# Impact of the Proliferation of Invasive Plants on Biodiversity and Women's Socio-Economic Adaptation Strategies in the Lake Chad Area

Alexis Dzokom

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Alexis Dzokom. Impact of the Proliferation of Invasive Plants on Biodiversity and Women's Socio-Economic Adaptation Strategies in the Lake Chad Area. SAHARA-J: Journal of Social Aspects of HIV/AIDS, In press. hal-04679428

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# Impact of the Proliferation of Invasive Plants on Biodiversity and Women's Socio-Economic Adaptation Strategies in the Lake Chad Area

Alexis DZOKOM

SAHEL NATURE CONSULTING FOR COMMUNITIES, Sahelian Zone Office, Cameroon

Department of Geography, Faculty of Art, Letter and Social Sciences, University of Maroua, Cameroon

## Abstract

The increase in the magnitude of the effects of the invasion of environments by prolific invasive plants which impact biodiversity, eliminate certain major economic activities while increasing social challenges, women are increasingly vulnerable to climate change. The study of the impact of the proliferation of invasive plants on biodiversity and the socio-economic adaptation strategies of women in the Lake Chad area could help in the medium and long term, as a decision-making tool. The objective of this study is to determine the effect of *Prosopis juliflora* and *Eichhornia crassipes* on biodiversity and the socio-economic adaptation strategies of women in the Lake Chad area. Taking floristic data on site made it possible to carry out the floristic inventory based on the Braun-Blanquet dominance abundance coefficients and the faunal inventory inspired and updated by the Biosedimentary Index (BSI) and Lake Chad Biotic Index (LCBI) methods. The study area was digitized and produced using ArcGis. The raw data were analyzed and formatted with Microsoft Office Excel software and imported as text files (separator: tab) into R and SPSS software. On an average of 4,167±2,786 sampling points, an average of 165,667±2,804 *Eichhornia crassipes* plants was observed, with an average abundance-dominance index of 3.833±1.169 and an average recovery rate of all the area of Lake Chad Cameroon which is 53.575±26.621%. However, the average regularity on the waters of Lake Chad is 0.598±0.217, higher in Makary (1.000) and lower in Blangoua (0.386). The average frequency of *Eichhornia Crassipes* in the waters of Lake Chad Cameroon is 16.7±0.11%; the highest is that of Makary (36%), while those observed in Darak (08) and Hilé Alifa (08) are weak. Women in the Lake Chad area and northern Cameroon carry out mainly agricultural subsistence activities. In any season on the water, the average rate of cleaning of spaces on the banks of Lake Chad for agricultural purposes is 8.6±0.55% while the average rate of use of methods for cleaning the bottom of the Lake Chad is 2.8±0.89% Sahelian semi-arid zone within the GIC and women's association. The transformations and sales of products carried out within the GICs is 12.32±7.23 Kilogram/Season/woman within the associations and 04.82±03.33 Kilogram/Season/woman within the GICs. The social strategy to adapt field production during the rainy season indicates that the average rate of diversification of forms of mutual aid is 25.80±3.27% in associations and 22.20±2.77% in GICs, while that the average rate of donation requests in the form of agricultural materials or support, seeds and nurseries is 85.00±9.13% in association and 89.60±5.02% in GIC.

**Keys words:** Invasive Plants, Biodiversity, Women, Adaptation Strategies, Lake Chad

## 1. Introduction

In recent years, many rivers and their tributaries have been invaded by invasive plants, notably *Eichhornia crassipes* (Tchiaze and Priso, 2016): this is the case in Cameroon of Lake Chad and the Lagdo water retention dam. In the case of the Lake Chad area, in addition to the invasion of waters by *Eichhornia crassipes*, there is also the invasion of dry land by *Prosopis juliflora*, and ecological and socio-economic corollaries. In addition to the invasion of water and arable land by invasive plants, the Lake Chad area and its surroundings are also subject to the ravages of desertification where the soil and the productivity of seasonal plants, from year to year, decline. cause of the widespread effects of climate change in the Sahel. Furthermore, the cost of living and in particular chemical fertilizers are becoming more and more expensive on local markets while the floral and faunal resources of village ponds, tributaries of Lake Chad, rivers, reservoirs, wetlands, channels, drains, etc. are being replaced by *Prosopis juliflora* and *Eichhornia crassipes*, thus disturbing the survival of local biodiversity with a lot of environmental damage.

*Eichhornia crassipes* consists of high biomass, fibrous tissue, high energy and protein content that can be used for a variety of useful applications such as wastewater treatment, compost and fertilizer, animal feed (Abhed, 2020). On the one hand, *Eichhornia crassipes* is a source of organic matter that can be transformed into compost to improve soil quality and

plant productivity (Sofyan et al. 2023). Compost has also been shown to suppress plant diseases and pests and improve agricultural crop yields (Sahana et al. 2018).

On the other hand, *Prosopis juliflora* is an invasive species in the arid and semi-arid zones of Lake Chad. This complex plant has become a major factor in eliminating the habitat of many native species to a catastrophic level. As experts report, *Prosopis juliflora* is included in the new IUCN (2020) list of the 100 worst invasive alien species in the world (Mwangi and Swallow, 2005). From experiences around the world, it appears that it is almost impossible to stop the growth of this plant, because it spreads widely in most arid and semi-arid areas of the world (Kazmi et al., 2010). Prosopis Juliflora stands are so common in the Lake Chad area that they have become the most common and intense plant in this area of northern Cameroon, compared to all plant species.

Women in the Lake Chad area and northern Cameroon carry out essentially agricultural subsistence activities, based on food crops (sorghum, millet, corn, rice, cowpea and fonio) with average yields between [0.85- 5] ton.ha-1 (Hervé et al., 2016). Their activities are characterized by poor environmental management of agricultural land and the mismatch between the price of inputs and that of food crops. These two factors constitute important elements of continued soil degradation (Ouedraogo and Hien, 2015) and the increase in the cost of living in the Sahelian agricultural
environment. The situation is exacerbated by the increase in the magnitude of the effects of the invasion of environments by prolific plants which impact biodiversity (destruction of aquatic resources such as fish, etc.), economic activities (decrease in fishing and obstruction waterways) and social (decrease in availability of drinking water and appearance of new diseases, increase in overpopulation of urban areas and desertion of landlocked villages due to invasive plants and social ills such as banditry, prostitution and others inhuman drift forms). In such a context, the study of the impact of the proliferation of invasive plants on biodiversity and the socio-economic adaptation strategies of women in the Lake Chad area could help in the medium and long term, to be a tool for decision support; hence the objective of this study which is to determine the effect of *Prosopis Juliflora* and *Eichhornia crassipes* on biodiversity and the socio-economic adaptation strategies of women in the Lake Chad area.

## 2. Materials and Methods

### 2.1. Study Area

#### 2.2.1. Assessment of available biomass and density

Three data collection campaigns on 06 quadras per locality and in batches of 3 were carried out to evaluate the available biomass and their density. Quadras (1m×1m) were carried out on ten sites of the lake, in order to collect *Eichhornia crassipes* plants using a wooden cube of 01 m3. The integral harvest method following the grid of nested squares (Daget et al., 2010; Daget and Poissonet, 1971) made it possible to harvest all the species present within each plot.

The collection of raw materials is an operation which consists of mowing *Eichhornia crassipes* plants, waste from other invasive plants or any other from the place of their proliferation to a place of final elimination. It begins with the identification of raw materials in proliferation sites.

#### 2.2.2. Taking floristic data on site

The first step consists of distinguishing the large areas of the basin based on the different natures of spatial heterogeneities of the basin: presence of water, density of vegetation, etc. This first zoning is done using in situ visits. for small basins and is supplemented by taking aerial photos for large surface basins (Saulais M. and Bedell, 2009). The floristic inventory based on the Braun-Blanquet dominance abundance coefficients was established with indices varying from 1 to 5. These abundance-dominance indices make it possible to calculate for each species its average coverage (MR) which is the percentage occupied by this species in a given environment:

$$RMi = \frac{Ri}{\text{Total number of Survey Points}}$$

L'indice de présence (Pi) correspond au recouvrement moyen de l'espèce i sur le recouvrement total des individus :

$$Pi = \frac{RMi}{\sum RM}$$

This five-index scale gives the distribution of individuals of a species as follows:

1 = recovery from 1% to 10%, with average recovery = 5%;

2 = recovery from 10% to 25%, with average recovery = 15%;

3 = recovery of 25% to 50%, with average recovery = 37.5%;

4 = coverage of 50% to 75%, with average coverage = 62.5%;

5 = coverage of 75% to 100%, with average coverage = 87.5%.

The Shannon-Weaver index (H') indicates the diversity or specific richness of the environment, it is therefore determined by the following relationship:

$$H' = - \sum Pi \times \ln (Pi)$$

The regularity index or “Evenness index” or evenness of Pielou is:

$$R = \frac{H'}{Hmax}$$

The frequency data for each species were calculated as follows: :

$$= \left[ \frac{\text{Number of Points where the species is present}}{\text{Total Number of Points}} \right] \times 100$$

Likewise, the Sorensen coefficient which emphasizes the presence of species in two environments is given by the following relationship:

$$CS = \left[ \frac{2a}{(2a + b + c)} \right]$$

With: 0<CS <1; a = number of species common to the two environments A and B; b = number of species present in environment A and absent in environment B; c = number of species present in environment B and absent in environment A.

## 3. The productivity of *Eichhornia crassipes* in Lake Chad

### 3.1. The absolute growth rate (TDA)

The absolute growth rate (TDA), which reflects the increase in the number of individuals and/or the quantity of fresh biomass as a function of time, can be considered from the angle of vegetative and/or sexual reproduction (Oumarou et al., 2008). In this study, the vegetative multiplication which was considered when evaluating the quantitative and demographic growth rate of *Eichhornia crassipes* is taken into account and the evaluation of this rate consisted of experimentally determining the speed of multiplication at from experimental results by applying the relationship described by Radford (1967):

$$TDA = \frac{W1-W2}{t1-t2} \text{ (millimeter/day)}$$
With: W1 = number of plants (or biomass) at the start of the experiment at time t1

W2 = number of plants (or biomass) at the end of the experiment at time t2

## 3.2. Assessment of multiplication speed

To measure the multiplication speed of *Eichhornia crassipes* (gram/day), 06 quadras/locality were installed, each measuring 01m² of surface materialized by wooden stakes fixed in the mud and surrounded by iron mesh protection. in which five plants of *Eichhornia crassipes* were placed, previously weighed on dates t1 and t2 following the method developed by Oumarou et al., (2008), which consists of taking out of the water at regular intervals (every 48 hours), *Eichhornia crassipes*, which are counted, drained, weighed and returned to the water. The measurements were carried out in the dry season and in the rainy season.

## 3.3. Modeling the potential evolution of *Eichhornia crassipes* in Lake Chad

Modeling the potential evolution of *Eichhornia crassipes* in the Lake Chad area consists of representing the risk of invasion present in the area by the reproduction and growth capacity of the plant and the abiotic and biotic factors that favor its success. scalable. Thanks to data obtained from 15 sampling points, its future distribution was determined with a view to providing decision support data for the planning and implementation of control appropriate to the management of *Eichhornia crassipes* which are invasive plants in this area. Firstly, the study area was digitized using the map produced using ArcGis as a mapping base. The calculations were carried out using the geostatistical analysis tool of the ArcGis program. Cross-validation was then carried out by obtaining different graphs and summaries of the measured and predicted values (Moreno and Valdez, 2005). Then another validation was carried out using MapInfo and Net Logo software to build predictive models of the potential distribution of the plant based on the physico-chemical parameters of the water (temperature, pH, conductivity and dissolved oxygen). Final maps were generated using ArcGis programs.

## 3.4. Physico-chemical characterization of water from the *Eichhornia crassipes* sampling site

After the work to quantify the species on site followed by a methodological update, a physicochemical analysis of the water was carried out at 12 points of effluent upstream and downstream of the sites, which could represent a source of contamination in the area of the site. Lake Chad: these are discharge points for wastewater and urban waste and/or Eichhornia crassipes proliferates. The samples were taken in 08 points which differ in the types of waste which were dumped there, their age and the way in which the waste is disposed there. The samples were collected in amber

Pyrex borosilicate glass bottles, and stored in the dark and at 4°C before extraction. They were also filtered on 0.45µm cellulose acetate membranes.

## 3.5. Assessment of the wildlife biomass of Lake Chad

The updated BSI and BILC index methods, used as part of this work, were validated and the benthic macrofauna sampling protocol stabilized, in order to obtain the best compromise cost/sampling effort/ecological relevance for a point sampling. It required an additional field campaign (30 sampling points located throughout Grande Terre with 15 unit samples taken per sampling point) (Mary, 2015). All of this work made it possible to define :

* the most suitable mesh size for sampling benthic macrofauna (500 µm);

* the optimal number of samples to be taken per sampling point (7);

* the order of priority for sampling substrates at a sampling point (table 1);

* the most efficient sampling protocol (paragraph 2/8);

* sensitivity scores, between 1 and 10, for each known taxon of benthic macrofauna in current environments;

* the boundaries of biological quality classes (very good, good, fair, poor, poor) using graphical and statistical methods.

