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Assessment of Changes in Land Use and Land Cover in Hadejia Nguru

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Assessment of Changes in Land Use and Land Cover in Hadejia Nguru
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U. U. Alkali1, D.F.Jatau2 E.E.Dishan2

1Department of Forestry Technology, Yobe State College of Agriculture, Science and Technology, Gujba, P.M.B-1104, Damaturu, Nigeria, email: alkaliumara2@gmail.com

2Department of Forestry and Wildlife Management, Modibbo Adama University, Yola Adamawa State, Nigeria, email: dfjatau@gmali.com and ephraimdischan@cmail.com

INTRODUCTION  

Land use and land cover (LULC) describe the economic use of land and surface features, respectively. The Land cover reflects the biophysical state of the earth‘s surface including the soil material, vegetation, forest estate natural and man-made features, cultivated and  

human settlements, and water. Land use, on the other hand, refers to the use of land by humans. It is the alterations done to Land cover as a result of human activities such as farming, road construction, human settlements/urbanization, and industrialization (Panel,  et al., 2023). 

Land use and land cover are dynamic in nature and they provide a comprehensive understanding of the interaction and relationship of anthropogenic activities with the environment. Land use/cover changes also involve the modification, either direct or indirect, of natural habitats and their impact on the ecology of the area. Land use/cover change has become a central component in current strategies for managing natural resources and monitoring environmental changes (Zaitunnah et al, 2018)  Humans play a major role as forces of change in the environment, inflicting environmental change at all levels, ranging from the local to the global scale. The various uses of land for economic purposes have greatly transformed land cover at a global scale over the last 10,000 years, almost half of the ice-free earth surface has changed and most of the result was due to the use of land by humans (Joseph, et al., 2020). Land use and land cover changes are environmental issues mostly linked to climate change in a complex manner,  and changes in both can have profound effects on an ecosystem‘s ability to provide goods and services to human society Land use and land cover changes play a key role in climate changes through the exchange of greenhouse gases, sensible heat, and local evapotranspiration Approximately 35% of the CO2  emissions to the atmosphere were from land use. In addition to climate change, the growth of human population and land cover changes have an effect on the biogeochemical cycles, habitat availability,  biodiversity, soil erosion, water quality, water flow,  and sediment flows (Ajibola, et al. 2016). 

Intensification of land conversion for agriculture is accelerating land use land cover (LULC) change with its consequential impact on the natural landscape. For practical purposes, intensification occurs when there is an increase in the total volume of agricultural production that results from a higher productivity of inputs (FAO, 2005). Agricultural intensification in response to the government’s quest for economic diversification is aggravating LULC change across  Nigeria particularly at the heart of wetland ecosystems. Despite the inherent dynamic system of  wetlands, the ecosystem is suffering from great  transformations worldwide (Arooba and Sheikh,  

2017). These changes are fundamental obstacles in the country’s effort towards the attainment of food security, economic diversification, growth, and sustainability of the physical environment. Similarly,  Sebastiá et al. (2012) affirmed that a wide range of pressures affect these ecosystems and alter the quality and quantity of water. The increasing pressure on the ecosystem and the consequential land degradation are intensifying runoff, siltation of river channels, and flood events. 

The wetland ecosystems in the country serve as a  direct and indirect pool of resources for the  population that derives maximum benefits from the  exploitation of these essential resources for socio 

economic and sustainable livelihood. Ehsan and  Farhad (2014) described wetlands as the kidneys of the landscape because of their functions in chemical and hydrological cycles. The vast riverine wetland ecosystem is used most importantly for agriculture  (farming, grazing, and fishing) and the inhabitants primarily depend on it for livelihood. The environmental destabilization of the wetlands and of the “dynamically” developing areas as far as the geomorphological processes are concerned is mainly due to certain anthropogenic interventions that alter  “critical” parameters of the environment (Grundling et al., 2013). These alterations incorporate the greatest environmental concerns of human populations in recent times vis-a-vis loss of biodiversity, land, vegetal and water degradation, soil erosion, climate change, and its impact. Globally, the landscape and hydrological cycle have been modified by anthropogenic activity thereby, reflecting the socio-economic conditions and pattern of land resource utilization (Li et al. 2013). Monitoring and mitigating the negative consequences of LULC  dynamics as well as sustaining the production of this vital riverine ecosystem should be the primary focus of most developing nations. 

In spite of this, there has not been any comprehensive documented information on the changes in land cover and land use viz-a-viz the interphase between the livelihood sustenance practices in the study area.  Similarly, the range of change in land and land cover in the study area has not been documented.  Furthermore, information on the changes in land use and land cover changes remains scanty.  

The aim of this study is to assess the changes in land use/land cover in HNWs. The specific objectives are  to; evaluate the changes in land use land cover over a 

40-year window (1979-2019) in the study area, and assess the interphase of livelihood sustenance practices in relation to changes in land cover/ land use. 

