Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Forecasting Kenya's Camel Population for Climate Adaptation and Sustainable Livestock Development

Domaine:

climateagriculture

Type de record:

paper
Créateur:
FloEll
Éditeur:
Uni
Hôte:
Camel production systems are increasingly central to livelihood resilience, climate adaptation, and food security in the arid and semi-arid lands (ASALs) of Kenya, where recurrent droughts and climate variability have undermined conventional cattle-based systems. Consequently, pastoral communities have progressively shifted towards camel-dominant production strategies. Despite the growing economic and ecological significance, systematic empirical forecasting of national camel population trajectories remains limited. Most existing livestock assessments rely on descriptive statistics rather than formal stochastic modelling frameworks. This study developed a comparative univariate time-series forecasting framework. Specifically, it evaluated the forecasting performance of Autoregressive Integrated Moving Average (ARIMA), Holt's linear trend, Exponential Smoothing State Space (ETS), and Linear Trend models using the annual FAOSTAT livestock stock database for Kenya (1961 to 2024). Model performance was evaluated using stationarity diagnostics, residual independence tests, and out-of-sample forecast accuracy metrics, including Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). Forecast comparisons were further evaluated using the Diebold–Mariano predictive accuracy test. The ARIMA (2,1,1) model achieved the lowest AIC (-46.55) and BIC (-36.25). However, the ETS (M, N, N) model demonstrated the highest predictive accuracy with the lowest forecast errors (RMSE = 622,710; MAE = 429,282; MAPE = 11.36%). The projections suggest that Kenya's camel population is likely to stabilise or moderately increase between 2025 and 2029, reflecting continued adaptation to climate variability. These findings provide valuable evidence for livestock planning, climate adaptation, and sustainable development of Kenya's camel sector.

Visit

doi.org

Licenses

https://creativecommons.org/licenses/by-nc-sa/4.0

Similaires

Climate Variability and Livestock Production in Nigeria: Lessons for Sustainable Livestock ProductionTourism, gender, and climate change adaptation in Kenya's coastClimate Change Adaptation Mechanism for Sustainable Development Goal 1 in Nigeria: Legal ImperativeChallenges of financing climate adaptation in Kenya's smallholder agricultureBrachiaria Grass for Climate Resilient and Sustainable Livestock Production in KenyaVulnerability of Water Resources to Climate Change: Adaptation and Resilience Strategies for Sustainable Development in Nigeria

Climate Variability and Livestock Production in Nigeria: Lessons for Sustainable Livestock Production

Abstract The study examined the relationship between climate variability and lives

Tourism, gender, and climate change adaptation in Kenya's coast

Tourism’s development along Kenya’s coast has undergone gradual yet significant transformation shape

Climate Change Adaptation Mechanism for Sustainable Development Goal 1 in Nigeria: Legal Imperative

Abstract Despite international efforts on poverty reduction in the last decade, poverty is rampant

Challenges of financing climate adaptation in Kenya's smallholder agriculture

Brachiaria Grass for Climate Resilient and Sustainable Livestock Production in Kenya

Abstract Brachiaria grass is a “climate smart” forage that produces high amount of palatable and

Vulnerability of Water Resources to Climate Change: Adaptation and Resilience Strategies for Sustainable Development in Nigeria

Nigeria faces inexorable climate change in recent times. This phenomenon will have a profound effect