The biotic index is calculated by considering the total number of taxa listed, according to the following formula :

$$ \text{BILC or IBS} = \frac{1}{n} \sum_{i=1}^{l=n} S_i $$

With n: number of indicator taxa and if: score of taxon i for the calculated index

## 3.6. Data analysis

The raw data are collected from each questionnaire, entered and formatted with Microsoft Office Excel software and imported in the form of text files (separator: tabulation) into R and SPSS software for subsequent statistical analyses, namely: analysis descriptive and the correlation test. The descriptive analysis consisted of calculations of proportions (percentages), means and standard deviations. Graphs and tables were constructed. The sperman correlation test made it possible to create a typology of the farms surveyed on the basis of the types of disturbance perceived. Given that the study sample was made up equally of men and women, only the variables “age” and “level of education” linked to workers were retained for this typology.:

- The “age” variable has three modalities: the “Young” (YOUN) modality for workers whose age is < 45 years, the “Aged” (AG)
modality for workers whose age is between 45 and 60 years old and the "Very elderly" (VE) modality for workers whose age is > 60 years old;

- The "level of education" variable has three categories: "workers without a formal level of education" (FLE), workers who have reached the primary level of formal education (PRIM) and workers who have reached the secondary level (SL) and more.

Three data collection campaigns of 30 samples over 06 quadras per locality and in batches of 3 were carried out for the evaluation of the available biomass and their density. Quadras (1m×1m) were carried out on ten sites of the lake, in order to collect Eichhornia crassipes plants using a wooden cube of 01 m³. The integral harvest method following the grid of nested squares (Daget and Poissonet, 1971; Daget et al., 2010) made it possible to harvest all the species present within each plot. The data collected is distributed as follows::

# 4. Results and discussion

## 4.1. Assessment of available invasive biomass and density

<table><caption>Table 1: Density of *Eichhornia crassipes* samples collected by batch between August-September 2022</caption><thead><tr><th>Sites</th><th>Number Quadras (1m×1m)</th><th>Number of plant species present (Plants/m²)</th><th>Density of <i>Eichhornia crassipes</i> harvested (Plants/m²)</th><th>Percentage of <i>Eichhornia crassipes</i> harvested/Quadra(%)</th></tr></thead><tbody><tr><td>Makary</td><td>06</td><td>07±0.4</td><td>137±1.1</td><td>95.5</td></tr><tr><td>Blangoua</td><td>06</td><td>17±0.1</td><td>296±2.3</td><td>83.9</td></tr><tr><td>Fotokol</td><td>06</td><td>08±0.1</td><td>151±0.3</td><td>88.1</td></tr><tr><td>Darak</td><td>06</td><td>12±0.3</td><td>152±1.3</td><td>87.2</td></tr><tr><td>Hilé Alifa</td><td>06</td><td>09±0.8</td><td>120±2.3</td><td>80.9</td></tr></tbody></table>

The mix of species present in the territory of Lake Chad and on the water surface in the sites is higher in Blangoua (17±0.1 plant species present/m²) and Darak (12±0.3 plant species present/m²) while in the lowest mix of species present on the water surface are found in Makary (07±0.4 plant species present/m²). The highest density of *Eichhornia crassipes* collected in Blangoua (296±2.3 *Eichhornia crassipes* plants present/m²) while the lowest density of *Eichhornia crassipes* collected is in Hilé Alifa (120±2.3 *Eichhornia crassipes* plants present/m²): this testifies to the vitality of biodiversity in these two wetlands of Lake Chad. However, the percentage of *Eichhornia crassipes* collected in relation to the number of plant species present per quadra is higher in Makary (95.5%) while it is lower in Hilé Alifa (80.9%). Consequently, Makary would be more invaded by *Eichhornia crassipes* than other localities.

## 4.2. Biomass of vegetation by city in the Lake Chad area Cameroon

The Sahelian herbaceous steppe is not devoid of perennials, the most characteristic is *Panicum turgidum*, developing on the coarse sands which it fixes by forming large tufts. Although its culms are hard, it is appreciated by camels and cattle. After the drought its area expanded, and it now occupies vast areas, in Chad in particular.

Other perennials exist in this area, often with low abundance, especially after drought: *Stipagrostis unipulis*, *Aristida pallida*, *Cymbopogon schoenanthus* and *Cyperus jeminicus*.

The herbaceous carpet of annuals, composed mainly of grasses, is very closely dependent on rainfall. The most abundant species are *Tragus berteronianus*, *Enneapogon spp.*, *Cenchrus biflorus*, *Aristida mutabilis*. A species of Saharan affinity, *Molkiopsis ciliata*, is common, while *Gisekia pharnacioides* reflects low and irregular rainfall. Woody plants are very rare, while *Panicum turgidum* forms the perennial layer, accompanied by *Cyperus jeminicus* and *Aristida papposa*, relatively rare.
<table><caption>Table 2: Cross-tabulation of types of shrub layer biomass by city</caption><thead><tr><th>Types of biomass</th><th>Images</th><th>Harvest location</th><th>Makary</th><th>Blangoua</th><th>Darak</th><th>Logone Birni</th><th>Fotokol</th><th>Hilé Alifa</th></tr><tr><td colspan="9">Shrub layer per km²</td></tr></thead><tbody><tr><td>Acacia senegal</td><td></td><td>Dry land</td><td>14±2.4</td><td>11±0.3</td><td>7±0.2</td><td>16±0.7</td><td>10±0.4</td><td>10±0.5</td></tr><tr><td>Balanites aegyptiaca</td><td></td><td>Dry land</td><td>12±2.2</td><td>10±3.2</td><td>5±0.8</td><td>13±4.2</td><td>13±2.5</td><td>9±2.1</td></tr><tr><td>Ziziphus mauritiana</td><td></td><td>Dry land</td><td>9±0.1</td><td>10±1.3</td><td>4±0.2</td><td>10±3.1</td><td>11±2.3</td><td>7±1.4</td></tr><tr><td>Cadaba farinosa</td><td></td><td>Dry land</td><td>8±0.3</td><td>3±0.6</td><td>2±0.9</td><td>3±0.5</td><td>6±0.7</td><td>1±0.1</td></tr><tr><td>Capparis decidua</td><td></td><td>Dry land</td><td>3±0.5</td><td>2±0.3</td><td>1±0.2</td><td>1±0.3</td><td>4±1.4</td><td>1±0.2</td></tr></tbody></table>

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<table><tr><td><strong>Salvadora persica</strong></td><td></td><td>Dry land</td><td>2±0.8</td><td>2±0.6</td><td>1±0.1</td><td>1±0.2</td><td>2±0.3</td><td>1±0.1</td></tr><tr><td><strong>Prosopis juliflora</strong></td><td></td><td>Dry land</td><td>8±0.5</td><td>6±0.1</td><td>2±0.3</td><td>8±0.6</td><td>3±0.4</td><td>0</td></tr><tr><td colspan="9" style="text-align: center;"><strong>Perennial herbaceous layer per m²</strong></td></tr><tr><td><strong>Tragus berteronianus</strong></td><td></td><td>Lake</td><td>9±0.6</td><td>8±0.2</td><td>8±0.3</td><td>9±0.6</td><td>9±0.8</td><td>8±0.4</td></tr><tr><td><strong>Enneapogon spp.</strong></td><td></td><td>Lake</td><td>8±0.1</td><td>7±0.6</td><td>7±0.2</td><td>8±0.3</td><td>8±0.6</td><td>7±0.8</td></tr><tr><td><strong>Cenchrus biflorus,</strong></td><td></td><td>Lake</td><td>7±0.9</td><td>7±0.1</td><td>5±0.6</td><td>7±0.2</td><td>7±0.3</td><td>5±0.6</td></tr><tr><td><strong>Aristida mutabilis</strong></td><td></td><td>Lake</td><td>5±0.5</td><td>5±0.9</td><td>3±0.1</td><td>5±0.6</td><td>5±0.2</td><td>3±0.3</td></tr></table>

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Impact of the Proliferation of Invasive Plants on Biodiversity and Women's Socio-Economic Adaptation Strategies in the Lake Chad Area

© August 2024, Volume 04, Issue 3 || https://sites.google.com/view/sahel-nature-consulting/accueil

<table><tr><td>Schoenefeldia gracilis</td><td></td><td>Lake</td><td>8±0.8</td><td>7±0.4</td><td>7±0.5</td><td>8±0.9</td><td>7±0.1</td><td>7±0.6</td></tr><tr><td>Aristida funiculata</td><td></td><td>Lake</td><td>7±0.9</td><td>7±0.8</td><td>5±0.4</td><td>7±0.5</td><td>5±0.9</td><td>5±0.1</td></tr><tr><td>Chloris pilosa</td><td></td><td>Lake</td><td>5±0.3</td><td>5±0.9</td><td>3±0.8</td><td>5±0.4</td><td>2±0.5</td><td>3±0.9</td></tr><tr><td>Pennisetum pedicellatum</td><td></td><td>Lake</td><td>3±0.1</td><td>2±0.3</td><td>2±0.9</td><td>2±0.8</td><td>1±0.4</td><td>2±0.5</td></tr><tr><td>Aristida funiculata</td><td></td><td>Lake</td><td>5±0.3</td><td>1±0.1</td><td>5±0.3</td><td>1±0.9</td><td>0</td><td>5±0.4</td></tr><tr><td>Echinochloa colona</td><td></td><td>Lake</td><td>3±0.2</td><td>0</td><td>3±0.1</td><td>1±0.3</td><td>1±0.9</td><td>3±0.8</td></tr></table>

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Impact of the Proliferation of Invasive Plants on Biodiversity and Women's Socio-Economic Adaptation Strategies in the Lake Chad Area

© August 2024, Volume 04, Issue 3 || https://sites.google.com/view/sahel-nature-consulting/accueil

<table><tr><td><strong>Panicum laetum</strong></td><td></td><td>Lake</td><td>8±0.2</td><td>5±0.2</td><td>8±0.3</td><td>1±0.1</td><td>5±0.3</td><td>8±0.9</td></tr><tr><td><strong>Mitragyna inermis</strong></td><td></td><td>Lake</td><td>1±0.6</td><td>3±0.1</td><td>5±0.2</td><td>5±0.3</td><td>3±0.1</td><td>1±0.3</td></tr><tr><td><strong>Cymbopogon proximus</strong></td><td></td><td>Lake</td><td>5±0.4</td><td>8±0.6</td><td>3±0.1</td><td>3±0.2</td><td>2±0.3</td><td>5±0.1</td></tr><tr><td><strong>Aristida pallens</strong></td><td></td><td>Lake</td><td>8±0.9</td><td>3±0.2</td><td>5±0.4</td><td>5±0.6</td><td>3±0.1</td><td>8±0.2</td></tr><tr><td><strong>Eichhornia Crassipes</strong></td><td></td><td>Lake</td><td>169±13.1</td><td>168±42.1</td><td>163±10.3</td><td>167±31.3</td><td>162±20.9</td><td>165±16.9</td></tr></table>

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<figure><img src="image_23.png" /></figure>
<table><tr><td>Panicum turgidum</td><td></td><td>Lake</td><td>3±0.5</td><td>5±0.1</td><td>8±0.1</td><td>8±0.3</td><td>5±0.1</td><td>3±0.9</td></tr><tr><td>Cyperus jeminicus</td><td></td><td>Lake</td><td>8±0.1</td><td>3±0.5</td><td>3±0.1</td><td>6±0.1</td><td>3±0.3</td><td>8±0.1</td></tr><tr><td>Eragrostis tremula</td><td></td><td>Lake</td><td>7±0.2</td><td>8±0.1</td><td>2±0.5</td><td>8±0.1</td><td>2±0.1</td><td>3±0.3</td></tr></table>

<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /></figure>
## 4.3 Abundance-dominance indices of *Eichhornia crassipes* on site

Floristic data collection of *Eichhornia crassipes* and *Prosopis juliflora* respectively in plots of 01 m² by 20m² (for *Eichhornia Crassipes*) and plots of 01 Km² by 20Km² (for *Prosopis juliflora*) carried out in each of the 06 sites (Makary: Point 1, 2, 3, 4, 5, 6, 7, 8 and 9,

Blangoua: Point 10,11, 12, Darak: Point 13 and 14 (Fig. 1); Hilé Alifa: Point 15, 16 and , Logone Birni; : Point 17, 18 and 19; Point 20, 21, 22, 23, 24 and 25, a total of 25 data collection points.

From 2022-2023, the five-index scale gives the distribution of *Eichhornia Crassipes* individuals in the Lake Chad area as follows:

<table><caption>**Table 3:** Estimation of the spatial heterogeneity of *Eichhornia Crassipes* and *Prosopis juliflora* in the water territories of Lake Chad Cameroon</caption><thead><tr><th rowspan="2">Study sites</th><th colspan="2">Number of relief points</th><th colspan="2">Number (Ri)</th><th colspan="2">Average coverage (RM) %</th><th colspan="2">Abundance-dominance indices</th></tr><tr><th><i>Eichhornia crassipes</i></th><th><i>Prosopis juliflora</i></th><th><i>Eichhornia crassipes</i></th><th><i>Prosopis juliflora</i></th><th><i>Eichhornia crassipes</i></th><th><i>Prosopis juliflora</i></th><th><i>Eichhornia crassipes</i></th><th><i>Prosopis juliflora</i></th></tr></thead><tbody><tr><td>Makary</td><td>9</td><td>9</td><td>169.2±14.83</td><td>29.8±4.8</td><td>18.78</td><td>71.88</td><td>2</td><td>5</td></tr><tr><td>Blangoua</td><td>3</td><td>7</td><td>168.7±15.78</td><td>49.4±1.4</td><td>56</td><td>66.96</td><td>4</td><td>5</td></tr><tr><td>Fotokol</td><td>6</td><td>8</td><td>162.5±20.28</td><td>25.3±3.5</td><td>27</td><td>77.64</td><td>3</td><td>5</td></tr><tr><td>Darak</td><td>2</td><td>7</td><td>163.3±31.52</td><td>47.1±4.3</td><td>81.5</td><td>84.15</td><td>5</td><td>5</td></tr><tr><td>Hilé Alifa</td><td>2</td><td>2</td><td>165.2±34.55</td><td>56.7±2.4</td><td>82.5</td><td>59.5</td><td>5</td><td>4</td></tr><tr><td>Logone Birni</td><td>3</td><td>3</td><td>167.4±32.66</td><td>62.9±4.7</td><td>55.67</td><td>65.75</td><td>4</td><td>4</td></tr><tr><td>Average</td><td>4.17±2.78</td><td>4.17±2.78</td><td>166.05±32.81</td><td>45.20±14.83</td><td>53.57±26.62</td><td>70.98±8.87</td><td>3.83±1.16</td><td>4.67±0.51</td></tr></tbody></table>

On an average of 4,167±2,786 sampling points, an average of 165,667±2,804 *Eichhornia crassipes* plants was observed, with an average abundance-dominance index of 3.833±1.169 and an average recovery rate (MR) of all the area of Lake Chad Cameroon which is 53.575±26.621%.

