Climate and landscape mediate patterns of low lentil productivity in Nepal

RESEARCH ARTICLE Climate and landscape mediate patterns of low lentil productivity in Nepal Gokul P. PaudelID1*, Mina Devkota1¤a, Alwin Keil2, Andrew J. McDonald1¤b 1 International Maize and Wheat Improvement Center (CIMMYT), South Asia Regional Office, Kathmandu, Nepal, 2 International Maize and Wheat Improvement Center (CIMMYT), National Agricultural Science Centre Complex (NASC), New Delhi, India ¤a Current address: International Center for Agricultural Research in the Dry Areas (ICARDA), Rabat, Morocco ¤b Current address: Section of Soil and Crop Sciences, School of Integrative Plant Sciences, Cornell University, New York, United States of America * g.paudel@cgiar.org Abstract Lentil (Lens culinaris Medik.) is a cool-season pulse grown in winter cropping cycle in South Asia and provides a major source of nutrition for many low-income households. Lentil pro- ductivity is perceived to be sensitive to high rainfall, but few studies document spatial and temporal patterns of yield variation across climate, soil, and agronomic gradients. Using farm survey data from Nepal, this study characterizes patterns of lentil productivity and effi- ciency for two cropping seasons. Additional insights were derived from on-farm trials con- ducted over a 5-year period that assess agronomic, drainage, and cultivar interventions. To contextualize the inferences derived from farm surveys and trials, the Stempedia model was used to simulate the severity of Stemphylium blight (Stemphylium botryosum) risk–the prin-

cipal fungal disease in lentil–with 30 years of historical climate data. Although development efforts in Nepal have prioritized pulse intensification, results confirm that lentil remains a risky enterprise highlighting the prevalence of crop failures (16%), modest yields (353 kg ha- 1), and low levels of profitability (US$ 33 ha-1) in wet winters. Nevertheless, site factors such as drainage class influence responses with upland sites performing well in wet winters and lowland sites performing well in dry winters. In wet winters, a phenomena perceived to be increasing, 76% of surveyed farmers reported significant disease pressure and simulations with Stempedia predict that conditions favoring Stemphylium occur in >60% of all years. Nevertheless, simulation results also suggest that these risks can be addressed through earlier planting. Based on the combined results, gains in yield, yield stability, and technical efficiency can be enhanced in western Nepal by: 1) ensuring timely lentil planting to mitigate climate-mediated disease risk, 2) evaluating new lentil lines that may provide enhanced resistance to diseases and waterlogging, and 3) encouraging the emergence of mechaniza- tion solutions to overcome labor bottlenecks. PLOS ONE PLOS ONE | https://doi.org/10.1371/journal.pone.0231377 April 16, 2020 1 / 19 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Paudel GP, Devkota M, Keil A, McDonald AJ (2020) Climate and landscape mediate patterns of low lentil productivity in Nepal. PLoS ONE 15(4): e0231377. https://doi.org/10.1371/journal.

pone.0231377 Editor: Vincent Vadez, Institut de Recherche pour le Developpement (IRD), FRANCE Received: December 2, 2019 Accepted: March 20, 2020 Published: April 16, 2020 Copyright: © 2020 Paudel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Part of the data used in this manuscript are online available while other data which are not available online are attached in the supplementary section of this article. The climate data related with this article were purchased from the Ministry of Environment, Department of Hydrology and Meteorology, Government of Nepal and can be found in http:// dhm.gov.np/meteorological-station/. The farm survey data can also be found in the CIMMYT dataverse. URL link is: https://data.cimmyt.org/ dataset.xhtml?persistentId=hdl:11529/10548086.