The intense infringements of land use systems into traditional forests and wetlands and also changes in land cover/ land use are contributing to the degradation of ecosystems leading to unsustainable development. Whereas such land developments could be contributing to the short-term socio-economic welfare of the people, they in the long run cause degradation and thus threaten the very livelihoods of the local people they were meant to sustain. History has it that, these lowlands were once occupied by a  massive water body that has since receded, leaving behind patches. This shrinkage has been blamed on varied causes including changes in land use and anthropogenic factors. If this trend continues, the remaining wetland ecosystems may eventually be transformed into terrestrial landforms, losing a lot of their ecological and economic importance (Grundling et al., 2013). 

Fishing, Nomadic pastoralism, hunting, collecting, and gathering of vegetation resources constituted the main source of livelihood. Today, however, due to increased population and penetration of forces and influences of development have enormous competitive alternative and uses which includes;  permanent human settlements, agriculture, and forest resources commerce. Therefore, household welfare that was previously assured by relatively smaller stable competing factors is no longer ascertain. This study will thus provide baseline information on livelihood sustenance practices, changes in climatic variables, and changes in climatic variables scenario viz-viz the environmental, social, and economic responses of the communities who depend on the resources for their livelihood sustenance. The result can provide an avenue for strategic management and conservation options for the government and other stakeholders. 

The study is limited to the assessment of livelihood sustenance practice in HNWs inhabitants in relation to changes in climatic factors and land use/land cover.  Data collection was limited to parameters related to the stated objectives. 

MATERIALS AND METHODS 

Study Area 

Location of the Study Area 

The HNWs are located at a point where Rivers Hadejia and Jama’are flow through a fossil dune field before converging and draining into Lake Chad (Barbier and  Thompson, 1998) and lie between longitude 10°15′E  and 11°30′E, and latitude 12°13′N and 12°55′N. The wetlands extend for approximately 120 km from West to East within Jigawa State and a further 60–70 km downstream in adjacent Yobe State (Barbier and  Thompson, 1998). In width, the wetlands range from  l0km to more than 50 km from North to South, with approximately 8000 km2 of floodplain covering three  Nigerian States (namely Bauchi, Jigawa, and Yobe).  The extent of the floodplain varies considerably from year to year depending on the volume of rainfall and complex interactions of river flow, dam releases, flood regimes, and topography. In Nigeria, wetlands cover about 28,000 km² (about 3%) of the 923,768 km2 of the country’s land area (Abubukar et al., 2016). One of these is the HNWs named after two major towns  (Hadeja and Nguru) in the area and are surrounded by many villages.  

The Hadeja-Nguru Wetlands (HNWs) is an extensive floodplain created by the Hadeja and Jama‘are Rivers to form the Komadugu- Yobe River which drains into  Lake Chad. The wetlands cover an area of about 350,  000 ha and have an altitude of (asl) 152 – 305m (Bird Life International, 2015). The Nguru Lake and Marma  Channel Complex Wetlands (located within the  HNWs) were designated as the first Nigerian wetlands of international importance under the Ramsar  Convention. According to Ramsar, (1994), the wetlands are notably known for the recharge and replenishment of underground water in the  Komadugu-Yobe Basin, economically rich habitats for the biodiversity of various fauna and flora. The area is a major tourism site for the Palearctic and Afrotropical migrant water birds (Eaton and Sarch, 1997). 

Vegetation of the study area 

The general vegetation is characteristic of the Sudan savanna, – Sparse shrubs and isolated tall trees mostly  Acacia Species. Three broad types of vegetation occur in HNWs. There is a scrub savanna, which consists of upland farmland areas and Acacia Woodlands. The  second includes the “tutu” (raised areas) which are  never inundated with tree species of Acacia, Ziziphus  species, Balanites aegyptiaca, Tamarindus indica and 

Adansonia digitata, while common grasses include  Cenchrusbiflorus, Andropogon species. and Vetiveria  nigritana. 

In addition, pockets of riparian forests and woodlands,  known as “kurmi” comprise species of Khaya senegalensis, Mitragyna inermis, and Diospyros mespiliformis. In some parts, the kurmi has been replaced with orchards of mango Mangifera indica,  and guava Psidium guajava, (Ezealor, 2001). The third vegetation type consists of the seasonally flooded  marshes in which the tree Acacia nilotica, is common while Dum palms (Hyphaene thebaica) grow on small,  raised islands (Ezealor, 2001). Aquatic grasses include  Echinochloa and Oryza species. While in drier parts  Dactylocteniu maegyptium, Setaria species and  Cyperus species, occur, and extensive vegetation of  Typhadomin genesis along the shore of the wetlands.  The favorable moisture regime due to the high ground water table supported Mitragyna ground water woodland and seasonally flooded grassland. The woodland is becoming degraded due to falling water table as reported by Hadeja-Nguru Wetlands  Conservation Projects (HNWCP, 1997). 

