• Rural Digital Europe
• 2017-2021close
• Open Access close
• Article close
• Agricultural and Forest Meteorology close

Abstract Biomass sorghum (Sorghum bicolor L. Moench) is a candidate bioenergy feedstock for the U.S. Midwest. Research suggests that biomass sorghum is more drought tolerant and has higher water-use-efficiency (WUE) than maize (Zea mays L.) in water-limiting environments, but most species comparisons of the seasonal evapotranspiration (total ET) and WUE have focused on irrigated systems (WUE defined as the ratio of cumulative dry biomass production (dry matter; DM) to total evapotranspiration (mm); g DM (mm H2O)−1). Since comparative data for the rain-fed Midwest are scarce, we conducted a side-by-side evaluation of the total ET and WUE of maize and biomass sorghum in central Iowa—a site within the U.S. Corn Belt. Total ET was estimated using a micrometeorological method, and aboveground plant biomass was determined using destructive hand harvests. Similar mean WUE was determined for maize (3.51 ± 0.26 g DM (mm H2O)−1) and biomass sorghum (3.47 ± 0.22 g DM (mm H2O)−1) over two non-drought growing seasons with total ET of 567 ± 26 mm and 600 ± 20 mm, respectively. Even though total ET and WUE were not statistically different between species (P > 0.1), maize had significantly greater theoretical ethanol yield (EY; L ethanol m−2) and lower ethanol water requirement (EWR; L water L ethanol−1), relative to biomass sorghum (P

Climate change and exotic pests and pathogens are causing alarming forest declines worldwide. However, we still lack a comprehensive understanding of how damage caused by exotic pests and pathogens might vary under the different scenarios of water availability imposed by a changing climate, particularly in water-limited forests as those that occupy Mediterranean areas. In this paper we aimed to experimentally analyse the interactive effects of the aggressive exotic pathogen Phytophthora cinnamomi and climate change-related reductions in soil moisture on seedling performance of the Mediterranean host Quercus suber. We conducted a full-factorial greenhouse experiment where the physiology and growth of Q. suber seedlings was measured in soils with different combinations of P. cinnamomi inoculum density (0, 30, 60 and 120 colony forming units per gram of dry soil) and soil moisture (15%, 40%, 50% and 100% soil water holding capacity) simulating different invasion and climate change scenarios. We found additive effects of P. cinnamomi and drought on Q. suber performance aboveground, although these effects were not always negative. In fact, seedlings showed a compensatory physiological response to P. cinnamomi infection by increasing their net photosynthetic rates. Our results also supported important interactive effects of pathogens and soil moisture on belowground performance. Thus, the inoculum density in the soil required to cause significant root damage in experimental seedlings decreased as soil moisture increased. From a climate change perspective, these results suggest that an average drier climate might imply sub-optimal conditions for P. cinnamomi infections allowing for a slower advance of the disease in invaded areas. However, this effect will be modulated by the also predicted more frequent extreme climatic events. A higher frequency of extreme rain events that saturate the soil might be particularly beneficial for P. cinnamomi, boosting its soil density beyond any possible response capacity of susceptible hosts. © 2019 This study was funded by the MICINN project INTERCAPA ( CGL2014-56739-R ). P.H. was supported by a FPI-MICINN grant, L.M. by an “Acción 6 UJA” fellowship (EI_RNM4_2017), O.G. by a Marie Sklodowska-Curie grant agreement ( No 661118-BioFUNC ), and I.M.P.R by a “Ramón & Cajal” contract ( RYC-2013-13937 ). 8 páginas.- 5 figuras.- 2 tablas.- 60 referencias Peer reviewed

