<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article">
 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">
    ajcc
   </journal-id>
   <journal-title-group>
    <journal-title>
     American Journal of Climate Change
    </journal-title>
   </journal-title-group>
   <issn pub-type="epub">
    2167-9495
   </issn>
   <issn publication-format="print">
    2167-9509
   </issn>
   <publisher>
    <publisher-name>
     Scientific Research Publishing
    </publisher-name>
   </publisher>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="doi">
    10.4236/ajcc.2024.133025
   </article-id>
   <article-id pub-id-type="publisher-id">
    ajcc-135761
   </article-id>
   <article-categories>
    <subj-group subj-group-type="heading">
     <subject>
      Articles
     </subject>
    </subj-group>
    <subj-group subj-group-type="Discipline-v2">
     <subject>
      Earth 
     </subject>
     <subject>
       Environmental Sciences
     </subject>
    </subj-group>
   </article-categories>
   <title-group>
    Farmers’ Knowledge and Perceptions of the Effects of Climate Variability and Pollution on Crop Production and Their Varying Adaptation Strategies in The Gambia
   </title-group>
   <contrib-group>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Pierre Anthony
      </surname>
      <given-names>
       Mendy
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Mawa
      </surname>
      <given-names>
       Kone
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Ado Baba
      </surname>
      <given-names>
       Ahmed
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Sidat
      </surname>
      <given-names>
       Yaffa
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff3"> 
      <sup>3</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Alpha
      </surname>
      <given-names>
       Kargbo
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Afua Amponsah
      </surname>
      <given-names>
       Amankwah
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Kossi-Messan Jacques
      </surname>
      <given-names>
       Agboka
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Blessing Chinomso
      </surname>
      <given-names>
       Okorie
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Assan
      </surname>
      <given-names>
       Sowe
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff4"> 
      <sup>4</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Echene
      </surname>
      <given-names>
       Jatta
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff5"> 
      <sup>5</sup>
     </xref>
    </contrib>
   </contrib-group> 
   <aff id="aff1">
    <addr-line>
     aDepartment of Physical and Natural Sciences, School of Arts&amp;Sciences, University of The Gambia, Banjul, The Gambia
    </addr-line> 
   </aff> 
   <aff id="aff2">
    <addr-line>
     aWest African Science Service Centre on Climate Change and Adapted Land Use (WASCAL), Department of Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d’Ivoire
    </addr-line> 
   </aff> 
   <aff id="aff3">
    <addr-line>
     aSchool of Agriculture and Environmental Sciences, University of The Gambia, Banjul, The Gambia
    </addr-line> 
   </aff> 
   <aff id="aff4">
    <addr-line>
     aSchool of Education, University of The Gambia, Banjul, The Gambia
    </addr-line> 
   </aff> 
   <aff id="aff5">
    <addr-line>
     aDepartment of Sociology and Social Work, College of Humanities and Social Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
    </addr-line> 
   </aff> 
   <pub-date pub-type="epub">
    <day>
     31
    </day> 
    <month>
     07
    </month>
    <year>
     2024
    </year>
   </pub-date> 
   <volume>
    13
   </volume> 
   <issue>
    03
   </issue>
   <fpage>
    543
   </fpage>
   <lpage>
    566
   </lpage>
   <history>
    <date date-type="received">
     <day>
      23,
     </day>
     <month>
      April
     </month>
     <year>
      2024
     </year>
    </date>
    <date date-type="published">
     <day>
      1,
     </day>
     <month>
      April
     </month>
     <year>
      2024
     </year> 
    </date> 
    <date date-type="accepted">
     <day>
      1,
     </day>
     <month>
      September
     </month>
     <year>
      2024
     </year> 
    </date>
   </history>
   <permissions>
    <copyright-statement>
     © Copyright 2014 by authors and Scientific Research Publishing Inc. 
    </copyright-statement>
    <copyright-year>
     2014
    </copyright-year>
    <license>
     <license-p>
      This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/
     </license-p>
    </license>
   </permissions>
   <abstract>
    Crop and livestock production is critical to food security in The Gambia. Over the years, the country has experienced a reduced yield due to perceived climate change events with limited studies on how climate change and pollution affect crop production. This study assesses farmers’ knowledge and perceptions of the effects of climate variability and pollution on crop production and their varying adaptation strategies in The Gambia. Both quantitative and qualitative methods were used in this study. The sample size for quantitative data collection was calculated as 432 while the qualitative data involves both the focus group discussions and key informant interviews. The focus group discussions comprised two districts in each of the six agricultural regions and two farming communities engaged in crop production were chosen from each district. Furthermore, eight key informant interviews from relevant institutions were conducted. The study shows that The Gambia is highly vulnerable to extreme climatic events. Although most farmers opined that agricultural land contamination emanates from farm runoff and indiscriminate waste dumping, they had little knowledge of heavy metal pollution and bioremediation. The results showed that farmers experienced constraints such as inadequate access to credit, water, and irrigation facilities, insufficient access to efficient inputs, salt intrusion, etc. which threatened food security. The study concludes that crop farmers acknowledged the existence and impacts of climate change, and therefore recommend the availability and affordability of climate change resilient crops and promote variability awareness campaigns to address climate change impacts in The Gambia.
   </abstract>
   <kwd-group> 
    <kwd>
     Climate Change
    </kwd> 
    <kwd>
      Extreme Weather
    </kwd> 
    <kwd>
      Vulnerability
    </kwd> 
    <kwd>
      Risks
    </kwd> 
    <kwd>
      Hazards
    </kwd> 
    <kwd>
      Adaptation Strategies
    </kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body>
  <sec id="s1">
   <title>1. Introduction</title>
   <p>Climate change is an environmental menace with devastating effects that have drawn scientists’ attention over the past several decades (<xref ref-type="bibr" rid="scirp.135761-50">
     Patt &amp; Schröter, 2008
    </xref>; <xref ref-type="bibr" rid="scirp.135761-1">
     Abid et al., 2015
    </xref>). In developing nations, the projections of weather and climate variabilities forecast changing climates with high vulnerability (<xref ref-type="bibr" rid="scirp.135761-25">
     Easterling et al., 2000
    </xref>; <xref ref-type="bibr" rid="scirp.135761-39">
     Khan et al., 2020
    </xref>). Regarding vulnerabilities, climate change has injurious effects on poor agricultural and rural communities of developing countries because of their low-income status and inadequate adaptive mechanisms (<xref ref-type="bibr" rid="scirp.135761-13">
     Barker et al., 2007
    </xref>; <xref ref-type="bibr" rid="scirp.135761-57">
     Skoufias et al., 2011
    </xref>). In addition, fluctuations in weather conditions are likely to upsurge the frequency and magnitude of several climatic threats, such as floods, storms, droughts, etc. (<xref ref-type="bibr" rid="scirp.135761-39">
     Khan et al., 2020
    </xref>).</p>
   <p>Nowadays, climate change is one of the main environmental hazards that greatly threatens plants, animals, and humans. This phenomenon can generate fluctuations, such as rising sea levels, erratic rainfall, and shifts in climatic regions due to increasing temperatures. The degree of droughts, storms, and floods is predicted to rise and be influenced greatly by the changes in climate patterns. The hazards associated with weather and extreme climate events can increase significantly due to the increase in climatic variability (<xref ref-type="bibr" rid="scirp.135761-6">
     Akcaoz &amp; Ozkan, 2005
    </xref>; <xref ref-type="bibr" rid="scirp.135761-5">
     Ahmad et al., 2007
    </xref>), consequently changing the degree, rate, and spatial amount of disasters, such as floods and droughts (<xref ref-type="bibr" rid="scirp.135761-60">
     Udmale et al., 2014
    </xref>). Such changes will cause the manifestation of extreme weather and climate events with substantial impact (<xref ref-type="bibr" rid="scirp.135761-13">
     Barker et al., 2007
    </xref>; <xref ref-type="bibr" rid="scirp.135761-32">
     Hay &amp; Mimura, 2010
    </xref>), which will generate immense pressure on communities, natural systems, societies, and economies struggling to cope with other non-climatic threats that seriously impede the sustainable development endeavours of the government and non-governmental organizations (<xref ref-type="bibr" rid="scirp.135761-32">
     Hay &amp; Mimura, 2010
    </xref>).</p>
   <p>Although there is rapid advancement in technology concerning mechanization, the weather is still a primary factor in determining agricultural productivity (<xref ref-type="bibr" rid="scirp.135761-39">
     Khan et al., 2020
    </xref>). Rainfall and temperature are the main drivers in crop production and rural food security (<xref ref-type="bibr" rid="scirp.135761-62">
     Wheeler &amp; Braun, 2013
    </xref>; <xref ref-type="bibr" rid="scirp.135761-7">
     Akhtar et al., 2019
    </xref>). Elevated climate variability and extreme weather conditions affect crop and livestock production (<xref ref-type="bibr" rid="scirp.135761-33">
     Howden et al., 2007
    </xref>; <xref ref-type="bibr" rid="scirp.135761-21">
     Chaudhary &amp; Aryal, 2009
    </xref>) with a considerable increase in the incidence of insects, pests, and diseases which are projected to affect the farming sector adversely as it would result to the deterioration of soil microorganisms’ metabolism and water content (<xref ref-type="bibr" rid="scirp.135761-40">
     Liverman, 2008
    </xref>; <xref ref-type="bibr" rid="scirp.135761-51">
     Paudel et al., 2014
    </xref>). Extreme weather and climate variabilities highly influence agricultural mechanization in climate conditions (e.g., rainfall, temperature, humidity, etc.), shaping the natural hazards and influencing income distribution and farmers’ livelihoods. The crop productivity in a specific area, region, or location is determined greatly by local rather than global climatic conditions (<xref ref-type="bibr" rid="scirp.135761-51">
     Paudel et al., 2014
    </xref>; <xref ref-type="bibr" rid="scirp.135761-39">
     Khan et al., 2020
    </xref>).</p>
   <p>Floods and droughts are the most common and frequent natural hazards that extensively cause economic and social risks for humans, especially in less economically endowed and vulnerable communities with meagre adaptive capabilities. Further, an increase in these extreme events can cause global warming and might impose additional hurdles to sustainable development, which will cause food insecurity and hinder poverty alleviation. Countries located at low latitudes, especially developing countries, are more prone to extreme weather and climate events than countries in high latitudes because they are highly exposed to climatic hazards in the form of increased surface temperature and fluctuation in precipitation (<xref ref-type="bibr" rid="scirp.135761-10">
     Ali &amp; Erenstein, 2017
    </xref>). Research has predicted that by 2080, the risk of hunger and starvation can seriously affect over 170 million people globally (<xref ref-type="bibr" rid="scirp.135761-55">
     Schmidhuber &amp; Tubiello, 2007
    </xref>).</p>
   <p>Although The Gambia contributes very little (less than 0.01%) to global greenhouse gas emissions as compared to other nations (<xref ref-type="bibr" rid="scirp.135761-20">
     Cham et al., 2018
    </xref>), its development agenda could be seriously impacted by climate events. Already droughts, floods, windstorms, increased temperatures, and shortened rainfall lengths are recorded and projected to occur in the future. Due to the subsistence nature of the agricultural production system, characterized by low investment and being highly rain-fed dependent, it is apparent that these menaces will affect agricultural productivity (<xref ref-type="bibr" rid="scirp.135761-20">
     Cham et al., 2018
    </xref>).</p>
   <p>There is little research being done on the risks associated with extreme weather and climate events, farm-level vulnerability, and adaptation strategies in The Gambia. Therefore, the specific objective of this study is to assess farmers’ knowledge and perceptions of the effects of climate variability and pollution on crop production and their varying adaptation strategies in The Gambia. This would enable the government, NGOs, and philanthropists to have a clearer picture and put more effort into the development of the agrarian industry in the country. The outcome of this research will serve as a benchmark for future research and a reference point for policymakers in devising appropriate adaptation policies to facilitate agrarian communities in sustaining their livelihoods against future climate-related risks.</p>
  </sec><sec id="s2">
   <title>2. Materials and Methods</title>
   <sec id="s2_1">
    <title>2.1. Study Area</title>
    <p>The Gambia is at the western end of West Africa, located at 13˚28.02' North 16˚34.02' West. The total territory area of the country is approximately 11,300 km<sup>2</sup>, which is divided into landmass and water surface areas of approximately 1300 km<sup>2</sup> and 10,000 km<sup>2</sup>, respectively, thus making the country one of the smallest in mainland Africa (<xref ref-type="bibr" rid="scirp.135761-11">
      Ampomah et al., 2012
     </xref>; <xref ref-type="bibr" rid="scirp.135761-15">
      Belford et al., 2023
     </xref>). The country is situated in the tropical sub-humid ecoclimatic zone, with annual rainfall ranging from 800 to 1200 mm annually (<xref ref-type="bibr" rid="scirp.135761-38">
      Kargbo et al., 2021
     </xref>). There are two seasons experienced in this climate zone: a rainy season (June to October) and a dry season (November to May) consisting of approximately six to seven months of dry period (<xref ref-type="bibr" rid="scirp.135761-37">
      Josephine et al., 2020
     </xref>; <xref ref-type="bibr" rid="scirp.135761-14">
      Barrow et al., 2020
     </xref>). During the dry season, the climate is dominated by dry, and dusty winds, which originate from the Sahara Desert (<xref ref-type="bibr" rid="scirp.135761-38">
      Kargbo et al., 2021
     </xref>).</p>