The diversity or specific richness of each environment in *Eichhornia crassipes*, which takes into account both richness and fairness, was determined using the Shannon-Weaver index, including the general average for Lake Chad Cameroon is 2.113±0.766 whose presence index is 0.207±0.095: the greatest diversity was observed in Hilé Alifa (0.256) while the lowest diversity is that observed in Makary (0.058).

## 4.4. Presence of *Eichhornia crassipes* in the sampling sites

<table><caption>**Table 4:** Quantification of species present on the sites</caption><thead><tr><th>Sites</th><th>Presence index of <i>Eichhornia crassipes</i> (Pi)</th><th>Shannon-Weaver index (H')</th><th>Regularity index (R)</th><th>Frequency of <i>Eichhornia crassipes</i> (%)</th></tr></thead><tbody><tr><td>Makary</td><td>0.058</td><td>3.531</td><td>1</td><td>36</td></tr><tr><td>Blangoua</td><td>0.333</td><td>1.363</td><td>0.386</td><td>12</td></tr><tr><td>Fotokol</td><td>0.167</td><td>2.219</td><td>0.628</td><td>24</td></tr><tr><td>Darak</td><td>0.253</td><td>1.704</td><td>0.482</td><td>08</td></tr><tr><td>Hilé Alifa</td><td>0.256</td><td>1.689</td><td>0.478</td><td>08</td></tr><tr><td>Logone Birni</td><td>0.173</td><td>2.175</td><td>0.616</td><td>12</td></tr><tr><td>Average</td><td>0.207±0.095</td><td>2.113±0.766</td><td>0.598±0.217</td><td>16.7±0.11</td></tr></tbody></table>

However, the average regularity on the waters of Lake Chad is 0.598±0.217, higher in Makary (1.000) and lower in Blangoua (0.386). The average frequency of *Eichhornia crassipes* in the waters of Lake Chad Cameroon is 16.7±0.11%: the highest is that of

Makary (36%), while those observed in Darak (08) and Hilé Alifa (08) are weak.

Three collection campaigns of 30 samples were carried out in batches of 3. The data collected was distributed as follow:

<table><caption>**Table 5:** Density of *Eichhornia crassipes* samples collected by batch between August-September 2022</caption><thead><tr><th>Sites</th><th>Quadras (1m×1m)</th><th>Number of plant species present (Plants/m²)</th><th>Density of Eichhornia crassipes harvested (Plants/m²)</th><th>Percentage of Eichhornia crassipes harvested / Quadra (%)</th></tr></thead><tbody><tr><td>Makary</td><td>06</td><td>07±0.4</td><td>137±1.1</td><td>95.5</td></tr><tr><td>Blangoua</td><td>06</td><td>17±0.1</td><td>296±2.3</td><td>83.9</td></tr><tr><td>Fotokol</td><td>06</td><td>08±0.1</td><td>151±0.3</td><td>88.1</td></tr><tr><td>Darak</td><td>06</td><td>12±0.3</td><td>152±1.3</td><td>87.2</td></tr><tr><td>Hilé Alifa</td><td>06</td><td>09±0.8</td><td>120±2.3</td><td>80.9</td></tr></tbody></table>

The mix of species present on the water surface in the sites is higher in Blangoua (17±0.1 species of plants

present/m²) and Darak (12±0.3 species of plants present/m²) while in the lowest mix of species present
on the water surface are found in Makary (07±0.4 plant species present/m²). The highest density of *Eichhornia crassipes* collected in Blangoua (296±2.3 *Eichhornia crassipes* plants present/m²) while the lowest density of *Eichhornia crassipes* collected is in Hilé Alifa (120±2.3 plants *Eichhornia crassipes* present/m²): this testifies to the vitality of biodiversity in these two wetlands of Lake Chad. However, the percentage of *Eichhornia crassipes* harvested in relation to the number of plant species present by Quadra is higher in Makary (95.5%) while it is lower in Hilé Alifa (80.9%). Consequently, Makary would be more invaded by *Eichhornia crassipes* than other localities.

4.5. Physico-chemical characterization of water from the Eichhornia crassipes sampling site in the Lake Chad area Cameroon

The analysis of the water parameters of the sampling
points was carried out on 12 points in six sites.

The Fotokol, Makary, Hilé Alifa, Darak and Logone
Birni site received numerous biodegradable household

pollutants such as household waste, sanitary and fecal waste, agricultural waste, etc., and the Blangoua site received non-household pollutants and non-biodegradable such as chemical and pesticide residues, petroleum products, etc. The following table illustrates the physicochemical parameters of each parameter studied.

The Fotokol site has a SS 3 to 4 times higher than that of the waters of the other sites over 24 hours. The presence of certain pollutants such as NH₄⁺, NO₃⁻, N.T.K. and Phosphate gives an idea of the level of pollution by nitrogen pollutants.

Overall, unpolluted sites have an average SS of 22.04±9.45 mg/l, sites polluted by organic matter have an average SS of 24.07±8.22 mg/l while sites polluted by non-organic matter have a TSS of 23.43±1.41 mg/l. Sites polluted by organic matter have an average COD, higher of the order of 34.63±15.18 mg/l while the unpolluted sites have an average COD of 32.18±16.19 mg/l, the sites polluted by non-organic matter have a COD of 32.56±12.02 mg/l.
<table><caption>Table 6: Physico-chemical parameters of effluents at the sites (sample collection points)</caption><thead><tr><th rowspan="2">Collection sites for <br/>Eichhornia crassipes samples</th><th rowspan="2">Type of site</th><th rowspan="2">Period and dates of collection</th><th colspan="2">Suspended matter (mg/l)</th><th colspan="2">Chemic Organic Demand (COD) (mg/l)</th><th colspan="2">Biologic Organic Demand in 5 days (BOD<sub>50</sub>)(mg/l)</th><th colspan="2">NH<sub>4</sub><sup>+</sup> (mg/l)</th><th colspan="2">NTK (mg/l)</th><th colspan="2">NO<sub>3</sub><sup>-</sup> (mg/l)</th><th colspan="2">P total (mg/l)</th><th colspan="2">Ph</th></tr><tr><th>Area invaded by <br/>Eichhornia crassipes (≤50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≤50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≤50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≤50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th><th>Area invaded by <br/>Eichhornia crassipes (≥50%) and <br/>Prosopis juliflora (≥50%)</th></tr></thead><tbody><tr><td>Makary</td><td>US</td><td>23/08/2022</td><td>8.4</td><td>8,1</td><td>16</td><td>14</td><td>5.6</td><td>5</td><td>0.99</td><td>0.79</td><td>3.76</td><td>3.15</td><td>2.72</td><td>2.32</td><td>0.78</td><td>0.21</td><td>7.6</td><td>7.1</td></tr><tr><td>Makary</td><td>OM</td><td>01/12/2022</td><td>28.8</td><td>28.4</td><td>57</td><td>55</td><td>5.3</td><td>5</td><td>34.87</td><td>34.31</td><td>37.77</td><td>37.31</td><td>0.48</td><td>0.28</td><td>0.46</td><td>0.26</td><td>7.4</td><td>7.6</td></tr><tr><td>Blangoua</td><td>NOM</td><td>10/08/2022</td><td>26.8</td><td>26.2</td><td>54</td><td>53</td><td>5.5</td><td>5.3</td><td>9.54</td><td>9.23</td><td>31.71</td><td>31.11</td><td>1.67</td><td>1.17</td><td>0.65</td><td>0.31</td><td>7.7</td><td>7.3</td></tr><tr><td>Blangoua</td><td>NOM</td><td>20/01/2023</td><td>28.6</td><td>28.2</td><td>34</td><td>36</td><td>4.6</td><td>4</td><td>8.73</td><td>8.21</td><td>32.61</td><td>32.01</td><td>1.8</td><td>1.19</td><td>0.66</td><td>0.28</td><td>7.2</td><td>7.4</td></tr><tr><td>Fotokol</td><td>OM</td><td>02/08/2022</td><td>28.4</td><td>28.9</td><td>35</td><td>39</td><td>5.3</td><td>5</td><td>33.87</td><td>33.29</td><td>38.65</td><td>38.91</td><td>0.75</td><td>0.29</td><td>0.74</td><td>0.37</td><td>7.6</td><td>7.2</td></tr><tr><td>Fotokol</td><td>OM</td><td>03/02/2023</td><td>27.8</td><td>28.8</td><td>42.8</td><td>42</td><td>7.2</td><td>7</td><td>32.66</td><td>32.21</td><td>38.66</td><td>38.72</td><td>1.69</td><td>1.09</td><td>0.48</td><td>0.34</td><td>7.8</td><td>7.2</td></tr><tr><td>Darak</td><td>US</td><td>09/08/2022</td><td>9.6</td><td>9.9</td><td>17</td><td>13</td><td>4.6</td><td>4</td><td>0.76</td><td>0.83</td><td>2.96</td><td>2.91</td><td>3.28</td><td>3.21</td><td>0.78</td><td>0.38</td><td>7.1</td><td>7.1</td></tr><tr><td>Darak</td><td>OM</td><td>05/01/2023</td><td>27.5</td><td>26.5</td><td>39.5</td><td>39</td><td>6.5</td><td>6</td><td>34.86</td><td>34.09</td><td>39.57</td><td>39.01</td><td>0.77</td><td>0.73</td><td>0.86</td><td>0.36</td><td>7.6</td><td>7.3</td></tr><tr><td>Hilé Alifa</td><td>US</td><td>13/08/2022</td><td>9.3</td><td>8.6</td><td>13.4</td><td>11</td><td>4.3</td><td>4</td><td>0.77</td><td>0.89</td><td>1.55</td><td>1.98</td><td>3.69</td><td>3.39</td><td>0.44</td><td>0.27</td><td>7.5</td><td>7.1</td></tr><tr><td>Hilé Alifa</td><td>OM</td><td>12/01/2023</td><td>28.5</td><td>28.2</td><td>38.3</td><td>37</td><td>7.6</td><td>7</td><td>31.86</td><td>31.23</td><td>37.76</td><td>37.87</td><td>0.99</td><td>0.92</td><td>0.65</td><td>0.29</td><td>7.3</td><td>7.5</td></tr><tr><td>Logone Birni</td><td>US</td><td>19/08/2022</td><td>8.7</td><td>8.5</td><td>17.4</td><td>15</td><td>3.5</td><td>3</td><td>0.99</td><td>0.93</td><td>2.99</td><td>2.82</td><td>3.98</td><td>3.58</td><td>0.37</td><td>0.31</td><td>7.8</td><td>7.2</td></tr><tr><td>Logone Birni</td><td>OM</td><td>04/02/2023</td><td>28.9</td><td>28.4</td><td>43</td><td>41</td><td>8.3</td><td>8</td><td>35.65</td><td>35.04</td><td>38.89</td><td>38.81</td><td>0.73</td><td>0.96</td><td>0.39</td><td>0.33</td><td>7.6</td><td>7.1</td></tr><tr><td>Average US</td><td></td><td></td><td>22.04±9.45</td><td></td><td>32.18±16.19</td><td></td><td>5.02±1.26</td><td></td><td>16.91±15.71</td><td></td><td>24.16±17.20</td><td></td><td>1.65±1.24</td><td></td><td>0.30±0.05</td><td></td><td>7.27±0.16</td><td></td></tr><tr><td>Average OM</td><td></td><td></td><td>24.07±8.22</td><td></td><td>34.63±15.18</td><td></td><td>5.3±1.55</td><td></td><td>20.02±15.59</td><td></td><td>27.40±16.18</td><td></td><td>1.52±1.23</td><td></td><td>0.31±0.04</td><td></td><td>7.27±0.16</td><td></td></tr><tr><td>Average NOM</td><td></td><td></td><td>23.43±1.41</td><td></td><td>32.56±12.02</td><td></td><td>5.30±0.91</td><td></td><td>18.44±0.72</td><td></td><td>26.21±0.63</td><td></td><td>1.65±0.01</td><td></td><td>0.32±0.02</td><td></td><td>7.24±0.07</td><td></td></tr></tbody></table>

With US=Unpolluted Site; OM=Site Polluted with Organic Matter; NOM= Site Polluted with Non-Organic Matter
## 4.6. Characterization of *Eichhornia crassipes* samples

To analyze the water, lipid, protein and ash contents, sampling was carried out on the leaves, stems and roots of *Eichhornia crassipes* collected from six sites. The samples analyzed are very rich in water (nearly 90%). Their average energy value is of the order of 314.454±25.367 kcal/100 g of dry leaves of *Eichhornia crassipes* and 306.273±35.271 kcal/100 g of dry roots of *Eichhornia crassipes*.

