In Tunisia, the agricultural sector faces multiple challenges that affect both productivity and farmers’ livelihoods. Although agroecology is increasingly recognized as a pathway to sustainable agriculture, the extent of its adoption by farmers remains unclear. This study assesses the agroecological performance of 50 farms in the Sbikha delegation of the Kairouan governorate (Central Tunisia), using the Tool for Agroecological Performance Evaluation (TAPE), developed by the FAO. This tool assesses how existing cropping systems align with the 10 principles of agroecology and explores their potential for further transition. The results reveal a modest level of agroecological adoption, averaging only 41%. Several factors influence this outcome, including limited farmer knowledge and technical capacity, a weak institutional and organizational framework, and low diversification of cropping systems. Furthermore, three types of farms were identified based on their production systems: farms specializing in fruit trees, farms specializing in cereal and vegetable crops, and farms specializing in olive and vegetable crops. Among these, fruit tree farms exhibit a higher level of agroecological transition, averaging 51%. This increased diversification enhances resilience to market fluctuations. To accelerate the agroecological transition, several key measures should be implemented. Updating land property titles would improve access to credit by enabling farmers to provide the necessary guarantees. Additionally, targeted training programs and awareness-raising initiatives could strengthen technical capacities, thereby facilitating the adoption of agroecological practices. These interventions would enhance farmers’ economic resilience, support sustainable agricultural production, and promote equitable rural development.

Climate change poses significant challenges to goat farming systems in arid regions, requiring integrated approaches combining genetic diversity, adaptive management, and value chain optimization. This study assessed breed performance, climate adaptation strategies, and dairy valorization potential in southeastern Tunisia's Gabes region. A comprehensive survey of 110 goat farmers documented climate perceptions and adaptation practices, while experimental analysis of 40 dairy goats representing four breeds (Local, Alpine, Maltese, Damascus) evaluated milk composition and cheese yield through 120 samples collected over nine weeks at three-week intervals. Statistical power analysis confirmed adequacy (>0.80) for detecting breed differences in key parameters. Morphometric characterization included 50 animals across five breeds and dairy valorization assessment complemented the analysis. Damascus goats demonstrated superior milk quality with significantly higher fat content (5.51% vs 3.83% in Local breeds, F=5.254, p=0.004) and lactose levels (3.98% vs 3.61%), but paradoxically achieved the lowest cheese yield (78.07% vs 85.57% in Maltese breeds, p<0.001). Alpine and Maltese breeds optimized processing efficiency with 84-86% cheese yields. Farmers implemented comprehensive adaptation strategies including crossbreeding (76%), infrastructure renovation (60%), and reduced grazing dependence (3.74 h/day average). Women dominated dairy processing (87%) with traditional products achieving 3.3-fold value multiplication over raw milk. Results reveal sophisticated breed-environment interactions where genetic specialization for arid conditions does not automatically translate to processing advantages. Strategic breed portfolio management combining Damascus for premium products, Alpine/Maltese for commercial efficiency, and Local breeds for climate resilience offers optimal sustainability outcomes.

Farmers' organizations have become a central element in agricultural policies and have established themselves as key partners in development programs in developing countries. This study aims to create a business model will define, on the one hand, the necessary resources (financial, technical, human) to realize its future projects and demonstrate their viability, and, on the other hand, the strategies to overcome existing constraints while leveraging local resources and creating sustainable activities. Semi-structured interviews and detailed surveys were thus conducted with the SMSA board of directors and its members. The business model, developed and validated by SMSA members, provides a clear strategy for income-generating activities to be implemented and investments to be made in the short and medium term. The development of SMSAs should therefore be integrated into a territorial development approach that focuses on enhancing local resources, with members leveraging their artisanal skills. Furthermore, considering the challenges SMSAs face in terms of effective management and visibility, their activities should be reinforced with a mechanism for technical assistance and support.