    <p>The socio-cultural activities are associated with customs, lifestyles, and values, which characterize the demographics, religion, attitudes, economic status, class, and language (<xref ref-type="bibr" rid="scirp.135761-44">
      Mutsikiwa &amp; Basera, 2012
     </xref>). The 2013 Population and Housing Census revealed that The Gambia has a population of 1,882,450 with a density of 176 persons per km<sup>2</sup> (<xref ref-type="bibr" rid="scirp.135761-30">
      Gambia Bureau of Statistics (GBoS), 2013
     </xref>; <xref ref-type="bibr" rid="scirp.135761-37">
      Josephine et al., 2020
     </xref>). The country has six Agricultural Administration Regions and an Urban Region, which comprises of Kanifing Municipal Council and Banjul. According to <xref ref-type="bibr" rid="scirp.135761-36">
      Jaiteh and Saho (2003)
     </xref>, the main ethnic groups were as follows: Mandingoes (36%), Fulani (22%), Wollofs (15%), Jolas (11%), Sarahuli (8%), Serer (2.5%)), Manjaku (1.7%) and others (4%) (<xref ref-type="bibr" rid="scirp.135761-12">
      Badgie, 2018
     </xref>).</p>
    <p>The Gambia is among those countries most vulnerable to climate change (<xref ref-type="bibr" rid="scirp.135761-17">
      Camara, 2013
     </xref>). The Coastal wetlands, tidal flats, marshes, colluvial slopes, and uplands along the River Gambia characterize the topography of The Gambia. Rice and other crops are cultivated in all these highly variable environments, with land preparation and cropping techniques depending on the soil type, hydraulic conductivity, and tidal flows (<xref ref-type="bibr" rid="scirp.135761-26">
      Engel-Di Mauro, 2012
     </xref>) (<xref ref-type="fig" rid="fig1">
      Figure 1
     </xref>).</p>
   </sec>
   <sec id="s2_2">
    <title>2.2. Research Design</title>
    <p>A cross-sectional study was conducted in the six Agricultural Regions of The Gambia from Number 2022 to March 2023. Primary data was used for the study. Primary data used was in the form of structured (quantitative research) questionnaires, Focus Group Discussions (FGDs), and Key Informant Interviews (KIIs) in 2023. The FGDs and KIIs used unstructured questionnaires (qualitative research). The structured questionnaires were administered to 432 crop farmers. Both the questionnaires (quantitative and qualitative) covered farmers’ knowledge and perceptions of the effects of climate variability and pollution on crop production and their varying adaptation strategies in The Gambia. The combination of both quantitative and qualitative approaches provides a more holistic understanding of the research question than either approach singly (<xref ref-type="bibr" rid="scirp.135761-23">
      Creswell &amp; Angeles, 2006
     </xref>).</p>
   </sec>
   <sec id="s2_3">
    <title>2.3. Data Collection</title>
    <p>Participants were carefully chosen using a random sampling approach. Adopting <xref ref-type="bibr" rid="scirp.135761-9">
      Al Mansour (2020)
     </xref> formula, where n is the sample size, z is the standard error associated with the chosen level of confidence (1.96), p is the estimated prevalence (0.50), q is 1 − p (0.50), and d is the acceptable error (0.05):</p>
    <p>n = Z<sup>2</sup> × p (1 − p)/d<sup>2</sup></p>
    <fig id="fig1" position="float">
     <label>Figure 1</label>
     <caption>
      <title>Figure 1. Map of The Gambia showing the study areas. The figure was generated and modified using ArcGIS 9.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2361443-rId11.jpeg?20240904020624" />
    </fig>
    <p>From the above formula, a sample size of 384 was obtained, which was multiplied by 10% for sampling error to obtain 432 as the number of participants (<xref ref-type="bibr" rid="scirp.135761-9">
      Al Mansour, 2020
     </xref>). Two districts from each of the five regions already described were randomly selected and within each selected district, two farming communities were purposively chosen for data collection. The purposive method of choosing the two communities for data collection stemmed from the fact that not all the communities were seriously engaged in crop farming but only the chosen communities were more involved in farming. In CRR-S, three districts such as Janjanbureh, Lower Fulladu, and Lower Fulladu West were chosen with one farming community in each of them except in Lower Fulladu West where two farming communities were chosen for data collection. The survey was conducted using 432 structured pre-tested questionnaires (228 males and 204 females) administered to crop farmers. The questionnaires were made up of both closed and open-ended questions, which were interpreted orally in the local languages (Mandinka, Fula, and Wolof) to the farmers and later translated back to the English Language consistently to enhance their applicability in various contexts.</p>
   </sec>
   <sec id="s2_4">
    <title>2.4. Statistical and Data Analyses</title>
    <p>Microsoft Excel spreadsheet program was used to manage the raw data. Epi info 7.2.5.0. Software statistical analysis tools were used to analyze and interpret the data. The obtained data was analyzed using descriptive statistics. The relationships between the predictor variable (gender, age, ethnic group, religion, marital status, and level of education) with knowledge and perceptions variables were examined using Pearson’s chi-square and Binomial Logistic Regression. P-value &lt; 0.05 was considered statistically significant.</p>
   </sec>
  </sec><sec id="s3">
   <title>3. Results and Discussion</title>
   <p>This study sought to investigate the existing farmers’ knowledge and perceptions of the effects of climate variability and pollution on crop production and their varying adaptation strategies in The Gambia. The findings of this study showed that the effects of climatic variability have had a significant impact on crop production in The Gambia. A report from Ethiopia by <xref ref-type="bibr" rid="scirp.135761-42">
     Mengistu (2011)
    </xref> observed that vulnerability analysis to climate change is closely linked to poverty and the living conditions of farmers, which determine their vulnerability and adaptation to climate change. An increase in the frequency of climate-related risks can lead households to anticipate lower income, potentially pushing them below the poverty threshold in the country. Other researchers have emphasized the strong effects of vulnerability on climate change in poor agricultural and rural communities of developing countries because of their low income and deprived adaptive capabilities (<xref ref-type="bibr" rid="scirp.135761-13">
     Barker et al., 2007
    </xref>; <xref ref-type="bibr" rid="scirp.135761-57">
     Skoufias et al., 2011
    </xref>). In addition, deviations in weather situations are likely to use the frequency and magnitude of several climatic hazards, such as floods, storms, droughts, etc. (<xref ref-type="bibr" rid="scirp.135761-39">
     Khan et al., 2020
    </xref>).</p>
   <sec id="s3_1">
    <title>3.1. Social Demographic Characteristics of the Participants</title>
    <p>Out of the 432 crop farmers that participated in this study, 228 (52.78%) are males while 204 (47.22%) are females. About one-quarter of the participants 92 (21.30%) were between 40 - 49 years old, about half of the respondents 194 (44.91%) were between 50 and 59 years old, and about a quarter of the respondents 117 (27.08%) were 60 years and above. The findings showed that the main population engaged in crop farming is the aged population (50 years and above), which accounted for about 72%. This is attributed to the fact that most people believed that farming was meant for the illiterates, the less educated, and the poor. In contrast to the study conducted in Uganda by <xref ref-type="bibr" rid="scirp.135761-4">
      Ahaibwe et al. (2013)
     </xref>, which revealed that young farmers were concentrated more on agricultural production than adults despite the fact that the majority of them are less educated. The majority of the respondents 157 (36.34%) are Mandinkas by ethnicity followed by Fulas 107 (24.77%) and then Wolof 75 (17.36%) and others accounted for the rest of the respondents. On marital status, 354 (81.94%) of the respondents are married while 58 (13.43%) were single and the rest are either widowed or divorced. Regarding educational status, the highest number 171 (39.58%) of the respondents were illiterate followed by those who only attained primary education 82 (18.98%) (<xref ref-type="table" rid="table1">
      Table 1
     </xref>).</p>
    <table-wrap id="table1">
     <label>
      <xref ref-type="table" rid="table1">
       Table 1
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 1. Demography of crop farmers.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.99%">Characteristics<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.74%">Frequency<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.27%">Percentage<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="100.00%" colspan="3">Gender<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.99%">Male<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.74%">228<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.27%">52.78<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Female<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">204<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">47.22<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.99%">Total<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.74%">432<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">100.00<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="100.00%" colspan="3">Age (years)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.99%">20 - 29<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.74%">10<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.27%">2.31<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">30 - 39<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">19<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">4.40<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">40 - 49<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">92<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">21.30<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">50 - 59<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">194<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">44.91<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">60 and above<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">117<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">27.08<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.99%">Total<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.74%">432<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.27%">100.00<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="100.00%" colspan="3">Ethnic group<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.99%">Mandinka<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.74%">157<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.27%">36.34<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Fula<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">107<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">24.77<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Wolof<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">75<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">17.36<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Others<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">93<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">21.53<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.99%">Total<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.74%">432<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.27%">100.00<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="100.00%" colspan="3">Religion<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.99%">Islam<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.74%">403<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.27%">93.29<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Christianity<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">29<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">6.71<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.99%">Total<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.74%">432<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.27%">100.00<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="100.00%" colspan="3">Marital status<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.99%">Married<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.74%">354<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.27%">81.94<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Single<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">58<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">13.43<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Widowed<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">15<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">3.47<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Divorced<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">5<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">1.16<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.99%">Total<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.74%">432<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.27%">100.00<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="100.00%" colspan="3">Highest level of education<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.99%">Primary<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.74%">82<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.27%">18.98<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Secondary<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">74<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">17.13<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Tertiary/University<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">32<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">7.41<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Informal/Madarasa<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">171<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">39.58<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">None<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">73<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">16.90<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.99%">Total<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.74%">432<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.27%">100.00<p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
   </sec>
   <sec id="s3_2">
    <title>3.2. Percentage of Farmers Involved in the Cultivation of Various Crops and Land Tenure Systems Used</title>
    <p>Participants in this survey were asked about the main crop they grow, the type of farmland, whether they have changed crops in the past 20 years, and if they have changed crops, what the reason for the change of crops was. The results showed that 138 (31.94%) of the respondents grew rice, 212 (49.07%) grew groundnuts, 21 (4.86%) grew maize, 41 (9.49%) grew millet, 9 (2.08%) grew cassava and the rest grew one of the following crops; banana, lettuce, okra, and onion as shown in <xref ref-type="table" rid="table2">