The ecosystem comprises permanent lakes and seasonally flooded pools connected by a network of channels. The ecosystem is an important site for biodiversity, especially migratory water birds from  Palearctic regions (Abubakar et al. 2016). For example,  at one time, the floodplain supports over 423,000  birds of 68 species, including significant numbers of  Ferruginous Duck (Aythyanyroca), Spur-winged Goose  (Plectropterus gambiensis), Black-tailed Godwit  (Limosalimosa), and Ruff (Philomachu spugnax) (Birdlife International, 2010). Other wildlife species found include species of gazelle (Gazella spp.), duiker  (Cephalophus spp.), jackal (Canissp), and hyena  (Crocuta crocuta) (Ogunkoya and Dami, 2007). In total,  there are about 378 bird species listed for the wetland, 103 fish species, 250 species of flowering plants, and more than 136 species of aquatic flora and fauna (Oduntan et al. 2010). 

Population 

The HNWs is the first Nigeria wetland to be named a  RAMSAR site (RAMSAR, 1994). The people in the area depend on this wetland for water supply and other daily activities. Hausa, Kanuri, Fulani, and Bade are the  most dominant tribes in the wetlands where Hadeja  has a population of 139,400 among which 54.6% are  male and 46.4% are female (National Bureau of  

Statistics, 2016). The population including farmers,  herders, and fishermen who entirely depend on the ecosystem for their livelihoods (Kaugama and Ahmed,  2014; Birdlife international, 2015). The wetlands provide essential income and nutrition benefits in the form of agriculture, grazing resources, Non-Timber  Forest Products, fuel wood, and fishing (RAMSAR,  2007).. 

Geology, Topography and Soil 

Permeable sedimentary rocks of the Chad formation  underlie this natural wetland, but a film of impervious layers has been formed at the bottom of the water body through successive years of clay deposition. This has significantly impeded percolation (Emmanuel,  2019). A monotonous low-lying plain that gently slopes northeastwards towards Lake Chad characterizes the relief around the site. River flow is highly seasonal and varies considerably depending on rainfall and run-off. Peak flow occurs between August and September when banks overflow and the area is inundated. The river regime in the area has however been affected by river regulation that peak discharge in the wetland is now in September-October  (Emmanuel, 2019). 

Drainage 

Hydrology of the Hadeja-Nguru Wetlands The hydrological genealogy of the Hadeja-Nguru Wetlands sustains water from rainfall and runoff supplements from the wet season and is later depleted by other hydrological output like infiltration to underground,  soil moisture recharge, and evaporation (RAMSAR,  2007). 

Climate 

The Hadeja-Nguru wetland is located as part of the  Komadugu-Yobe River basin, it has a semi-arid climate influenced by the strong convection storm of the  Inter-Tropical Convergence Zone (ITCZ). The climate of the wetland is characterized by two distinct seasons;  wet season (May- September) and dry season  (October-April), The rainfall period is from June to  October and has an annual mean of over 1,000mm in the upstream Basement complex area and approximately 500mm in the Hadeja-Nguru Wetlands  (Sanyu, 1994). The dry season normally sets in  October and remains until late May. The temperature recorded in the dry season ranges between 35°C and  40°C. Significant water flows to the wetlands begin in 

late June or early July with peak discharges in August.  Occasionally there may be a mean minimum temperature of 12°C from the month of December to  January, (Ogunkoya and Dami, 2007). 

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Figure: 1 Map showing boundary demarcations of HNWs between States Sources: GIS University of Maiduguri  (2019) 

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Figure: 2 legend map of HNWs 

Source: GIS University of Maiduguri. (2022)

J. Agric. For. Res. Vol. 2, No. 4, pp. 1-15, Year 2023 

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S7 n9zzLHtfVgZAJbXdN807FL04wXJfjXpueotswhHJxDro1thOwwqJgS0PRjARxSzgTph3SjGhSeaogrm7J1xAtA1E1o1vM6le7szNu9b1rD32CBINMgLWhYup8mRkBVR

Figure 3: Map showing the extracted coordinate location of the study sites 

Sources: GIS University of Maiduguri (2019)

Assessment of land use changes in HNW 

The imageries of HNWs were officially sourced and downloaded from the official website of the United States Geological Survey  (https://earthexplorer.usgs.gov/). The study area was classified into four classes or categories based on field study and personal experience of the study sites. Four land use/land cover (LULC) themes were decided for this research. These land use/cover categories or classes are: Water body, Thick vegetation, Grasses, and bare land. The description and composition of these classes are presented in Table 2. This presents the remote sensing aspect of the study as it provides the land use/land cover change information for the selected study region. The detailed characteristics of the imageries used to produce the LULC maps are provided in (Table 2).  

As can be observed in Table 3, the multispectral  Landsat imageries covering the period from 1979 to  2019 were specifically selected from those available based on image quality. In all, three different epochs  (1979, 1999, and 2019) were selected. 

Data Analysis 

Analysis of land use changes in HNW 

To get the extent of the observed changes, post-classification change detection approach was used to assess the five classified land cover maps using simple descriptive statistics. The Areal Statistics for the five land cover types were generated using the calculate area tool of ERDAS Imagine version 15 software, and this was generated in Hectares (H). Overall, from the statistics of the land cover maps, the change magnitude, change trend, and Annual rate of change  of the observed changes were then computed using  the following formula (Abbas, 2012). 

