Productivity impacts and environmental trade-offs of livestock-based systems in the northern uplands of Lao PDR

To better understand these dynamics, a baseline environmental assessment of livestock systems was conducted in Nonghet District, Xiengkhouang Province (Dao et al., 2025), complemented by a feed resource analysis using the Gendered Feed Assessment Tool (G-FEAST) (Philp et al., 2024). Together, these...

Descripción completa

Detalles Bibliográficos
Autores principales: Dao Thu, Hang Thi, Notenbaert, An, Van Der Hoek, Rein, Philp, Joshua, Jalonen, Riina, Mponela, Powell, Atieno, Mary
Formato: Informe técnico
Lenguaje:Inglés
Publicado: 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/180286
Descripción
Sumario:To better understand these dynamics, a baseline environmental assessment of livestock systems was conducted in Nonghet District, Xiengkhouang Province (Dao et al., 2025), complemented by a feed resource analysis using the Gendered Feed Assessment Tool (G-FEAST) (Philp et al., 2024). Together, these studies identified distinct farm typologies and demonstrated that more than 70% of upland households face seasonal feed deficits during the dry months, with limited adoption of improved forages. The baseline findings highlighted the need for context-specific interventions that both address feed scarcity and mitigate environmental impacts. In particular, integrating improved forages, managing grazing lands more efficiently, and strengthening crop-livestock linkages were identified as promising pathways for sustainable intensification. However, these interventions must be carefully designed to fit local agroecological and socioeconomic conditions and to minimize trade-offs related to land, water, and emissions. Building on this foundation, the present report develops intervention scenarios for sustainable livestock intensification in Nonghet District. The scenarios focus on two representative farm types identified in the baseline typology including extensive livestock-oriented systems (Type 1) and semi-intensive mixed systems (Type 4), which together capture the main livestock-based production systems and environmental gradients of the region (Dao et al., 2025).