The role of soil water availability in potential rainfed rice productivity in Bangladesh: applications of the CERES-Rice mode

Soil water stress and its impact on the monsoon season potential rainfed rice productivity in Bangladesh is investigated. A crop growth simulation model, CERES-Rice, is applied to 16 locations representative of the major rice growing regions of Bangladesh to determine the impact of soil water stress on the regional scale potential yield for four transplanting dates: 1 June, 1 July, 15 July, and 15 August. A quantified estimate of potential yield loss for four regions and for Bangladesh as a whole is calculated for water stress during flowering and maturing stages. For example, in Bangladesh, average potential yield for 1 June transplanting date, under low water stress during both flowering and maturing stages, is 7218 kg ha–1. On the other hand, high water stress during maturing, flowering, and both flowering and maturing stages, results in yield reduction of 37%, 46%, and 73%, respectively. Model applications show that for a 15 July transplanting date, average potential yield under low water stress during both flowering and maturing stages is 6077 kg ha–1. However, the loss of potential yields are 39%, 57%, and 70% for this transplanting date, due to high water stress during maturing, flowering, and both flowering and maturing stages, respectively. For a 15 August transplanting, average potential yield is 4217 kg ha–1 and loss is 32%, 38%, and 38% for high water stress during maturing, flowering, and both flowering and maturing stages, respectively. The results of this study can be further utilized for future agricultural planning in Bangladesh and other parts of monsoonal Asia

The CERES-Rice Model-Based Estimates of Potential Monsoon Season Rainfed Rice Productivity in Bangladesh

Agricultural practices in Bangladesh are largely dependent on the monsoonal rainfall. Historically, Bangladesh often experiences severe droughts and floods during the monsoon months, with significant crop losses during both extreme conditions. This article provides a quantitative assessment of potential monsoon-season aman rice for four transplanting dates: 1 June, 1 July, 15 July, and 15 August. A crop-growth simulation model, the CERES-Rice, is applied to sixteen locations representing major rice-growing regions of Bangladesh to determine baseline yield estimates for four transplanting dates. The applications were conducted for 1975 through 1987. Average potential yield in Bangladesh is 6,907, 5,039, 3,637, and 1,762 kg ha–1 for the above transplanting dates, respectively. In other words, Bangladesh would obtain 27 percent, 48 percent, and 75 percent less yield for 1 July, 15 July, and 15 August transplanting, respectively, than for 1 June transplanting. Potential yield vulnerability is the least for 1 June transplanting (up to 5 percent) and the highest (up to 66 percent) for 15 July transplanting date. The model applications show that regional variations exist for potential yield and yield vulnerability for a particular transplanting date. In addition, response of yield and vulnerability for a region changes with transplanting dates

Phenoseasonal subcanopy light dynamics and the effects of light on the physiological ecology of a common understory shrub, Lindera benzoin.

The purpose of this work was to quantify the variation of subcanopy spatiotemporal light dynamics over the course of a year and to link it to the physiological ecology of the understory shrub, Lindera benzoin L. Blume (northern spicebush). Covering all seven phenoseasons of a deciduous forest, this work utilized a line quantum sensor to measure the variation in subcanopy light levels under all sky conditions at different times of the day. A total of 4,592 individual subcanopy measurements of photosynthetic photon flux density (PPFD, μmol m-2 s-1) were taken as 15-second spatially-integrated one-meter linear averages to better understand the dynamism of light exposure to L. benzoin. Both open (n = 2, one continuous and one instantaneous) and subcanopy location (n = 25) measurements of PPFD were taken on each sampling date in and near the forested plot (Maryland, USA). In addition, we explored the effect of four photointensity-photoperiod combinations on the growth of L. benzoin under controlled conditions to compare to field conditions. On average, understory PPFD was less than 2% of open PPFD during the leafed months and an average of 38.8% of open PPFD during leafless winter months, indicating that: (1) often overlooked woody surfaces intercept large amounts of light; and (2) spicebush within the plot receive limited light even in early spring before canopy leaf-out. Statistical results suggested phenoseason accounted for nearly three-quarters of the variation in incident radiation between the three plant canopy heights. Spicebush under controlled conditions exhibited the highest fitness levels at an intensity of 164.5 μmol m-2 s-1 for 12-hour duration. Similarly, spicebush growth in the field occurred at subcanopy locations receiving higher incidence of PPFD (i.e., >128 μmol m-2 s-1). Results suggest that the ecological niche for these plants is very specific in terms of light intensity

Northern Hemisphere Snow-Cover Trends (1967–2018): A Comparison between Climate Models and Observations

Observed changes in Northern Hemisphere snow cover from satellite records were compared to those predicted by all available Coupled Model Intercomparison Project Phase 5 (“CMIP5”) climate models over the duration of the satellite’s records, i.e., 1967–2018. A total of 196 climate model runs were analyzed (taken from 24 climate models). Separate analyses were conducted for the annual averages and for each of the seasons (winter, spring, summer, and autumn/fall). A longer record (1922–2018) for the spring season which combines ground-based measurements with satellite measurements was also compared to the model outputs. The climate models were found to poorly explain the observed trends. While the models suggest snow cover should have steadily decreased for all four seasons, only spring and summer exhibited a long-term decrease, and the pattern of the observed decreases for these seasons was quite different from the modelled predictions. Moreover, the observed trends for autumn and winter suggest a long-term increase, although these trends were not statistically significant. Possible explanations for the poor performance of the climate models are discussed