent Wetlands 11 Permanently inundated lands with 30-60%

water cover and >10% vegetated cover Croplands 12 At least 60% of area is cultivated cropland Urban and Built-up

At least 30% impervious surface area including building materials, asphalt, and vehicles

Cropland/Natural

Vegetation Mosaics 14

Mosaics of small-scale cultivation 40-60% with natural tree, shrub, or herbaceous vegetation

Permanent Snow and 15 At least 60% of area is covered by snow

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Ice and ice for at least 10 months of the year

At least 60% of area is non-vegetated barren (sand, rock, soil) areas with less than 10% vegetation

Water Bodies 17 At least 60% of area is covered by

permanent water bodies

Unclassified 255 Has not received a map label because of

missing inputs

2.2 Methods of identifying and calculating drought indicators

The drought extension over time is determined by rainfall as follows (Vietnam Meteorological and Hydrological Administration, 2014):

- Drought occurs when the amount of rainfall per month is less (equal) than 30mm

- Drought frequency month caculated by:

P = Where: m is drought frequency observation month

n is frequency of rainfall observation month

- To describe the general situation of drought in the areas and their evolutions over time, the drought indices (Nguyen Trong Hieu, 1998) of months and years was used:

Km =

Where: Km: Drought indices month (year)

Pm: Evaporation amount according to Piche month (year)

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Rm: Monthly (annual) rainfall

Table 2.2 Classification used for K indices

2.3 Soil sampling and processing

Soil was sampled from topsoil (0 – 30cm) of pineapple and neighboring forest

in Dai Loc district Quang Nam province where drought happens annually The sample collection time was the beginning of the dry season (3rd January 2020)

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Figure 2.1 Soil sampling locations at Phiem Ai Village, Dai Nghia

Commune, Dai Loc District, Quang Nam Province The samples were preserved in laboratory under 5oC and sieved through 2mm mesh to remove plant litter, roots and gravels larger than 2mm A subsample was detached to measure basic soil properties Table 2.3

Table 2.3 Methodologies to analyze soil physic-chemical properties

WHC (%) = (Water saturated soil weight dry weight)

300g of sieved soil (oven-dry equivalent) of each land use type was separately weighed in a plastic box and the soil moisture was adjusted to 60% WHC using sterilized water The amount of added sterilized water to attain 60% or 10% WHC:

 Set 1 – harvested right after pre-incubation (60% WHC)

 Set 2 – harvested as soil moisture reduced to 10% WHC

 Set 3 – harvested as a control for set 2 (60% WHC)

Figure 2.2 Experiment setup for drought condition Each treatment setup with 4 replicates (Figure 2.3)

a) Forest soil

Control

Dry

2.6 Identification of microbial basal respiration

50g soil subsample was incubated in Mason Jars for 6 hours, 18 hours and 24 hours at a fixed temperature and atmosphere pressure (28oC) A small vial containing 10ml NaOH 1N was placed in the jar to trap CO2 The vial was measured every 6 hours, 18 hours and 24 hours The trapped CO2 defined using titration with HCl 0.1N against the phenolphthalein endpoint (Zibilske, 1994) CO2 trapped was the net emissions of CO2 for soil, which was calculated as follows:

(g.mol-1)/2/dry weight of bulk sample (kg)

Control

Dry (20%

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The microbial basal respiration was calculated by dividing sum of trapped

CO2 by 48 hours (mg.kg−1) (Qiao et al., 2013)

2.7 Statistical analysis

Data were analyzed using SPSS 20.0 software (SPSS Inc., Chicago, IL, USA) Independent sample t-test was conducted to test the differences between the two land-use types in the soil properties Effects of soil WHC treatments on soil respiration were analyzed in the forest soil and pineapple soil, respectively, considering the dependent differences in the initial soil and drought soil Effects of soil WHC treatments on average values of soil respiration during constant moisture period were tested using one-way analysis of variance (ANOVA) In order to understand the effect of soil biochemical properties (explanatory variables) on soil microbial biomass (response variables), we used Pearson’s correlation analysis Significance for all statistical analyses was accepted at the level of p<0.05

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CHAPTER 3 RESULTS AND DISCUSSION 3.1 Results

3.1.1 Land use and land cover maps

The interpretation of the MODIS satellite image (MCD12Q1) from 2003 to

2018 (Figure 3.1) shows that the forest area is largest, account for 60.27±1.77% total area The agriculture area just is 5.89±0.23% and concentrated on the coastal plain