Goat farming represents a critical component of rural livelihoods, food security, and cultural heritage in southeastern Tunisia. This study adopts a multi-stakeholder approach to analyze the goat value chain in Tataouine, incorporating focus groups, semi-structured questionnaires, and direct observations with 80 farmers, 3 veterinarians, 13 butchers, and 100 consumers. The findings reveal strong local demand, with 72% of consumers purchasing goat meat and 66% consuming milk. However, significant inefficiencies exist, particularly a misalignment between production and market requirements: while 92% of butchers prefer fattened animals, only 16% of farmers engage in fattening practices. Women constitute 49% of dairy processors, yet face persistent resource constraints. Climate pressures exacerbate these challenges, with 80% of farmers reporting water scarcity and 93.8% observing pasture degradation. Three strategic interventions emerge as pivotal for sustainable development: targeted support for feed-efficient fattening techniques, establishment of women-led dairy processing collectives, and implementation of climate-resilient water management systems. These measures address core constraints while leveraging existing strengths of the production system. The study presents a transferable framework for livestock value chain analysis in arid regions, demonstrating how integrated approaches can enhance both economic viability and adaptive capacity while preserving traditional pastoral systems.

In Tunisian arid regions, farming systems are increasingly exposed to quick environmental and socio-economic changes, which may reduce their performance and resilience. This paper seeks to assess the performance of farming systems in the district of Sidi Makhlouf (Southeast of Tunisia) considering their diversity. Thus, a typology of farms based on data from the 2004-2005 structure surveys was developed using multidimensional analyzes and the expert method. Multidimensional analyzes have identified three groups of farms: “Rain-fed olive farms”, “Irrigated farms”, and “Livestock farms”. Representative farms were chosen by local agricultural experts to conduct an in-depth analysis of the identified groups. Then, two field surveys were performed with the chosen farmers. Characterization and analysis of homogeneous "reference farm groups" confirm their socioeconomic and technical performance diversity, according to the capital endowment and the strategies implemented by farmers. These results suggest that agricultural policies and interventions should be targeted to strengthen performances and to respond to the specific contexts of each farms’ group.

This paper presents a livelihood vulnerability assessment and compares the levels of exposure, sensitivity and adaptation to climate change of the local populations in mountains area and coastal plains in Tunisian arid regions. The United Nations Intergovernmental Panel on Climate Change vulnerability index (LVI-IPCC) has been adapted and applied to assess this livelihood vulnerability, based on socio-economic surveys and semi-structured interviews with the local populations. Findings show that households in coastal plains are more vulnerable in terms of socio-demographic profile, food security, social networks, access to water and climate variability. This territory is much more exposed to climate change, despite being slightly less sensitive. On the other hand, households in mountainous territory are more vulnerable in terms of livelihood strategies, land tenure and health, despite their adaptation capacity, which reduces their vulnerability to climate change. Based on this vulnerability assessment, this work suggests specific adaptation strategies and measures for livelihoods sustainability in each territory.

This paper presents a livelihood vulnerability assessment and compares the levels of exposure, sensitivity and adaptation to climate change of the local populations in mountains area and coastal plains in Tunisian arid regions. The United Nations Intergovernmental Panel on Climate Change vulnerability index (LVI-IPCC) has been adapted and applied to assess this livelihood vulnerability, based on socio-economic surveys and semi-structured interviews with the local populations. Findings show that households in coastal plains are more vulnerable in terms of socio[1]demographic profile, food security, social networks, access to water and climate variability. This territory is much more exposed to climate change, despite being slightly less sensitive. On the other hand, households in mountainous territory are more vulnerable in terms of livelihood strategies, land tenure and health, despite their adaptation capacity, which reduces their vulnerability to climate change. Based on this vulnerability assessment, this work suggests specific adaptation strategies and measures for livelihoods sustainability in each territory.