Magnitude =  

CGUamHe8fE5TzANxZbhdM NNhv0Iodhvqu J61CSK4aqRdmltyLqF

Percentage change (trend) for each LULC type was  computed by dividing magnitude change by sum of  observed changes between the years concerned and  multiplied by 100 as shown in the equation: 

pvdRBalSFeYoJhp2pmn8aocYq0lHtsqnzRMl2 7UGWKilX nrsHKPsPNY2Gr4sc1n7p2TFSDz1r7NRcioxJXc97hJOeo2yyoOvM2LNZwe sMFl3V WVaFxjoC H6hukiyGBzfs84Lz1ITa4ZvevQT 0

To generate the annual rate of change for each LC  type, the trend (percentage change) was divided by  100 and multiplied by the number of study years in  between the two periods, for example, 1972 – 1986,  1999-2009, 2009-2020 as shown below in the  equation: 

(Abbas, 2012)  

Assess the interphase of livelihood sustenance  practices and changes in land cover land use 

Paired sample T-test of differences was used to test the differences in livelihood before and present while  chi-square test of association was used to test the influence of the changes in LULC and climate on the livelihood as observed by the respondents in the area. 

i. Students t-test 

mE3vn8z11VQ9Ok6hwtGqkyvAk1XeMNMLIB4nf68KWt6dFX892OPTVypx32jSIOi0YbkIeFaZ 7g3rI0lnAT6uXqVXgiEU7TV5KciZ4HN1hJ1VNCBhqNpzGh8FmK wciEqZ3niDtXzB dtyyqDkSiVY4

Where t = t-test 

x = Livelihood before 

y = Livelihood After 

n = number of observations 

ii. Chi-square 

Where X2 = chi-square 

O = Observed frequency 

E = Expected frequen 

Assessment of land use changes in HNW 

The imageries of HNWs were officially sourced and downloaded from the official website of the United States Geological Survey  (https://earthexplorer.usgs.gov/). The study area was classified into four classes or categories based on field study and personal experience of the study sites. Four land use/land cover (LULC) themes were decided for this research. These land use/cover categories or  classes are: Water body, Thick vegetation, Grasses and 

bare land. The description and composition of these classes are presented in Table 2. This presents the remote sensing aspect of the study as it provides the land use/land cover change information for the selected study region. The detailed characteristics of the imageries used to produce the LULC maps are provided in (Table 2).  

As can be observed in Table 3, the multispectral  Landsat imageries covering the period from 1979 to  2019 were specifically selected from those available based on image quality. In all, three different epochs  (1979, 1999, and 2019) were selected. 

Image Classification 

Landsat 5 ETM, 7 ETM+ and 8 (OLI) images of 30m  resolution with worldwide reference system (WRS)  address of; path 187 row 051/052 (20/11/1979- 

20/11/1980), (08/12/1999-08/12/2000), and  (05/01/2019-05/01/2019) for 1979, 1999, and 2019  respectively were downloaded from glovis.usgs.gov.  The Landsat images were processed and mosaic to  give a comprehensive coverage of the wetland area with help of image analysis and spatial analysis tool in  Arc GIS 10.3. Unsupervised classification was adopted for the study. 

Areas of the classes were calculated in km2 one after the other by highlighting the layer (class) in the attribute table, reclassified the map to produce the area of the selected class. The area of the reclassified layer (class) was then converted into a polygon and was letter calculated using calculates area tool in  spatial statistics toolbox (Figures 4 and 5). All these procedures were applied in producing the LULC of each year and calculation of the areas. 

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Figure: 4 Conversion of Images from Raster to Polygon

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Figure: 5 calculation of total area of each class. 

Table: 1 The description and characteristics of the LULC types used in the study 

LULC Types Description/composition 

Water bodies – This land cover type represents all areas of open water bodies, generally with less than 10% vegetal cover. This also represents all open water bodies irrespective of depth (both shallow and depth waters).  

Thick Vegetation – These are plants of an area that grow in disturbed or undisturbed conditions in wooded plant communities in any combination of trees, saplings, shrubs, vines, and herbaceous plants, including mature and successional forests and cutover stands. 

Bare-land – These are areas characterized by open land with little or no NTFPs. It also includes fallow agricultural fields and lands that are being subjected to continuous cultivation. Areas where soil exposure is apparent.  

Grassland These represent degraded and dried-off areas of the wetland or areas that before were occupied by  NTFPs and water. It also represents inundated and dried floodplain areas. These areas largely lack vegetal cover or NTFPs and it appears dark and whitish in the raw satellite imagery.  

Source: Field Work, (2021). 

Analysis of land use changes in HNW 

To get the extent of the observed changes, post-classification change detection approach was used to assess the five classified land cover maps using simple descriptive statistics. The Areal Statistics for the five land cover types were generated using the calculate  

area tool of ERDAS Imagine version 15 software, and this was generated in Hectares (H). Overall, from the statistics of the land cover maps, the change magnitude, change trend, and Annual rate of change of the observed changes were then computed using the following formula (Abbas, 2012).

