Effects Of Precipitation Variability Research Articles

Effects of precipitation variability and conservation tillage on soil moisture, yield and quality of silage maize

To cope with the change of precipitation pattern, we explored the effects of conservation tillage and precipitation variability on soil moisture status and silage maize productivity, seeking solutions to improve the yield and quality of maize in the karst areas of China. In this study, precipitation variability and conservation tillage were jointly analyzed by precipitation levels (normal precipitation, 30% lower and 30% greater than normal precipitation), tillage methods (conventional tillage and no-tillage) and cover crop mulching (mulching and no mulching). It was found that no tillage (NT) increased the maize yield by 12.85% compared with the conventional tillage (CT) treatments. Above-normal precipitation treatments did not significantly increase biomass and soil water content across different fertility stages, but below-normal precipitation treatments reduced maize yield, crude protein (CP) content and soil water content at all soil levels. CT treatment significantly increased soil water content in the tillage layer (0–40 cm), but NT treatment significantly increased dry matter yield, plant height and CP content at harvest by 10.99, 3.41, 5.62%. Cover crop mulching significantly increased maize yield by 8.26% and soil moisture content at the seedling stage in 0–40 cm soil by 2.76 and 2.52%. The three-way interaction effects involving precipitation levels, tillage methods and cover crop mulching were significant for maize yield, CP content and soil water content (p < 0.05). In addition, this study found that soil water content was positively correlated with crude protein content of maize (p < 0.05). In conclusion, this study concluded that a combination of NT and cover crop mulching should be used to mitigate maize production risks caused by precipitation variability in the karst areas.

Response of soil organic carbon decomposition to intensified water variability co-determined by the microbial community and aggregate changes in a temperate grassland soil of northern China

The effect of precipitation variability on soil organic carbon (SOC) decomposition is vital in regulating the global carbon (C) cycle and climate change. However, the response of SOC decomposition to different magnitudes of precipitation variability and its dependence on moisture level are still controversial. In this study, we conducted a three-month incubation experiment that manipulated soil water levels and the intensity of water variability with a homogenized topsoil from a temperate grassland. Results showed that intensified water variability significantly reduced CO2 emissions at the low-water level, but did not affect the SOC decomposition at the high-water level. Meanwhile, the microbial community was significantly altered by the intensified water variability, showing a decrease in microbial biomass and increases in the fungi: bacterial ratio and Gram-positive: Gram-negative bacteria ratio, which tended to suppress the SOC decomposition. However, the intensified water variability significantly stimulated the breakdown of macro-aggregates to micro-aggregates at the high-water level, which promoted the substrate availability in soil and compensated for the suppressed SOC decomposition by microbial community responses. The findings highlight that the response of SOC decomposition to intensified water variability is co-determined by the microbial community responses and aggregate instabilities.

The effects of precipitation variability on the canopy cover of forage species in arid rangelands, Iran

This research was conducted to monitor changes in canopy cover of typical species during a 10-year period in the part of arid rangelands, to find out the relationship between two important climate variables (precipitation and temperature) and canopy cover changes. For that reason, canopy cover percentages of six dominant perennials and all annual plant species combined were measured during a 10-year period at phenological maturity of plant in thirty 2 m × 2 m plots which were placed along two 250-m transect lines. The results demonstrated that the maximum canopy cover for water year 2006–2007 (wet year) and the minimum value for water year 2012–2013 (drought) were 15 and 5.5%, respectively. The canopy cover was modeled by linear regression in which precipitation and temperature variables were considered independent variables. April precipitation explained 65% of changes in the canopy cover percentage of Artemisia sieberi at 95% confidence level (RRMSE = 0.26 and MAE = 0.49). The best simple linear regression models for estimating canopy cover percentages of Stipa barbata and Zygophyllum eurypterum corresponded to cumulative 4-month precipitation from March to June and March precipitation respectively, representing 77% (at 99% confidence level) and 67% (at 95% confidence level) of changes correspondingly. Considering the dominance of A. sieberi, S. barbata, and Z. eurypterum in floristic composition of the study area, it can be concluded that most changes in canopy cover of the studied rangeland are predicted by variability of precipitation during growing seasons.

