Climate Change Awareness, Impact and Adaptation in Portharcourt, Nigeria.

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Isaac Omachi-Attah Sule¹; Prof. A. A. Obafemi²; Prof. L. C. Osuji³; Prof. A. I. Hart⁴

¹Institute of Natural Resources,

Environment and Sustainable Development, (INRES) University of Port Harcourt.

Pmb 5323, Choba, Port Harcourt, Nigeria. Email: Isaac_Sule@Uniport.Edu.Ng

²Department of Geographyand Environmental Mangement, University of Port Harcourt.
Email: Andrew.Obafemi@Uniport.Edu.Ng

³Department of Industrial and Pure Chemistry, Petroleum and Environmental Chemistry Research

Group, University of Port Harcourt., Choba, Port Harcourt, Rivers State, Nigeria.
Email: Leo.Osuji@Uniport.Edu.Ng

⁴Department of Animal & Environmental Biology, University of Port Harcourt.

Choba, Port Harcourt, Rivers State, Nigeria. Email: Adaubobo.Hart@Uniport.Edu.Ng

ABSTRACT

The study evaluated socio-demographics, climate change awareness, impact/vulnerability and adaptation for adult residents of Port Harcourt. a purposive random sampling was employed selecting adult participants who had dwelt up to a year in Port Harcourt. 412 questionnaires were distributed. Descriptive statistics, including frequencies and percentages, were generated. Additionally, regression analysis was employed investigating the relationships between independent variables and climate change awareness, adaptation and impact/vulnerability and ANOVA for evaluating the overall fit and significance of regression models. prevalent age groups were 28-37 and 38-47 at (31% and 28% respectively), gender distribution was male (51%) and female (49%), (65%) fall within the educational brackets. largest category of Households size ranged from 6 to 10 members (53.4 %); awareness levels was prevalent at 85% with 60% of awareness attributable to television. 87.9% attributed observable changes in their communities to climate change with most frequencies as shifts in the community rainfall patterns (72.6%) and temperature (63%), whilst a significant 74% did not take any action for adaptation only 35% depended on climate sensitive resources with 65% not believing they or their family members had health conditions impactable by climate change. A significant 74% took no adaptation measures and 57% were uncertain of any community adaptation measures available while 88% had no idea of any government or non- governmental programmes focused on adaptation. overall, a good number had concerns about the future impacts of climate change though many respondents did not feel their communities were prepared enough for future impacts. The study recommends the need for promoting awareness, encouraging responsible behaviours, and establishing resilient infrastructure as critical components of government non-governmental, community and individual response to climate-related challenges as collaborative efforts involving residents, authorities, and relevant organizations are key to fostering resilience and implementing sustainable strategies to tackle the consequences of climate change.

Keywords: Climate Change, Climate change awareness, Climate change impact/ Vulnerability, Climate change adaptation.

1. INTRODUCTION

Climate change is a pressing global issue that has significant implications for various aspects of society, including the environment, economy, and human health (He, 2017). The impacts of climate change are wide-ranging and can be observed in various regions around the world (Pawełczyk, 2018). To address and mitigate the effects of climate change, it is important to understand the factors that influence individuals’ and communities’ responses and adaptation measures (Devi et al., 2020).

Climate change is a complex issue that requires a multidisciplinary approach to understand and address its impacts (Farida et al., 2017). Factors such as cognitive bias, social discourse, time, money, knowledge, power, entitlements, and social and institutional support all play a role in shaping individuals’ and communities’ responses to climate change (Devi et al., 2020). Effective communication, education, and support systems are crucial in facilitating adaptation to climate change (Terefe, 2022). Furthermore, understanding the economic impacts of climate change and learning from the scientific literature can inform evidence-based policymaking and help mitigate the effects of climate change (Callaghan et al., 2022).

The changing climate in Nigeria is characterized by increasing temperatures, variable rainfall patterns, rising sea levels, and more frequent extreme weather events (Ladan, 2014; Ikumbur & Iornumbe, 2019). These changes have led to adverse effects such as drought, desertification, flooding, and land degradation (Ojomo et al., 2015; Ladan, 2014; Ikumbur & Iornumbe, 2019; Akeh & Mshelia, 2016).

One of the major contributors to climate change in Nigeria is gas flaring, which accounts for approximately 30% of O₂ emissions in the country (Afinotan, 2022). Nigeria has the second highest gas flaring level in the world, and this has significant implications for climate change (Afinotan, 2022).

Climate change has significant impacts on the Niger Delta region of Nigeria, which is known for its oil and gas production. The region is considered a climate change vulnerability hotspot (Atedhor & Odjugo, 2022). The adverse effects of global warming, including rising temperatures and sea levels, have had severe consequences for the Niger Delta ecosystem and its inhabitants (Ogele, 2022).

Studies have revealed that the Niger Delta region of Nigeria is only three meter above mean sea level and their coastline is dynamic in nature which renders hundreds of coastal communities exposed and vulnerable to climate change risk and hazards. The region is faced with seasonal flooding, increase in temperature, high precipitation, erosion, river salinization, ocean surges and siltation (Benson, 2020).

The city of Port Harcourt in the South-south region of Nigeria is not immune to these impacts and has been experiencing the effects of climate change, such as increased temperatures, changing rainfall patterns, rising sea levels, frequent flooding, increased incidence of diseases and agricultural disruptions, extreme climate variations have been observed in recent times and many scholarly works have been carried in this area but the challenges still persist, in order to address these challenges, it is crucial to understand the climate change awareness levels, the impact/ vulnerability and adaptation in Port Harcourt, as well as develop effective adaptation and mitigation strategies.

2. LITERATURE REVIEW

Important theories for climate change encompass a wide range of disciplines and perspectives, reflecting the complex and multifaceted nature of the phenomenon. The understanding of climate change involves not only scientific theories but also social, political, economic, and ethical theories. Frankcombe et al. (2010) emphasize the significance of understanding the dominant time scales and processes in climate variability, which is crucial for developing a comprehensive theory of climate change. This highlights the interdisciplinary nature of climate change theories, as they draw from climatology, geology, and oceanography.

the theories of climate change are multifaceted, encompassing scientific, social, political, economic, and ethical dimensions. They reflect the interdisciplinary nature of climate change and the need for comprehensive, integrated theories to address this complex global challenge.

Climate change awareness is a critical aspect of addressing the challenges posed by climate change. It encompasses the public’s understanding of climate change issues, its impacts, and the necessary behavioural and attitudinal changes to mitigate its effects. Research has shown that climate change awareness is influenced by various factors such as education, gender, and accessibility to information (Kousar et al., 2022; Demaidi & Al-Sahili, 2021; Sesay & Kallon, 2022).

The public’s perception of climate change is also an important aspect of climate change awareness. It has been observed that more vulnerable groups, such as those with lower income and education levels, tend to perceive climate change as more consequential and closer, and as a more natural phenomenon than those from less vulnerable groups (Brügger et al., 2021).

The impact of climate change on Port Harcourt can be seen in various sectors, including the environment, public health, and the economy. A study conducted in the Trans Amadi Industrial area of Port Harcourt assessed climate change adaptation, mitigation, and resilience strategies (Wobo & Benjamin, 2018; Nyashilu et al., 2023). The study utilized satellite imagery and field surveys to gather information and identified the inventory of tree species used in urban greening activities. This highlights the importance of implementing strategies to enhance the resilience of urban areas to climate change.