Percentage change (trend) for each LULC type was  computed by dividing magnitude change by sum of  observed changes between the years concerned and  multiplied by 100 as shown in the equation: 

To generate the annual rate of change for each LC  type, the trend (percentage change) was divided by  100 and multiplied by the number of study years in  between the two periods, for example 1972 – 1986,  1999-2009, 2009-2020 as shown below in the  equation: 

RESULTS 

The Trajectories of the LULC Change from 1979-2019 

Table 1 presents the change trajectories of the four  LULC classes identified in the area under study. The classified maps are also presented in Plates I and III  which portrays the change trajectories of the entire landscape of HNW between 1979 and 2019. The result indicated that water body in HNW in 1979 was  4131.70 Km2 and in 1999 it occupied an area of about  1,255.99 Km2 which decreased by -69.60%. Bare surface which occupied a total area of 1,556.35 Km2  in 1979 increased to 9,466.04 Km2 in 1999 indicating an increase of 508.22%. Grassland had an area of  6,339.38 Km2 in 1979 and decreased to 2,709.38 Km2  in 1999 indicating a decrease by -57.26%, while thick vegetation which occupied a total area of 14,284.25  Km2 in 1979 decreased to 12,880.27 Km2 in 1999  indicating a decrease by -9.83%. 

The percentage change in land use land cover classes between 1999 and 2019 as presented in Table 2 and 3  and Plates I and III. The result indicated that water body which occupied a total area of 1,255.99 Km2 in  1999 decreased to 1,095.62 Km2 in 2019 indicating a  decrease by -12.77%. Bare surface which occupied a  total area of 9,466.04 Km2 in 1999 decreased to  8,348.98 Km2 in 2019 indicating a decrease by – 11.80%. Grassland had an area of 2,709.38 Km2 in  1999 and increased to 7,306.72 Km2 in 2019 indicating  an increase of 169.68 %, while thick vegetation which occupied a total area of 12,880.27 in 1999 had reduced to 9,560.36 Km2 in 2019 indicating a decrease by -25.78%. 

The percentage change in land cover classes between  1979 and 2019 is presented in Table 8 and 9, Plates I  and III. The result indicated that water body which occupied an area of 4,131.70 Km2 in 1979 decreased to 1,095.62 Km2 in 2019 indicating a decrease by – 277.11%. Bare surface which occupied a total area of  1,556.35 Km2 in 1979 increased to 8,348.98 Km2 in  2019 indicating an increase of 81.36%. Grassland had an area of 6,339.38 Km2 in 1979 but increased to  7,306.72 Km2 in 2019 indicating an increase by 13.24  %, while thick vegetation which was 14,284.25 Km2 in  1979 decreased to 9,560.36 Km2 in 2019, indicating a  decrease by -49.41%. All land cover classes indicated losses of varying degrees and rates between 1979 and  2019. The rates at which selected surfaces changed were; Thick vegetation (118.10); water bodies (75.90),  Bare surfaces (169.82), and grassland (24.18)  respectively. The projected years of exhaustion of  thick vegetation showed that in approximately 80.95  years there will not be vegetation while water body indicated that in approximately 14 years the HNWs will disappear. 

Table: 2 Area and Percentages of Land cover classes in Hectare (H) during the Study Period 1979-2019 

LULC Themes 1979 (%) 1999 (%) 2019 (%) Thick Vegetation 14,284.25 54.29 12,880.27 48.95 9,560.36 36.34 Grass land 6,339.38 24.09 2,709.38 10.30 7,306.72 27.77 Water Bodies 4,131.70 15.70 1,255.99 4.77 1,095.62 4.16 Bare Surfaces 1,556.35 5.92 9,466.04 35.98 8,348.98 31.73 Total 26,311.67 100.00 26,311.67 100.00 26,311.67 100.00 

Source: GIS Analysis, (2019)

J. Agric. For. Res. Vol. 2, No. 4, pp. 1-15, Year 2023 

Table: 3 Magnitudes of Change in the four identified LULC themes from 1979-2019 in HNWs 

LULC Themes 1979- 1989 

Thick  

%∆ 1999-2009 %∆ 1979-2019 %∆ Rate Projection 

Vegetation -1,403.99 -9.83 -3,319.91 -25.78 -4,723.90 -49.41 -118.10 -80.95 Grass land -3,630.00 -57.26 4,597.34 169.68 967.34 13.24 24.18 302.14 Water Bodies -2,875.70 -69.60 -160.38 -12.77 -3,036.08 -277.11 -75.90 -14.43 Bare Surfaces 7,909.69 508.22 -1,117.05 -11.80 6,792.64 81.36 169.82 49.16 Source: GIS Analysis, (2019) 

Plate: I The classified Land cover map of HNWs as at 1999 

Source: GIS Analysis, (2019) 

Plate: II The classified Land cover map of HNWs as at 2019 

Source: GIS Analysis, (2019)

DISCUSSION 

Findings from the classification of the imageries indicated continuous decrease in the water bodies from 1979 to 2019, which could be due to agricultural land use conversion. This could impact negatively on hydrological processes and ecosystem health. These observations agree with the findings of a similar study by Chen et al. (2009) on Impacts of land use change scenarios on storm-runoff generation in Xitiaoxi basin,  China; Tadesse et al. (2015) who also reported on  Assessing the impact of land-use land-cover change on stream water and sediment yields at an assessment of watershed level using SWAT; Woldesenbet et al.  (2017) on Hydrological responses to land use/cover changes in the source region of the Upper Blue Nile basin, Ethiopia; Uluocha and Okeke (2004) on impacts of climate variability and land use change on streamflow in the Hailiutu river basin and Adepoju et al. (2019) on Vegetation Response to Recent Trends in  Climate and Land Use Dynamics in a Typical Humid and  Dry Tropical Region under Global Change. 

