Background:
Climate variability significantly constrains agricultural productivity, particularly in rainfed systems where precipitation governs soil moisture and crop growth. In Nigeria, declining and erratic rainfall patterns threaten rice production, a staple crop critical for food security. Precipitation effectiveness, including rainfall timing and distribution, plays a key role in determining yield outcomes and shaping agroecosystem resilience under changing climatic conditions.

Objectives:
This study examines the influence of precipitation effectiveness indices on rice yield in Langtang South, Nigeria, aiming to identify key rainfall determinants of productivity and evaluate their implications for agroecosystem resilience under rainfed agricultural conditions.

Methods:
The study was conducted in Langtang South LGA, Plateau State, Nigeria, a tropical wet–dry climate region. Daily rainfall data (2001–2025) were obtained from the College of Agriculture Garkawa, while rice yield data were sourced from the Plateau State Ministry of Agriculture. Precipitation effectiveness indices (PEI) including hydrologic ratio, dry spells, rainfall onset, cessation, length of rainy season, and number of rainy days were computed. Descriptive statistics were used to summarize temporal patterns. Relationships between PEI variables and rice yield were examined using multiple linear regression, with additional Generalized Additive Models (GAM) applied in R to capture potential non-linear effects and thresholds.

Results:
The results indicated that onset dates typically begin in April which fluctuate slightly from year to year, the variation remains within a relatively narrow window of about nine days. The onset of rainfall was highly consistent across the study period. Cessation dates indicated that rainfall generally ends in late October, cessation dates indicated that rainfall generally ends in late October, with year 2010 and 2017 having earlier cessation dates resulting in shorter growing seasons, therefore, had less yield of 1.76 yield/ha and 2.1 yield/ha respectively. While the highest yield was recorded in 2006 (4.0 yield/ha), 2014 (3.81 yield/ha), 2012 (4.0 yield/ha) and 2020 (4.0 yield/ha). Results revealed that rainfall at cessation, showed a high variability. It is evident that the total annual rainfall showed that the intra-seasonal rainfall variability, play a critical role in influencing agricultural outcomes rather than total annual rainfall. The regression model showed a moderate relationship between precipitation effectiveness indices and yield per hectare (R = 0.589), explaining 34.7% of the variance. However, the model was not statistically significant (F = 2.016, p = 0.122), indicating that the predictors did not collectively explain yield variability. Among the independent variables, only rainfall showed a significant effect (p = 0.048), with a negative relationship indicating that higher rainfall reduced crop yield. Other variables, including cessation date, total annual rainfall, and length of growing season, were not statistically significant.

Conclusion:
The study concludes that precipitation effectiveness indices are critical predictors of rice yield variability in Langtang South and should be integrated into climate-smart agricultural planning, extension services, and policy interventions aimed at improving rice productivity under increasing climate variability.