However, they only contain traces of lipids. The protein content varies between 223.281% dry matter and 262.681% dry matter with an average of

239.386±13.159% dry matter in the leaves and 242.418±13.001% dry matter in the roots. The carbohydrate contents are high (varying from 28 to 71 g per 100 g). The ash contents, which reflect those of the mineral elements, at the level of the roots vary slightly, i.e. 33 g/100 g in Fotokol and 48 g/100 g in Makary, while at the level of the leaves, they vary slightly, i.e. 32 g/100 g. in Fotokol and 43g/100g in Makary. All these values vary significantly on the one hand between the roots and the leaves (P < 0.05), on the other hand between the different sites (P < 0.05). The following table illustrates the physicochemical parameters of each sample studied.

<table><caption>Table 7: Chemical characterization of *Eichhornia crassipes* in the Lake Chad area Cameroon</caption><thead><tr><th>Collection sites for <i>Eichhornia crassipes</i> samples</th><th>Carbohydrate content (g/100g)</th><th>Nitrogen percentage (%)</th><th>Protein content (%ms)</th><th>Lipid content (% g/100g MF)</th><th>Ash content (g/100g)</th><th>Metabolic energy (EM in kcal/100 g of <i>Eichhornia crassipes</i>)</th></tr></thead><tbody><tr><td rowspan="2">Makary</td><td>Leaves</td><td>71</td><td>36.021</td><td>225.131</td><td>0.002</td><td>43</td><td>322</td></tr><tr><td>Roots</td><td>28</td><td>37.003</td><td>226.002</td><td>0.001</td><td>48</td><td>305</td></tr><tr><td rowspan="2">Blangoua</td><td>Leaves</td><td>69</td><td>38.291</td><td>239.318</td><td>0.001</td><td>36</td><td>288</td></tr><tr><td>Roots</td><td>35</td><td>36.390</td><td>223.281</td><td>0.001</td><td>34</td><td>309</td></tr><tr><td rowspan="2">Fotokol</td><td>Leaves</td><td>68</td><td>42.029</td><td>262.681</td><td>0.001</td><td>32</td><td>348</td></tr><tr><td>Roots</td><td>31</td><td>43.102</td><td>252.311</td><td>0.001</td><td>33</td><td>332</td></tr><tr><td rowspan="2">Darak</td><td>Leaves</td><td>70</td><td>38.054</td><td>237.837</td><td>0.001</td><td>41</td><td>342</td></tr><tr><td>Roots</td><td>30</td><td>39.201</td><td>234.131</td><td>0.001</td><td>43</td><td>331</td></tr><tr><td rowspan="2">Hilé Alifa</td><td>Leaves</td><td>67</td><td>39.028</td><td>243.925</td><td>0.001</td><td>38</td><td>311</td></tr><tr><td>Roots</td><td>29</td><td>38.711</td><td>245.131</td><td>0.001</td><td>39</td><td>312</td></tr><tr><td rowspan="2">Logone Birni</td><td>Leaves</td><td>69</td><td>41.029</td><td>256.431</td><td>0.001</td><td>40</td><td>259</td></tr><tr><td>Roots</td><td>30</td><td>42.201</td><td>255.443</td><td>0.002</td><td>41</td><td>232</td></tr><tr><td colspan="2">Average in leaves</td><td>49.75±20.15</td><td>38.575±1.905</td><td>239.386±13.159</td><td>0.0011±0.0003</td><td>38.818±4.875</td><td>314.454±25.367</td></tr><tr><td colspan="2">Average in roots</td><td>49.75±19.98</td><td>39.194±1.986</td><td>242.418±13.001</td><td>0.0011±0.0003</td><td>38.636±4.738</td><td>306.273±35.271</td></tr></tbody></table>

## 4.7. The productivity of *Eichhornia crassipes* in Lake Chad

### 4.7.1. The absolute growth rate (AGR)

In this study, data were collected on samples during 90 days of the dry season (from October 1 to December 30) and 90 days of the rainy season (from June 1 to

August 30). Vegetative propagation was evaluated by determining the quantitative and demographic growth rate of *Eichhornia crassipes*, taking into account the environments in which the *Eichhornia crassipes* samples grew. The parameters of the growth media that were taken into account for the evaluation of this rate are:

<table><caption>Table 8: Physico-chemical parameters of growth waters of *Eichhornia crassipes* samples</caption><thead><tr><th rowspan="2"></th><th colspan="2">Makary</th><th colspan="2">Blangoua</th><th colspan="2">Fotokol</th><th colspan="2">Darak</th><th colspan="2">Hilé Alifa</th></tr><tr><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th></tr></thead><tbody><tr><td>Samples</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td></tr><tr><td>pH</td><td>7.50±0.23</td><td>8.75±0.13</td><td>7.80±0.32</td><td>8.41±0.47</td><td>8.01±0.74</td><td>8.11±0.32</td><td>7.02±0.11</td><td>8.58±0.01</td><td>7.12±0.11</td><td>8.15±0.67</td></tr><tr><td>Conductivity (µS/cm)</td><td>164±0.32</td><td>143±0.41</td><td>165±0.12</td><td>153±0.65</td><td>165±0.82</td><td>169±0.74</td><td>161±0.64</td><td>156±0.83</td><td>163±0.23</td><td>163±0.63</td></tr><tr><td>Dissolved oxygen (mg/l)</td><td>6.5±0.12</td><td>6.9±0.74</td><td>6.3±0.36</td><td>6.1±0.83</td><td>6.3±0.23</td><td>7.3±0.41</td><td>5.1±0.11</td><td>5.4±0.47</td><td>6.2±0.11</td><td>6.6±0.2</td></tr><tr><td>Temperature (°C) (day/night)</td><td>37/28</td><td>31/22</td><td>36/29</td><td>35/23</td><td>36/26</td><td>32/21</td><td>40/32</td><td>34/25</td><td>36/24</td><td>33/20</td></tr><tr><td>Turbidité (UNT)</td><td>6</td><td>7</td><td>5</td><td>5</td><td>8</td><td>6</td><td>5</td><td>5</td><td>6</td><td>7</td></tr></tbody></table>

The competitive success of *Eichhornia crassipes* also seems linked to levels of eutrophication and the area occupied by the rest of the vegetation present in the habitat (Morris et al., 1999). One of the determining factors for the growth of *Eichhornia crassipes* is the pH which must be between 6 and 8 (Téllez et al., 2008). From the data obtained, it appears that the waters of Lake Chad which cross the Fotokol area have a

higher pH (8.06±0.56) with average conductivities of the order of 167± 0.78 µS/cm and of dissolved oxygen 6.8± 0.32 mg/l, while the waters of the lake which cross the Darak area have a lower pH (7.80 ±0.06) with average conductivities of around of 158.5± 0.73 µS/cm and dissolved oxygen 5.8± 0.29 mg/l. These results are close to those of Téllez et al. (2008) who obtained maximum growth of *Eichhornia*
crassipes in the waters of the Guadiana River with a pH between 7.25 and 8.1. The optimal average temperature for plant growth is between 25°C and 27°C (Arthaud, 2015). In the study area, the optimal average day/night water temperature during the study is 34.5/36°C to 40/25°C, and the relative humidity is 15/40% to 75/95%. The temperatures of *Eichhornia crassipes* growth media vary between 31/22°C and 40/32°C.

Measurements taken during the dry and rainy season show an absolute population growth rate of 0.091/plant/day, so it takes approximately ten days for one plant of *Eichhornia crassipes* to give rise to another plant. This contrasts with the results

obtained by Oumarou et al. (2008) which indicates that the absolute population growth rate of water hyacinth is 0.083/plant/day and it takes approximately twelve days for one plant of hyacinth to give rise to another plant in the Bangr-Wéoogo urban park.

The increase in phytomass is 0.37 g/DM/day per plant. During the period of the experiment, *Eichhornia crassipes* did not completely cover the 1m² quadras. By examining the rate of multiplication during the dry season and the rainy season, we note that the curves which reflect the demographic and biomass increase (figure 3) are not regular, they present levels almost every three weeks.

<figure><img src="image_26.png" /></figure>

<figure><img src="image_27.png" /><figcaption>**Figure 1:** Quantitative evolution and absolute rate of increase in the quantity of fresh biomass of *Eichhornia crassipes* in the dry and rainy season by quadras</figcaption></figure>

The absolute rate of increase in the quantity of fresh biomass of *Eichhornia crassipes* as a function of time (Δt =5 days) made it possible to observe the variation in the growth in length of the biomass as the increase of

the plants was carried out during a variation of constant time, over a total duration of 25 days. During this period, all other environmental parameters were met such as:

<table><caption>**Table 9:** Absolute rate of increase (ARI) in the quantity of fresh biomass of *Eichhornia crassipes* as a function of time</caption><thead><tr><th rowspan="2"></th><th colspan="2">5 days</th><th colspan="2">10 days</th><th colspan="2">15 days</th><th colspan="2">20 days</th><th colspan="2">25 days</th></tr><tr><th>Δw<sub>1</sub><br>(mm)</th><th>ARI<br>(mm/day)</th><th>Δw<sub>1</sub><br>(mm)</th><th>ARI<br>(mm/day)</th><th>Δw<sub>1</sub><br>(mm)</th><th>ARI<br>(mm/day)</th><th>Δw<sub>1</sub><br>(mm)</th><th>ARI<br>(mm/day)</th><th>Δw<sub>1</sub><br>(mm)</th><th>ARI<br>(mm/day)</th></tr></thead><tbody><tr><td><strong>Eichhornia crassipes in Makary</strong></td><td>1.9</td><td>0.38</td><td>2.8</td><td>0.56</td><td>3.3</td><td>0.66</td><td>4.1</td><td>0.82</td><td>4.4</td><td>0.84</td></tr><tr><td><strong>Eichhornia crassipes in Blangoua</strong></td><td>1.8</td><td>0.36</td><td>2.7</td><td>0.54</td><td>3.6</td><td>0.72</td><td>4.3</td><td>0.86</td><td>4.5</td><td>0.9</td></tr><tr><td><strong>Eichhornia crassipes in Fotokol</strong></td><td>1.9</td><td>0.38</td><td>2.8</td><td>0.56</td><td>3.7</td><td>0.74</td><td>4.4</td><td>0.88</td><td>4.7</td><td>0.94</td></tr><tr><td><strong>Eichhornia crassipes in Darak</strong></td><td>1.7</td><td>0.34</td><td>2.9</td><td>0.58</td><td>3.4</td><td>0.68</td><td>4.8</td><td>0.96</td><td>4.9</td><td>0.98</td></tr><tr><td><strong>Eichhornia crassipes àin Hilé Alifa</strong></td><td>1.7</td><td>0.34</td><td>2.8</td><td>0.56</td><td>3.6</td><td>0.72</td><td>4.2</td><td>0.84</td><td>4.4</td><td>0.84</td></tr><tr><td><strong>Average</strong></td><td>1.8±0.1</td><td>0.36±0.02</td><td>2.8±0.07</td><td>0.56±0.01</td><td>3.52±0.16</td><td>0.70±0.03</td><td>4.36±0.27</td><td>0.87±0.05</td><td>4.58±0.22</td><td>0.9±0.06</td></tr><tr><td><strong>Percentage increase (%)</strong></td><td colspan="2">5.5</td><td colspan="2">5.3</td><td colspan="2">4.9</td><td colspan="2">4.7</td><td colspan="2">4.1</td></tr></tbody></table>

The relative growth rates, at a time interval of 05 days, vary between 4.1 and 5.5%. These results are close to those of the work of Gopal (1987) which indicates a relative daily growth rate which varied between 4% and 6%, at doubling times of between 10 and 60 days, depending on the experimental conditions.