The increase in bare surfaces in the wetlands between  1979 and 2019 could be attributed to increased  farming and grazing (including lopping of trees for livestock as well as for tradomedicinal uses) as  observed during ground truthing. These findings are in consonance with those of Ikusemoran and Ezekiel  (2011) in their study of Remotely Sensed Data and  Geographic Information System Techniques for  Monitoring the Shrinking HNWs, Nigeria where they affirmed human interventions especially agricultural practices to be the major cause of the changes in the wetlands, also grazing by herdsmen in the wetlands area for several generations. Geist and Lambin (2002)  and FAO (2005) reported grouping of the land cover classes gave rise to three groups, which included the water body, the vegetation covers and the bare surfaces/farmland. This is in agreement with the fact that most areas in Africa, including Nigeria and HNWs in particular experience land tenure insecurity,  particularly due to increasing land transactions for expansion of agri-business in conformity to the studies of Woldesenbet et al. (2017) and Pare, (2008). 

Since, several factors contribute to a more complex land use dynamics pattern, the vegetation experienced losses as it decreased over the period in the study location. The overall change of thick vegetation in HNWs study sites between 1979 and  2019 was on the negative side (-49.41%) indicating a  decrease. The marginal depletion of vegetation of the  site may not be unconnected with the interruption of the natural flood regime via diverting flood water in the wet season and releasing damaging flood surges during the dry season and also as a result of several dams (including two large ones at Tiga and Challawa)  and other hydro agricultural projects with intensive water demand have been commissioned at locations upstream as noted by Ikusemoran and Ezekiel (2011).  The combined effects of these factors must have caused the dynamics of vegetation of the study site. 

CONCLUSION AND RECOMMENDATION

Conclusion  

Both natural and human activities are known to modify the natural environment, and HNWs is not an exception. The communities in the wetlands depend largely on the natural resources for their livelihood and survival. These natural resources have been significantly altered and continue to deplete due to unsustainable practices and over population. The natural resource scarcity that resulted from environmental changes have had severe impacts on  wetland through loss of biodiversity, soil productivity  and accelerated environmental degradation thereby increasing vulnerability and reduction in biodiversity.  This hardship imposed led to a number of adjustments by individuals and communities to continue making out a living within the same environment. However, the current community level of adaptation measures may not be sufficient to meet the challenges of the current environmental change particularly in the face of change in LULC. It is therefore very important to improve the understanding of local populations and communities on the prevailing changes in their immediate environment because their behavior of removing vegetation cover , over the study period and the test of the relationship on vegetation cover as represented by the land use changes showed that there is an interwoven relationship among all the factors. The massive increased in removal of vegetation cover had the strongest impact amongst other factors that the research examined on the deterioration of the vegetation cover, wind speed increased steadily as observed during study periods.  Based on the findings of this study, it is clear that the  HNWs area should be protected because of the richness in biodiversity.

Recommendation 

Based on the findings of the study the following are  some of the recommendations  

i. There is need to put in place right policies to protect and preserve wetland to enhance its sustainability and resilience to climatic changes and variability.  

ii. Policy making as well as academic research on ecosystem changes should integrate people’s testimonies and their stories as evidence of those changes. Such integration of local knowledge will help in foregrounding place-based sustainability models. 

ii. Finally, there is the need for the government to have a plan action of mitigation and adaption measures in place and to provide a legal framework for their adoption. 

REFERENCES 

Abbas, I.I. An assessment of land use/land cover changes in a section of Niger Delta, Nigeria.  Frontiers in Science, 2012, 2(6), 137-143. 

Abubakar, M.M.; Kutama, A.S.; Suleiman, I.M.; Ringim,  A.S. Impact of climate change on the Hadeja Nguru Wetlands: A review. Dutse Journal of Pure and Applied Sciences, 2016), 2(1): 150-158. 

Adepoju, K.; Viola, F.; Adelabu, S. Fashae, O.  Vegetation Response to Recent Trends in Climate and Landuse Dynamics in a Typical Humid and  Dry Tropical Region under Global Change.  Advances in Meteorology, 2019, Volume 20  |Article ID 4946127, 15 pages.  https://doi.org/10.1155/2019/4946127 

Ajibola, M.O.; Adeleke, A.M.; Ogungbemi, O.A. An assessment of wetland loss in Lagos Metropolis,  Nigeria. Developing Country Studies, 2016,  6(7),1-7. 

Arooba, Z.; Sheikh, S.A. Land Cover Classification of  Ucchali Wetlands Complex and Assessment of its  Correlation with Temporal Climatic Changes.  Science, Technology and Development, 2017, 36  (1), 17-29. 

