Climate and landscape mediate patterns of low lentil productivity in Nepal

46. Erskine W, Tufail M, Russell A, Tyagi MC, Rahman MM, Saxena MC. Current and future strategies in breeding lentil for resistance to biotic and abiotic stresses. Euphytica. 1993; 73: 127–135. 47. Erskine W, El Ashkar F. Rainfall and temperature effects on lentil (Lens culinaris) seed yield in Mediter- ranean environments. Journal of Agricultural Science. 1993; 121: 347. 48. Wiraguna E, Malik AI, Erskine W. Waterlogging tolerance in lentil (Lens culinaris Medik. subsp. culi- naris) germplasm associated with geographic origin. Genetic Resources and Crop Evolution. 2017; 64: 579–586. 49. Salam MU, Day TK, Ahmed AU, Nessa B, Haque AHMM, Subedi S, et al. Stempedia: A weather-based model to explore and manage the risk of lentil Stemphylium blight disease. Australasian Plant Pathol- ogy. 2016; 45: 499–507. 50. Subedi S, Shrestha SM, KC GB, Thapa RB, Ghimire SK, Neupane S, et al. Botanical, chemical and bio- logical management of Stemphylium botryosum blight disease of lentil in Nepal. Indian Phytopath. 2015; 68: 415–423. 51. Lutz AF, Immerzeel WW, Shrestha AB, Bierkens MFP. Consistent increase in high Asia’s runoff due to increasing glacier melt and precipitation. Nature Climate Change. 2014; 4: 587–592. 52. Pradhan P, Fischer G, Van Velthuizen H, Reusser DE, Kropp JP. Closing yield gaps: How sustainable can we be? PLoS ONE. 2015; 10(6): e0129487. https://doi.org/10.1371/journal.pone.0129487 PMID: 26083456 53. Devendra C. Small farm systems to feed hungry Asia. Outlook on Agriculture. 2007; 36: 7–20.

54. MoPE. Ministry of Population and Environment. Department of Hydrology and Meteorology. Govern- ment of Nepal; 2017; http://dhm.gov.np/meteorological-station/. 55. Lu GY, Wong DW. An adaptive inverse-distance weighting spatial interpolation technique. Computers and Geosciences. 2008; 34: 1044–1055. 56. Farell M. The measurement of productive efficiency. Journal of the Royal Statistical Society. 1957; 120: 253–290. 57. Seiford L. Data envelopment analysis: The evolution of the state of the art (1978–1995) Journal of Pro- ductivity Analysis. 1996; 7: 99–137. 58. Aigner D, Lovell CAK, Schmidt P. Formulation and estimation of stochastic frontier production function models. Journal of Econometrics. 1977; 6: 21–37. 59. Meeusen W, van Den Broeck J. Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review. 1977; 18: 435–444. 60. Stevenson RE. Likelehood functions for generalized stochastic frontier estimation. Journal of Econo- metrics. 1980; 13: 57–66. 61. Greene WH. A gamma-distributed stochastic frontier model. Journal of Econometrics. 1990; 46: 141– 163. 62. Battese G., Coelli T. A model for technical inefficiency effects in a stochastic frontier production function. Empirical Economics. 1995; 20: 325–332. 63. Wang HJ, Schmidt P One-step and two-step estimation of the effects of exogenous variables on techni- cal efficiency levels. Journal of Productivity Analysis. 2002; 18: 129–144. 64. Kumbhakar SC, Ghosh S, McGuckin JT. A generalized production frontier approach for estimating

determinnatns of inefficiency in US dairy farms. Journal of Business & Economic Statistics. 1991; 9: 279–286. 65. Reifschneider D, Stevenson R. Systematic departures from the frontier: a framework for the analysis of firm inefficiency. International Economic Review. 1991; 32: 715–723. 66. Tobin J. Estimation of relationships for limited dependent variables. Econometrica. 1958; 26: 24–36. 67. Dey MM. Analysis of demand for fish in Bangladesh. Aquaculture Economics and Management. 2000; 4: 63–81. 68. Rahman S. Environmental impacts of technological change in Bangladesh agriculture: Farmers’ per- ception and empirical evidence. Outlook on Agriculture. 1999; 28: 233–238. 69. Thapa G, Otsuka K, Barker R. Effect of modern rice varieties and irrigation on household income distri- bution in Nepalese villages. Agricultural Economics. 1992; 7: 245–265. 70. Beneito P, Ferri J, Molto´ ML, Uriel. Determinants of the demand for education in Spain. Applied Eco- nomics. 2001; 32: 1541–1551. 71. Rahman S. Farm-level pesticide use in Bangladesh: Determinants and awareness. Agriculture, Ecosys- tems and Environment. 2003; 95: 241–252. 72. Bravo-Ureta BE, Pinheiro AE. Efficiency analysis of developing country agriculture: A review of the fron- tier function literature. Agricultural and Resource Economics Review. 1993; 22: 88–101. PLOS ONE Climate and landscape mediate low lentil productivity PLOS ONE | https://doi.org/10.1371/journal.pone.0231377 April 16, 2020 18 / 19