Climate change has significant impacts on various aspects of the environment, society, and economy, leading to increased vulnerability in many regions. Vulnerability to climate change is defined as the degree to which a system is susceptible to and unable to cope with the adverse effects of climate change (Tanny & Rahman, 2017). Research has shown that climate change vulnerability varies across different sectors and regions, with poorer and hotter countries being more susceptible to its negative impacts (Tol, 2020). Vulnerability is influenced by a range of factors, including economic development, social dynamics, and environmental conditions (Grecequet et al., 2017; Lovett, 2015). For instance, studies have indicated that climate change has profound adverse effects on human health, particularly affecting children’s health (Odunola et al., 2018; Sulistyawati & Nisa, 2016). Nigeria is particularly vulnerable to the devastating effects of climate change due to its low coping capability. However, there is a scarcity of studies on the impacts of climate change on health risks in Nigeria. Monday (2019) investigated the effects of climate change on health risks in Nigeria. The study found that climate change-related causes such as increased temperature, rainfall, sea level rise, extreme weather events, and especially increased health risks have led to several direct consequences of climate change.

Okunola et al., (2022) investigated the factors influencing individual and household adaptation strategies to climate risks in Port Harcourt, the key findings underscore a predominant reactive nature in the adopted climate change adaptation strategies, emphasizing the critical necessity for the incorporation of proactive measures such as early warning systems and preparedness initiatives. Additionally, the study revealed that the effectiveness and intensity of adaptation strategies vary based on residential densities within the city, indicating the importance of tailored approaches that account for specific local contexts. Also, low adaptive capacity of rural households in the region has been said to be influenced by factors such as poverty, lack of education, and limited access to alternative livelihood options (Tonbra, 2021).

Efforts to mitigate and adapt to climate change in the Niger Delta have been limited. The adoption of sustainable land management practices and the promotion of renewable energy sources are potential strategies for addressing climate change in the region (Lokonon & Mbaye, 2018). However, there is a need for increased awareness, capacity building, and policy support to facilitate the adoption of these strategies (Ikehi et al., 2022).

The political and regulatory response to climate change and environmental degradation in the Niger Delta has been inadequate (Benson, 2020; “undefined”, 2019). There is a lack of political will and interest among politicians at all levels of government to address the crisis posed by climate change and environmental degradation (Benson, 2020). The failure to enforce strict antipollution laws and the skewed revenue distribution framework have contributed to the perpetuation of environmental degradation in the region (“undefined”, 2019).

3. METHODOLOGY

The research design employs a detailed desktop review of available research publications, materials and other quantitative and qualitative data, building a qualitative case study backed up with primary survey data acquisition. The primary survey entailed the use of survey tools distributed to a sample size drawn from the sample population of the study area and field observation.

The study area covers Port Harcourt, cutting across several communities. Port Harcourt, affectionately nicknamed “Garden City” or “PH City,” is the capital and largest city of Rivers State in southern Nigeria. Located at 4°45′N 7°00′E, (Figure1.) it rests along the Bonny River, placing it at the heart of one of Africa’s richest oil regions.

Port Harcourt boasts a bustling population of over 3 million people, making it the fifth most populous city in Nigeria. Its diverse inhabitants hail from various ethnic groups, including the Ijaw, Ikwerre, Igbo, and Ogoni, contributing to a rich cultural tapestry. Port Harcourt is bordered by other Rivers State Local Government Areas, including Obio/Akpor, Ikwerre, Etche, and Port Harcourt Local Government Area itself.

Fig. 1 Map showing the location of the study area; Port Harcourt.

Rivers State is one of the 36 States of Nigeria, The State falls within the Niger Delta area known as the South-South geo-political zone, with 40 different ethnic groups, and a population of 5,198,716, according to the 2006 Census by the National Population Commission making it the sixth-most populous state in the country.

Data Collection

A total of 412 questionnaires were administered to same sample size (412) the questionnaire contained 28 questions distributed into various sections including Sociodemographic, Climate change awareness, Climate change impact and vulnerability, Climate change adaptation.

Data Sampling

The study employed a purposive random sampling procedure in the selection of respondents for the study a method chosen to eliminate bias and ensure that each member of the population had an equal chance of being selected. The choice of purposive sampling technique was to select participants who were residents of Port Harcourt, had dwelt up to a year and more in Port Harcourt and were adults above the age of 18 the aim of the purposive sampling was to capture only the perspective of adults who had experienced a longer period of climatic conditions. This approach guarantees a fair representation of the various demographic, socio-economic, and geographic perspective of adult residents who had dwelt a year and more in Port Harcourt. By distributing 412 questionnaires using this method, the study seeks to capture the heterogeneity of the population’s experiences and perspectives regarding climate change.

The Taro Yamane’s formula (Yamane, 1967) was used to come up with an appropriate sample size for the study with five percent (5%) significance level.

n=N/ (1+N (e^2)) where:

n = sample size N = population e = significance level (0.05)

Thus

n = 963,373/ (1+963,373 (0.05^2))

n = 963,373/ (1+963,373 (0.0025))

n = 963,373/ (1+2,408.4325)

n = 963,373/2,409.4325

n = 400

This resulted to a sample size of 400, though 412 respondents were sampled for the primary survey this is because it is not out of place since a sample that is larger than the exact sample size will be a better representative of the population and will hence provide more accurate results.

To collect primary data, a structured questionnaire was designed, encompassing a range of variables to facilitate a comprehensive analysis. The questionnaire included sections addressing climate change awareness, adaptation strategies, resilience measures, and demographic information (such as age, gender, education level, household size, and occupation). The inclusion of these variables allows for a nuanced exploration of how socio-demographic factors may influence individual responses to climate change.

Data Analysis

The initial analysis of primary data, Microsoft Excel was the chosen statistical analysis tool. Descriptive statistics, including frequencies and percentages, were generated to provide a snapshot of participants’ responses. Additionally, regression analysis was employed for a deeper investigation into the relationships between independent variables (e.g., age, gender, education level) and climate change awareness. Logistic regression was specifically used for modelling, while multiple linear regression aided in assessing adaptation measures as well as impact/vulnerability.

ANOVA (Analysis of Variance) was performed to evaluate the overall fit and significance of the regression models. This statistical approach adds robustness to the analysis, allowing for a more comprehensive understanding of the selected factors (variables) influencing climate change awareness, impact/vulnerability and adaptation in the study area.

4. RESULTS

The results of the primary survey on climate change impact awareness and adaptation are presented in four separate tables as follows: table 1. Captures the socio-demographics, table 2. Climate change knowledge and awareness, table 3. Climate change vulnerability assessment and table 4. Climate change adaptation.