      Table 2
     </xref>. A similar study was conducted in the Central River Region of The Gambia, which indicated that 46.8% of the respondents grew rice, 45.2% grew groundnuts, while 1.4%, 5.3% and 2.08% grew maize, millet, and cassava respectively, and the rest grew other crops in the study area (<xref ref-type="bibr" rid="scirp.135761-12">
      Badgie, 2018
     </xref>). About the type of farmland, 6 (1.39%) of the respondents cultivated their crops on state land, 81 (18.75%) cultivated their crops on communal land, 304 (70.37%) cultivated on individual land and 41 (9.49%) grown on rented land (<xref ref-type="table" rid="table2">
      Table 2
     </xref>). In contrast, <xref ref-type="bibr" rid="scirp.135761-12">
      Badgie (2018)
     </xref> revealed that 18.75% of respondents cultivated their crops on communal land, 49.3% on individual land, and 9.49% on rented land. On the question of change of crops in the last 20 years, 421 (97.45%) of the respondents agreed that they have changed crops in the last 20 years and 11 (2.55%) said they have not changed crops in the last 20 years. The reasons for the change of crops were as follows; 135 (31.25% of the respondents argued that they changed crops due to short rainfall duration, 43 (9.95%) of them said because of drought, 175 (40.51%) attributed their change of crops to low soil fertility and 79 (18.29%) opined that incidence of pest and disease compelled them to change crops. Although these findings were supported by <xref ref-type="bibr" rid="scirp.135761-56">
      Seo and Mendelsohn, (2008)
     </xref> in South American farms, they pointed out that this may not be the case if the adjustment requires heavy investment. These findings are contrasted by the study conducted by <xref ref-type="bibr" rid="scirp.135761-22">
      Crane et al. (2011)
     </xref>, which reported that high climatic variability and unpredictable rain have led not only to changes in crops but almost every farmer now practices mixed agro-pastoralism and may also intermittently engage in fishing and hunting when possible. The diversification of crops and other sectors of the economy would minimize the total failure of the enterprises should the farmer encounter extreme climate events.</p>
    <table-wrap id="table2">
     <label>
      <xref ref-type="table" rid="table2">
       Table 2
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 2. The main crops grown under various land tenure systems.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.81%">Characteristics<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.67%">Frequency<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.21%">Percentage<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.81%">Rice<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.67%">138<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.21%">31.95<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Groundnuts<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">212<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">49.07<p style="text-align:center"></p></td> 
       <td class="acenter" width="0.30%"><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Maize<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">21<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">4.86<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Millet<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">41<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">9.49<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Cassava<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">9<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">2.08<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Others<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">11<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">2.55<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.81%">Total<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.67%">432<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.21%">100.00<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="99.70%" colspan="3">Type of farmland<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.81%">State<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.67%">6<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.21%">1.39<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Communal<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">81<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">18.75<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Individual<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">304<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">70.37<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Rented<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">41<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">9.49<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.81%">Total<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.67%">432<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.21%">100.00<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="99.70%" colspan="3">Have you changed crops in the past 20 years?<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.81%">Yes<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.67%">421<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.21%">97.45<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">No<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">11<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">2.55<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="58.81%">Total<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.67%">432<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="21.21%">100.00<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="99.70%" colspan="3">If yes, what was the reason for the change of crops?<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="58.81%">Short rainfall duration<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.67%">130<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="21.21%">30.88<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Drought<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">43<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">10.21<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Low soil fertility<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">171<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">40.62<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Incidence of pest and disease<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">77<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">18.29<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="58.81%">Total<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">421<p style="text-align:center"></p></td> 
       <td class="acenter" width="21.21%">100.00<p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
   </sec>
   <sec id="s3_3">
    <title>3.3. Farmers’ Perception of the Effects of Climate Variability on Crop Production in The Gambia</title>
    <p>The perception of farmers on the effects of climate variability on crop production shows that, 426 (98.61%) respondents reported being aware of climate change. Almost all the respondents except for salt intrusion 241 (55.79%) reported that they have observed and experienced a change in temperature 422 (97.69%), rainfall pattern 430 (99.54%), erosion 427 (98.84%), windstorm 426 (98.61%, drought 418 (96.76%) and flood 432 (100.00%) over the past 20 years (<xref ref-type="table" rid="table3">
      Table 3
     </xref>). According to meteorological evidence from <xref ref-type="bibr" rid="scirp.135761-20">
      Cham et al. (2018)
     </xref>, rainfall has decreased, the period of the rainy season has decreased, minimum temperatures have decreased, maximum temperatures have increased and the frequency of severe weather events such as drought and dust storms has increased in The Gambia over the past 60 years. This study revealed that crop farmers in The Gambia are very aware of the effects of climate variability on crop production. Except for salt intrusion, the overwhelming majority of more than 95% of the respondents are aware of climate change and perceived changes in temperature and rainfall patterns, a frequent occurrence in erosion, windstorms, drought, and flood as the main hazards caused by climate variability in the study area. A similar study was conducted in Ebonyi State, Nigeria, which demonstrated the majority of rice farmers perceived climate change events such as unpredictable rainfall patterns and distribution, prolonged dry season, frequent floods, increased temperature, and severe windstorms, which are in consonant with other scientific data resulting in poor yields and products (<xref ref-type="bibr" rid="scirp.135761-48">
      Onyeneke et al., 2021
     </xref>). Another similar study in Uganda also revealed almost 99% of the respondents had perceived a change in the climate in the last decade (<xref ref-type="bibr" rid="scirp.135761-47">
      Okonya et al., 2013
     </xref>). The farmers’ views on the causes of climate variability on crop production in The Gambia in the last 20 years are consistent with the study conducted in South Africa which shows that the risk of unprecedented high January-March (JFM) average temperatures is increasing, posing a growing threat to Agriculture (<xref ref-type="bibr" rid="scirp.135761-16">
      Bradshaw et al., 2022
     </xref>). The majority (98.61%) of the respondents in The Gambia perceived the effects of climate variability on crop production. This is similar to the study conducted in Pakistan which reported that 91% of respondents in Pashawar perceived droughts as a major threat caused by weather and climate variability (<xref ref-type="bibr" rid="scirp.135761-39">
      Khan et al., 2020
     </xref>). During the FGDs and KIIs with stakeholders, it was established that all the informants from the selected communities and institutions respectively were fully aware of climate variability and its effects on crop production.</p>
    <table-wrap id="table3">
     <label>
      <xref ref-type="table" rid="table3">
       Table 3
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 3. Crop farmers’ perception of the occurrence of climate variability on crop production in The Gambia in the last 20 years.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="59.05%">Climate variable<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="23.70%">Yes<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="17.24%">No<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="59.05%">Awareness of climate change<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="23.70%">426 (98.61%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="17.24%">6 (1.39%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="59.05%">Observed changes in temperature pattern<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">422 (97.69%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">10 (2.31%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="59.05%">Observed changes in rainfall pattern<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">430 (99.54%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">2 (0.46%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="59.05%">Experienced erosion<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">427 (98.84%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">5 (1.16%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="59.05%">Experienced windstorm<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">426 (98.61%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">6 (1.39%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="59.05%">Experienced salt intrusion on arable land<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">241 (55.79%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">191 (44.21%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="59.05%">Experienced drought in this region<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">418 (96.76%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">14 (3.24%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="59.05%">Experienced flood<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">432 (100.00%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">0 (0.00%)<p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
    <p>Under the causes of climate variability, 71 (16.67%), 76 (17.59%), and 76 (17.59%) of respondents attributed climate change, temperature change, and change in rainfall to natural causes, whereas 100 (23.47%), 105 (24.31%) and 101 (23.38%) opined that it is due to human-induced activities. In contrast, the other respondents 245 (57.51%), 244 (56.48%), and 251 (58.10%) argued that both natural and human-induced activities are the causes of change in climate, change in temperature and change in rainfall respectively while 10 (2.34%), 7 (1.62%) and 4 (0.93%) said that they do not know the cause of climate change, change in temperature and change in rainfall respectively (<xref ref-type="table" rid="table4">
      Table 4
     </xref>).</p>
    <table-wrap id="table4">
     <label>
      <xref ref-type="table" rid="table4">
       Table 4
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 4. Perceived causes of climate variability on crop production in The Gambia.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="28.89%">Climate variable<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="17.24%">Natural<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.39%">Human-induced<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="19.67%">Natural &amp; human-induced<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="14.81%">I don’t know<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="28.89%">Change in climate<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="17.24%">71 (16.67%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.39%">100 (23.47%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="19.67%">245 (57.51%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="14.81%">10 (2.34%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="28.89%">Change in temperature<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">76 (17.59%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.39%">105 (24.31%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">244 (56.48%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="14.81%">7 (1.62%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="28.89%">Change in rainfall<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">76 (17.59%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.39%">101 (23.38%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="19.67%">251 (58.10%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="14.81%">4 (0.93%)<p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
    <p>The findings as shown in <xref ref-type="table" rid="table4">
      Table 4
     </xref>, revealed that more than 50% of the farmers attributed the causes of climate variability such as temperature and rainfall to the interplay of both natural and human-induced activities. A similar study was conducted in Nigeria, which opined that changes in climate and environmental conditions occur as a result of both natural and human factors (<xref ref-type="bibr" rid="scirp.135761-45">