## 4.8. Assessment of multiplication speed

In this study, the evaluation of the vegetative multiplication speed was evaluated by determining the quantitative and demographic values of *Eichhornia crassipes* taking into account the parameters of the water sampling media in which these samples of *Eichhornia crassipes* was growing. The parameters of the growth media that were taken into account for the evaluation of this multiplication speed are:

<table><caption>**Table 10:** Parameters of the water sample collection locations used to evaluate the rate of multiplication of fresh biomass of *Eichhornia crassipes*</caption><tr><td>Collection location</td><td>Makary</td><td>Blangoua</td><td>Fotokol</td><td>Darak</td><td>Hilé Alifa</td></tr></table>
Impact of the Proliferation of Invasive Plants on Biodiversity and Women's Socio-Economic Adaptation Strategies in the Lake Chad Area

© August 2024, Volume 04, Issue 3 || https://sites.google.com/view/sahel-nature-consulting/accueil

<table><thead><tr><th></th><th></th><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th></tr></thead><tbody><tr><td>Samples</td><td></td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td><td>10</td></tr><tr><td>Water clarity (visibility) (cm)</td><td></td><td>2.12±0.65</td><td>1.94±0.13</td><td>1.6±0.4</td><td>1.83±0.31</td><td>1.93±0.1</td><td>1.31±0.39</td><td>1.91±0.03</td><td>1.47±0.89</td><td>1.92±0.29</td><td>1.62±0.19</td></tr><tr><td>Lake depth (m)</td><td></td><td>7.53</td><td>8.13</td><td>6.38</td><td>7.47</td><td>7.71</td><td>7.31</td><td>6.21</td><td>6.85</td><td>5.21</td><td>7.67</td></tr><tr><td>Soil type</td><td></td><td colspan="8">ferrugineux tropicaux lessivés</td></tr><tr><td rowspan="3">Sands (mm)</td><td>Coarse</td><td>5-12</td><td>6-10</td><td>7-12</td><td>6-12</td><td>6-12</td><td>7-12</td><td>5-12</td><td>6-12</td><td>7-12</td><td>6-12</td></tr><tr><td>Average</td><td>2-4</td><td>2-3</td><td>2-3</td><td>2-4</td><td>2-4</td><td>2-4</td><td>2-3</td><td>2-4</td><td>2-3</td><td>2-4</td></tr><tr><td>End</td><td>1-2</td><td>1-3</td><td>1-2</td><td>1-3</td><td>1-2</td><td>1-3</td><td>1-2</td><td>1-3</td><td>1-2</td><td>1-3</td></tr><tr><td>Number of wildlife species harvested/liter</td><td></td><td>150±0.73</td><td>375±0.23</td><td>128±0.93</td><td>741±0.74</td><td>201±0.94</td><td>711±0.32</td><td>132±0.41</td><td>258±0.61</td><td>132±0.71</td><td>85±0.21</td></tr></tbody></table>

From the data obtained, it appears that the waters of Lake Chad have a low clarity (visibility) of the water (2.12±0.65 cm) in the dry season in Makary with 150±0.73 wildlife species harvested/liter, while the highest Water Clarity (visibility) (1.31±0.39cm) in rainy season was observed in Fotokol with 711±0.32 wildlife species harvested/liter. Variations in the invasive potential of an exotic aquatic plant reflect its novel habitat preference and propagule availability (Mandryk and Wein, 2006). *Eichhornia crassipes* is a plant that reproduces both vegetatively and sexually, the former being the most important for the rapid expansion and colonization of the plant through the formation of stolons (Téllez et al., 2008).

The evaluation of the biomass density of *Eichhornia crassipes* was made during the period from September

2022 to February 2023 in the dry season and from May 2023 to August 2023 in the rainy season, a period during which the site is mono specifically and completely populated with *Eichhornia crassipes* on the body of water. The average density is 164±0.23 feet of *Eichhornia crassipes* per square meter with an average weight of 0.36±0.14kg of fresh biomass per unit (Graph 2). Passage to the oven reveals a proportion of average dry matter (DM) of 6.16±0.08% and an average water content of 94.67±0.54% (Ganesh et al., 2005) places the water content between 94 and 95%. This high water content makes *Eichhornia crassipes* a biological material of choice for biomethanization, to the extent that the anaerobic environment is obtained by saturation of the reaction medium with water, which is, moreover, a rare commodity in the Sahel.

<figure><img src="image_28.png" /><figcaption>Graph 2: Quantitative evolution of *Eichhornia crassipes* in dry and rainy seasons</figcaption></figure>

The evaluation of the multiplication speed of the fresh biomass of *Eichhornia crassipes* as a function of time (Δt =5 days) made it possible to observe the variation in the weight of the biomass as the growth

of the plants increases was carried out during a constant time variation, over a total duration of 25 days.

<table><caption>Table 11: Evaluation of the multiplication speed of fresh biomass of *Eichhornia crassipes* as a function of time</caption><thead><tr><th rowspan="2"></th><th colspan="2">5 days</th><th colspan="2">10 days</th><th colspan="2">15 days</th><th colspan="2">20 days</th><th colspan="2">25 days</th></tr><tr><th>Δw<sub>1</sub> (mm)</th><th>ARG (mm/day)</th><th>Δw<sub>1</sub> (mm)</th><th>ARG (mm/day)</th><th>Δw<sub>1</sub> (mm)</th><th>ARG (mm/day)</th><th>Δw<sub>1</sub> (mm)</th><th>ARG (mm/day)</th><th>Δw<sub>1</sub> (mm)</th><th>ARG (mm/day)</th></tr></thead><tbody><tr><td>Eichhornia crassipes in Makary</td><td>0,7</td><td>0,14</td><td>0,8</td><td>0,16</td><td>1,3</td><td>0,26</td><td>1,5</td><td>0,3</td><td>1,7</td><td>0,34</td></tr><tr><td>Eichhornia crassipes in Blangoua</td><td>0,5</td><td>0,1</td><td>0,6</td><td>0,12</td><td>1,2</td><td>0,24</td><td>1,7</td><td>0,34</td><td>1,9</td><td>0,38</td></tr><tr><td>Eichhornia crassipes in Fotokol</td><td>0,8</td><td>0,16</td><td>1,3</td><td>0,26</td><td>1,6</td><td>0,32</td><td>1,9</td><td>0,38</td><td>2,2</td><td>0,44</td></tr><tr><td>Eichhornia crassipes in Darak</td><td>0,5</td><td>0,1</td><td>0,8</td><td>0,16</td><td>1,4</td><td>0,28</td><td>1,8</td><td>0,36</td><td>1,9</td><td>0,38</td></tr><tr><td>Eichhornia crassipes in Hilé Alifa</td><td>0,6</td><td>0,12</td><td>0,9</td><td>0,18</td><td>1,3</td><td>0,26</td><td>1,9</td><td>0,38</td><td>2,1</td><td>0,42</td></tr><tr><td>Average</td><td>0,62±0,13</td><td>0,12±0,03</td><td>0,88±0,26</td><td>0,18±0,05</td><td>1,36±0,15</td><td>0,27±0,03</td><td>1,76±0,17</td><td>0,35±0,03</td><td>1,96±0,19</td><td>0,39±0,04</td></tr></tbody></table>

*Eichhornia crassipes* has an extraordinary growth rate with, in other countries, an increase in biomass of 400 to 700 tons per ha per day, or an increase in water area coverage by a factor of 1.012 to 1,077 per day (Téllez et al., 2008).
<figure><img src="image_29.png" /><figcaption>**Graph 3.** Quantitative evolution and growth rate of *Eichhornia crassipes* in the dry and cold season</figcaption></figure>

### 4.8.1. Modeling the potential evolution of *Eichhornia crassipes* in Lake Chad

In Figure 3, the map shows the division of the risk level of the sections of the watershed studied into four

categories: sections where the risk of infestation is high, very high, extremely high and maximum. Figure 2 shows the main areas (Ha) and risks

<figure><img src="image_30.png" /><figcaption>**Graph 4:** Graph of risk levels of sections of the Lake Chad watershed</figcaption></figure>

In the study area, there are therefore no physicochemical conditions that would limit the distribution and persistence of the plant. Indeed, this part of the Lake Chad basin is extraordinarily

vulnerable to infestation. The area also showed favorable conditions for the continued growth and expansion of *Eichhornia crassipes* year after year.

<figure><img src="image_31.png" /><figcaption>**Figure 1:** Map of areas on risk of being recovered by *Eichhornia crassipes* in the lac Tchad Basin in Cameroon.</figcaption></figure>

The different risk levels are never far from habitable zones, the maximum risk level (red) is located in the town of Makary (12°33'45.98 north latitude and 14°26'51.3 east longitude, 1845 km²) and in the area of the mouth of the tributary of the city of Fotokol (12°22'39.74 north latitude and 14°13'30.22 east

longitude. 3285 Km²). The high risk areas (pink) correspond to the town of Blangoua (12°44'57" North Latitude and 14°34'49" East Longitude, 2116 Km²) and rivers of the town of Hilé Alifa (12° 42' 0" North latitude, 14° 19' 0" east longitude). Other areas of Lake Chad that are either at very high (orange) or
extremely high (yellow) risk levels are found in the Hilé Alifa and Fotokol areas respectively. Therefore, it is predictable to expect major infestations in the currently colonized area, both in population size and spatial extent. Its expansion into areas currently free of infestation is also expected. These include the Logone Birni area (lower floodplains, between El Béid and Kousseri) and the Chari reservoir towards Chad. Given the size of the potential distribution area, it would seem necessary to provide for a significant increase and subsequent maintenance of the level of resources and logistics intended for the prevention and control of *Eichhornia crassipes*.

### 4.8.2. Impact on the animal biomass present by city in waters prey to *Eichhornia crassipes* in the Lake Chad area Cameroon

Lake Chad and the rivers, aquifers and aquatic ecosystems contained in its hydrographic basin are declared international waters. During our surveys in 2010, the sampling points surveyed made it possible to count a total of 124 aquifer species. In 2024, we counted a total of 92 species at the same sampling points surveyed. Since 2010-2024, we note an average overall loss of aquatic biodiversity of 25.21±1.72% in the waters of Lake Chad and a loss of waterways due to invasive plants of 78.80±1.30%.

<table><caption>Table 12: Density of *Eichhornia crassipes* samples collected by batch between August-September 2022</caption><thead><tr><th>Sites</th><th>Number of sampling points</th><th>Number of animal species present /m² in 2010</th><th>Number of animal species present /m² in 2024</th><th>Loss of aquatic biodiversity (%)</th><th>Waterways present in 2010 (%)</th><th>Waterways present in 2024 (%)</th><th>Loss waterways (%)</th></tr></thead><tbody><tr><td>Makary</td><td>7</td><td>22,06±0,71</td><td>13,02±0,27</td><td>40,91±0,51</td><td>100</td><td>21±0,91</td><td>79±0,43</td></tr><tr><td>Blangoua</td><td>7</td><td>31,01±0,02</td><td>26,01±0,65</td><td>03,85±0,11</td><td>100</td><td>22±0,19</td><td>78±0,66</td></tr><tr><td>Fotokol</td><td>7</td><td>26,03±0,01</td><td>16,07±0,32</td><td>38,46±0,13</td><td>100</td><td>20±0,73</td><td>80±0,87</td></tr><tr><td>Darak</td><td>7</td><td>21,02±0,17</td><td>19,01±0,94</td><td>9,52±0,05</td><td>100</td><td>20±0,67</td><td>80±0,53</td></tr><tr><td>Hilé Alifa</td><td>7</td><td>24,08±0,29</td><td>16,01±0,15</td><td>33,33±0,19</td><td>100</td><td>23±0,35</td><td>77±0,74</td></tr><tr><td>Moyenne</td><td></td><td>41,33±3,96</td><td>30,33±4,95</td><td>25,21±1,72</td><td>100</td><td>21,2±1,30</td><td>78,8±1,30</td></tr></tbody></table>

The majority of the profiles of the sampling points are generally in a meandering concavity (figure x) in

running water environments of the rivers which flow towards Lake Chad.

<figure><img src="image_32.png" /><figcaption>Figure 2: Concavity mold</figcaption></figure>

The order of priority for sampling the substrates at the

sampling points made it possible to obtain the following data (table 13):

<table><caption>Table 13: Identification of substrates (% coverage) and speed classes characterizing them</caption><thead><tr><th rowspan="2">HABITABILITY ORDER</th><th rowspan="2">SUBSTRAT</th><th rowspan="2">% COVERAGE AT THE SAMPLING POINT</th><th rowspan="2">REPRESENTATIVENESS (MARGINAL / DOMINANT)</th><th colspan="4">SPEED (V) IN CM/S</th><th rowspan="2">WATER VISIBILITY/CM</th></tr><tr><th>Cascade V>150</th><th>Fast 150>V>75</th><th>Medium 75>V>25</th><th>Low to none V<25</th></tr></thead><tbody><tr><td>11</td><td>Bryophytes</td><td>1</td><td>M</td><td>II</td><td>I</td><td></td><td></td><td>1</td></tr><tr><td>10</td><td>Branches/trunks</td><td>1</td><td>M</td><td></td><td></td><td></td><td>I</td><td>1</td></tr><tr><td>9</td><td>Stones/pebbles (25 to 250 mm)</td><td>3</td><td>D</td><td></td><td>I</td><td>II</td><td></td><td>3</td></tr><tr><td>8</td><td>Litter (+slime)</td><td>2</td><td>M</td><td></td><td></td><td>II</td><td>I</td><td>2</td></tr><tr><td>7</td><td>Hydrophytes*</td><td>4</td><td></td><td></td><td></td><td></td><td></td><td>4</td></tr><tr><td>6</td><td>Root hair</td><td>2</td><td>M</td><td></td><td></td><td></td><td>I</td><td>1</td></tr><tr><td>5</td><td>Blocks "liftable" by hand (size greater than 250 mm)</td><td>5</td><td>D</td><td></td><td>III</td><td>I</td><td>II</td><td>1</td></tr><tr><td>4</td><td>Gravel (2 to 25 mm)</td><td>10</td><td>D</td><td></td><td></td><td>I</td><td>II</td><td>3</td></tr><tr><td>3</td><td>Sands (&lt; 2 mm)</td><td>48</td><td>M</td><td></td><td></td><td></td><td>I</td><td>2</td></tr><tr><td>2</td><td>Lateritic fines (&lt; 2 mm)</td><td>1</td><td></td><td></td><td></td><td></td><td></td><td>4</td></tr><tr><td>1</td><td>Rocks, slabs (non-movable support)</td><td>15</td><td>D</td><td>I</td><td>II</td><td>IV</td><td>II</td><td>1</td></tr><tr><td>0</td><td>Algae</td><td>8</td><td></td><td></td><td></td><td></td><td></td><td>1</td></tr><tr><td></td><td>Total</td><td>100</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

The average water height of the sampling locations is 85±7.07 cm while the current speed is on average low.

