Adapting to the projected epidemics of Fusarium head blight of wheat in Korea under climate change scenarios.

Fusarium head blight (FHB) of wheat, mainly caused by Fusarium graminearum Schwabe, is an emerging threat to wheat production in Korea under a changing climate. The disease occurrence and accumulation of associated trichothecene mycotoxins in wheat kernels strongly coincide with warm and wet environments during flowering. Recently, the International Panel for Climate Change released the 6th Coupled Model Intercomparison Project (CMIP6) climate change scenarios with shared socioeconomic pathways (SSPs). In this study, we adopted GIBSIM, an existing mechanistic model developed in Brazil to estimate the risk infection index of wheat FHB, to simulate the potential FHB epidemics in Korea using the SSP245 and SSP585 scenarios of CMIP6. The GIBSIM model simulates FHB infection risk from airborne inoculum density and infection frequency using temperature, precipitation, and relative humidity during the flowering period. First, wheat heading dates, during which GIBSIM runs, were predicted over suitable areas of winter wheat cultivation using a crop development rate model for wheat phenology and downscaled SSP scenarios. Second, an integrated model combining all results of wheat suitability, heading dates, and FHB infection risks from the SSP scenarios showed a gradual increase in FHB epidemics towards 2100, with different temporal and spatial patterns of varying magnitudes depending on the scenarios. These results indicate that proactive management strategies need to be seriously considered in the near future to minimize the potential impacts of the FHB epidemic under climate change in Korea. Therefore, available wheat cultivars with early or late heading dates were used in the model simulations as a realistic adaptation measure. As a result, wheat cultivars with early heading dates showed significant decreases in FHB epidemics in future periods, emphasizing the importance of effective adaptation measures against the projected increase in FHB epidemics in Korea under climate change.

Comparison of projected rice blast epidemics in the Korean Peninsula between the CMIP5 and CMIP6 scenarios.

Recently, the International Panel for Climate Change released the 6th Coupled Model Intercomparison Project (CMIP6) climate change scenarios with shared socioeconomic pathways (SSPs). The SSP scenarios result in significant changes to climate variables in climate projections compared to their predecessor, the representative concentration pathways from the CMIP5. Therefore, it is necessary to examine whether the CMIP6 scenarios differentially impact plant-disease ecosystems compared to the CMIP5 scenarios. In this study, we used the EPIRICE-LB model to simulate and compare projected rice blast disease epidemics in the Korean Peninsula using five selected family global climate models (GCMs) of the CMIP5 and CMIP6 for two forcing scenarios. We found a similar decrease in rice blast epidemics in both CMIP scenarios; however, this decrease was greater in the CMIP6 scenarios. In addition, distinctive epidemic trends were found in North Korea, where the rice blast epidemics increase until the mid-2040s but decrease thereafter until 2100, with different spatial patterns of varying magnitudes. Controlling devastating rice blast diseases will remain important during the next decades in North Korea, where appropriate chemical controls are unavailable due to chronic economic and political issues. Overall, our analyses using the new CMIP6 scenarios reemphasized the importance of developing effective control measures against rice blast for specific high-risk areas and the need for a universal impact and vulnerability assessment platform for plant-disease ecosystems that can be used with new climate change scenarios in the future. Supplementary information: The online version contains supplementary material available at 10.1007/s10584-022-03410-2.

Uncertainty in hydrological analysis of climate change: multi-parameter vs. multi-GCM ensemble predictions.

The quantification of uncertainty in the ensemble-based predictions of climate change and the corresponding hydrological impact is necessary for the development of robust climate adaptation plans. Although the equifinality of hydrological modeling has been discussed for a long time, its influence on the hydrological analysis of climate change has not been studied enough to provide a definite idea about the relative contributions of uncertainty contained in both multiple general circulation models (GCMs) and multi-parameter ensembles to hydrological projections. This study demonstrated that the impact of multi-GCM ensemble uncertainty on direct runoff projections for headwater watersheds could be an order of magnitude larger than that of multi-parameter ensemble uncertainty. The finding suggests that the selection of appropriate GCMs should be much more emphasized than that of a parameter set among behavioral ones. When projecting soil moisture and groundwater, on the other hand, the hydrological modeling equifinality was more influential than the multi-GCM ensemble uncertainty. Overall, the uncertainty of GCM projections was dominant for relatively rapid hydrological components while the uncertainty of hydrological model parameterization was more significant for slow components. In addition, uncertainty in hydrological projections was much more closely associated with uncertainty in the ensemble projections of precipitation than temperature, indicating a need to pay closer attention to precipitation data for improved modeling reliability. Uncertainty in hydrological component ensemble projections showed unique responses to uncertainty in the precipitation and temperature ensembles.