Table1. Socio-demographics

	SN	Variable	Frequency	Percentage %
	1	Age
		28 – 37	127	31
		38-47	115	28
		48-57	82	20
		18 – 27	49	12
		68 -77	35	8
		78 or over	4	1
	2	Gender
		Males	209	51
		Females	203	49
3		Level of Education
		SSCE/ O-Level	99	24
		Degree or HND	90	21.8
		A-Level/ Higher/ BTEC	77	19
		Vocational/ NVQ	36	8.7
		NCE/ND	30	7.2
		No formal qualifications	28	6.8
		FSLC/Primary Education	28	6.8
		Postgraduate qualification	21	5
		Others	3	0.7
4		Occupation
		Self-employed/Entrepreneur	121	29
		Business	80	19
		Academia/Education	74	18
		Student/Unemployed	41	10
		Other	36	9
		Civil Servant	31	8
		Retired	29	7
5		Household size
		6 to 10	220	53.39
		1 to 5	109	26.46
		More than 10	79	19.17
		5 to 10	2	0.49
		1 to 4	2	0.49
6		Length of residence in Port Harcourt
		More than 10 years	270	65.53%
		6 to 10years	102	24.76%
		1 to 5 years	37	8.98%
		At Least 1 year	3	0.73%

Table 2. Climate Change Knowledge and Awareness

SN	Variable	Frequency	Percentage %
1	Response to awareness about climate change
	Yes	351	85
	No	61	15
2	Response to Notice of any changes in the climate in the study area over the past few years (e.g., temperature, rainfall patterns, extreme events)
	Yes	362	87.9
	Not Sure	38	9.2
	No	12	2.9
3	Respondents’ response to awareness of the potential impacts of climate change in their community
	Yes	252	61
	Partially	98	24
	No	62	15
4	Respondents’ response to knowledge about the Impact of Climate Change
	Extreme weather conditions	266	64.6
	Extremely cold temperature	229	55.6
	Heatwaves	174	42.2
	Flooding	163	39.6
	Others	7	1.7
5	Respondents’ response to the source of their awareness about climate change
	Television	253	60.4
	Radio	188	44.9
	Social Media platform	175	41.8
	Friends/ Family	155	37.0
	Internet	114	27.2
	Newspaper	106	25.3
	Other	69	16.5
	School/ College/ University	47	11.2
	Energy suppliers	26	6.2
	Local Government Council	18	4.3
	Public libraries	16	3.8
	Government Agencies/ Information	15	3.6
	Specialist publications/academic journals	13	3.1
	Environmental Advocacy groups (e.g., Worldwide Fund for Nature)	12	2.9

Table 3. Climate Change Impact/ Vulnerability Assessment

SN	Value	Frequency	Percentage %
1	Respondents’ response to whether there has been changes in their community they could attribute to Climate Change
	Yes	349	84.7
	No	63	15.3
	Total	412	100
2	Respondents’ response to If yes to (whether there has been changes in your community you can attribute to Climate Change) then what are the changes in climate in your community.
	Changes in rain fall pattern	304	72.6
	Changes in Temperature	264	63.0
	Changes in Relative humidity	60	14.3
	Others	8	2.0
3	Respondents’ response to what the impacts of the changes in climate were.
	Extreme cold	209	50.7
	Heat waves	161	39.1
	Flooding	131	31.8
	Others	15	3.6
4	Respondents’ response to If your answer is No in (13. if there have been changes in your community you can attribute to climate change), then have you experienced extreme heat, cold, flooding, changes in rain fall pattern or Storms?
	Yes	54	12.89
	No	2	0.48
5	Response to whether they were directly dependent on climate-sensitive resources or industries.
	Partially	152	37
	Yes	144	35
	No	116	28
6	Respondents’ response to whether they or any family members had any health condition that could be exacerbated by climate change Impact.
	No	268	65
	Not Sure	79	19
	Yes	65	16

Table 4. Climate Change Adaptation

SN	Value	Frequency	Percentage %
1	Respondents’ response to whether they or their household had taken any measures to adapt to the impact of climate change
	No	304	74
	Yes	108	26
	Total	412	100
2	Respondents’ response to what measures they have taken to cope with climate related challenges in their community.
	Renewable anergy adoption	191	46
	Climate resilient house	98	24
	Water management	87	21
	Others	36	9
3	Respondents’ response to whether there are any existing community-based adaptation measures in place
	Not Sure	245	59
	No	115	28
	Yes	52	13
4	Respondents’ response to aware of any government or non-government programs focused on climate change adaptation.
	No	363	88
	Yes	49	12
5	Respondents’ response to how concerned they were about the future impacts of climate change in their community.
	Concerned	170	41
	Somewhat Concerned	150	36
	Very Concerned	67	16
	Not Concerned	25	6
6	Respondents’ response to whether they thought their community was prepared to handle future climate challenges.
	Not Prepared	254	62
	Somewhat Prepared	136	33
	Prepared	17	4
	Very Prepared	5	1

Statistical Regression Analysis of the Primary Survey.

i. Climate Change Awareness: Tables 5-7 showthe regression statistics, Anova and model results for climate change awareness (the dependent Variable) and Age, Gender, Education Level, Household Size and Occupation (the Independent Variables).

The Multiple R value is 0.2188, suggesting a weak positive correlation between the independent variables and climate change, the R-squared value from the regression statistics of climate change awareness (0.0479) indicates that approximately 4.79% of the variance in climate change can be explained by the combined influence and suggests that the model explains a relatively small proportion of the variance in climate change awareness, indicating that other factors not included in the model may also be influencing the outcomes. The ANOVA table 4.54 suggests that there is a statistically significant relationship between the independent variables (age, gender, education level, household size, and occupation) collectively and the dependent variable (climate change awareness). The low p-value (0.001259394) associated with the F-statistic indicates that at least one of the independent variables in the model is contributing significantly to explaining the variability in climate change awareness.

Looking at the individual predictor coefficients to understand which specific variables are driving this relationship, overall education level and household size have statistically significant relationships with climate change awareness with p-values of 0.005 and 0.008 respectively in this model, while age, gender, and occupation do not.

ii. Climate Change Impact and Vulnerability: Tables 8-10 showthe regression statistics, Anova and model results for climate change impact and mitigation (dependent variable) and changes in temperature, changes in rainfall pattern, changes in relative humidity, Respondents dependence on Climate-Sensitive Resources or Industries? (e.g., Agriculture, Fishing, Forestry), Respondent or family members of respondents having any health conditions that could be exacerbated by Climate Change? (e.g., Respiratory Issues, Cardiovascular Problems) (Independent variables).

The regression statistics suggest that there is a moderate to strong relationship between the predictor variables and the climate change vulnerability assessed. The R squared value indicates that around 51.38% of the variability in vulnerability can be explained by the independent variables in the model. The adjusted R-squared considers the model’s complexity and suggests that approximately 50.78% of the variability is explained.

The Anova result presents a large F-statistic value, with an extremely small associated p-value is, suggesting that the model is a good fit and that the independent variables collectively have a significant impact on explaining the climate change vulnerability being assessed.

the statistical significance of the specific variables in the model using p-values showed changes in temperature, changes in rainfall pattern and changes in relative humidity with p-values of 3.01E-12, 1.5E-33 and 0.010103 respectively to have high significant impact on climate change vulnerability as their p-values were close to 0 (zero).

iii Climate Change Adaptation: Tables 11-13 showthe regression statistics, Anova and model results for climate change adaptation (Dependent Variable) and Climate resilient house, Renewable energy adoption, Water management, whether there are any existing Community-Based Adaptation Measures in place, whether respondents are aware of any Government or Non-Government programs focused on Climate Change Adaptation, how concerned respondents are about the future impacts of Climate Change in their community (the independent variables).

The multiple R value for the regression statistics for climate change adaptation, (0.5218) suggests that there is a moderate positive correlation between the predicted and observed values. R² value of 0.2723 indicates that approximately 27.23% of the variability in the dependent variable is explained by the independent variables included in the model. This means that the model is accounting for a significant portion of the variability, but there are other factors not included in the model that also influence the dependent variable.