The substrates which contribute to the survival of invasive aquatic plants are classified from the most
biogenic (bryophytes) to the least biogenic (green algae) with almost no and stable clogging and whose aquatic vegetation is made up of 98% *Eichhornia crassipes*

### 4.8.3. Taxa to consider when studying

The taxonomic richness of Lake Chad was an essential element to consider to explain the index scores. This

parameter is usually well correlated with the nature of the habitats when water quality is not limiting (Gay, 2000). The experience of Lake Chad shows that in sampling points where a low number of indicator taxa is collected, the index notes have been contradictory and difficult to interpret.

<table><caption>Table 14: Sampling table</caption><thead><tr><th rowspan="2">Levy</th><th rowspan="2"></th><th rowspan="2">Current speed</th><th rowspan="2">Water height (cm)</th><th colspan="3">Substrate</th><th colspan="2">Aquatic vegetation</th></tr><tr><th>Nature</th><th>Clogging (no / weak / medium / strong)</th><th>Stability (stable/moderately)</th><th>Nature</th><th>Abundance (%)</th></tr></thead><tbody><tr><td rowspan="3">Phase 1 and 3 on marginal sites</td><td>L1</td><td>Fast</td><td>80</td><td>Pontederiaceae</td><td>null</td><td>stable</td><td>Eichhornia crassipes</td><td>98</td></tr><tr><td>L2</td><td>Weak</td><td>90</td><td>Branchages, Pontederiaceae</td><td>weak</td><td>stable</td><td>Eichhornia crassipes</td><td>98</td></tr><tr><td>L3</td><td>Fast</td><td>90</td><td>Litter, Pontederiaceae</td><td>weak</td><td>stable</td><td>Eichhornia crassipes</td><td>98</td></tr><tr><td rowspan="4">Phase 2: 4 on dominant sites</td><td>L4</td><td>Weak</td><td>85</td><td>Rock, Pontederiaceae</td><td>null</td><td>stable</td><td>Eichhornia crassipes</td><td>98</td></tr><tr><td>L5</td><td>Fast</td><td>80</td><td>Rock, Pontederiaceae</td><td>null</td><td>stable</td><td>Eichhornia crassipes</td><td>98</td></tr><tr><td>L6</td><td>Weak</td><td>75</td><td>Hand lifting blocks, Pontederiaceae</td><td>weak</td><td>stable</td><td>Eichhornia crassipes</td><td>98</td></tr><tr><td>L7</td><td>Fast</td><td>95</td><td>Stones/pebbles and Pontederiaceae</td><td>null</td><td>stable</td><td>Eichhornia crassipes</td><td>98</td></tr></tbody></table>

### 4.8.4. Determination of biological quality

The biological quality class thresholds for LCBI and BSI are shown in Table 16. They were readjusted by Dzokom (2024). On the other hand, the observation

made is that in the heavily disturbed sampling points, the taxonomic richness was low; which is similar to the score obtained by Mary and Archaimbault, (2012).

<table><caption>Table 15: Sensitivity scores of indicator taxa of the Lake Chad Biotic Index (LCBI) and the Biosedimentary Index (BSI).</caption><thead><tr><th>Taxon</th><th>LCBI Score</th><th>BSI Score</th><th>Taxon</th><th>BILC Score</th><th>BSI Score</th></tr></thead><tbody><tr><td><strong>INSECTS</strong></td><td></td><td></td><td><strong>Diptera</strong></td><td></td><td></td></tr><tr><td>Lepidoptera</td><td>6</td><td>4</td><td>Blephariceridae</td><td>10</td><td>8</td></tr><tr><td>Springtails</td><td>2</td><td>4</td><td>Ceratopogoninae</td><td>5</td><td>2</td></tr><tr><td><strong>Ephemeroptera</strong></td><td></td><td></td><td>Forcipomyiinae</td><td>7</td><td>5</td></tr><tr><td>Baetidae</td><td>8</td><td>5</td><td>Chironomini</td><td>5</td><td>3</td></tr><tr><td>Leptophlebiidae</td><td></td><td></td><td>Chironomus</td><td>1</td><td>4</td></tr><tr><td>Amoa</td><td>8</td><td>9</td><td>Corynoneura</td><td>5</td><td>6</td></tr><tr><td>Celiphlebia</td><td>6</td><td>7</td><td>Harrisius</td><td>5</td><td>4</td></tr><tr><td>Coula</td><td>10</td><td>10</td><td>Orthocladiinae</td><td>1</td><td>2</td></tr><tr><td>Fasciamirus</td><td>10</td><td>6</td><td>Pseudochironomini</td><td>9</td><td>5</td></tr><tr><td>Kariona</td><td>10</td><td>10</td><td>Tanypodinae</td><td>5</td><td>3</td></tr><tr><td>Kouma</td><td>7</td><td>10</td><td>Tanytarsini</td><td>2</td><td>4</td></tr><tr><td>Lepegenia</td><td>10</td><td>4</td><td>Cecidomyiidae</td><td>3</td><td>3</td></tr><tr><td>Lepeorus</td><td>6</td><td>7</td><td>Culicidae</td><td>6</td><td>9</td></tr><tr><td>N. genre 4</td><td>7</td><td>9</td><td>Dixidae</td><td>9</td><td>5</td></tr><tr><td>N. genre A</td><td>10</td><td>10</td><td>Dolichopodidae</td><td>3</td><td>5</td></tr><tr><td>N. genre B</td><td>10</td><td>10</td><td>Empididae</td><td>9</td><td>4</td></tr><tr><td>Notachalcus</td><td>7</td><td>8</td><td>Ephydridae</td><td>2</td><td>6</td></tr><tr><td>Oumas</td><td>8</td><td>4</td><td>Limoniidae</td><td>3</td><td>6</td></tr><tr><td>Ounia</td><td>9</td><td>8</td><td>Muscidae</td><td>8</td><td>5</td></tr><tr><td>Papposa</td><td>10</td><td>10</td><td>Psychodidae</td><td>1</td><td>8</td></tr><tr><td>Paraluma</td><td>5</td><td>4</td><td>Rhagionidae</td><td>10</td><td>5</td></tr><tr><td>Peloracantha</td><td>10</td><td>10</td><td>Simuliidae</td><td>2</td><td>5</td></tr><tr><td>Poya</td><td>10</td><td>9</td><td>Stratiomyidae</td><td>2</td><td>4</td></tr><tr><td>Simulacala</td><td>7</td><td>7</td><td>Syrphidae</td><td>3</td><td>3</td></tr><tr><td>Tenagophila</td><td>10</td><td>7</td><td>Tabanidae</td><td>5</td><td>6</td></tr><tr><td>Tindea</td><td>9</td><td>7</td><td>Tanyderidae</td><td>5</td><td>5</td></tr><tr><td><strong>Trichoptera</strong></td><td></td><td></td><td><strong>Coleoptera</strong></td><td></td><td></td></tr><tr><td>Ecnomidae</td><td>6</td><td>4</td><td>Cucurlionidae</td><td>9</td><td>7</td></tr><tr><td>Helicophidae</td><td>8</td><td>10</td><td>Dytiscidae</td><td>8</td><td>3</td></tr></tbody></table>
<table><tr><td>Helicopscychidae</td><td>6</td><td>9</td><td>Gyrinidae</td><td>5</td><td>5</td></tr><tr><td>Hydrobiosidae</td><td>5</td><td>7</td><td>Hydraenidae</td><td>6</td><td>5</td></tr><tr><td>Hydropsychidae</td><td>5</td><td>5</td><td>Hydrophilidae</td><td>3</td><td>3</td></tr><tr><td>Hydroptilidae</td><td>4</td><td>2</td><td>Noteridae</td><td>5</td><td>5</td></tr><tr><td>Kokiriidae</td><td>10</td><td>9</td><td>Scirtidae / Helodidae</td><td>10</td><td>3</td></tr><tr><td>Gracilipsodes</td><td>6</td><td>8</td><td>Staphylinidae</td><td>3</td><td>3</td></tr><tr><td>Oecetis</td><td>5</td><td>6</td><td>Haliplidae</td><td>5</td><td>5</td></tr><tr><td>Symphitoneuria</td><td>9</td><td>6</td><td>Heteroptera</td><td></td><td></td></tr><tr><td>Triplectides</td><td>5</td><td>7</td><td>Belostomatidae</td><td>5</td><td>5</td></tr><tr><td>a. genr. Leptoceridae</td><td>8</td><td>7</td><td>Corixidae</td><td>5</td><td>5</td></tr><tr><td>Philopotamidae</td><td>7</td><td>7</td><td>Gerridae</td><td>7</td><td>9</td></tr><tr><td>Polycentropodidae</td><td>7</td><td>8</td><td>Hebridae</td><td>5</td><td>5</td></tr><tr><td><strong>Odonatoptera</strong></td><td></td><td></td><td>Hydrometridae</td><td>9</td><td>7</td></tr><tr><td>Aeshnidae</td><td>5</td><td>5</td><td>Leptopodidae</td><td>5</td><td>5</td></tr><tr><td>Coenagrionidae</td><td>4</td><td>5</td><td>Mesoveliidae</td><td>8</td><td>4</td></tr><tr><td>Corduliidae</td><td>7</td><td>10</td><td>Notonectidae</td><td>7</td><td>10</td></tr><tr><td>Isostictidae</td><td>7</td><td>9</td><td>Ochteridae</td><td>5</td><td>5</td></tr><tr><td>Lestidae</td><td>5</td><td>5</td><td>Pleidae</td><td>5</td><td>5</td></tr><tr><td>Libellulidae</td><td>3</td><td>4</td><td>Saldidae</td><td>5</td><td>5</td></tr><tr><td>Argiolestidae*</td><td>7</td><td>8</td><td>Veliidae</td><td>5</td><td>9</td></tr><tr><td>Synthemistidae</td><td>5</td><td>8</td><td>Planipennes</td><td>5</td><td>5</td></tr><tr><td><strong>Cnidarians (Hydras)</strong></td><td>3</td><td>3</td><td><strong>GASTEROPOD MOLLUSKS</strong></td><td></td><td></td></tr><tr><td>Platyhelminths</td><td>3</td><td>9</td><td>Gyraulus</td><td>6</td><td>10</td></tr><tr><td>Buy</td><td>1</td><td>10</td><td>Physastra</td><td>2</td><td>10</td></tr><tr><td>Nematodes</td><td>2</td><td>30</td><td>Physa</td><td>2</td><td>3</td></tr><tr><td>Nemertians</td><td>6</td><td></td><td>Pseudosuccinea</td><td>8</td><td>3</td></tr><tr><td>Oligochaetes</td><td>1</td><td>7</td><td>Melanoides</td><td>3</td><td>4</td></tr><tr><td><strong>CRUSTACEANS</strong></td><td></td><td></td><td>Melanopsis</td><td>7</td><td>9</td></tr><tr><td>Amphipode</td><td>7</td><td>13</td><td>Thiara</td><td>5</td><td>3</td></tr><tr><td>Isopode</td><td>3</td><td>3</td><td>Hydrobiidae</td><td>8</td><td>4</td></tr><tr><td>Atyidae</td><td>5</td><td>7</td><td>Neritidae</td><td>6</td><td>5</td></tr><tr><td>Grapsidae</td><td>5</td><td>5</td><td><strong>MICROBENTHOS</strong></td><td></td><td></td></tr><tr><td>Hymenosomatidae</td><td>7</td><td>5</td><td>Ostracodes</td><td>2</td><td>9</td></tr><tr><td>Palaemonidae</td><td>8</td><td>9</td><td>Copépodes</td><td>9</td><td>5</td></tr><tr><td></td><td></td><td></td><td>Hydracariens</td><td>5</td><td>4</td></tr></table>

The most pollutant-sensitive taxa have the highest scores.

* Formerly Megapodagrionidae

In the case of low taxonomic richness identified (less than 10 taxa), Mary and Archaimbault (2012) recommend the calculation of BSI and/or LCBI index scores and the argumentation of the values obtained according to the characteristics of the environment, especially if they demonstrate good or very good biological quality. Indeed, a low taxonomic richness

reflects, in the case of Lake Chad, the disturbances due to the invasion of Eichhornia crassipes. A good quality sampling point generally includes at least fifteen different taxa or characterizes a particular type of environment (source area, outcrop, seepage, etc.) (Mary, 2015).

<table><caption>Table 16: Quality classes for LCBI and BSI (7 unit samples)</caption><thead><tr><th>LCBI</th><th>BSI (Biosedimentary Index)</th><th>Quality</th></tr></thead><tbody><tr><td>LCBI ≤ 4,15</td><td>BSI ≤ 4,25</td><td>Bad</td></tr><tr><td>4,15 &lt; LCBI ≤ 4,85</td><td>4,25 &lt; BSI ≤ 4,75</td><td>Poor</td></tr><tr><td>4,85 &lt; LCBI ≤ 5,50</td><td>4,75 &lt; BSI ≤ 5,25</td><td>Fair</td></tr><tr><td>5,50 &lt; LCBI ≤ 6,50</td><td>5,50 &lt; BSI ≤ 6,00</td><td>Good</td></tr><tr><td>LCBI &gt; 6,50</td><td>BSI &gt; 6,00</td><td>Very good</td></tr></tbody></table>

## 4.9. Local adaptation strategies for disturbances linked to invasive plants

### 4.9.1. Local economic strategy for adaptation to disturbances linked to invasive plants

In any season on the water, the average rate of cleaning of the banks of Lake Chad is 8.6±0.55% while the average rate of use of methods of cleaning the bottom of Lake Chad is 2.8 ±0.89% Sahelian semi-arid zone within GICs and women's associations. To be able to
# Impact of the Proliferation of Invasive Plants on Biodiversity and Women's Socio-Economic Adaptation Strategies in the Lake Chad Area

© August 2024, Volume 04, Issue 3 | https://sites.google.com/view/sahel-nature-consulting/accueil

catch fish, some women create oases for fishing and fish farming (93.12±0.44%) while the average rate of use (or valorization) of invasive plants is low 5.48±2.91% in the hydraulic zone of Lake Chad.