Model for prioritizing best management practice implementation: sediment load reduction.

Understanding the best way to allocate limited resources is a constant challenge for water quality improvement efforts. The synoptic approach is a tool for geographic prioritization of these efforts. It uses a benefit-cost framework to calculate indices for functional criteria in subunits (watersheds, counties) of a region and then rank the subunits. The synoptic approach was specifically designed to incorporate best professional judgment in cases where information and resources are limited. To date, the synoptic approach has been applied primarily to local or regional wetland restoration prioritization projects. The goal of this work was to develop a synoptic model for prioritizing watersheds within which suites of agricultural best management practices (BMPs) can be implemented to reduce sediment load at the watershed outlets. The model ranks candidate watersheds within an ecoregion or river basin so that BMP implementation within the highest ranked watersheds will result in the most sediment load reduction per conservation dollar invested. The model can be applied anywhere and at many scales provided that the selected suite of BMPs is appropriate for the evaluation area's biophysical and climatic conditions. The model was specifically developed as a tool for prioritizing BMP implementation efforts in ecoregions containing watersheds associated with the USDA-NRCS conservation effects assessment project (CEAP). This paper presents the testing of the model in the little river experimental watershed (LREW) which is located near Tifton, Georgia, USA and is the CEAP watershed representing the southeastern coastal plain. The application of the model to the LREW demonstrated that the model represents the physical drivers of erosion and sediment loading well. The application also showed that the model is quite responsive to social and economic drivers and is, therefore, best applied at a scale large enough to ensure differences in social and economic drivers across the candidate watersheds. The prioritization model will be used for planning purposes. Its results are visualized as maps which enable resource managers to identify watersheds within which BMP implementation would result in the most water quality improvement per conservation dollar invested.

Micron and submicron patterning of dicyanopyrazine-linked porphyrin molecules using micro-contact printing and Langmuir-Blodgett assembly.

We describe a method to conveniently fabricate micron- and submicron-sized patterns of well-ordered and densely-packed dicyanopyrazine-linked porphyrin (4-TDCPP) molecules by using micro-contact printing (micro-CP) in conjunction with Langmuir-Blodgett (LB) deposition. SEM and AFM images reveal that the sizes and shapes of the 4-TDCPP patterns are well-matched with the geometric features of the polydimethylsiloxane (PDMS) stamps used for micro-CP. Fluorescence images show strong, red emission from the 4-TDCPP patterns. However, the thicknesses of the 4-TDCPP patterns transferred onto a silicon substrate by micro-CP are not the same, even though the same amount of 4-TDCPP layers are deposited on the surface of PDMS stamps in the LB process. The thicknesses of the 10 microm line, 2 microm dot and 300 nm line patterns of 10-layered 4-TDCPP molecules are 34.6, 26.7 and 5.9 nm, respectively. These differences may be due to variations in adhesion forces between the silicon substrate and 4-TDCPP on PDMS stamps having different size patterns. Larger patterns have greater contact areas compared to smaller patterns. This phenomenon can cause stronger adhesion forces, resulting in greater pattern thickness.

Simulating fecal coliform bacteria loading from an urbanizing watershed.

The fate and transport of fecal coliform bacteria in the urbanizing Polecat Creek watershed, located in Virginia, was simulated using the Hydrological Simulation Program-FORTRAN (HSPF). Both point and nonpoint sources of fecal coliform were included in the simulation. Hydrologic and water quality parameters of HSPF were calibrated and validated using observed data collected from October 1994 to June 2000 at three monitoring stations. The percent errors in total runoff volumes between observed and simulated values ranged from 0.4 to 4.2% for the calibration period, and 0.4 to 6.7% for the validation period. The geometric mean of simulated fecal coliform concentrations at the outlet of the watershed was 10% lower than that of observed values for the calibration period. HSPF moderately under-predicted the geometric mean concentration by 16.4% for one sub-watershed and slightly over-predicted by 7.3% for another. Observed fecal coliform concentrations were compared with the range defined by the minimum and maximum simulated concentrations occurring within a 3-day window centered on the day the water sample was collected. Over 42% of grab sample data collected at the three monitoring sites in the watershed fell within the max min range of simulated concentrations over the 3-days window for the calibration period. For all monitoring sites, 39.5% of the total samples taken during the validation period fell in the range of simulated concentrations over the 3-day window period. Results presented in this study demonstrate that HSPF reasonably represents the hydrology and water quality of an urbanizin watershed and that it could be utilized as a planning tool for future assessment of land use impacts on fecal coliform on in-stream concentrations.