The F-statistic is quite high (25.25904), and the associated p-value (1.7544E-25) is extremely low. This suggests that the variability explained by the regression model is significantly greater than what would be expect by chance alone.

Overall, for statistical significance of specific variables, climate resilient house, renewable energy adoption, water management, Community-Based Adaptation Measures and concern about future impacts of Climate Change have statistically significant effects on the dependent variable with p-values of (1.21E-06), (4.24E-05), (2.13E-07) and (0.003261) and (0.000389) respectively. However, Government/Non-Government Programs is not statistically significant in this model with high p-value of (0.9178).

Table 5. Regression statistics for climate change awareness

Regression Statistics
Multiple R	0.218755808
R Square	0.047854104
Adjusted R Square	0.036128169
Standard Error	0.35377172
Observations	412

Table 6. ANOVA for the regression model used for climate change awareness.

ANOVA
	df	SS	MS	F	Significance F
Regression	5	2.553806	0.510761	4.081048	0.001259394
Residual	406	50.8127	0.125154
Total	411	53.3665

Table 7. The regression model variables used in the assessment of climate change awareness.

Variables	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	1.280236532	0.108450991	11.8047472	7.51634E-28	1.067040952	1.49343211	1.067040952	1.493432113
Age	0.03157876	0.017031498	1.85413874	0.064444316	-0.00190217	0.06505969	-0.00190217	0.065059691
Gender	0.065187864	0.035981487	1.811705687	0.070770428	-0.005545412	0.13592114	-0.005545412	0.135921141
Education Level	-0.024131803	0.008483011	-2.84472152	0.004669989	-0.04080791	-0.0074557	-0.04080791	– 0.007455695
Household Size	-0.069495577	0.026084575	-2.66424035	0.008023628	-0.120773264	-0.01821789	-0.120773264	– 0.018217889
Occupation	-0.011930487	0.010463623	-1.14018701	0.254880568	-0.032500131	0.00863916	-0.032500131	0.008639156

Table 8. Regression statistics for Climate Change Impact and Vulnerability

Regression Statistics
Multiple R	0.716815668
R Square	0.513824702
Adjusted R Square	0.507837322
Standard Error	0.240715376
Observations	412

Table 9. ANOVA for the regression model used in the climate change Impact and vulnerability assessment.

ANOVA	df	SS	MS	F	Significance F
Regression	5	24.86313	4.972626	85.81795	2.13699E-61
Residual	406	23.52522	0.057944
Total	411	48.38835

Table 10. The regression model variables used in the climate change vulnerability assessment.

Variables	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95%	Upper 95%
Intercept	0.119150878	0.08522	1.398163	0.162827	-0.048375832	0.286678	-0.04838	0.286678
Changes in temperature	0.205270227	0.028523	7.196549	3.01E-12	0.14919819	0.261342	0.149198	0.261342
Changes in rainfall pattern	0.407610376	0.030765	13.24905	1.5E-33	0.34713132	0.468089	0.347131	0.468089
Changes in relative humidity	0.087637427	0.03391	2.584397	0.010103	0.020975936	0.154299	0.020976	0.154299
Are you dependent on Climate-Sensitive Resources or Industries? (e.g., Agriculture, Fishing, Forestry)	-0.003687286	0.014732	-0.25029	0.802491	-0.03264807	0.025273	-0.03265	0.025273
Do you or any family members have any health conditions that could be exacerbated by Climate Change? (e.g., respiratory Issues, Cardiovascular Problems)	0.03358013	0.021488	1.562722	0.118897	-0.008661951	0.075822	-0.00866	0.075822

Table 11. Regression statistics for Climate Change Adaptation and Resilience

Regression Statistics
Multiple R	0.52183149
R Square	0.272308104
Adjusted R Square	0.261527484
Standard Error	0.380625135
Observations	412

Table 12. ANOVA for the regression model used for Climate Change Adaptation and Resilience

ANOVA	df	SS	MS	F	Significance F
Regression	6	21.95649	3.659416	25.25904	1.7544E-25
Residual	405	58.67457	0.144875
Total	411	80.63107

Table 13. The regression model variables used in the climate change adaptation and resilience.

Variables	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95%	Upper 95%
Intercept	0.18543009	0.160518	1.155199	0.24869	-0.130122233	0.500982	-0.13012	0.500982
climate resilient house	0.228580948	0.046377	4.928738	1.21E-06	0.137410898	0.319751	0.137411	0.319751
renewable energy adoption	0.157359029	0.038015	4.139356	4.24E-05	0.082627006	0.232091	0.082627	0.232091
water management	0.265179948	0.050239	5.278382	2.13E-07	0.16641843	0.363941	0.166418	0.363941
Are there any existing Community-Based Adaptation Measures in place?	0.084938344	0.028699	2.959672	0.003261	0.028521584	0.141355	0.028522	0.141355
Are you aware of any Government or Non-Government programs focused on Climate Change Adaptation?	0.00656221	0.063512	0.103323	0.917758	-0.118291811	0.131416	-0.11829	0.131416
How concerned are you about the future impacts of Climate Change in your Region?	0.086041574	0.024049	3.577705	0.000389	0.038764379	0.133319	0.038764	0.133319

DISCUSSION OF FINDINGS

The most prevalent age groups were 28-37 and 38-47, comprising a significant portion of the respondents (31% and 28% respectively), studies have shown that younger generations are more likely to be concerned about climate change and express a higher level of awareness and interest in climate-friendly behaviours (Petrescu-Mag et al., 2023; Korkala et al., 2014). The gender distribution in the survey demonstrated a balanced representation of male (51%) and female (49%) respondents though with males slightly higher, gender has been said to play a crucial role in climate change adaptation and awareness, gender dimensions in the context of climate change adaptation in coastal communities have shown that gender influences factors such as asset risk and livelihood risk perceptions (Graziano et al., 2018). Three categories of education levels (SSCE/O-Level, Degree or HND & A-Level/Higher/BTEC) had made up most of the responses, accounting for about 65% of the total participants, this is indicative of the fact that a significant portion of the respondents fall within these educational brackets, education has been identified as a key factor in understanding and employing adaptation strategies for climate change and unpredictability (Megabia et al., 2022). Households with a size ranging from 6 to 10 members were the largest category (53.4 %), this observation indicated that a significant portion of families within the community had relatively larger household sizes. Larger households have been noted to have implications for resource consumption, energy usage, and communal dynamics, potentially influencing the strategies and challenges related to climate change resilience. Ahmed & Alam (2015) in Bangladesh found that larger households faced greater challenges in dealing with climate change due to higher resource needs and lower per capita income. Household size has also been found to impact awareness of climate change effects, with larger household sizes being more vulnerable to adverse effects such as reduced agricultural production and food shortages (Ibrahim et al., 2015). Individuals who had lived in Port Harcourt for more than 10 years (66%) constituted the largest group. This significant percentage indicated a substantial portion of long-term residents who likely had deep ties to the community. A study in Chile by Fernandez et al., (2015) have shown that long-term residents tend to perceive more significant climate change over time compared to newcomers.

It is noteworthy that majority of respondents (85%) had heard about climate change, which indicated a relatively high level of awareness on climate change, however, a notable proportion (15%) of respondents had still not heard about climate change. This majority proportion indicates that a substantial segment of the population is indeed conscious of the potential consequences that climate change could bring to their community. The prevalence of climate-related content in television programs, played a significant role in spreading awareness on climate change followed by other media this agrees with (Ju & Jo 2021) who also identified the sources of information through which rural farmers received information on climate change, including personal observation, friends, radio, and television.