      Nwankwoala, 2015
     </xref>). This is in consonant with the study conducted by <xref ref-type="bibr" rid="scirp.135761-31">
      Hartter et al. (2018)
     </xref> in eastern Oregon (USA), where most of the respondents did not accept human causation as the only agent of climate change. However, a large majority (85% - 86%) of them agree that the climate is changing, either by natural or human-induced causes (<xref ref-type="bibr" rid="scirp.135761-31">
      Hartter et al., 2018
     </xref>). In contrast with the study conducted by <xref ref-type="bibr" rid="scirp.135761-52">
      Perkins-Kirkpatrick et al. (2022)
     </xref> which opined that extreme events that influence climate change are attributed to anthropogenic activities.</p>
    <p>The perception of crop farmers towards the effects of elevated temperature on crop production shows that 400 respondents (92.59%) reported a decrease in crop production, 20 (4.63%) stated an increase, 8 (1.85%) believed that the elevated temperature has no effect, and 4 (0.93%) were unsure of any effects (<xref ref-type="fig" rid="fig2">
      Figure 2
     </xref>). This is in consonant with the research conducted in Slovakia by <xref ref-type="bibr" rid="scirp.135761-61">
      Varga (2021)
     </xref>, which argued that the impacts of climate change would be felt in agriculture leading to reduced production in warmer areas due to temperature stress, risk of erosion as a result of more extreme weather conditions, the occurrence of new pests, etc.</p>
    <fig id="fig2" position="float">
     <label>Figure 2</label>
     <caption>
      <title>Figure 2. Effects of elevated temperature on crop production.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2361443-rId12.jpeg?20240904020625" />
    </fig>
    <p>The crop farmers were asked about the effects of changes in rainfall patterns on crop growth, development, and production. The results show that 403 (93.29%) reported that they observed reduced crop growth, development, and production, 22 (5.09%) stated that there was an increase in crop growth, development, and production, 3 (0.69%) said that it does not affect crop growth, development, and production while 4 (0.93%) reported that they had no idea about the resultant effects of changes in rainfall pattern on crop growth, development, and production (<xref ref-type="fig" rid="fig3">
      Figure 3
     </xref>).</p>
    <fig id="fig3" position="float">
     <label>Figure 3</label>
     <caption>
      <title>Figure 3. Effects of changes in rainfall pattern on crop growth, development, and production.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2361443-rId13.jpeg?20240904020625" />
    </fig>
    <p>
     <xref ref-type="fig" rid="fig4">
      Figure 4
     </xref> shows the various effects of climate variability and pollution on the environment such as high temperatures 198 (45.83%), less or erratic rainfall 48 (11.11%), floods increase on farms 28 (6.48%), late onset of rains 34 (7.87%), less crop yield 79 (18.29%), increased winds before rains 17 (3.94%) and land degradation 28 (6.48%). A similar study in Nigeria pointed out that the majority (more than 70%) of farmers perceived an increase in temperature and a decrease in precipitation patterns (<xref ref-type="bibr" rid="scirp.135761-58">
      Sofoluwe et al., 2011
     </xref>).</p>
    <fig id="fig4" position="float">
     <label>Figure 4</label>
     <caption>
      <title>Figure 4. Observed changes in climate variability and pollution in the environment.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2361443-rId14.jpeg?20240904020625" />
    </fig>
    <p>A study conducted by <xref ref-type="bibr" rid="scirp.135761-3">
      Agwu et al. (2018)
     </xref> showed that farmers in Nigeria are well aware of climate change, and its impact on crop productivity stressing that the variability of the Harmattan season influences fruit production of the Garcinia kola. <xref ref-type="bibr" rid="scirp.135761-43">
      Mertz et al. (2009)
     </xref>, which analyzed the perceptions of climate change and the strategies for coping and adaptation in the savannah zone of central Senegal agreed that households are aware of climate variability and identified wind and occasional excess rainfall as the most destructive climate events. The findings of <xref ref-type="bibr" rid="scirp.135761-46">
      Odewumi et al. (2013)
     </xref> in Ibadan, South-western Nigeria, on farmers’ perception of the effect of climate change and variations on urban agriculture indicated that 89.6% of the respondents had agreed that climate is changing. Similarly, research has revealed that about 89% of the farmers perceived a significant increase in temperature, 72% perceived high evapotranspiration rates, 68% showed that there had been violent rain and hailstorms, and 65% experienced delayed rainfall and early cessation (<xref ref-type="bibr" rid="scirp.135761-19">
      Chalchisa &amp; Sani, 2016
     </xref>).</p>
   </sec>
   <sec id="s3_4">
    <title>3.4. Factors Associated with Farmers’ Perception of the Effects of Climate Variability on Crop Production in The Gambia Using Pearson Chi-Square Test</title>
    <p>
     <xref ref-type="table" rid="table5">
      Table 5
     </xref> shows Pearson chi-square results on farmers’ perception of the effects of climate variability on crop production in The Gambia. The analysis indicates that marital status is the only demographic variable that showed a significant association with all questions about climate variability effects on crop husbandry in The Gambia. Furthermore, the chi-square analysis test showed that the highest level of education is significantly associated with farmers’ perception of the effects of erosion, windstorms, and salt intrusion on crop production in their communities. These findings suggest that crop farmers in The Gambia know the adverse effects of climate variability on food security. Furthermore, the chi-square analysis tests also showed that age and ethnic group were also significant in determining crop farmers’ perception of the effects of salt intrusion on crop production in their communities. In contrast, a study conducted in the Nile Basin of Ethiopia by <xref ref-type="bibr" rid="scirp.135761-24">
      Deressa et al. (2011)
     </xref>, showed only age as being significantly related to farmers’ perception of climate change.</p>
    <table-wrap id="table5">
     <label>
      <xref ref-type="table" rid="table5">
       Table 5
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 5. Pearson chi-square results on farmers’ perception of the effects of climate variability on crop production in The Gambia.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="41.39%">Items<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="34.27%">Factors<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="13.64%">X<sup>2</sup> values<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="10.70%">P-value<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td rowspan="4" class="custom-top-td acenter" width="41.39%">Have you ever experienced erosion in the last 20 years in The Gambia?<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="34.27%">Age<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="13.64%">3.1008<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="10.70%">0.541<sup>ns</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Ethnic group<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">0.6677<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.716<sup>ns</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Marital status<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">15.7696<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.001*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="34.27%">Highest level of education<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="13.64%">13.1948<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="10.70%">0.010*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td rowspan="4" class="custom-top-td acenter" width="41.39%">Have you experienced windstorms in the past 20 years?<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="34.27%">Age<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="13.64%">3.2733<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="10.70%">0.513<sup>ns</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Ethnic group<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">0.6955<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.706<sup>ns</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Marital status<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">9.2015<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.027*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="34.27%">Highest level of education<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="13.64%">9.7389<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="10.70%">0.044*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td rowspan="4" class="custom-top-td acenter" width="41.39%">Have you experienced salt intrusion for the past 20 years on your arable land?<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="34.27%">Age<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="13.64%">9.8123<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="10.70%">0.044*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Ethnic group<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">26.7692<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">&lt;0.001*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Marital status<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">9.9964<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.019*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Highest level of education<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">17.6778<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.001*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td rowspan="4" class="custom-top-td acenter" width="41.39%">Have you ever experienced drought in the last 20 years in this region?<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="34.27%">Age<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="13.64%">2.4970<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="10.70%">0.645<sup>ns</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Ethnic group<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">5.1251<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.077<sup>ns</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Marital status<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">8.5958<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.035*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="34.27%">Highest level of education<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.64%">8.3664<p style="text-align:center"></p></td> 
       <td class="acenter" width="10.70%">0.079<sup>ns</sup><p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
    <p>*= significant difference at P &lt; 0.05; <sup>ns</sup> = not significant.</p>
   </sec>
   <sec id="s3_5">
    <title>3.5. Farmers’ Perceptions of the Contamination of Agricultural Land</title>
    <p>
     <xref ref-type="bibr" rid="scirp.135761-"></xref><xref ref-type="table" rid="table6">
      Table 6
     </xref> shows the binomial logistic regression result of how crop farmers perceived the contamination of agricultural land in The Gambia. This result shows that farmers’ ages (CL −0.135 to −0.020 and P = 0.008) and ethnic groups (CL 0.068 to 0.188 and P ≤ 0.001) were the main factors significantly influencing their perception of the awareness of HM pollution on land. Farmers’ ages (CL −0.167 to −0.054 and P ≤ 0.001) and ethnic groups (CL 0.053 to 0.171 and P ≤ 0.001) were also highly significantly associated with their awareness of threats posed by HM contamination in soil and water.</p>
    <table-wrap id="table6">
     <label>
      <xref ref-type="table" rid="table6">
       Table 6
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 6. Binomial logistic result of Farmers’ perceptions on the contamination of agricultural land.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="89.93%" colspan="2">Variables<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="22.61%">95% C<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="13.26%">Limits<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="16.51%">P-Value<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td custom-top-td acenter" width="47.38%">Outcome<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td custom-top-td acenter" width="94.94%" colspan="4">Independence<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td rowspan="6" class="custom-top-td acenter" width="47.38%">Have you experienced soil and water pollution for farming?<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="42.56%">Gender<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="22.61%">−0.037<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="13.26%">0.099<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="16.51%">0.375<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Age<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.021<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.061<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.344<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Ethnic group<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.003<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.083<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.070<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Religion<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.044<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.845<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.077<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Marital status<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.051<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.068<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.772<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="42.56%">Highest level of education<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="22.61%">−0.011<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="13.26%">0.039<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="16.51%">0.283<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td rowspan="6" class="custom-top-td acenter" width="47.38%">Are you aware of heavy metal (HM) pollution?