Barbier, E.B.; Thompson, J.R. The value of water:  floodplain versus large-scale irrigation benefits in  Northern Nigeria. Ambio, 1998, 27(6), 434-440. 

Bird Life International. Important Bird Areas factsheet:  Hadeja- Nguru wetlands. 2015. 

Campos, J.C.; Sillero, N.B.; José C. Normalized difference water indexes have dissimilar performances in detecting seasonal and permanent water in the Sahara-Sahel transition zone. Journal. Hydrology, 2012, 464, 438–446. 

Chen, Y.; Xu, Y.; Yin, Y. Impacts of land use change scenarios on storm-runoff generation in Xitiaoxi basin, China. Quat. Int. 2009, 208, 121–128. 

Eaton, D.; Sarch, T.M. The economic importance of wild resources in the Hadeja-Nguru wetlands:  Collaborative Research in the Economics of  Environment and Development (CREED).-London  (International Institute for Environment and  Development) (No. 13). Working Paper., 1997, Pp  10-19. 

Ehsa, D.; Farhad, T. Analytical Study on Threats to  Wetland Ecosystems and their Solutions in the  Framework of the Ramsar Convention.  International. Journal of Environmental and  Ecological Engineering, 2014, 8 (7), 2108-2118. 

Emmanuel, J. The shrinking of the Wetland. The depletion of Hadeja Nguru Ramsar site, causes and implication from geophysical Approach. 2019. 

Eric, F.L.; Jianchu, X. The causes of land-use and land cover change: Moving beyond the myths. Global environmental change. 2011, Volume 2 issues 4,  2011. 

Ezealor, A.U. Important Bird areas in Africa and associated islands. Report by Nigeria  Conservation Foundation (NCF), Lagos, Nigeria.,  2001, Pp 675-688. 

Food and Agricultural organization (FAO). State of the  World’s Forest. FAO Forestry Paper No. 140.  2001, 84pp. 

Food and Agricultural organization (FAO). Adaptation of forest ecosystems and the forest sector to climate change. Forests and Climate Change  Working Paper No. 2, Rome, FAO/Swiss Agency for Development and cooperation. 2005. 

Gauthier, G.; Giroux, J.F.; Reed, A.; Bechet, A.; Belanger, L. Interactions between land use,  habitat use, and population increase in greater snow geese: what are the consequences for natural wetlands? Glob. Change Biol., 2005, 11  (6), 856–868. 

Geist, H.J.; Lambin, E.F. Proximate causes and underlying forces of tropical deforestation.  Bioscience, 2002, 52, 2:143–150. 

Giannecchini, M.; .Twine, W.; Vogel, C. Land cover change and human environment interaction in a  rural cultural landscape in South Africa. The  Geophysical Journal, 2007, 173(1) 26-42. 

Grundling, A.T.; Van den Berg, E.; Price, J.S. Assessing  the distribution of wetlands over wet and dry  periods and land-use change on the Maputo land

Coastal Plain, north-eastern KwaZulu-Natal,  South Africa. South African. Journal., 2013, Geomatics. 2 (2), 120–138. 

Hadeja Nguru Wetland Conservation Project  (HNWCP), Dynamic of livelihood System and the resources base in the Hadeja-Nguru Wetlands.  Submission to the renewable natural Resources  (RNR). Sector Coordinator of the United  Kingdom, Development (DFID) Kaduna by  HNWCP-Nguru, July 1997. 

Ikusemoran, M., Ezekiel, Y. Remotely Sensed Data and  Geographic Information System Techniques for  Monitoring the Shrinking Hadejia – Nguru  Wetlands, Nigeria., 2011. 

Inuwa, K.B. Assessment of land use and land cover  change in Nguru Part of Hadejia-Nguru Wetlands,  Yobe State, Nigeria. M.Sc Thesis, Department of  Geography, Unimaid, Nigeria., 2016, pp: 1-98. 

Inuwa, K.B. Assessment of land use and land cover  change in Nguru Part of Hadejia-Nguru Wetlands,  Yobe State, Nigeria. M.Sc. Thesis, Department of  Geography, Unimaid, Nigeria, 2016, pp: 1-98. 

Joseph. S.; Ibrahim, N.M.; Raghavan, S.; John, B.; Venkat, L. Mapping Land Use Land Cover Change  in the Lower Mekong Basin from 1997 to 2010.  Front. Environ. Sci., 2020, 19 March 2020Sec.  Land Use Dynamics Volume 8 – 2020 |  https://doi.org/10.3389/fenvs.2020.00021 

Lambin, E.F.; Geist, H.J.; Lepers, E. Dynamics of land Use and Land-Cover change in tropical regions.  Annual. Review. Environmental Resources., 2003,  28:205–41doi:  

10.1146/annurev.energy.28.050302.105459Cop yrightc∞ 2003 by Annual Reviews. All rights  reserved first published online as a Review in  Advance on July 16, 2003 

Lambin, E.F.; Geist, H.J.; Lepers, E. Dynamics of land use and land-cover change in tropical regions.  Annual review of environment and resources,  2003, 28(1), 205-241. 