The references to changes in weather patterns, increased rainfall, and partial flooding suggested broader alterations in climatic conditions, potentially affecting the community’s susceptibility to extreme weather events and the capacity to manage water-related challenges. A significant majority (84.7%) had indicated noticing changes in their community attributable to climate change, with the most reported frequency as shifts in the community rainfall patterns (72.6%) and temperature, (63%) this substantial percentage underscores the fact that a significant portion of the community perceives climate change as a tangible factor influencing their local environment. This result is in line with the reports of (Stanley et al., 2021) that had high percentage (85-93%) of respondents who had perceived climate change impacts in their community and Ojo et al., (2019) in their study among fishing communities in the Niger Delta, who found that 98% of respondents perceived changes in climate variables like rainfall patterns, temperature, and sea level rise. The most reported impacts as direct results of these changes were extreme cold, heatwaves and flooding.

On the dependence on climate sensitive resources respondents’ perception had suggested that some individuals had recognized a certain level of reliance on sectors such as agriculture, fishing, or forestry, but this dependence hadn’t been absolute as 37% went for “Partially” and 35% “Yes”. Though a study by Onwumodu and Chukwu (2020) found that 85% of respondents relied on climate-sensitive sectors like agriculture and fishing.

Majority of respondents had expressed (“No” 65%) that they didn’t believe that they or their family members had health conditions that might have been worsened by climate change Impact, this perspective suggests that most individuals perceived their health conditions or those of their family members to have been relatively unaffected by changing climatic conditions. Nwaogu and Agunwoke (2020) in neighbouring Imo and Rivers States mentioned limited understanding of health impacts, potentially aligning with the “No” category while the study of Ajaegbu et al. (2015) reflects the (“Not Sure” 19%) category as it mentions limited awareness about specific health impacts. The study of Ebi et al. (2017) which focused on the Niger Delta, highlighted the potential for climate change to worsen existing health conditions aligning with the (“Yes”16%) category of this study.

On climate change adaptation, majority of respondents (74%), had indicated that they or their household hadn’t taken any specific measures to adapt to the impacts of climate change while only 26% did take measures that include the use of renewable energy, climate resilient houses and water management related measures. Low adaptive capacity of rural households in the region has been said to be influenced by factors such as poverty, lack of education, and limited access to alternative livelihood options (Tonbra, 2021).

A good number of respondents (59%) were not sure of any existing community-based adaptation measures in place while some others (28%) believed there were none, this uncertainty could be said to indicate a lack of awareness about such initiatives, potentially pointing towards a need for increased communication and education about community-based adaptation efforts, only 13% were aware of some community initiatives. While for government and non-governmental initiatives a significant 88% were not aware of programmes focused on climate change adaptation, This significant percentage suggests a widespread lack of awareness about initiatives that are specifically aimed at addressing the impacts of climate change and building resilience within the community this corroborates with (Oramah & Olsen, 2021) whom though stated that vulnerability of Nigeria to climate change has led to efforts by the government to develop adaptation and mitigation strategies also noted that institutional capacity for climate change adaptation at the federal, state, and local government levels were still weak. Though with varying levels of concern, overall, a good number of respondents have concerns about the future impacts of climate change in their region. Likewise varying levels of the perceived community preparedness to tackle future climate change impacts; many respondents did not feel their community was prepared for future impacts of climate change.

The individual predictor coefficients to understand which specific variables were driving the relationship between Climate change awareness and the independent variables, overall education level and household size have statistically significant relationships with climate change awareness with p-values of 0.005 and 0.008 respectively in the regression model, while age, gender, and occupation were not statistically significant.

For climate change impact and vulnerability, the statistical significance of the specific variables in the model using p-values showed changes in temperature, changes in rainfall pattern and changes in relative humidity with p-values of 3.01E-12, 1.5E-33 and 0.010103 respectively to have high significant impact on climate change vulnerability as their p-values were close to 0 (zero).

For climate change adaptation Overall, for statistical significance of specific variables, climate resilient house, renewable energy adoption, water management, Community-based adaptation measures and concern about future impacts of climate change had statistically significant effects on climate change adaptation with p-values of (1.21E-06), (4.24E-05), (2.13E-07) (0.003261) and (0.000389) respectively. However, Government/Non-Government Programs was not statistically significant with p-value of (0.9178).

CONCLUSION AND RECOMMENDATIONS.

This study reflects individuals and community’s challenges and opportunities in the face of climate change impacts. These underscores the necessity of promoting awareness, encouraging responsible behaviours, and establishing resilient infrastructure as critical components of government, community and individual response to climate-related challenges.

Although the survey recorded high awareness level of Climate change, many respondents still do not know what the impacts of climate change are though a good number of respondents are aware it is worthy of note that a good number of persons within the sample population relative to the sample size may not be aware of climate change as well as its impact.

likewise, a very low awareness level was recorded for government and non-government initiatives geared towards adaptation and resilience to climate change impact. If this initiatives exist in communities better awareness needs to be created as high percentage of respondent agreed to have heard about climate change via predominantly television and other media platforms same avenues could be utilised by the appropriate authorities to propagate and spread climate change adaption and resilience initiatives, many communities are also not prepared for future outturn of events that may exacerbate the impact of climate change, it is important for the government, local authorities, communities as well as individuals to play an active role in the fight for survival against climate change impact.

Collaborative efforts that involved local residents, authorities, and relevant organizations are key to fostering resilience and implementing sustainable strategies to tackle the consequences of climate change. Integrating climate change into policy processes and improving climate science education can enhance the effectiveness of adaptation and mitigation efforts to reduce the effect of climate change.

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Growing Stronger: The Importance of Mobile Apps in Modern Agriculture

The agricultural sector has undergone a remarkable transformation, transitioning from traditional methods to a highly sophisticated and technologically advanced industry. This digital revolution, often referred to as the agrarian revolution, has profoundly impacted the way we cultivate, harvest, and distribute food. However, with the ever-increasing global population and mounting environmental concerns, traditional farming practices have faced significant challenges in meeting the rising demand for food while maintaining sustainability.

It is in this context that mobile applications have emerged as powerful tools, revolutionizing the agricultural landscape. These innovative apps are designed to address the unique needs of farmers, empowering them with cutting-edge technologies and real-time data insights. By harnessing the power of mobile devices, farmers can now access a wealth of information and capabilities that were once unimaginable, enabling them to make informed decisions and optimize their operations.

The Rise of Mobile Apps in Agriculture

Mobile applications in agriculture have rapidly gained traction, offering a comprehensive suite of features and functionalities tailored to the specific requirements of modern farming. From precision agriculture techniques to automated farming tasks, these apps provide a plethora of tools that streamline operations and enhance productivity. By leveraging advanced algorithms and data analytics, farmers can now make data-driven decisions, reducing the risks associated with traditional farming methods and ensuring optimal resource allocation.

One of the key advantages of these apps from https://www.softwarerepublic.com/ is their ability to provide real-time monitoring and alerts. Farmers can receive timely notifications regarding weather conditions, soil moisture levels, and pest infestations, enabling them to take proactive measures and mitigate potential threats. Additionally, these apps offer seamless integration with various sensors and IoT devices, allowing for remote monitoring and control of farming equipment, irrigation systems, and greenhouses.