<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="42.56%">Gender<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="22.61%">−0.149<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="13.26%">0.039<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="16.51%">0.251<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Age<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.135<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">−0.020<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.008*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Ethnic group<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">0.068<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.188<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">&lt;0.001*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Religion<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.516<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.715<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.750<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Marital status<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.045<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.120<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.368<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-bottom-td acenter" width="42.56%">Highest level of education<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="22.61%">−0.018<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="13.26%">0.051<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="16.51%">0.348<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td rowspan="6" class="custom-top-td acenter" width="47.38%">Are you aware of threats posed by HM contamination in soil and water?<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="42.56%">Gender<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="22.61%">−0.152<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="13.26%">0.034<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="16.51%">0.213<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Age<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.167<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">−0.054<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">&lt;0.001*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Ethnic group<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">0.053<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.171<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">&lt;0.001*<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Religion<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.549<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.666<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.849<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Marital status<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.049<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.113<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.437<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="42.56%">Highest level of education<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.61%">−0.013<p style="text-align:center"></p></td> 
       <td class="acenter" width="13.26%">0.055<p style="text-align:center"></p></td> 
       <td class="acenter" width="16.51%">0.231<p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
    <p>The age of the respondents represents experience in farming and research has shown that experienced farmers are more likely to perceive climate change (<xref ref-type="bibr" rid="scirp.135761-35">
      Ishaya &amp; Abaje, 2008
     </xref>; <xref ref-type="bibr" rid="scirp.135761-24">
      Deressa et al., 2011
     </xref>).</p>
    <p>
     <xref ref-type="table" rid="table7">
      Table 7
     </xref> shows the responses of crop farmers about their perceptions of the contamination of agricultural land. The majority of 358 (82.87%) of the informants had experienced soil and water pollution on their farms. These findings revealed that although the farmers in The Gambia had never experienced HM pollution on their farms, 109 (25.23%) of them are aware of the threats posed by these recalcitrant substances to the environment (<xref ref-type="table" rid="table7">
      Table 7
     </xref>). This may be because there is little or no analysis of the content of heavy metals in the fertilizers, chemicals, and pesticides used on the arable soil. With this little knowledge of HM contamination in The Gambia, bioremediation technology, which is not only meant for HM removal but also those contaminants with organic substances origin, is an exotic phenomenon. In contrast with the study conducted in Lankao County, China by <xref ref-type="bibr" rid="scirp.135761-53">
      Ren et al. (2018)
     </xref>, which showed from the questionnaire that the content of heavy metal in various arable soils is closely related to the input of fertilizer, pesticide, farmyard manure, etc. In addition, another study conducted by <xref ref-type="bibr" rid="scirp.135761-41">
      Lu (2019)
     </xref>, opined that farmers in China believe that their cultivated land is moderately polluted by heavy metals and they have a strong awareness of HM pollution in locally cultivated land. Research conducted by <xref ref-type="bibr" rid="scirp.135761-53">
      Ren et al. (2018)
     </xref> revealed that HM contamination remediation of arable soil indicates that the adoption of appropriate treatment measures can reduce the HM content of arable soil to some extent, such as the adjustment of planting patterns, deep ploughing for soil amelioration, formula fertilization, and adoption of phytoremediation (an aspect of bioremediation), etc.</p>
    <table-wrap id="table7">
     <label>
      <xref ref-type="table" rid="table7">
       Table 7
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 7. Farmers’ perceptions of the contamination of agricultural land.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="67.68%">Variables<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="15.08%">Yes<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="17.24%">No<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="67.68%">Have you experienced soil and water pollution on your farm?<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="15.08%">358 (82.87%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="17.24%">74 (17.13%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="67.68%">Are you aware of heavy metal (HM) pollution?<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">109 (25.23%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">323 (74.77%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="67.68%">If yes, have you experienced HM pollution on your farmland in the last 20 years?<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">…<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">109 (100.00%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="67.68%">Are you aware of HM contamination’s threats to soil and water?<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">109 (25.23%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="17.24%">323 (74.77%)<p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
    <p>
     <xref ref-type="fig" rid="fig5">
      Figure 5
     </xref> shows the main soil and water pollution in The Gambia. The findings revealed that the main soil and water pollution emanates from both organic and inorganic contaminants, 163 (45.53%) attributed the pollution to chemical fertilizers, 39 (10.89%) said that pesticides cause the pollution, 81 (22.63%) argued that industrial and agricultural wastes cause the pollution, 74 (20.67%) of them opined that their farmlands are polluted by sewage and 1 (0.28%) of the farmers said that other agents cause the pollution (<xref ref-type="fig" rid="fig5">
      Figure 5
     </xref>). Similarly, the research of <xref ref-type="bibr" rid="scirp.135761-59">
      Srivastav (2020)
     </xref>, showed that several researchers have reported the risks to environmental systems due to overuse and prolonged application of chemical fertilizers and pesticides, which would invariably promote soil health deterioration along with environmental pollution.</p>
    <p>It was also revealed in the FGD sessions that, most of the upstream farmers were less affected by pollution than those farmers in the coastal and riverine agricultural areas. Contrastingly, the research conducted in the United States by <xref ref-type="bibr" rid="scirp.135761-18">
      Chakraborti (2021)
     </xref> concluded that point sources have a significant negative impact on ambient water quality net of non-point sources of contamination at upstream locations. However, during the FDG sessions, the coastal and riverine farmers complained of pollution emanating from indiscriminate disposal of plastic bags, agrochemicals, pesticides, salt intrusion, oil spillage, and runoff from dump sites, to name a few. HM pollution was not mentioned which could be attributed to the fact that there is little or no evidence of any study on HM pollution in The Gambia.</p>
    <fig id="fig5" position="float">
     <label>Figure 5</label>
     <caption>
      <title>Figure 5. The main soil and water pollutants on farmland in The Gambia.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2361443-rId15.jpeg?20240904020625" />
    </fig>
   </sec>
   <sec id="s3_6">
    <title>3.6. Constraints Militating against Farmers’ Response in the GAMBIA in Their Crop Production toward Climate Change</title>
    <p>The field surveys showed (<xref ref-type="table" rid="table8">
      Table 8
     </xref>) the challenges faced in responding to climate variability in the study area. Inadequate access to credit facilities and efficient inputs was ranked first with a high number of respondents 288 (66.67%) each in militating against farmers in their response to climate change. This was followed by labour constraints, inadequate access to the market, inadequate access to water and irrigation facilities, inadequate access to information, and use of poor skills, salt intrusion, and inadequate access to ideal land as they ranked third 240 (55.56%), fourth 239 (55.32%), fifth 222 (51.39%), sixth 165 (38.19%), seventh 134 (31.02%) and eighth 101 (23.38%) respectively. These findings are in consonant with that of <xref ref-type="bibr" rid="scirp.135761-34">
      Idrisa et al. (2012)
     </xref> who reported that inadequate financial resources (credit), inadequate access to extension services, poor access to technologies required for adaptation and inadequate weather information were the challenges confronting farmers’ adaptation to climate change in Borno State, Nigeria. However, research conducted in India by <xref ref-type="bibr" rid="scirp.135761-54">
      Satishkumar et al. (2013)
     </xref> had a divergent perspective which revealed that personal constraints like the small size and fragmented landholdings, low literacy level, and inadequate knowledge of how to cope or build resilience are the main hurdles confronting agrarian industry. The same research also pointed out that the farmers faced poor extension service on climate risk management, non-availability of drought-tolerant varieties, lack of access to weather forecasting technology, poor reliability, and dependence on monsoon were the major institutional and technological constraints.</p>
    <table-wrap id="table8">
     <label>
      <xref ref-type="table" rid="table8">
       Table 8
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 8. Constraints militating against farmers’ response in The Gambia in their crop production toward climate change.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="38.73%">Constraints<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="23.70%">High<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="23.70%">Medium<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="23.72%">Low<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="23.70%">None<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="15.08%">Rank<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="38.73%">Inadequate access to<p style="text-align:center"></p>credit facilities<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="23.70%">288 (66.67%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="23.70%">101(23.38%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="23.72%">35 (8.10%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="23.70%">8 (1.85%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="15.08%">1<sup>st</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="38.73%">Inadequate access to<p style="text-align:center"></p>efficient inputs<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">288 (66.67%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">101 (23.38%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.72%">35 (8.10%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">8 (1.85%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">1<sup>st</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="38.73%">Labour constraints<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">240 (55.56%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">123 (28.47%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.72%">65 (15.05%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">4 (0.93%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">3<sup>rd</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="38.73%">Inadequate access to the market<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">239 (55.32%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">104 (24.07%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.72%">48 (11.11%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">41 (9.49%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">4<sup>th</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="38.73%">Inadequate access to<p style="text-align:center"></p>water and irrigation facilities<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">222 (51.39%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">149 (34.49%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.72%">52 (12.04%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">9 (2.08%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">5<sup>th</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="38.73%">Inadequate access to<p style="text-align:center"></p>information and the use of poor skills<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">165 (38.19%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">164 (37.96%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.72%">90 (20.83%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">13 (3.01%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">6<sup>th</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="38.73%">Salt intrusion<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">134 (31.02%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">49 (11.34%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.72%">78 (18.06%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">171 (39.58%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">7<sup>th</sup><p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="38.73%">Inadequate access to an ideal land<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">101 (23.38%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">131 (30.32%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.72%">174 (40.28%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.70%">26 (6.02%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="15.08%">8<sup>th</sup><p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
   </sec>
   <sec id="s3_7">
    <title>3.7. Adaptation Strategies Employed by Farmers in The Gambia toward Climate Change</title>
