Browsing by Subject "soil texture"
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Item Crop yield and soil organic carbon under ridge–furrow cultivation in China: A meta-analysis(Wiley, 2021-06) Wang, Yunqi; Gao, Fuli; Wang, Lixin; Guo, Tongji; Qi, Liuran; Zeng, Huanyu; Liang, Yuexin; Zhang, Kai; Jia, Zhikuan; Zhang, Rui; Earth Sciences, School of ScienceRidge–furrow cultivation (RF) is a popular emerging technique that can increase crop productivity in dry areas. However, the efficacy of RF on crop yield and soil organic carbon (SOC) remains uncertain under different climate and management conditions. Here, we compiled data from 48 publications to evaluate the response of yield and SOC to RF in China. Overall, our meta-analysis showed that RF increased yield by 30.2%, but it had no effects on SOC. When differentiated based on different categories, yield and SOC varied by crop species, climate, soil textures, mulching management, and ridge–furrow patterns. RF increased the yield of wheat, maize, soybean, rape, linseed, potato, and SOC under soybean cultivation. Yield increase with RF was also consistent across temperature and precipitation. Yield increase was observed in all the soil textures. There were no RF effects on SOC under different soil textures. RF enhanced yields under no mulching, straw mulching and plastic film mulching, but increased SOC only in combination with straw mulching. A higher yield increase was observed under alternating small and large ridges (ASLR) than alternating ridges and furrows (AR). RF decreased SOC by 11.7% under AR, but had no effects on SOC under ASLR. Together, ASLR with straw mulching could increase yield and SOC in coarse soil texture regions with annual mean temperature >10°C and annual mean precipitation > 400 mm. This study showed the importance of considering local environmental conditions with management practices in identifying appropriate RF practices for improving crop productivity and soil carbon sequestration.Item Global synthesis of vegetation control on evapotranspiration partitioning(2014-10) Wang, Lixin; Good, Stephen P.; Caylor, Kelly K.Evapotranspiration (ET) is an important component of the global hydrological cycle. However, to what extent transpiration ratios (T/ET) are controlled by vegetation and the mechanisms of global-scale T/ET variations are not clear. We synthesized all the published papers that measured at least two of the three components (E, T, and ET) and leaf area index (LAI) simultaneously. Nonlinear relationships between T/ET and LAI were identified for both the overall data set and agricultural or natural data subsets. Large variations in T/ET occurred across all LAI ranges with wider variability at lower LAI. For a given LAI, higher T/ET was observed during later vegetation growing stage within a season. We developed a function relating T/ET to the growing stage relative to the timing of peak LAI. LAI and growing stage collectively explained 43% of the variations in the global T/ET data set, providing a new way to interpret and model global T/ET variability.Item Meta-analysis of ridge-furrow cultivation effects on maize production and water use efficiency(Elsevier, 2020-05) Wang, Yunqi; Guo, Tongji; Qi, Liuran; Zeng, Huanyu; Liang, Yuexin; Wei, Shikun; Gao, Fuli; Wang, Lixin; Zhang, Rui; Jia, Zhikuan; Earth Sciences, School of ScienceRidge-furrow cultivation (RF) is a popular dryland agricultural technique in China, but its effects on maize yield, total water consumption during crop growing stage (ET), and water use efficiency (WUE) have not been systematically analyzed. Here we conducted a meta-analysis of the RF effects on maize yield, ET and WUE based on the data collected from peer-reviewed literature. Yield, ET and WUE varied with climate, soil and mulching management. Averaged across all the geographic locations, RF increased the yield and WUE of maize by 47 % and 39 %, respectively, but no effects on ET. An increase in the yield and WUE occurred under RF in regions regardless of the mean growing season air temperature (MT) or a mean precipitation during the growing season (MP), although there was a trend that RF is more beneficial under low MP. RF also decreased ET in regions with MT>12 °C. RF increased the yield and WUE in regions with medium or fine soil texture. RF increased the yield, ET, and WUE in regions with low soil bulk density (BD) (≤1.3 g cm−3). But in areas where BD is larger than 1.3 g cm−3, RF only increased the yield and WUE. RF increased the yield and WUE with or without mulching, but decreased ET when no mulching was used. Together, optimizing RF effects on the yield, ET and WUE in maize was largely dependent on environmental conditions and management practices.Item Vulnerability of tropical forest ecosystems and forest dependent communities to droughts(Elsevier, 2016-01) Vogt, D. J.; Vogt, K. A.; Gmur, S. J.; Scullion, J. J.; Suntana, A. S.; Daryanto, Stefani; Sigurðardóttir, R.; Department of Earth Sciences, School of ScienceEnergy captured by and flowing through a forest ecosystem can be indexed by its total Net Primary Productivity (NPP). This forest NPP can also be a reflection of its sensitivity to, and its ability to adapt to, any climate change while also being harvested by humans. However detecting and identifying the vulnerability of forest and human ecosystems to climate change requires information on whether these coupled social and ecological systems are able to maintain functionality while responding to environmental variability. To better understand what parameters might be representative of environmental variability, we compiled a metadata analysis of 96 tropical forest sites. We found that three soil textural classes (i.e., sand, sandy loam and clay) had significant but different relationships between NPP and precipitation levels. Therefore, assessing the vulnerability of forests and forest dependent communities to drought was carried out using data from those sites that had one of those three soil textural classes. For example, forests growing on soil textures of sand and clay had NPP levels decreasing as precipitation levels increased, in contrast to those forest sites that had sandy loam soils where NPP levels increased. Also, forests growing on sandy loam soil textures appeared better adapted to grow at lower precipitation levels compared to the sand and clay textured soils. In fact in our tropical database the lowest precipitation level found for the sandy loam soils was 821 mm yr−1 compared to sand at 1739 mm yr−1 and clay at 1771 mm yr−1. Soil texture also determined the level of NPP reached by a forest, i.e., forest growing on sandy loam and clay reached low-medium NPP levels while higher NPP levels (i.e., medium, high) were found on sand-textured soils. Intermediate precipitation levels (>1800–3000 mm yr−1) were needed to grow forests at the medium and high NPP levels. Low thresholds of NPP were identified at both low (∼750 mm) and high precipitation (>3500 mm) levels. By combining data on the ratios of precipitation to the amount of biomass produced in a year with how much less precipitation input occurs during a drought year, it is possible to estimate whether productivity levels are sufficient to support forest growth and forest dependent communities following a drought. In this study, the ratios of annual precipitation inputs required to produce 1 Mg ha−1 yr−1 biomass by soil texture class varied across the three soil textural classes. By using a conservative estimate of 20% of productivity collected or harvested by people and 30% precipitation reduction level as triggering a drought, it was possible to estimate a potential loss of annual productivity due to a drought. In this study, the total NPP unavailable due to drought and harvest by forest dependent communities per year was 10.2 Mg ha−1 yr−1 for the sandy textured soils (64% of NPP still available), 8.4 Mg ha−1 yr−1 for the sandy loam textured soils (60% available) and 12.7 Mg ha−1 yr−1 for the clay textured soils (29% available). Forests growing on clay textured soils would be most vulnerable to drought triggered reductions in productivity so NPP levels would be inadequate to maintain ecosystem functions and would potentially cause a forest-to-savanna shift. Further, these forests would not be able to provide sufficient NPP to satisfy the requirements of forest dependent communities. By predicting the productivity responses of different tropical forest ecosystems to changes in precipitation patterns coupled with edaphic data, it could be possible to spatially identify where tropical forests are most vulnerable to climate change impacts and where mitigation efforts should be concentrated.