Abstract A new open-path methane analyzer (LI-7700) was adopted to measure methane (CH4) fluxes using eddy covariance method over irrigated rice fields in Yancheng, Jiangsu Province, China, throughout the 2016 growing season. A clear seasonal variation in the daily CH4 flux was observed. The CH4 flux started to increase 3 days after the fields were flooded. The peak CH4 flux was 0.37 gC m−2 d−1 and was reached during late vegetative stage (August 2). A distinct single-peak diurnal pattern of the CH4 flux was observed during the vegetative stages. The CH4 flux started to increase after sunrise and reached the peak at approximately 14:30 in the afternoon. Similar results were not observed during the reproductive and ripening stages. The diurnal patterns of soil temperature (Tsoil) and gross ecosystem photosynthesis (GEP) were consistent with that of the CH4 flux. The partial F tests showed that soil temperature and volumetric water content (VWC) were the most important factors controlling CH4 emissions from rice fields on seasonal timescale. The friction velocity (u*) was also found related to the CH4 emissions. Good agreements between the measured and modeled CH4 fluxes were obtained (R2 = 0.82, 0.86 and 0.86) using the models with different factors over the whole season. Including ambient pressure (P) and GEP in the model did not significantly improve the performance of the model. The best agreement between the measured and modeled CH4 fluxes was achieved by running the regression separately for each growth stage (R2 = 0.90). After the daily CH4 series was gap-filled, the total amount of CH4 emitted over the whole season was 19.20 ± 3.20 gC m−2.

Abstract Recycled moisture contributed by continental evaporation and transpiration plays an important role in regulating the hydrological processes and atmospheric humidity budget in arid inland river basins. However, knowledge of moisture recycling within many large inland basins and the factors that control moisture recycling is generally lacking. Based on a three-component isotopic mixing model, we assessed the characteristics of moisture recycling in China’s semi-arid Heihe River Basin. During the active growing season, almost half of the precipitation in the upper reaches was provided by local moisture recycling, and the main contribution came from transpiration. In the middle reaches, almost half of the precipitation in the artificial oasis and the desert-oasis ecotone was also provided by local moisture recycling, and the transpiration fraction (fTr) and evaporation fraction (fEv) of the artificial oasis differed from those of the desert-oasis ecotone. In the lower reaches, less than 25% of the precipitation was provided by local moisture recycling. Mean fTr values were relatively low in the Gobi (15.0%) in the middle reaches and in the riparian forest at Ejina (25.6%) in the lower reaches. The positive correlations between fTr and both precipitation and relative humidity suggest that higher precipitation and relative humidity promote transpiration fraction, whereas higher vapor pressure deficit reduces transpiration fraction. The positive correlation between fEv and temperature and vapor pressure deficit, and the negative correlation between fEv and relative humidity indicate that higher temperature and vapor pressure deficit promotes evaporation fraction, whereas higher relative humidity reduces the evaporation fraction. Our results show that contributions of recycled moisture (especially transpiration) to local precipitation play an important role in regional water resource redistribution in the arid and semi-arid region of northwestern China.

We present results from the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI) Phase I, which aligned 14 global gridded crop models (GGCMs) and 11 climatic forcing datasets (CFDs) in order to understand how the selection of climate data affects simulated historical crop productivity of maize, wheat, rice and soybean. Results show that CFDs demonstrate mean biases and differences in the probability of extreme events, with larger uncertainty around extreme precipitation and in regions where observational data for climate and crop systems are scarce. Countries where simulations correlate highly with reported FAO national production anomalies tend to have high correlations across most CFDs, whose influence we isolate using multi-GGCM ensembles for each CFD. Correlations compare favorably with the climate signal detected in other studies, although production in many countries is not primarily climate-limited (particularly for rice). Bias-adjusted CFDs most often were among the highest model-observation correlations, although all CFDs produced the highest correlation in at least one top-producing country. Analysis of larger multi-CFD-multi-GGCM ensembles (up to 91 members) shows benefits over the use of smaller subset of models in some regions and farming systems, although bigger is not always better. Our analysis suggests that global assessments should prioritize ensembles based on multiple crop models over multiple CFDs as long as a top-performing CFD is utilized for the focus region.