    <p>The agrarian industry has over the years proven to have the capability of responding to changing climate events by adopting various strategies and innovations as the circumstances may deem fit. The survey shows the most common adaptation strategies employed by farmers to cope with the changing climate (<xref ref-type="table" rid="table9">
      Table 9
     </xref>).</p>
    <table-wrap id="table9">
     <label>
      <xref ref-type="table" rid="table9">
       Table 9
      </xref></label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.135761-"></xref>Table 9. Agricultural crop production adaptation strategies employed by farmers in The Gambia toward climate change.</title>
     </caption>
     <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
      <tr> 
       <td class="custom-bottom-td acenter" width="49.20%">Adaptation strategies<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="23.46%">Always<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="23.16%">Occasionally<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="24.37%">Rarely<p style="text-align:center"></p></td> 
       <td class="custom-bottom-td acenter" width="22.12%">Never<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="custom-top-td acenter" width="49.20%">Planting of drought-resistant varieties of crops<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="23.46%">141 (32.79%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="23.16%">160 (37.21%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="24.37%">113 (26.28%)<p style="text-align:center"></p></td> 
       <td class="custom-top-td acenter" width="22.12%">16 (3.72%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Crop diversification<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">187 (43.29%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">164 (37.96%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">67 (15.51%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">14 (03.24%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Improved irrigation efficiency<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">60 (13.89%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">144 (33.33%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">181 (41.90%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">47 (10.88%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Afforestation and agroforestry<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">61 (14.12%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">137 (31.71%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">188 (43.52%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">46 (10.65%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Crop rotation system<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">118 (27.31%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">139 (32.18%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">121 (28.01%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">54 (12.50%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Chemical fertilizer<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">101 (23.38%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">189 (43.75%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">122 (28.24%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">20 (4.63%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Organic manure<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">215 (49.77%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">178 (41.20%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">32 (7.41%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">7 (1.62%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Zero tillage<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">27 (6.25%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">68 (15.74%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">98 (22.69%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">239 (55.32%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Early maturing varieties<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">254 (58.80%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">121 (28.01%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">46 (10.65%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">11(2.55%)<p style="text-align:center"></p></td> 
      </tr> 
      <tr> 
       <td class="acenter" width="49.20%">Migration to different locations<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.46%">252 (58.33%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="23.16%">80 (18.52%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="24.37%">66 (15.28%)<p style="text-align:center"></p></td> 
       <td class="acenter" width="22.12%">34 (7.87%)<p style="text-align:center"></p></td> 
      </tr> 
     </table>
    </table-wrap>
    <p>The possible adaptation strategies employed by farmers in The Gambia towards climate change indicated that about 141 (32.79%) of the farmers specified that planting drought-resistant crop varieties would help solve challenges and increase their crop yields. This is in agreement with research conducted in Nigeria, Senegal, Burkina Faso, and Ghana, which pointed out that smallholder farmers have used, drought-resistant crop varieties as an adaptation method to climate change (<xref ref-type="bibr" rid="scirp.135761-8">
      Akinnagbe &amp; Irohibe, 2015
     </xref>). Again, 187 (43.29%) of the informants opined that the adoption of crop diversification has helped a great deal to reduce the loss they normally encountered on their farms. According to them, if the government can supply them with various crop varieties to grow, some may fail because of the harsh climatic conditions but others will thrive. Similar research conducted in Tanzania revealed that farmers diversified crop varieties as a way of spreading risks on the farm (<xref ref-type="bibr" rid="scirp.135761-49">
      Orindi &amp; Eriksen, 2005
     </xref>; <xref ref-type="bibr" rid="scirp.135761-2">
      Adger et al., 2003
     </xref>). Crop diversification can serve as insurance against rainfall variability (<xref ref-type="bibr" rid="scirp.135761-8">
      Akinnagbe &amp; Irohibe, 2015
     </xref>).</p>
    <p>Other respondents representing 60 (13.89%) indicated that improved irrigation efficiency would enable them to grow their crops all year round. This would ensure the availability of food security at all times instead of seasonality. A study conducted by <xref ref-type="bibr" rid="scirp.135761-8">
      Akinnagbe and Irohibe (2015)
     </xref> stressed that the impacts of climate change have resulted in elevated crop water demand due to high evapotranspiration (<xref ref-type="bibr" rid="scirp.135761-29">
      FAO, 2006
     </xref>). In addition, 61 (14.12%) of the respondents argued that afforestation and agroforestry would help prevent erosion and maintain soil fertility, eventually boosting their crop yields. Research has revealed that a practice similar to this has been described in the southwestern part of Nigeria to raise shade-tolerant crops, such as Dioscorea spp., and cocoyam in essentially permanent forest settings. In the drier parts of the Sahel, African baobab (Adansonia digitata) and acacia (Acacia spp.) trees are usually planted by local farmers since they are also economically valuable trees, especially during the hot and dry parts of the year (<xref ref-type="bibr" rid="scirp.135761-8">
      Akinnagbe &amp; Irohibe, 2015
     </xref>). Another 118 (27.31%) of the respondents opined that the practice of a crop rotation system would help replenish the depleted soil nutrients thereby improving crop yield. Further, 101 (23.38%) of the respondents pointed out that the use of chemical fertilizers could also help enhance their adaptation to climate change and reduce the losses incurred on farms. They cried out that the price of fertilizers set by the government was too high for average farmers hence most of them could not afford them. Almost half 215 (49.77%) of the respondents settled for the use of organic manure as a means of adaptation strategy to mitigate the effect of climate change. Although zero tillage is not a familiar method used by farmers in The Gambia to reduce the adverse effects of climate change on their crop production, few 27 (6.25%) of them embraced the strategy to improve crop yields. The majority 254 (58.80%) and 252 (58.33%) of the respondents employed early maturing varieties and migration to different locations respectively as crop adaptation strategies towards climate change. These findings are in line with a survey conducted in the Zou Department of South Benin, which revealed that farmers adopted many strategies such as mulching, organic fertilizer, the use of improved varieties, chemical fertilizers, and pesticides in response to climate change: agroforestry and perennial plantation diversification of income-generating activities (<xref ref-type="bibr" rid="scirp.135761-27">
      Fadina &amp; Barjolle, 2018
     </xref>). Although the findings of this research show some similarities with research conducted by <xref ref-type="bibr" rid="scirp.135761-8">
      Akinnagbe and Irohibe (2015)
     </xref>, the common agricultural adaptation strategies adopted by farmers in Nigeria were the use of drought-resistant varieties of crops, crop diversification, changes in cropping patterns and calendar of planting, conserving soil moisture through appropriate tillage methods, improving irrigation efficiency, and afforestation and agro-forestry. In the West African Sahel, recent studies have shown that the region has suffered a prolonged drought for much of the past three decades and one way that farmers have adapted is by sending young men and women in search of wage labour after each harvest. However, how far they travel depends, in part, on the success of the harvest (<xref ref-type="bibr" rid="scirp.135761-8">
      Akinnagbe &amp; Irohibe, 2015
     </xref>). More generally, environmental migrants are, most of the time, people affected by long-term and permanent climate variations in temperature and precipitations; hence, they consider the migration process as a long-run adaptation strategy (<xref ref-type="bibr" rid="scirp.135761-28">
      Falco et al., 2018
     </xref>). This study showed that adaptation strategies such as improved irrigation efficiency, afforestation and agroforestry, and zero tillage were not always used (<xref ref-type="table" rid="table9">
      Table 9
     </xref>).</p>
    <p>However, participants in the KIIs stressed that activities such as the use of clean energy (solar, windmills, hydrogen-powered vehicles), afforestation, selective exploitation, avoidance of excessive use of fertilizers, the use of anti-littering policy, crop rotation, bush fallowing, adoption of climate-smart agricultural practices (minimum tillage, improved crop varieties, farmyard manure, water-saving technology, biopesticides, etc.), raise awareness through campaigns would help attitudinal change towards the environment and environmental policy formulation and implementation can help mitigate the effects of climate change.</p>
   </sec>
  </sec><sec id="s4">
   <title>4. Conclusion</title>
   <p>Climate change is a global phenomenon and its impacts on agricultural production cannot be overemphasized. The agricultural sector has played a significant role for many communities because it is a source of food, income, and foreign exchange earnings. Therefore, understanding the farmers’ knowledge and perceptions of the effects of climate variability and pollution on crop production is important for formulating adaptation strategies. Arising from this research, the conclusion is that, farmers were relatively the aged adult population with a minimal level of education. With the necessary support and interventions from the government, NGOs, and philanthropists, there is a likely shift from the aged population to the active youthful population engaged in agricultural production. The study unearthed the fact that climate change and pollution are phenomena that are closely linked, and are capable of affecting all spheres of life, such as the economy, and urban and rural development patterns, just to name but a few. However, very little is known about bioremediation in The Gambia. For this reason, more research and awareness creation are needed to help farmers understand the need to employ bioremediation technology, which has the advantage of using natural processes that are eco-friendly, cost-effective, and scalable to clean up sites without having to dig, pump, or transport them elsewhere.</p>
   <p>The challenges farmers in The Gambia faced include but are not limited to inadequate credit facilities, inadequate access to efficient inputs, inadequate access to information and poor skills, labour constraints, and inadequate market access. It is recommended that the government and NGOs help farmers adopt the following adaptation strategies but are not limited to improved irrigation efficiency, afforestation and agroforestry, crop rotation system, chemical fertilizer, and zero tillage through financial assistance in the form of loans, grants, and subsidies.</p>
  </sec><sec id="s5">
   <title>Acknowledgements</title>
   <p>The German Federal Ministry of Education and Research (BMBF), through the West African Science Service Center on Climate Change and Adapted Land Use (WASCAL), sponsored this research as part of the Graduate Research Program on Climate Change and Biodiversity at the Université Felix Houphouët-Boigny, Cote d’Ivoire. The authors express profound gratitude to these institutions for the opportunity and financial support they offered during the research. To our enumerators and respondents, we shall be forever grateful for their efforts during the fieldwork.</p>
  </sec>
 </body><back>
  <ref-list>
   <title>References</title>
   <ref id="scirp.135761-ref1">
    <label>1</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Abid, M., Scheffran, J., Schneider, U. A.,&amp;Ashfaq, M. (2015). Farmers’ Perceptions of and Adaptation Strategies to Climate Change and Their Determinants: The Case of Punjab Province, Pakistan. Earth System Dynamics, 6, 225-243. &gt;https://doi.org/10.5194/esd-6-225-2015
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref2">
    <label>2</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Adger, W. N., Huq, S., Brown, K., Conway, D.,&amp;Hulme, M. (2003). Adaptation to Climate Change in the Developing World. Progress in Development Studies, 3, 179-195. &gt;https://doi.org/10.1191/1464993403ps060oa
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref3">
    <label>3</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Agwu, O. P., Bakayoko, A., Jimoh, S. O.,&amp;Stefan, P. (2018). Farmers’ Perceptions on Cultivation and the Impacts of Climate Change on Goods and Services Provided by Garcinia Kola in Nigeria. Ecological Processes, 7, Article No. 36. &gt;https://doi.org/10.1186/s13717-018-0147-3
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref4">
    <label>4</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ahaibwe, G., Mbowa, S.,&amp;Lwanga, M. M. (2013). Youth Engagement in Agriculture in Uganda: Challenges and Prospects. Research Series, 7, 4-20.