Figure 3.1 Land use and land cover maps in Quang Nam (2003 – 2018)

The change of land-use area occurred at most different land-use types (Figure 3.2) Land-use types tended to increase from 2003 to 2018, except for non-vegetated The agricultural land area increased slightly from 2003 to 2018,

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about 0.83% of the total agriculture area The forest area gradually decreased from 2003 to 2013, about 8.34% of the total forest area However, until 2018, the forest area increased by up to 5.86% compared with 2013 By contrast, non-vegetated land tended to be the complete opposite of forest land Non-vegetated areas increased by about 7.93% from 2003 to 2013 and decreased

by 6.65% during 2013 – 2018

Figure 3.2 The total area of each land-use type and land cover in Quang Nam

2003 – 2018

3.1.2 Drought progress characteristic

The calculated drought frequency by observed rainfall at two monitoring stations showed a similar trend during 2000 – 2019 in two areas, namely mountainous and coastal plain The drought frequency month trended to increase (Figure 3.3) In particular, the drought frequency month in 2010 and

2013 of the coastal plain was highest In general, the drought frequency of mountainous was lower than the drought frequency of coastal plain However, the drought frequency was similar in both areas in 2005 and 2019

Croplands Urban and built-up

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Figure 3.3 Drought frequency month during 2000 – 2019

The K indices of dry season months is used to assess the drought severity level The K indices calculated results showed that the drought severity level has decreased slightly during 2003 - 2019 Figure 3.4 revealed that the severity drought concentrated in the coastal plain The drought years appeared

11 times (out of 19 years of observation) and the highest K indices in 2003 showed that this was the most severe drought

Figure 3.4 K indices of mean drought months in dry season

Linear (Coastal plain) Linear (Mountainous)

Linear (Coastal plain) Linear (Mountainous)

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In general, drought mainly occurs in the dry season from February to August (Figure 3.5) in the period 2000 – 2019 Severe drought concentrates mainly from February to April The highest K indices in February showed that this month was the most severe drought month of the year Moreover, the drought level in the coastal plain was severer than mountainous

a) Coastal plain

b) Mountainous Figure 3.5 K indices of drought months during dry season (2000 – 2019)

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3.1.3 Basic soil properties

The results in Table 3.1 indicated that the soil texture of the two types of land use is silt loam The bulk density result is similar between forest soil and pineapple soil

Table 3.1 The basic properties of forest soil and pineapple soil

Forest soil Pineapple soil

Soil bulk density (g/cm3) 1.3±0.015a 1.3±0.117a

Soil moisture 0.163±0.010a 0.117±0.034b

Soil texture

Clay (%) 27.538±0.625 28.458±0.231 Silt (%) 51.768±1.173 49.55±1.270 Sand (%) 20.695±1.783 21.992±1.082 SOC (%) 1.041±0.023a 0.817±0.023b Total Nitrogen (%) 0.15±0.007a 0.12±0.004b

Total Phosphorus (%) 0.8±0.390a 0.87±0.502a

C:N ratio 6.99±0.35a 6.8±0.29a Note: Values shown in Table 3.1 are means ± standard error (n = 4) a, b in a row indicated the significant difference at p = 0.05

The differences in basic properties of soil, namely soil moisture, pHH2O, total

C and total N, found between two types of land use The independent samples t-test revealed significantly lower soil pHH2O in pineapple soil compared with forest soil (p = 0.0002598 < 0.05) And, the soil moisture of forest soil was higher than soil moisture of pineapple soil (p = 0.0007349 < 0.05) The total

C and N of forest soil had the same pattern with p-value < 0.05 However, there was no significant difference in soil bulk density, total phosphorus and C:N ratio between forest and pineapple soil

in the incubated soil (control, 60% WHC) was significantly higher than that

of initial period (60% WHC) (p < 0.05) There was still a significant difference between the MBC of the initial period soil and incubated soil at 10% WHC in pineapple soil, while forest soil did not have a significant difference between them Moreover, in both soils, the MBC value of incubated soil at 10% WHC was significantly lower than the MBC value of incubated soil with 60% WHC, account for 1019.710 µgC.g-1soil in forest soil and 972.093 µgC.g-1soil in pineapple soil

Figure 3.6 MBC of forest soil and pineapple soil MBN showed higher values in the forest soil compared with those in pineapple soil At three treatments, significantly lower MBN of pineapple soil