Enhancing Productivity and Efficiency

The advent of mobile apps in agriculture has ushered in a new era of precision agriculture, where data-driven decision-making is paramount. By collecting and analyzing vast amounts of data related to soil conditions, weather patterns, and crop growth, these apps empower farmers to make informed decisions regarding planting, irrigation, and harvesting. This level of precision not only optimizes resource utilization but also minimizes waste, ensuring maximum yields and profitability.

Moreover, mobile apps have introduced automation to farming tasks, alleviating the burden of manual labor and streamlining operations. From automated irrigation systems to robotic harvesting machines, these apps seamlessly integrate with advanced technologies, enabling farmers to focus on strategic decision-making while delegating routine tasks to intelligent systems.

Promoting Sustainability and Reducing Waste

In an era where environmental concerns are at the forefront, mobile apps in agriculture play a pivotal role in promoting sustainability and reducing waste. By optimizing resource utilization, such as water, fertilizers, and pesticides, these apps contribute to minimizing the environmental impact of farming activities. Precision agriculture techniques facilitated by mobile apps ensure that resources are applied judiciously, reducing excessive use and minimizing harmful runoff.

Furthermore, mobile apps aid in maximizing crop yields through data-driven decision-making and real-time monitoring. This not only increases profitability for farmers but also contributes to global food security by optimizing the production of essential crops. Additionally, by reducing waste and promoting sustainable practices, these apps align with the growing consumer demand for eco-friendly and ethically sourced agricultural products.

The Future of Smart Farming

The integration of mobile apps in agriculture is just the beginning of a transformative journey towards smart farming. As emerging technologies such as Internet of Things (IoT), Artificial Intelligence (AI), and Big Data continue to evolve, the capabilities of these apps will expand exponentially. Farmers will soon be able to leverage advanced predictive analytics, enabling them to anticipate potential risks and make proactive decisions to mitigate adverse effects.

Furthermore, the integration of mobile apps with autonomous farming equipment and drones will revolutionize the way we approach agriculture. These cutting-edge technologies will not only enhance efficiency but also reduce the physical demands on farmers, paving the way for a more sustainable and environmentally conscious agricultural industry.

In this rapidly evolving landscape, digital literacy among farmers becomes paramount. Embracing these technological advancements and fostering a culture of continuous learning will be crucial for reaping the full benefits of mobile apps and unlocking the true potential of smart farming.

As the world grapples with the challenges of feeding a growing population while preserving the planet’s finite resources, the importance of mobile apps in agriculture cannot be overstated. By empowering farmers with powerful tools, real-time data insights, and innovative solutions, these apps are driving a revolution that promises to shape the future of food production. With their ability to enhance productivity, promote sustainability, and reduce waste, mobile apps are truly the catalysts for a stronger, more resilient, and more prosperous agricultural sector. Embrace the digital transformation, and let the https://www.softwarerepublic.com/ mobile apps pave the way for a greener, more abundant tomorrow.

Sustainable Coffee Farming Practices in Costa Rica

Costa Rica, synonymous with lush landscapes and a commitment to conservation, has long been celebrated for its high-quality coffee. But beyond its flavorful beans lies a deep-rooted dedication to sustainable agriculture that sets it apart. As the world increasingly values eco-friendly practices, Costa Rica’s coffee industry is a beacon of sustainability, blending traditional methods with innovative techniques to ensure a greener future.

Photo by Viktoria Alipatova on Pexels.com

The Role of History:

The history of coffee in Costa Rica is not just a tale of economic success; it’s a narrative deeply intertwined with sustainability. Since coffee first graced its soil in the 19th century, the nation has witnessed the crop shape its cultural and environmental landscape. This legacy continues influencing modern practices, steering the industry towards ecological stewardship and responsible production.

1. Shade-Grown Coffee: Expanded

In Costa Rica, the tradition of shade-grown coffee cultivates a harmonious relationship between agriculture and nature. By growing coffee under the canopy of native trees, farmers create a microclimate that mimics the natural forest environment. This practice conserves water by reducing evaporation and provides an environment for many bird species and insects, promoting biodiversity. The shade regulates temperature, which is essential for the optimal growth of coffee plants, leading to beans that mature slowly and develop a fuller flavor profile. Additionally, the leaf litter from the canopy trees enhances the soil with organic matter, improving its fertility and structure, which is crucial for sustainable coffee farming.

2. Organic Certification: Expanded

Securing organic certification is a significant step for Costa Rican coffee farms, marking their commitment to environmentally friendly and sustainable farming practices. This certification ensures that farms abstain from using harmful synthetic pesticides and fertilizers, opting for natural alternatives that nurture the ecosystem. The move towards organic farming is not just about producing coffee eco-consciously; it’s about ensuring the health of the land for future generations. Organic practices help maintain the balance of the local ecosystems, supporting everything from the microorganisms in the soil to the wildlife that calls these coffee plantations home. In doing so, they also reduce the carbon footprint associated with coffee production, contributing to global environmental sustainability efforts.

3. Water Conservation Techniques: Expanded

Water is a precious resource in coffee production, and Costa Rican coffee farms are at the forefront of implementing innovative conservation techniques. By recycling wastewater from coffee washing, farms can significantly reduce water usage. This recycled water is often treated and reused for irrigation, minimizing the impact on local water bodies. Additionally, moisture-conserving irrigation systems, such as drip irrigation, target water directly to the roots of the plants, where it’s most needed, reducing wastage. These water conservation efforts are crucial in ensuring the sustainability of coffee farming in Costa Rica, especially in the face of changing climate weather patterns and water scarcity.

4. Use of Biodegradable Products: Expanded

The shift towards using biodegradable products in Costa Rican coffee farms is a testament to the industry’s commitment to reducing environmental impact. From biodegradable coffee bags to natural pest control methods, these practices minimize waste and pollution, preserving Costa Rica’s pristine environment. This approach extends beyond the farms, influencing packaging and distribution processes to ensure the coffee reaches consumers with the smallest possible ecological footprint. By adopting biodegradable materials, coffee producers safeguard the environment and appeal to eco-conscious consumers worldwide, further promoting sustainable coffee consumption.

5. Soil Erosion Control: Expanded

Soil is the foundation of any agricultural endeavor, and its preservation is paramount in sustainable coffee farming. In Costa Rica, erosion control measures such as terracing, cover cropping, and planting nitrogen-fixing plants are employed to protect and enhance soil health. Terracing prevents runoff and conserves soil on sloped plantations, while cover crops protect the soil surface from erosion by rain or wind. Nitrogen-fixing plants enrich the soil by naturally adding nitrogen, reducing the need for synthetic fertilizers. These practices maintain soil fertility and ensure the long-term viability of coffee plantations, securing the future of coffee farming in the region.

6. Agroforestry Systems: Expanded

Agroforestry systems represent a blend of agriculture and forestry, creating a diversified, productive, and sustainable land-use system. In Costa Rica, integrating coffee plants with other crops and trees enhances the ecological value of coffee plantations. This method increases biodiversity, improves pest and disease control, and strengthens the resilience of the coffee plants against extreme weather conditions. The additional trees and crops provide alternative income sources for farmers, further contributing to the economic sustainability of coffee farming. Agroforestry benefits the environment and enriches the social fabric of farming communities by offering a more stable and diversified livelihood.