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref5">
    <label>5</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ahmad, S., Jamal, M.,&amp;Ikramullah, A. (2007). Role of Extension Services on the Farm Productivity of District Swat (a Case Study of Two Villages). Sarhad Journal of Agriculture, 23, 1265-1272.
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref6">
    <label>6</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Akcaoz, H.,&amp;Ozkan, B. (2005). Determining Risk Sources and Strategies among Farmers of Contrasting Risk Awareness: A Case Study for Cukurova Region of Turkey. Journal of Arid Environments, 62, 661-675. &gt;https://doi.org/10.1016/j.jaridenv.2005.01.018
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref7">
    <label>7</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Akhtar, K., Wang, W., Ren, G., Khan, A., Feng, Y., Yang, G. et al. (2019). Integrated Use of Straw Mulch with Nitrogen Fertilizer Improves Soil Functionality and Soybean Production. Environment International, 132, Article ID: 105092. &gt;https://doi.org/10.1016/j.envint.2019.105092
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref8">
    <label>8</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Akinnagbe, O.,&amp;Irohibe, I. (2015). Agricultural Adaptation Strategies to Climate Change Impacts in Africa: A Review. Bangladesh Journal of Agricultural Research, 39, 407-418. &gt;https://doi.org/10.3329/bjar.v39i3.21984
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref9">
    <label>9</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Al Mansour, M. A. (2020). The Prevalence and Risk Factors of Type 2 Diabetes Mellitus (DMT2) in a Semi-Urban Saudi Population. International Journal of Environmental Research and Public Health, 17, Article No. 7. &gt;https://doi.org/10.3390/ijerph17010007
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref10">
    <label>10</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ali, A.,&amp;Erenstein, O. (2017). Assessing Farmer Use of Climate Change Adaptation Practices and Impacts on Food Security and Poverty in Pakistan. Climate Risk Management, 16, 183-194. &gt;https://doi.org/10.1016/j.crm.2016.12.001
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref11">
    <label>11</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ampomah, G., Energy, E., Agency, N. E.,&amp;Fofana, G. F. (2012). Climate Change Vulnerability Assessment and Adaptation in Greater Banjul—Gambia.
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref12">
    <label>12</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Badgie, D. (2018). Implications of Farmers’ Perception, Local Knowledge and Climate Change on Rice Production in the Central River Region, The Gambia. 
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref13">
    <label>13</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Barker, T., Bashmakov, I., Bernstein, L., Bogner, J., Bosch, P., Dave, R., Davidson, O., Fisher, B., Grubb, M., Gupta, S., Halsnaes, K., Heij, B., Kahn Ribeiro, S., Kobayashi, S., Levine, M., Martino, D., Masera Cerutti, O., Metz, B., Meyer, L.,&amp;Dadi, Z. (2007). Summary for Policymakers IPCC Fourth Assessment Report, Working Group III. Intergovernmental Panel on Climate Change, 1-36. &gt;https://escholarship.org/uc/item/4sb32788 
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref14">
    <label>14</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Barrow, A., Badjie, M., Touray, J., Kinteh, B., Nget, M., Touray, E. et al. (2020). Knowledge, Attitude, and Practice of Provincial Dwellers on Prevention and Control of Schistosomiasis: Evidence from a Community-Based Cross-Sectional Study in the Gambia. Journal of Tropical Medicine, 2020, Article ID: 2653096. &gt;https://doi.org/10.1155/2020/2653096
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref15">
    <label>15</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Belford, C., Huang, D., Ahmed, Y. N., Ceesay, E.,&amp;Sanyang, L. (2023). An Economic Assessment of the Impact of Climate Change on the Gambia’s Agriculture Sector: A CGE Approach. International Journal of Climate Change Strategies and Management, 15, 322-352. &gt;https://doi.org/10.1108/ijccsm-01-2022-0003
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref16">
    <label>16</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Bradshaw, C. D., Pope, E., Kay, G., Davie, J. C. S., Cottrell, A., Bacon, J. et al. (2022). Unprecedented Climate Extremes in South Africa and Implications for Maize Production. Environmental Research Letters, 17, Article ID: 084028. &gt;https://doi.org/10.1088/1748-9326/ac816d
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref17">
    <label>17</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Camara, I. F. (2013). Mainstreaming Climate Change Resilience into Development Planning in Kenya. IIED. &gt;http://pubs.iied.org/10044IIED.html
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref18">
    <label>18</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Chakraborti, L. (2021). Impact of Upstream Plant Level Pollution on Downstream Water Quality: Evidence from the Clean Water Act. Journal of Environmental Planning and Management, 64, 517-535. &gt;https://doi.org/10.1080/09640568.2020.1776227
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref19">
    <label>19</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Chalchisa, T.,&amp;Sani, S. (2016). Farmers’ Perception, Impact, and Adaptation Strategies to Climate Change among Smallholder Farmers in Sub-Saharan Africa: A Systematic Review. Journal of Reso. Journal of Resources Development and Management, 26, 1-8. 
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref20">
    <label>20</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Cham, F. O., Secka, A., Yaffa, S.,&amp;Sawanneh, M. (2018). Climate Variability Perception and Adaptation: Differences between Male and Female Cattle Owners. International Journal of Agriculture and Environmental Research, 4, 158-178. &gt;https://www.ijaer.in 
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref21">
    <label>21</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Chaudhary, P.,&amp;Aryal, K. P. (2009). Global Warming in Nepal: Challenges and Policy Imperatives. &gt;https://www.forestaction.org 
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref22">
    <label>22</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Crane, T. A., Roncoli, C.,&amp;Hoogenboom, G. (2011). Adaptation to Climate Change and Climate Variability: The Importance of Understanding Agriculture as Performance. NJAS: Wageningen Journal of Life Sciences, 57, 179-185. &gt;https://doi.org/10.1016/j.njas.2010.11.002
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref23">
    <label>23</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Creswell, J. W.,&amp;Angeles, L. (2006). Designing and Conducting Mixed Methods Research (2nd Ed.). Sage Publications.
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref24">
    <label>24</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Deressa, T. T., Hassan, R. M.,&amp;Ringler, C. (2011). Perception of and Adaptation to Climate Change by Farmers in the Nile Basin of Ethiopia. The Journal of Agricultural Science, 149, 23-31. &gt;https://doi.org/10.1017/s0021859610000687
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref25">
    <label>25</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Easterling, D. R., Evans, J. L., Groisman, P. Y., Karl, T. R., Kunkel, K. E.,&amp;Ambenje, P. (2000). Observed Variability and Trends in Extreme Climate Events: A Brief Review. Bulletin of the American Meteorological Society, 81, 417-425. &gt;https://doi.org/10.1175/1520-0477(2000)081&lt;0417:ovatie&gt;2.3.co;2
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref26">
    <label>26</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Engel-Di Mauro, S. (2012). Minding History and World-Scale Dynamics in Hazards Research: The Making of Hazardous Soils in The Gambia and Hungary. Journal of Risk Research, 15, 1319-1333. &gt;https://doi.org/10.1080/13669877.2011.591500
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref27">
    <label>27</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Fadina, A.,&amp;Barjolle, D. (2018). Farmers’ Adaptation Strategies to Climate Change and Their Implications in the Zou Department of South Benin. Environments, 5, Article No. 15. &gt;https://doi.org/10.3390/environments5010015
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref28">
    <label>28</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Falco, C., Donzelli, F.,&amp;Olper, A. (2018). Climate Change, Agriculture and Migration: A Survey. Sustainability, 10, Article No. 1405. &gt;https://doi.org/10.3390/su10051405
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref29">
    <label>29</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     FAO (2006). Livelihood Adaptation to Climate Variability and Change in Drought-Prone Areas of Bangladesh: Developing Institutions and Options. In Case Study—Institutions for Rural Development (pp. 1-115). FAO (Issue No. 5).