Abstract Droughts pose a major risk to agricultural production. By comparing the outputs from an ecophysiological crop model (Sirius) with four drought severity indicators (DSI), a comparative assessment of the impacts of drought risk on wheat yield losses has been evaluated under current (baseline) and two future climate scenarios. The rationale was to better understand the relative merits and limitations of each approach from the perspective of quantifying agricultural drought impacts on crop productivity. Modelled yield losses were regressed against the highest correlated variant for each DSI. A cumulative distribution function of yield loss for each scenario (baseline, near and far future) was calculated as a function of the best fitting DSI (SPEI-5July) and with the equivalent outputs from the Sirius model. Comparative analysis between the two approaches highlighted large differences in estimated yield loss attributed to drought, both in terms of magnitude and direction of change, for both the baseline and future scenario. For the baseline, the average year differences were large (0.25 t ha−1 and 1.4 t ha−1 for the DSI and Sirius approaches, respectively). However, for the dry year, baseline differences were substantial (0.7 t ha−1 and 2.7 t ha−1). For the DSI approach, future yield losses increased up to 1.25 t ha−1 and 2.8 t ha−1 (for average and dry years, respectively). In contrast, the Sirius modelling showed a reduction in future average yield loss, down from a baseline 1.4 t ha−1 to 1.0 t ha−1, and a marginal reduction for a future dry year from a baseline of 2.7 t ha−1 down to 2.6 t ha−1. The comparison highlighted the risks in adopting a DSI response function approach, particularly for estimating future drought related yield losses, where changing crop calendars and the impacts of CO2 fertilisation on yield are not incorporated. The challenge lies in integrating knowledge from DSIs to understand the onset, extent and severity of an agricultural drought with ecophysiological crop modelling to understand the yield responses and water use relations with respect to changing soil moisture conditions.

Abstract The water balance of tropical dry deciduous forests is less well understood than some other forest ecosystems. To help close this knowledge gap, we separately measured the evapotranspiration from the whole ecosystem (ETW), transpiration (TR) and interception loss (IL) from overstory trees, and evapotranspiration from the understory vegetation (ETU) in a tropical dry deciduous forest in Cambodia. It was found that ETW was equivalent to 73.7% of rainfall (P) at the annual scale. In the dry season, ETW corresponded to 120.1% of P, which indicates the utilization of soil water replenished during the wet season. The sum of transpiration estimated by the thermal dissipation (TD) method with the original coefficient (TRG), IL, and ETU was smaller than ETW, except for the middle of the dry season, due to an underestimation of TRG. Although recently reported calibration coefficients can reasonably correct TRG, future calibrations of the TD method are highly recommended for the precise evaluation of single-tree-scale transpiration in tropical dry forests. The annual contribution of the understory vegetation to ETW (ETU/ETW) was 34.6%, leading to the conclusion that the understory vegetation cannot be ignored when trying to gain a comprehensive understanding of the hydrologic cycle in tropical dry forests. The seasonal variations in ETU/ETW were mainly controlled by the leaf area index (LAI) of overstory trees, resulting from the overall stability of ETW and decreasing trend of ETU with increasing LAI in the wet season, with the opposite holding true in the dry season, i.e., decreasing ETW with the decline of LAI and less variations of ETU. Thus, LAI influenced both the seasonality and the annual contribution in ETU/ETW, exerting a notable influence on hydrological cycling in this forest.

Abstract Lack of understanding of how plant diversity of different flowering functional groups mediates response patterns of community phenophases to climate change limits our ability to predict future phenology. We used reciprocal transplant experiments across four elevations (i.e., 3200, 3400, 3600 and 3800 m) on the Tibetan Plateau for three years to investigate how temperature change (i.e., warming and cooling) affects the temperature responses of plant functional diversity and community phenophases and their relationships. Our results showed that a nonlinear regression model was the best fitting model for most temperature responses of SDI and community phenophases under warming and cooling. Meanwhile, decreased diversity of early-spring flowering (ESF) and mid-summer flowering (MSF) groups under warming, and increased diversity of ESF under cooling, reduced temperature sensitivities of nearly all community phenophases. These results illustrate that changes in plant diversity should be taken into account when predicting the response pattern of temperature sensitivities of community phenophases.