7. Renewable Energy Use: Expanded

The adoption of renewable energy sources by Costa Rican coffee producers marks a significant step towards reducing the environmental impact of coffee production. Solar panels, biomass energy from coffee waste, and hydroelectric systems are increasingly common on farms, powering everything from coffee processing facilities to irrigation systems. This transition to renewables decreases coffee production’s carbon footprint and leads to cost savings in the long run. By harnessing the power of nature to fuel their operations, coffee farms set an example for sustainable practices that other industries can follow.

8. Supporting Local Communities: Expanded

Sustainability in coffee farming extends beyond environmental considerations to include the well-being of local communities. In Costa Rica, fair trade practices ensure coffee farmers receive a reasonable crop price, promoting social equity. Additionally, many coffee producers invest in community projects, such as building schools and health clinics, and offer educational programs to improve literacy and agricultural knowledge. These initiatives encourage a sense of community and shared responsibility, ensuring that the benefits of coffee production are felt by everyone involved.

9. Crop Diversification: Expanded

Diversification is a crucial strategy for resilience in coffee farming. Costa Rican farmers can protect their income against market fluctuations and environmental challenges by cultivating various crops alongside coffee. This approach also benefits the soil by reducing the risk of pest and disease outbreaks associated with monoculture. Furthermore, diversification promotes a more balanced diet for farming communities and enhances the overall sustainability of agricultural practices in the region.

10. Continuous Education and Training: Expanded

Knowledge is at the heart of sustainable coffee farming. In Costa Rica, ongoing education and training for farmers are crucial in promoting the best agriculture practices. Workshops, seminars, and field days provide farmers with the latest information on sustainable techniques, from organic pest management to water conservation. This continuous learning ensures that coffee production evolves with new environmental challenges and market demands, securing its place as a model of sustainability for the world.

Conclusion:

Costa Rica’s journey in sustainable coffee farming is a testament to the country’s dedication to environmental stewardship and social responsibility. These ten practices highlight how the nation’s coffee industry has become a global leader in sustainability, setting standards that others aspire to. The commitment to a greener future is palpable for those fortunate enough to experience these initiatives firsthand while staying in a luxury villa in Costa Rica. Beyond enjoying the serene beauty and comfort of such accommodations, visitors can savor a cup of Costa Rican coffee, knowing it comes from a place where luxury meets sustainability and where every bean tells a story of dedication to the planet and its people.

COTTON

PATTIKONDA:26/02/2020.

Cotton is a soft, fluffy staple fiber that grows in a boll, or protective case, around the seeds of the cotton plants of the genus Gyopssisum in the mallow family Malvacae. The fiber is almost pure cellulose. Under natural conditions, the cotton bolls will increase the dispersal of the seeds. The plant is a shrub native to tropical and subtropical regions around the world, including the Americas, Africa, Egypt and India.

The fiber is most often spun into yarn or thread and used to make a soft, textile.Current estimates for world production are about 25 million tonnes or 110 million bales annually, accounting for 2.5% of the world’s arable land. India is the world’s largest producer of cotton. it is the most widely use natural fiber cloth in clothing today.The United States has been the largest exporter for many years.

There are 4 types of cotton:
Gossypium hirsutum – upland cotton, native to america
Gossypium barbadense– known as extra-long staple cotton, native to tropical South America
Gossypium arboreum– tree cotton, native to India
Gossypium Herbecea – Levant cotton

Planting time in spring in the Northern hemisphere varies from the beginning of February to the beginning of June.Cotton is naturally a perennial but is grown as an annual to help control pests.cotton grown today is cultivated in areas with less rainfall that obtain the water from irrigation.Cotton can also be cultivated to have colors other than the yellowish off-white typical of modern commercial cotton fibers.

The bacterium Bacillus thuringiensis (Bt) naturally produces a chemical harmful only to a small fraction of insects, most notably the larvae of moths,insects,butterflies and flies, and harmless to other forms of life.The gene coding for Bt toxin has been inserted into cotton, causing cotton, called Bt cotton, to produce this natural insecticide in its tissues.Cotton has gossypol, a toxin that makes it inedible. Bt cotton is ineffective against many cotton pests, and however, such as plant bugs,aphids and stink plants.

Cotton is used to make a number of textile products. These include terrycloth for highly absorbent bath towels,denims,robes,cambric, popularly used in the manufacture of blue work shirts and cotton twill. Socks ,clothes and most T shirts are made from cotton. Bed sheets often are made from cotton. Cotton also is used to make yarn used in crocheted and knitting. In the Textile industry, cotton is used in Fishing nets,coffee filters,Tentsexplosives manufacture cotton paper, and in book binding. Fire hoseswere once made of cotton.

DAM FAILURES

PATTIKONDA:24/07/2020.

A dam failure or dam burst is a catastrophic type of failure characterized by the sudden, rapid, and uncontrolled release of impounded water. Between the years 2000 and 2009 more than 200 notable dam failures happened worldwide. A dam is a barrier across flowing water that obstructs, that directs or slows down the flow, often creating a reservoir,lake or impoundments.

Dam failures are comparatively rare, but can cause immense damage and loss of life when they occur.Other cases include the Chinese bombing of multiple dams during typhoon NINA in 1975 in an attempt to drain them before their reservoirs overflowed.

Sub-standard construction materials/techniques
Spillway design error (near failure of
Lowering of dam crest height, which reduces spillway flow
Geological instability caused by changes to water levels during filling or poor surveying
Sliding of a mountain into the reservoir – not exactly a dam failure, but caused nearly the entire volume of the reservoir to be displaced and overtop the dam)
Poor maintenance, especially of outlet pipes
Extreme inflows.
Human, computer or design error or piping, especially in earthen dams
Earthquakes.

The main causes of dam is overtopping: The crest dam is too high than capacity level.Foundation defects: error in constructions and failures of dam.Piping and seepage failures:These failures occur as a result of internal erosion caused by seepage and erosion.Conduit and valve failure: These failures occur as a result of problems with values and conduits.

Dam failures can be extremely harmful, especially because dams are considered “installations containing dangerous forces”.Many dam failures are also secondary results of other natural disasters such as earthquakes, land slides,heavy stroms, or heavy snow-melt. Other causes include equipment malfunction, structural damage, and sabotage.

In INDIA, The major failure is Machchhu dam failure or Morbi disaster was a dam-related flood disaster which occurred on 11 August 1979. The Machchu-2 dam, situated on the Machhu river, burst, sending a wall of water through the town of Morbi of Gujarat, India. The another dam failure is ratnagiri dam failure in 2019 in maharastra.

‘Need To Push Agricultural Related Infrastructure In Rural Parts Of The India”

Despite of Indian backbone and huge possibilities and potential sector Agriculture treated as a sick industry in India, why this so ironic to call Sick even it involved about sixty percent of the people gives about twenty percent of the GDP still marked as a symbol of low status in India, it was eighteen hundred and fifty seven when Indian peasantry aroused against the Britishers ignited the the great revolt of independence which was supported by peasants on large scale Indian peasants gives their man money and spirit to rise against the Britishers. and this urge britishers to impose tax collection systems they invented Zamidari system Ryotwari system collected tax according to their wish and britishers broke the backbone of indian agriculture breaking peasants and putting them under harsh conditions. and up-to the 1947 Indian Agriculture was at the weakest point and Britishers policies and systems create a mindset of sickness towards agriculture. But instead of all the miserable conditions Agriculture connects man to land in rural India agriculture is treated as a tradition as a social practice and means to life. Today if we need Economy on stable basis if economy have to be strengthened that strength can be induced by agriculture. India had twelve months of the sunshine water and we are capable of growing crops full twelve months otherwise united states they can not grow crops three month in a year Several parts of Europe can not grow six months in a year. but In India we can grow crops full year and almost we can do triple the production. we need only Some good practices , monitoring and infrastructural changes.