Li, Q.; Cai, T.; Yu, M.; Lu, G.; Xie, W.; Bai, X.  Investigation into the Impacts of Land-Use  Change on Runoff Generation Characteristics in  the Upper Huaihe River Basin, China. J. Hydrol.  Eng., 2013, 18, pp. 1464-1470. 

Liang, S., Automatic land-cover update approach integrating interative training sample selection and a Markov Random Field model. Remote Sens.  Lett. 2014, 5(2). 148–156. 

Mundia, C.N.; Aniya, M. Dynamics of land use/cover changes and degradation of Nairobi city, Kenya.  Land degradation and development, 2006,  volume 17, issue 1.pp-97 

Mundia, C.N.; Aniya, M. Dynamics of landuse/cover changes and degradation of Nairobi city, Kenya.  2006, Land degradation and development  volume 17, issue 1.pp-97. 

Obang, O.O.; Sintayu, L.G.; Dessalegn, O.G. Analyzing the rate of land use and land cover change and determining the causes of forest cover change in  Gog District, Gambella Regional State, Ethiopia.  Journal of remote sensing and GIS, 2017. 

Oduntan, O.O.; Akinyemi, A.F., Adetoro, A.O.; Osunsina, I.O.O. Seasonal availability of farmland and its contribution in wildbirds-landuse conflicts in Hadejia-Nguru wetlands, Nigeria. African  Journal of Agriculture, 2010, 6:3, 131-137. 

Ogunkoya, O.O.; Dami, A. Information Sheet on  Ramsar Wetlands (RIS) – 2006-2008 version:  Dagona Sanctuary Lake, Hadejia-Nguru wetlands.  Annual report submitted to Ramsar. Gland,  Switzerland, 2007. 

Panel, H.W.; Xiong, X.; Kehuan, W.; Xin, L.; Hongjuan  H.; Quanliang, L.; Hengqing, Y.; Chenxi, W. The effects of land use on water quality of alpine  rivers: A case study in Qilian Mountain, China.  Science total environment, 2023, volume 875, 2023162696.https://doi.org/10.j.scitotenv.2023. 162696. 

Paré, S. Land use dynamics, tree diversity and local  perception of dry forest decline in southern  Burkina Faso, West Africa. Land Use Dynamics,  Tree. Faculty of Forest Sciences Department of  Forest Genetics and Plant Physiology Umeå  Doctoral Thesis Swedish University of  Agricultural Sciences, 2008. 

Ramsar. The Ramsar Convention on Wetlands;  Convention on wetlands of international importance‘s especially waterfowl‘s habitat,  Paris. 13 July 1994. Ramsar convention secretariat, Gland, Switzerland. 

Sanyu. The study of the National Water Resources  Master Plan. Sanyu Consultants Inc. For Japan  International Cooperation Agency., 1994.,  Science, Technology and Development 36 (1), pp.  17-29. 

Sebastiá, M.T.; Rodilla, M.; Sanchis, J.A.; Altur, V.; Gadea, I.; Falco, S. Influence of nutrient inputs from a wetland dominated by agriculture on the phytoplankton community in a shallow harbour at the Spanish Mediterranean coast. Agric.  Ecosystem. Environment, 2012, 152, pp. 10–20. 

Tadesse, W.; Whitaker, S.; Crosson, W.; Wilson, C..  Assessing the Impact of Land-Use Land-Cover  Change on Stream Water and Sediment Yields at a Watershed Level Using SWAT. Open Journal.  Mod. Hydrol., 2012, 2015, 5, 68. 

Tijjani, M.N.; Adekoya, A.E.; Fashae, O.A.; Tijjani, S.A.; Aladejana, J.A. Land-Use Changes and  Urbanization Impacts on Livelihood and  Groundwater Sustainability of Coastal Areas of  Lagos, SW-Nigeria: Integrated GIS-based,  Livelihood and Hydro chemical Assessments.  Journal of Mining and Geology, 2018, 54(2) 2018,  187– 202 

Uluocha, N.O.; Okeke, I.C. Implications of wetlands degradation for water resources management:  Lessons from Nigeria. Geo Journal, 2004, 61, 151- 154. 

Umar, I.A.; Yaduma, Z.B.; Dishan, E.E.; Adaeze, J.E.  Land cover Change of Gashaka Gumti National  Park within 21 Years Window (1991 to 2011)  Using Satellite Imageries. Open Access Library  Journal, 2019, Volume 6, e5750. ISSN Online:  2333-9721. ISSN Print: 2333-9705 DOI:  10.4236/oalib.1105750 Sep. 26, 2019 1  

Woldesenbet, T.A.; Elagib, N.; Ribbe, L.; Heinrich, J.  Hydrological responses to land use/cover changes in the source region of the Upper Blue  Nile Basin, Ethiopia. Science of the Total  Environment., 2017, 575. 724-741.  10.1016/j.scitotenv.2016.09.124. 

Zaitunnah, A.; Samsuri, Ahmad, A. G.; Safitri, R.A. Normalized differences Vegetation index.  Analysis for land cover type using landsat. IOP  Publishing Conference series earth and environmental science, 2018, 126.

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