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref30">
    <label>30</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     GBoS. (2013). The Gambia 2013 Population and Housing Census Preliminary Results. The Gambia Bureau of Statistics. &gt;https://catalog.ihsn.org/index.php/catalog/6065/download/74258
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref31">
    <label>31</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Hartter, J., Hamilton, L. C., Boag, A. E., Stevens, F. R., Ducey, M. J., Christoffersen, N. D. et al. (2018). Does It Matter If People Think Climate Change Is Human Caused? Climate Services, 10, 53-62. &gt;https://doi.org/10.1016/j.cliser.2017.06.014
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref32">
    <label>32</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Hay, J.,&amp;Mimura, N. (2010). The Changing Nature of Extreme Weather and Climate Events: Risks to Sustainable Development. Geomatics, Natural Hazards and Risk, 1, 3-18. &gt;https://doi.org/10.1080/19475701003643433
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref33">
    <label>33</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Howden, S. M., Soussana, J., Tubiello, F. N., Chhetri, N., Dunlop, M.,&amp;Meinke, H. (2007). Adapting Agriculture to Climate Change. Proceedings of the National Academy of Sciences, 104, 19691-19696. &gt;https://doi.org/10.1073/pnas.0701890104
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref34">
    <label>34</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Idrisa, Y. L., Ogunbameru, B. O., Ibrahim, A. A.,&amp;Bawa, D. B. (2012). Analysis of Awareness and Adaptation to Climate Change among Farmers in the Sahel Savannah Agro-Ecological Zone of Borno State, Nigeria. British Journal of Environment and Climate Change, 2, 216-226. &gt;https://doi.org/10.9734/bjecc/2012/1475
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref35">
    <label>35</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ishaya, S.,&amp;Abaje, I. (2008). Indigenous People’s Perception of Climate Change and Adaptation Strategies in Jema’a Local Government Area of Kaduna State, Nigeria. Journal of Geography and Regional Planning, 1, 138-143.
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref36">
    <label>36</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Jaiteh, M. S.,&amp;Saho, A. (2003). The Gambia Atlas of 2003 Population and Housing Census. Gambia Bureau of Statistics. 
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref37">
    <label>37</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Josephine, M., Godswill Azinwie, A.,&amp;Raymond Ndip, N. (2020). Vulnerability to Food Insecurity and Coping Strategies of Agrarian Households in the Lower River Region of the Gambia: Implication for Policy. International Journal of Agricultural Science and Food Technology, 6, 115-126. &gt;https://doi.org/10.17352/2455-815x.000064
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref38">
    <label>38</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Kargbo, A., Koua, H., Kuye, R., Jwao, E., Amoutchi, Al., Bojang, A., Zainabou, D.,&amp;Flourence, J. K. (2021). Livestock Farmers’ Perceptions of How Changes in Climate Variabilities Are Impacting the Production Systems in The Gambia.
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref39">
    <label>39</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Khan, I., Lei, H., Shah, I. A., Ali, I., Khan, I., Muhammad, I. et al. (2020). Farm Households’ Risk Perception, Attitude and Adaptation Strategies in Dealing with Climate Change: Promise and Perils from Rural Pakistan. Land Use Policy, 91, Article ID: 104395. &gt;https://doi.org/10.1016/j.landusepol.2019.104395
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref40">
    <label>40</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Liverman, D. (2008). Assessing Impacts, Adaptation and Vulnerability: Reflections on the Working Group II Report of the Intergovernmental Panel on Climate Change. Global Environmental Change, 18, 4-7. &gt;https://doi.org/10.1016/j.gloenvcha.2007.09.003
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref41">
    <label>41</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Lu, H. (2019). Impact of Non-Agricultural Employment and Environmental Awareness on Farmers’ Willingness to Govern the Heavy Metal Pollution of Farmland: A Case Study of China. Sustainability, 11, Article No. 2068. &gt;https://doi.org/10.3390/su11072068
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref42">
    <label>42</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Mengistu, D. K. (2011). Farmers’ Perception and Knowledge on Climate Change and Their Coping Strategies to the Related Hazards: Case Study from Adiha, Central Tigray, Ethiopia. Agricultural Sciences, 2, 138-145. &gt;https://doi.org/10.4236/as.2011.22020
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref43">
    <label>43</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Mertz, O., Mbow, C., Reenberg, A.,&amp;Diouf, A. (2009). Farmers’ Perceptions of Climate Change and Agricultural Adaptation Strategies in Rural Sahel. Environmental Management, 43, 804-816. &gt;https://doi.org/10.1007/s00267-008-9197-0
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref44">
    <label>44</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Mutsikiwa, M.,&amp;Basera, C. H. (2012). The Influence of Socio-Cultural Variables on Consumers’ Perception of Halal Food Products : A Case of Masvingo Urban, Zimbabwe. International Journal of Business and Management, 7, 112-119. &gt;http://dx.doi.org/10.5539/ijbm.v7n20p112 
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref45">
    <label>45</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Nwankwoala, H. N. L. (2015). Causes of Climate and Environmental Changes: The Need for Environmental-Friendly Education Policy in Nigeria. Journal of Education and Practice, 6, 224-234. &gt;http://ezproxy.wheaton.edu/login?url=&gt;http://search.ebscohost.com/login.aspx?direct=true&amp;db=eric&amp;AN=EJ1081366&amp;site=ehost-live
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref46">
    <label>46</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Odewumi, O. et al. (2013). Farmers Perception on the Effect of Climate Change and Variation on Urban Agriculture in Ibadan Metropolis, South-Western Nigeria. Journal of Geography and Regional Planning, 6, 209-217. &gt;https://doi.org/10.5897/jgrp2013.0370
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref47">
    <label>47</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Okonya, J. S., Syndikus, K.,&amp;Kroschel, J. (2013). Farmers’ Perception of and Coping Strategies to Climate Change: Evidence from Six Agro-Ecological Zones of Uganda. Journal of Agricultural Science, 5, 252-263. &gt;https://doi.org/10.5539/jas.v5n8p252
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref48">
    <label>48</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Onyeneke, R. U., Amadi, M. U., Njoku, C. L.,&amp;Osuji, E. E. (2021). Climate Change Perception and Uptake of Climate-Smart Agriculture in Rice Production in Ebonyi State, Nigeria. Atmosphere, 12, Article No. 1503. &gt;https://doi.org/10.3390/atmos12111503
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref49">
    <label>49</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Orindi, V. A.,&amp;Eriksen, S. H. (2005). Mainstreaming Adaptation to Climate Change in the Development Process in Uganda. Ecopolicy Series No. 15, African Centre for Technology Studies (ACTS). &gt;https://www.africaportal.org/publications/mainstreaming-adaptation-to-climate-change-in-the-development-process-in-uganda/
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref50">
    <label>50</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Patt, A.,&amp;Schroter, D. (2008). Perceptions of Climate Risk in Mozambique: Implications for the Success of Adaptation Strategies. Global Environmental Change, 18, 458-467. &gt;https://doi.org/10.1016/j.gloenvcha.2008.04.002
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref51">
    <label>51</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Paudel, B., Acharya, B. S., Ghimire, R., Dahal, K. R.,&amp;Bista, P. (2014). Adapting Agriculture to Climate Change and Variability in Chitwan: Long-Term Trends and Farmers’ Perceptions. Agricultural Research, 3, 165-174. &gt;https://doi.org/10.1007/s40003-014-0103-0
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref52">
    <label>52</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Perkins-Kirkpatrick, S. E., Stone, D. A., Mitchell, D. M., Rosier, S., King, A. D., Lo, Y. T. E. et al. (2022). On the Attribution of the Impacts of Extreme Weather Events to Anthropogenic Climate Change. Environmental Research Letters, 17, Article ID: 024009. &gt;https://doi.org/10.1088/1748-9326/ac44c8
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref53">
    <label>53</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ren, S., Li, E., Deng, Q., He, H.,&amp;Li, S. (2018). Analysis of the Impact of Rural Households’ Behaviors on Heavy Metal Pollution of Arable Soil: Taking Lankao County as an Example. Sustainability, 10, Article No. 4368. &gt;https://doi.org/10.3390/su10124368
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref54">
    <label>54</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Satishkumar, N., Tevari, P.,&amp;Singh, A. (2013). A Study on Constraints Faced by Farmers in Adapting to Climate Change in Rainfed Agriculture. Journal of Human Ecology, 44, 23-28. &gt;https://doi.org/10.1080/09709274.2013.11906639
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref55">
    <label>55</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Schmidhuber, J.,&amp;Tubiello, F. N. (2007). Global Food Security under Climate Change. Proceedings of the National Academy of Sciences, 104, 19703-19708. &gt;https://doi.org/10.1073/pnas.0701976104
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref56">
    <label>56</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Seo, S. N.,&amp;Mendelsohn, R. (2008). An Analysis of Crop Choice: Adapting to Climate Change in South American Farms. Ecological Economics, 67, 109-116. &gt;https://doi.org/10.1016/j.ecolecon.2007.12.007
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref57">
    <label>57</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Skoufias, E., Rabassa, M.,&amp;Olivieri, S. (2011). The Poverty Impacts of Climate Change a Review of the Evidence: The World Bank Poverty Reduction and Economic Management Network Poverty Reduction and Equity Unit.
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref58">
    <label>58</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Sofoluwe, N. A., Tijani, A. A.,&amp;Baruwa, O. I. (2011). Farmers’ Perception and Adaptation to Climate Change in Osun State, Nigeria. African Journal of Agricultural Research, 6, 4789-4794.
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref59">
    <label>59</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Srivastav, A. L. (2020). Chemical Fertilizers and Pesticides: Role in Groundwater Contamination. In M. N. Vara Prasad (Ed.), Agrochemicals Detection, Treatment and Remediation: Pesticides and Chemical Fertilizers (pp. 143-159). Elsevier. &gt;https://doi.org/10.1016/b978-0-08-103017-2.00006-4
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref60">
    <label>60</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Udmale, P., Ichikawa, Y., Manandhar, S., Ishidaira, H.,&amp;Kiem, A. S. (2014). Farmers’ Perception of Drought Impacts, Local Adaptation and Administrative Mitigation Measures in Maharashtra State, India. International Journal of Disaster Risk Reduction, 10, 250-269. &gt;https://doi.org/10.1016/j.ijdrr.2014.09.011
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref61">
    <label>61</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Varga, A. (2021). Climate Change and Its Impact on Agriculture. Acta Horticulturae et Regiotecturae, 24, 50-57. &gt;https://doi.org/10.2478/ahr-2021-0010
    </mixed-citation>
   </ref>
   <ref id="scirp.135761-ref62">
    <label>62</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Wheeler, T.,&amp;von Braun, J. (2013). Climate Change Impacts on Global Food Security. Science, 341, 508-513. &gt;https://doi.org/10.1126/science.1239402
    </mixed-citation>
   </ref>
  </ref-list>
 </back>
</article>