Is Indian land capable of sustaining it ?

Indian land without any question is capable of sustaining it. it was under ‘Lal Bahadur Sastri’ tenure when India nearly had a Famine Every Indian waiting for another bag of wheat from United states and a famous headline of those times India living ship to mouth but Lal Bahadur Sastri brought up a package of Seeds and gave ten to twenty percent to farmers and India became self sufficient in Food grain production.

Hence, Indian Rural Agriculture needs Infrastructural development which can contribute to prosper Living standards and have might to increase per capita income.

Initial needs : farmers need quality seeds , procurement market of seeds good machines for seeding.

At the time of cultivation :

farmers needs proper facility of fertilizers, good pesticides, good insecticides and practices with modified machines.

Irrigation Facilities:

Irrigation is one of the important factor for growing Crops for which farmers needs good canals tube-wells electricity for deriving them or farmers can approach to solar energy used pumps etc.

Stock Facilities :

After cultivating the crops stock of the material is another challenge in front of farmers. In India in the rural parts of it Farmers does not have proper Storage Facilities. Farmers Need good Stock markets so that they can stay their stock for long time.

Transportation Facilities :

Transportation is the major problem of every rural farmer. Rural parts of the country does not have good means of connectivity Transportation is considered to be the important aspect of Buisness and good connectivity can lead Agricultural products to the new markets where farmers can available with better prices for their agricultural commodities.

Marketing Facilities:

Lack Of local ‘Mandi’ and markets farmers are unable to Sell their Agriculture Commodities on better prices. and this leads benefits to the stakeholders which make it lucrative between the farmers and retailers.

There are various ways which should be regulated for enhancing the Rural Infrastructure like GOI should increase the financial assistance to the farmers through NABAR credit facilities and various cooperatives societies and loan facilities. Contract farming should be encouraged between farmers and company. etc.

Agriculture is the basis of Livelihood, it connects people with the land and have huge potential and Power to transform Indian socio economic vision.

Let us change and make a revolution

Time for change *

“The door for change is open for all time. The next moment we take the first step from us, the universe will create all the forces for achieving it,” said , Nammazlvar – The agriculture scientist
This proverb is very consistent with the changes of the emerging 2020s. It is time for change. * Food is the medicine and the medicine is the food* where this line gets immunity nowadays in this pandemic of Covid 19 to grow up our immune system.
The claim is that this community is growing and growing. With the economic downturn, hunger, disease and long-distance migrant workers, all they can expect is just a good meal.
Agriculture is the backbone of the Indian economy but it accounts for only 14% of GDP.

Reliance, Tata Families Why Don’t Invest in Agriculture?
If they do, the new farming technologies abroad will benefit the Indian people, and it may inspire a lot of small investors. We go with the lure of money. So the top investment in agriculture is to make a good profit.

Have Ambani not invested in agriculture ? In 1997, the Jamnagar Refinery was one of the country’s largest pollutants and was the biggest threat to Reliance. After a serious threat from the government, they turned the Jamnagar barren wasteland into a mango orchid. Currently it is said to be * Dhirubai Ambani Lakhibag Amrayee *. It is the best mango orchid in Asia. More than 1.3 lakh plants of over 200 species.

In a few years the barren lands were turned into lush countryside.
The mangoes produced are excellent in quality and are widely exported worldwide. The company has become one of the biggest exporters of mangoes in the society and a great business opportunity.
While large investment firms invest in agriculture, the resilience of farmers of intermediaries and agricultural marketing comes to an end. It will also be a major contributor to Indian GDP and stimulate raise in the standard of living. Needs are becoming greater for man because of the involvement of money but changes in lifestyle.

Similarly, the impact of food production on India’s independence was very worrying. The sky is gone. Due to the lack of food, starvation deaths among people have developed into a disease in India. The Green Revolution was a project introduced in the 1940s. It is still spoken of as a major contributor to the uplift of the socioeconomic economy.
The result? Controversies of the Green Revolution Project. The project was based on the people then, and as a result, chemicals are causing diabetes, cancer and infertility. We have been restoring natural agriculture quite a bit. We need to create natural agriculture as a gateway to change.

The kitchen gardening revolution of 2020 where you grow you eat healthier as much . It helps in preventing the toxic chemicals , purely hygienic nutrients that enhance your immune and to a part of hobby, exercise etc.

“It’s time for change, let’s get rid of the sickness, let the dawn of the eyes of the owl come to life. Let us value the nutritious food.
Dharshini N.

World Food prize 2020

Soil scientist Dr. Rattan Lal

The World Food Prize is an international award recognizing the achievements of individuals who have advanced human development by improving the quality, quantity, or availability of food in the world. The prize has been awarded annually to recognize contributions in any field involved in the world food supply: Animal Science/Aqua Culture, Soil Science/Water/Conservation, Nutrition/Health, Plant Science/Seed Science, Plant Pathology/Crop Protection, Food Technology/Food Safety, Policy/Research/Extension, Infrastructure/Emergency Relief, & Poverty Alleviation/Hunger. The World Food Prize is considered equivalent to the Nobel Prize in the field of Agriculture, and the recipient is awarded $250,000 for improving the quality and availability of food.

“This year 2020, Indian- American Soil scientist Dr. Rattan Lal wins prestigious World Food Prize.”An alumnus of Punjab Agricultural University (PAU) and Indian Agricultural Research Institute,New Delhi and a renowned agricultural soil scientist from Ohio State University (OSU). Dr.Lal has been named as this year’s recipient of the World Food Prize for developing and mainstreaming a soil-centric approach to increasing food production that conserves natural resources and mitigates climate change.

The World Food Prize Foundation President Barbara Stinson announced Lal as the winner in an online ceremony in Washington DC ,Thursday 11 June. The ceremony featured pre-recorded remarks from US Secretary of State Mike Pompeo and US Secretary of Agriculture Sonny Perdue.

“The unbound joy and excitement of receiving the 2020 World Food Prize reminds me about the gratitude, privilege and honour of working for farmers from around the world ” Dr. Lal said.

Dr. Lal’s model indicates that restoring soil health can lead to multiple benefits by the year 2100, including more than doubling the global annual grain yield to feed the growing world population, while decreasing the land area under grain cultivation by 30 per cent and decreasing fertiliser use by half. His research led a better understanding of how no-till farming, cover crops, crop residues, mulching, and agroforestry can restore degraded soils, increasing organic matter by sequestering atmospheric carbon in the soil, and help combat rising carbon dioxide levels in the air.

“Dr Lal’s research in soil science shows that the solution to this problem is right under our feet. He’s helping the earth’s estimated 500 million small farmers be faithful stewards of their land through improved management, less soil degradation, and the recycling of nutrients. The billions of people who depend on these farms stand to benefit greatly from his work. “- Secretary Pompeo.

The World Food Prize was established by Nobel Peace Prize laureate Norman E Borlaug in 1986.The first recipient of this award was Indian Agricultural Scientist Dr. M. S. Swaminathan in 1987,regarded as “Father of India’s Green Revolution.

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