Climate change is a worldwide environmental issue to all economic sectors, mainly the agricultural sector. Tunisia is one of the countries adversely affected by climate change because of its low adaptive capacity. Adapting to climate threat is the main goal of farmers, who are the primary stakeholders in agriculture, to increase the resilience of their farming systems. Based on a survey between March and May 2018 with 100 agricultural households from the governorate of Medenine, which belongs to Southeast Tunisia, this paper examined the main adaptive measures to climate change used by farmers, the factors influencing their choice of measures and the constraints to adaptation. To explore the factors affecting the choice of adaptive measures, this study employed a multinomial logit regression. Results showed that irrigation, crop diversification, integration of crop with livestock and shifting from farm to non-farm activities were the main adaptive measures implemented by farmers in the study area. Further, the multinomial logit model indicated that the factors influencing the choice of adaptive measures included household head age, access to extension services, household income, number of years of experience of the household head in agriculture, and the distance to the market. The results demonstrated also that adaptation to climate change was hindered by many factors such as constrained resources, lack of money, and water shortage. The findings of this research suggest the need for improving the access to extension services, to water, and to means of production to enhance the resilience of vulnerable agricultural households and to improve their wellbeing.

Since the end of December 2019, the COrona VIrus Disease (COVID-19) is sweeping the world and has caused huge damage to the health, economy, and social life of the communities. Meteorological variables are among the factors influencing the spread of contagious diseases. The aim of this study was to explore the correlation between climatic parameters and COVID-19 spread in Tunisia. To do this, we designed a daily dataset including the number of confirmed and deaths cases, minimum temperature (°C), maximum temperature (°C), mean temperature (°C), rainfall (mm), and wind speed (km/h) during the period of June 27 to October 22, 2020. To investigate the association between climatic variables and COVID-19, the Spearman correlation test was employed. The Mann-Kendall test has been also used to detect the direction of the COVID-19 trend. As many researchers have demonstrated that the incubation period of the ongoing pandemic varies from 1 to 14 days, the correlation of each parameter with COVID-19 was examined on the day of the confirmed cases and deaths, and before 7 and 14 days. The results showed that out of the five selected climatic variables, four variables were correlated with COVID-19 cases and deaths (statistically significant at a 99% confidence level). A positive correlation of the rainfall with COVID-19 confirmed cases and deaths was observed, the highest was 14 days ago. However, negative correlations were observed for minimum, maximum, and mean temperature, the highest was on the day of the incident. Besides, the Mann-Kendall test showed increasing trends for COVID-19 cases and deaths (statistically significant at a 99% confidence level). The results of this study might be useful to understand the role of climatic factors in the spread of COVID-19 and provide insights for healthcare policymakers to well manage this global pandemic.

The Sustainable Livelihood Approach (SLA) assumes that all capitals are complementary and that more capital assets would lead to greater adaptive capacity. However, the SLA neglects the interactions and transformations between different livelihood capitals. This paper suggests a methodological approach to understand how different capitals may be structured, transformed, and used to improve the farm households’ adaptive capacity to climatic stresses. Data for this study were gathered by means of a questionnaire survey during 2018 from 100 farm households representing the main farming systems of Medenine governorate, Southeast of Tunisia. The analyses were carried out using three tools following a stepwise approach. First, to understand the interactions that exist between the different capitals, a Principal Component Analysis (PCA) was carried out. Then, the adaptive capacity was calculated using the PCA results. Finally, using the Pearson's correlation index, the impact of livelihood assets on adaptive capacity was tested. The results demonstrated that households are trying to compensate for the lack of certain assets through interactions with others in order to improve their adaptive capacity. Moreover, human, natural and financial capital seem to better influence the adaptive capacity of farmers, while the impacts of physical and social capital are relatively less important. These results have improved our comprehension of the livelihood capital purpose for strengthening the existing approaches that enhance the adaptive capacity. Finally, this study has demonstrated that exploring the interactions between livelihood capitals is a first concern, which should be incorporated into adaptive capacity planning and policy development.