In any season on dry land, the average rate of cleaning of the banks of Lake Chad is 8.6±0.55% while the average rate of use of methods of cleaning the bottom

of Lake Chad is 2.8±0.89% semi-arid Sahelian zone within GICs and women's associations. To be able to catch fish, some women create oases for fishing and fish farming (93.12±0.44%) while the average rate of use (or valorization) of invasive plants is low 5.48±2.91% in the hydraulic zone of Lake Chad

<table><caption>**Table 17:** Economic strategy for adaptation to disturbances linked to invasive plants</caption><thead><tr><th rowspan="2"></th><th colspan="4">Economic adaptation strategy linked to water</th><th colspan="3">Economic adaptation strategy linked to land</th></tr><tr><th>Cleaning of the banks of Lake Chad (%)</th><th>Cleaning of the bottom of Lake Chad (%)</th><th>Development of oases for fishing and fish farming (%)</th><th>Use / Valorization of invasive plants (%)</th><th>Manual cleaning of invasive plants (%)</th><th>Chemical cleaning of invasive plants (%)</th><th>Development of invasive plant exploitation sites (%)</th><th>Use/valorization of invasive plants (%)</th></tr></thead><tbody><tr><td>Makary</td><td>8±0,3</td><td>2±0,9</td><td>93,7±0,9</td><td>08,8±0,9</td><td>8±0,2</td><td>2±0,3</td><td>38,27±8,17</td><td>05,2±0,9</td></tr><tr><td>Blangoua</td><td>9±0,9</td><td>1±0,3</td><td>92,9±0,7</td><td>07,3±0,3</td><td>9±1,5</td><td>3±0,5</td><td>49,32±1,32</td><td>04,1±0,3</td></tr><tr><td>Fotokol</td><td>8±0,7</td><td>1±0,7</td><td>92,7±0,4</td><td>06,2±0,7</td><td>7±0,9</td><td>2±0,6</td><td>37,56±4,13</td><td>07,1±0,7</td></tr><tr><td>Darak</td><td>9±0,4</td><td>1±0,4</td><td>92,8±0,9</td><td>01,5±0,4</td><td>8±0,4</td><td>3±0,3</td><td>44,13±2,22</td><td>08,1±0,4</td></tr><tr><td>Hilé Alifa</td><td>8±0,9</td><td>9±0,3</td><td>93,5±0,2</td><td>03,6±0,3</td><td>9±0,7</td><td>2±0,7</td><td>51,21±3,56</td><td>04,9±0,3</td></tr></tbody></table>

In the rainy season, the average use rate of fertilizers and chemical inputs is 86.40±5.55% among GIC women and 89.20±5.31% among association women, while the rate of using fertilizers and organic inputs is 16.40±9.12% among women in GICs and 13.20±4.02% within associations. The average rate of

modification of the need for water to be put in the fields is 30.40±3.97% among the women of the associations and 33.80±3.42% the women of the GIC while the average rate of modification of spacing between lines is 15.20±2.68% for women in GICs and 14.60±3.84% within associations

<table><caption>**Table 18:** Economic strategy for adapting agricultural production to disruptions linked to invasive plants</caption><thead><tr><th>Site</th><th></th><th>Use/cost of fertilizers and chemical inputs (%)</th><th>Use/cost of organic fertilizers (%)</th><th>Change in the need for water to be applied to the fields (%)</th><th>Changes in the spacings between the rows (%)</th><th>Changes in the spacings between the pockets during transplanting (%)</th><th>Change in depth of transplanting holes (%)</th></tr></thead><tbody><tr><td rowspan="6">Dry season</td><td>Makary</td><td>79±0,11</td><td>32±1,27</td><td>31±0,73</td><td>17±0,65</td><td>25±0,77</td><td>21±0,23</td></tr><tr><td>Blangoua</td><td>89±1,17</td><td>12±0,65</td><td>37±1,15</td><td>13±0,19</td><td>21±0,05</td><td>28±0,57</td></tr><tr><td>Fotokol</td><td>91±0,56</td><td>17±0,32</td><td>29±0,11</td><td>19±1,15</td><td>23±0,35</td><td>29±0,03</td></tr><tr><td>Darak</td><td>82±0,65</td><td>11±0,94</td><td>27±0,56</td><td>14±0,53</td><td>22±0,57</td><td>27±0,77</td></tr><tr><td>Hilé Alifa</td><td>91±2,72</td><td>10±0,15</td><td>28±0,21</td><td>13±0,12</td><td>28±0,63</td><td>24±0,13</td></tr><tr><td>Makary</td><td>81±0,05</td><td>9±0,13</td><td>35±0,59</td><td>11±0,15</td><td>20±0,15</td><td>21±0,27</td></tr><tr><td rowspan="6">Rainy season</td><td>Blangoua</td><td>87±0,93</td><td>11±0,23</td><td>39±2,72</td><td>16±0,55</td><td>22±0,09</td><td>20±0,37</td></tr><tr><td>Fotokol</td><td>91±1,59</td><td>18±0,10</td><td>33±0,76</td><td>18±0,32</td><td>21±0,94</td><td>27±0,36</td></tr><tr><td>Darak</td><td>94±2,07</td><td>17±0,32</td><td>32±0,77</td><td>10±0,39</td><td>27±0,67</td><td>21±0,55</td></tr><tr><td>Hilé Alifa</td><td>93±1,23</td><td>11±0,55</td><td>30±0,12</td><td>18±0,76</td><td>29±0,17</td><td>22±0,51</td></tr></tbody></table>

In the dry season, by means of modifications to the spacing between the pockets during transplanting in order to minimize losses when the plants emerge, it is 23.80±2.77% and 23.80±3.96 within the associations that within the associations while the average rate of modifications to the depth of transplanting holes in order to ensure the retention and saving of water at ground level is 25.80±3.27% within the associations and 22.20±2.77% in GIC. In the dry season, the average immediate sale after harvest, carried out within

the GIC is 837.57±135.90 Kilogram/Season/woman in and 795.00±40.56 Kilogram/Season/woman in association while the average sale after harvest storage is 519.89±60.04 Kilogram/Season/woman in association and 596.6±100.44 Kilogram/Season/woman within the GIC. The transformations and sales of products carried out within the GICs is 23.37±22.02 Kilogram/Season/woman and in association, we note 04.00±02.54 Kilogram/Season/woman.

<table><caption>**Table 19:** Economic adaptation strategy linked to the market and the sale of products harvested by season in the face of disturbances linked to invasive plants</caption><thead><tr><th rowspan="2">Site</th><th rowspan="2"></th><th colspan="2">Immediate sale after harvest (KG/Season)</th><th colspan="2">Sale after harvest storage (KG/Season)</th><th colspan="2">Processing and Sale (KG/Season)</th></tr><tr><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th><th>Dry season</th><th>Rainy season</th></tr></thead><tbody><tr><td rowspan="5">Area invaded by <i>Eichhornia crassipes</i> (≤50%) and <i>Prosopis juliflora</i> (≥50%)</td><td>Makary</td><td>897,31 ± 90,31</td><td>678,45 ± 21,98</td><td>567,87 ± 42,21</td><td>678,12 ± 12,12</td><td>07,17 ± 4,01</td><td>06,88 ± 01,02</td></tr><tr><td>Blangoua</td><td>897,41 ± 54,13</td><td>791,23 ± 73,65</td><td>437,11 ± 04,01</td><td>597,13 ± 76,35</td><td>09,81 ± 02,99</td><td>05,73 ± 00,60</td></tr><tr><td>Fotokol</td><td>899,76 ± 21,53</td><td>902,87 ± 62,11</td><td>587,67 ± 20,03</td><td>701,11 ± 26,81</td><td>05,12 ± 01,04</td><td>09,19 ± 02,41</td></tr><tr><td>Darak</td><td>594,47 ± 23,23</td><td>804,54 ± 71,07</td><td>495,47 ± 33,00</td><td>482,17 ± 39,01</td><td>49,45 ± 03,06</td><td>22,27 ± 03,90</td></tr><tr><td>Hilé Alifa</td><td>898,93 ± 20,83</td><td>799,92 ± 96,78</td><td>511,37 ± 24,01</td><td>597,92 ± 96,08</td><td>45,31 ± 24,01</td><td>17,52 ± 06,98</td></tr></tbody></table>
<table><tr><td>Area invaded by <i>Eichhornia crassipes</i> and <i>Juliflora</i></td><td>Makary</td><td>791,14 ± 38,41</td><td>798,97 ± 31,54</td><td>654,64 ± 33,01</td><td>791,01 ± 27,19</td><td>04,34 ± 03,36</td><td>01,79 ± 00,27</td></tr><tr><td rowspan="4">(≥50%)<br/>Prosopis<br/>(≤50%)</td><td>Blangoua</td><td>729,77 ± 23,92</td><td>877,65 ± 47,65</td><td>692,61 ± 39,43</td><td>797,12 ± 49,02</td><td>02,67 ± 01,4</td><td>07,82 ± 02,42</td></tr><tr><td>Fotokol</td><td>839,79 ± 31,97</td><td>879,91 ± 01,58</td><td>432,65 ± 13,01</td><td>416,14 ± 20,73</td><td>03,69 ± 01,37</td><td>01,14 ± 00,23</td></tr><tr><td>Darak</td><td>809,10 ± 53,41</td><td>780,34 ± 21,45</td><td>580,01 ± 34,76</td><td>683,79 ± 19,22</td><td>08,15 ± 04,22</td><td>08,39 ± 01,11</td></tr><tr><td>Hilé Alifa</td><td>805,24 ± 43,10</td><td>810,97 ± 10,93</td><td>621,41 ± 43,31</td><td>539,92 ± 21,11</td><td>01,41 ± 03,39</td><td>04,95 ± 01,09</td></tr></table>

In the rainy season, the average immediate post-harvest sale made within the GICs is 795.57±79.61 Kilogram/Season/woman and in association we have 829.57±46.23 Kilogram/Season/woman while the average sale after harvest and storage is 611.29±86.00 Kilogram/Season/woman within the GICs and 645.60±165.36 Kilogram/Season/woman within the associations. The transformations and sales of products carried out within the GICs is 12.32±7.23 Kilogram/Season/woman within the associations and 04.82±03.33 Kilogram/Season/woman within the GICs.

### 4.9.2. Local social strategy for adaptation to climate disruption within GICs and associations

In the dry season, the average rate of diversification of forms of mutual aid is 88.80±4.43% in association and

<table><caption>Table 20: Social strategy to adapt field production during the dry season</caption><thead><tr><th>Site</th><th>Diversification of forms of mutual aid (%)</th><th>Request for donation (materials or agricultural support, seeds and nurseries) (%)</th><th>Prayer or rites of invocation of the gods (%)</th><th>Solidarity between members (%)</th><th>Solidarity with others GIC (%)</th></tr></thead><tbody><tr><td rowspan="5">Dry season</td><td>Makary</td><td>89±1,21</td><td>32±0,17</td><td>31±3,19</td><td>17±0,93</td><td>25±0,37</td></tr><tr><td>Blangoua</td><td>82±2,15</td><td>12±0,27</td><td>37±0,16</td><td>13±0,27</td><td>21±0,56</td></tr><tr><td>Fotokol</td><td>94±1,57</td><td>17±0,32</td><td>29±0,77</td><td>19±0,05</td><td>23±0,24</td></tr><tr><td>Darak</td><td>88±0,79</td><td>11±0,35</td><td>27±0,39</td><td>14±0,35</td><td>22±0,03</td></tr><tr><td>Hilé Alifa</td><td>91±2,65</td><td>10±0,75</td><td>28±1,65</td><td>13±0,13</td><td>28±0,37</td></tr><tr><td rowspan="5">Rainy season</td><td>Makary</td><td>21±0,07</td><td>89±3,56</td><td>91±7,75</td><td>37±0,63</td><td>2±0,05</td></tr><tr><td>Blangoua</td><td>28±0,33</td><td>99±6,37</td><td>81±0,36</td><td>65±1,36</td><td>2±0,03</td></tr><tr><td>Fotokol</td><td>29±0,56</td><td>76±1,63</td><td>97±2,55</td><td>79±2,31</td><td>1±0,07</td></tr><tr><td>Darak</td><td>27±0,36</td><td>80±0,01</td><td>91±1,33</td><td>67±0,03</td><td>7±1,63</td></tr><tr><td>Hilé Alifa</td><td>24±0,65</td><td>81±0,06</td><td>99±2,07</td><td>68±0,63</td><td>9±1,35</td></tr></tbody></table>

The social strategy to adapt field production during the rainy season indicates that the average rate of diversification of forms of mutual aid is 25.80±3.27% in associations and 22.20±2.77% in GICs, while that the average rate of donation requests in the form of agricultural materials or support, seeds and nurseries is 85.00±9.13% in association and 89.60±5.02% in GIC. Faced with climatic hazards, certain GICs and associations opt for prayer sessions or rites of invocation of the gods, including 91.80±7.01% in associations and 94.00±3.31% in GICs. Solidarity between the members of certain GICs and associations is on average 63.20±15.62% in associations and 88.00±7.42% in GICs, while the average of favorable responses to inter-associative requests (or GIC), a guarantee of solidarity with other GICs.

Social and religious adaptations result in the purchase and/or donation of nurseries and invocation rites in the event of a rainfall deficit scenario (Yakouba et al., 2017). Many beliefs attribute the decrease in “water

92.20±7.01% in GIC, while the average rate of Request for donation in the form of agricultural, seed and nursery equipment or support is 16.40±9.12% in association and 13.20±4.02% in GIC. Faced with climatic hazards, certain GICs and associations opt for prayer sessions or rites of invocation of the gods, including 30.40±3.97% in associations and 33.80±3.42% in GICs and this situation is observed more in certain localities of the semi-arid Sahelian zone (in Guirvidig and Laf than in Mindif) according to Yakouba et al. (2017). Solidarity between members of certain GICs and associations is on average 15.20±2.68% in the dry season, while the average of favorable responses to inter-association requests (or GICs), a guarantee of solidarity with other GICs is 23.80±3.96% in the dry season.

coming from the sky” to divine punishment due to non-compliance with divine rules such as libidinal practices in the fields of production and the desecration of sacred places (Brou et al., 2005; Yakouba et al., 2017). This results in the organization of specific rituals performed in order to bring back the rain.

## 5. Conclusion

The objective of this study is to determine the effect of *Prosopis juliflora* and *Eichhornia crassipes* on biodiversity and the socio-economic adaptation strategies of women in the Lake Chad area.

In sum, on an average of 4,167±2,786 sampling points, an average of 165,667±2,804 *Eichhornia crassipes* plants was observed, with an average abundance-dominance index of 3,833±1,169 and an average recovery rate of the entire area of Lake Chad Cameroon which is 53.575±26.621%. However, the average regularity on the waters of Lake Chad is 0.598±0.217, higher in Makary (1.000) and lower in Blangoua (0.386). The
average frequency of *Eichhornia crassipes* in the waters
of Lake Chad Cameroon is 16.7±0.11%: the highest is
that of Makary (36%), while those observed in Darak
(08) and Hilé Alifa (08) are weak

Overall, unpolluted sites have an average SS of 22.04±9.45 mg/l, sites polluted by organic matter have an average SS of 24.07±8.22 mg/l while sites polluted by non-organic matter have a TSS of 23.43±1.41 mg/l. Sites polluted by organic matter have an average COD higher in the order of 34.63±15.18 mg/l while the unpolluted sites have an average COD of 32.18±16.19 mg/l, the sites polluted by non-organic matter have a D.C.O. of 32.56±12.02 mg/l.

In 2010, the sampling points surveyed made it possible
to count a total of 124 aquifer species while in 2024, a
total of 92 species were counted at the same sampling
points surveyed. Since 2010, we note an average overall
loss of aquatic biodiversity of 25.21±1.72% in the
waters of Lake Chad and a loss of waterways due to
invasive plants of 78.80±1.30%.

Women in the Lake Chad area and northern Cameroon carry out mainly agricultural subsistence activities. In any season on the water, the average rate of cleaning of spaces on the banks of Lake Chad for agricultural purposes is 8.6±0.55% while the average rate of use of methods for cleaning the bottom of the Lake Chad is 2.8±0.89% in Sahelian semi-arid zone (Area invaded by *Eichhornia crassipes* (≥50%) and *Prosopis juliflora* (≤50%)) within the GIC and women's association. To be able to catch fish, some women create oases for fishing and fish farming (93.12±0.44%) while the average rate of use (or valorization) of invasive plants is low 5.48±2.91% in the hydraulic zone of Lake Chad (Area invaded by *Eichhornia crassipes* (≤50%) and *Prosopis juliflora* (≥50%)).

In the rainy season, the average immediate post-harvest sale made within the GICs is 795.57±79.61 Kilogram/Season/woman and in association we have 829.57±46.23 Kilogram/Season/woman while the average sale after harvest and storage is 611.29±86.00 Kilogram/Season/woman within the GICs and 645.60±165.36 Kilogram/Season/woman within the associations. The transformations and sales of products carried out within the GICs is 12.32±7.23 Kilogram/Season/woman within the associations and 04.82±03.33 Kilogram/Season/woman within the GICs.

The social strategy to adapt field production during the
rainy season indicates that the average rate of
diversification of forms of mutual aid is 25.80±3.27%
in associations and 22.20±2.77% in GICs, while that
the average rate of donation requests in the form of
agricultural materials or support, seeds and nurseries is
85.00±9.13% in association and 89.60±5.02% in GIC.
Faced with climatic hazards, certain GICs and
associations opt for prayer sessions or rites of

invocation of the gods, including 91.80±7.01% in
associations and 94.00±3.31% in GICs. Solidarity
between the members of certain GICs and
associations is on average 63.20±15.62% in
associations and 88.00±7.42% in GICs, while the
average of favorable responses to inter-associative
requests (or GIC), a guarantee of solidarity with other
GICs.

Bibliographic Reference

Alexis DZOKOM. VALORISATION ENERGETIQUE ET ENVIRONNEMENTALE DES DECHETS PAPIERS ET CARTONS. Ingenieurie de l'environnement. Ecole Nationale Supérieure Polytechnique de Maroua (Cameroun), 2021. Français. –Archive ouverte HAL https://hal.science/tel-03624011

Syed Jamil Hasan Kazmi, Saima Shaikh, Umair Bin Zamir, Hina Zafar, Akhar Rasool, Faiza Tariq, Ambreen Afzal and Tanveer Arif, 2010. Ecological and Socio-economic Evaluation of the Use of *Prosopis juliflora* for Bio-char Production in Pakistan. Drynet Science & Technology Expertise. University of Karachi, Karachi, Pakistan December 21, 2009. Pp 54.

Gay C., 2000. Étude des Agences de l’Eau n°00, Indice Biologique Global Normalisé I.B.G.N. NF T 90ème – 350. Guide technique. 2 éditions. 36 p. ISSN : 1161-0425.

Mary N., 2015. Amélioration des méthodes
indicielles IBNC et IBS. Phase 3 : Validation
des indices. OEIL Observatoire de l'Environnement,
DAVAR SESER, Pôle de l'Observatoire de la
Ressource en Eau, CNRT « Nickel & son
Environnement ». 115 p. + annexes.

Morris MJ. Wood AR, Den BA. (1999). Plant pathogens and biological control of weeds in South Africa: a review of projects and progress during the last decade. In Olckers T., Hill MP. (eds.). Biological control of weeds in South Africa (1990–1998). African Entomology Memoir n° 1. Hatfi eld, USA: Entomological Society of Southern Africa, p. 129–137.

Florent Arthaud, 2015. « Formes d'adaptation des plantes aux milieux aquatiques » in L'eau à découvert : Troisieme partie : l'eau et le milieu. Université Savoie Mont Blanc, CARRTEL, Chambéry, 2015 p. 118-119 DOI: 10.4000/books.editionscnrs.9746. https://books.openedition.org/editionscnrs/9872?la ng=en#anchor-persons

B. Gopal 1987. Water hyacinth. (Aquatic Plant Studies 1). Elsevier, Amsterdam. Journal of Tropical Ecology
Mary N. & Archaimbault V., 2012. Amélioration des méthodes indicielles Indice Biotique de la Nouvelle-Calédonie (IBNC) et Indice Bio-sédimentaire (IBS). Phase 2. Rapport ETHYC'O et IRSTEA. Observatoire de l'environnement en Nouvelle-Calédonie. 75 p. + annexes.

Téllez T. R., López E. M. de R., Gloria L. G., Eva A. P., Ricardo M. L. and Juan M. S. G., 2008. The Water Hyacinth, *Eichhornia crassipes*: an invasive plant in the Guadiana River Basin (Spain) Special issue "Invasive species in inland waters of Europe and North America: distribution and impacts" Sudeep Chandra and Almut Gerhardt (Guest Editors): Aquatic Invasions (2008) Volume 3, Issue 1: 42-53 doi: 10.3391/ai.2008.3.1.8

Yakouba OUMAROU, Abdoul-Aziz SAÏDOU, Ali MADI, Felix WATANG ZIEBA et Oberline FOKOU YEMETA, 2017. Perception paysanne des perturbations pluviométriques et stratégies d'adaptation dans les systèmes de culture à sorgho repique en zone soudano-sahélienne du Cameroun, Afrique SCIENCE 13(4) (2017) 50-65, ISSN 1813-548X, http://www.afriquescience.info.

Nathalie Mary, 2015. Guide méthodologique et technique. Indice Biotique de Nouvelle-Calédonie et Indice Biosédimentaire. Ethyco. Etude Hydrosystemes Continentaux. DAVAR NC/ŒIL/CNRT « Nickel & son environnement ». Version revisée, 2015. Pp 78

Daget Philippe, Poissonet Jacques et Huguenin Johann, 2010. Prairies et Paturages- Methode d'étude de terrain et interpretation. Monpellier : CIRAD, 955 p. https://umr-selmet.cirad.fr/publications-et-ressources/documents-techniques

Daget Philippe et Poissonet Jacques, 1971. Une méthode d'analyse phytologique des prairies : critères d'application. Annales Agronomiques, 22(1) : 5-4

Muriel SAULAIS; Jean-Philippe BEDELL, 2009, FICHE TECHNIQUE OTHU N° 15, Vers une méthodologie d'étude de la végétalisation naturelle de bassins d'infiltration. Rue Maurice Audin, 69518 Vaulx en velin, 2009, Pp 6.

Mwangi, E and B. Swallow (2005) Invasion of *Prosopis juliflora* and local livelihoods Case study from the Lake Baringo area of Kenya, ICRAF

Working Paper no. 3, World Agro-forestry Centre: Nairobi

Tchiaze I. A. V. et Priso R. J., 2016. Répartition et valorisation des macrophytes envahissantes dans la région du littoral (Cameroun) : cas d'Eichhornia crassipes (Mart.) Solms-Laubach, Journal of Applied Biosciences 100:9522-9534, 2016, ISSN 1997-5902, http://dx.doi.org/10.4314/jab.v100i1.4

Sofyan E.T., Gumelar F.A., Yuniarti A., Joy B., Wicaksono F.Y., 2023. Effectiveness of water hyacinth compost and N, P, K, S fertilizer on S available, S uptake, protein content, and yield of shallot in Inceptisols from Jatinangor, Jurnal Kultivasi Vol. 22 (1) April 2023 ISSN: 1412-4718, eISSN: 2581-138x, DOI: http://dx.doi.org/10.24198/kultivasi.v22i1.38589

Sahana S., Pramod V. P., Ramalingappa, 2018. Effect of Eichhornia crassipes (Mart.) Solms. Compost on MorphoPhysiological Parameters of Blackgram (Vigna mungo (L) Hepper). International Journal of Science and Healthcare Research Vol.3; Issue: 4; Oct.-Dec. 2018. ISSN: 2455-7587, www.ijshr.com

Abhed Pandey, 2020. Water hyacinth as potential feed and compost in aquaculture: A review. Journal of Entomology and Zoology Studies 2020; 8(5): 1434-1437. E-ISSN: 2320-7078 P-ISSN: 2349-6800 www.entomoljournal.com

Hervé G., Pinardel K. K., Jean-Paul O.B. et Mathurin M., 2016. Intensifier la culture du maïs pour améliorer la securité alimentaire : le producteur du Nord Cameroun y a-t-il interet ? Article de recherche, Cahiers Agricultures 2016, 25 (6), 65006, www.cahiersagricultures.fr

Ouedraogo E. et Hien E., 2015. Effet d'un compost enrichi par des spores du clone Trichoderma harzianum (rifaï) sur le rendement du niébé et du maïs sous abris au Burkina Faso. International Journal of Biological and Chemical Sciences, 9(3): 1330-1340, 2015. DOI: http://dx.doi.org/10.4314/ijbcs.v9i3.18

Mandryk, A.M., Wein, R.W. Exotic vascular plant invasiveness and forest invasibility in urban boreal forest types. *Biol Invasions* 8, 1651-1662 (2006). https://doi.org/10.1007/s10530-005-5874-6

Oumarou A., Jeanne M.-R. et Siméon K., 2008. Production de Biogaz et de Compost à Partir de la Jacinthe d'eau pour un Développement Durable en Afrique Sahélienne. VertigO - La revue en sciences de l'environnement, Vol8 n°1, avril 2008
Radford, P. J., 1967. Growth analysis formulae: their use and abuse. Crop. Science, 7: 171-15.

Vannakambadi K. Ganesh, Nik Muller, Ken Judge, Chi-Hao Luan, Radhakrishnan Padmanabhan, Krishna H.M. Murthy. 2015. Identification and characterization of nonsubstrate based inhibitors of the essential dengue and West Nile virus proteases. *Bioorganic & Medicinal Chemistry. Volume 13, Issue 1, 3 January 2005, Pages 257-264.*
https://doi.org/10.1016/j.bmc.2004.09.036

Moreno, R. and Valdez, A. (2005) Cognitive load and learning effects of having students organize pictures and words in multimedia environments: The role of student interactivity and feedback. Educational Technology Research and Development, 53, 35-45.
http://www.etc.edu.cn/Cognitive_Load_and_Learning_Effects_of_Having_Students_Organize_Pictures_and_Words_in_Multimedia_Environments.pdf
http://dx.doi.org/10.1007/BF02504796

BROU Y. T., AKINDES F. F. et BIGOT S., 2005. La variabilité climatique en Côte d'Ivoire : entre perceptions sociales et réponses agricoles, Cahiers Agricultures, 14 (6) (2005)
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