Assessing the effects of grazing on variations of vegetation NPP in the Xilingol Grassland, China, using a grazing pressure index

The objective of this study was to map and discriminate variations of vegetation net primary production (NPP) from the effects of precipitation variability and thereby identify the effects of grazing on NPP variations in the Xilingol Grassland. Satellite-based simulations of NPP collected over 14-year period and residuals method were used to normalize the effects of interannual precipitation on NPP. A fixed-size moving-window method was developed in this paper to quantify the annual grazing pressure (defined as grazing pressure index, GPI) on the regional scale, using vegetation cover images from 2001 to 2014. Temporal and spatial analysis methods were conducted to show patterns and trends of GPI and NPP residuals (NPPres), and further to examine the effects of grazing pressure changes on variations of NPPres. Our results showed 80.7% of the study area experienced increasing NPPres and 18.5% with significantly increasing trends (p < 0.05). 76.7% of the study area showed decreasing grazing pressure, and 11.8% of areas experienced significantly decreasing trends (p < 0.05), with a small patches scattered distribution pattern. The negative correlations between NPPres and GPI were found in 94.6% of the study area, and 41.9% with significant correlation (p < 0.05); and long-term decreasing grazing pressure had positive impacts on vegetation NPP. They indicate grazing is a main driving factor of variations in vegetation NPP other than precipitation in Xilingol Grassland. The spatial patterns and temporal trends of NPPres, grazing pressure and responses of NPPres to grazing pressure changes varied among three main grassland types.

The response of sub‐Mediterranean grasslands to rainfall variation is influenced by early season precipitation

AbstractQuestionClimate change will likely modify patterns of precipitation, with an expected increase in intra‐annual variability and increased frequency and magnitude of extreme events. The Mediterranean area is expected to be very sensitive to such events because water availability is already limited. However, the effect of precipitation variability on ecosystem services, such as plant productivity, is little known. What is the short‐term effect of an experimental precipitation gradient on above‐ground net primary productivity (ANPP) of two contrasting sub‐Mediterranean grassland ecosystems? How does early season precipitation, i.e. dry or wet spring, influence ANPP? Do the functional groups of grasses and forbs differ in their response?LocationTorricchio Nature Reserve, Central Apennines, Italy.MethodsWe selected two grasslands characterized by contrasting geophysical and soil chemical parameters (north‐ and south‐facing slopes). In both sites, during two climatically different years, mid‐season (summer) precipitation was manipulated in order to obtain a gradient of rainfall availability, comprising additional rainfall, ambient rainfall conditions and rainfall reduction. The above‐ground biomass, subdivided according to the functional groups of forbs and grasses, was collected at the end of each treatment period.ResultsA significant increase in ANPP due to experimental increase in summer rainfall appeared in the year with the wet spring, but only in the mesic north‐facing slope. This response was driven by the increased productivity of perennial forbs, while grasses showed stable above‐ground production. In contrast, in the year with the dry spring, ANPP did not respond to the experimental rainfall gradient, meaning that a dry spring leads to lower ANPP even under increased summer rainfall. The variability of ANPP increased significantly in the xeric south‐facing slope in the year with the wet spring, most likely reflecting indirect effects of small‐scale heterogeneity such as variations in soil depth.ConclusionsIntra‐annual precipitation variation can have noticeable implications for sub‐Mediterranean montane grassland agriculture: to avoid degradation due to overgrazing, livestock pressure should be limited in years with a spring drought, regardless of summer precipitation, especially in mesic grasslands.

Enhanced precipitation variability effects on water losses and ecosystem functioning: differential response of arid and mesic regions

Climate change will result in increased precipitation variability with more extreme events reflected in more frequent droughts as well as more frequent extremely wet conditions. The increase in precipitation variability will occur at different temporal scales from intra to inter-annual and even longer scales. At the intra-annual scale, extreme precipitation events will be interspersed with prolonged periods in between events. At the inter-annual scale, dry years or multi-year droughts will be combined with wet years or multi-year wet conditions. Consequences of this aspect of climate change for the functioning ecosystems and their ability to provide ecosystem services have been underexplored. We used a process-based ecosystem model to simulate water losses and soil-water availability at 35 grassland locations in the central US under 4 levels of precipitation variability (control, +25, +50+75 %) and six temporal scales ranging from intra- to multi-annual variability. We show that the scale of temporal variability had a larger effect on soil-water availability than the magnitude of variability, and that inter- and multi-annual variability had much larger effects than intra- annual variability. Further, the effect of precipitation variability was modulated by mean annual precipitation. Arid-semiarid locations receiving less than about 380 mm yr �1 mean annual precipitation showed increases in water availability as a result of enhanced precipitation variability while more mesic locations (>380 mm yr �1 ) showed a decrease in soil water

Effects of precipitation variability on carbon and water fluxes in the understorey of a nitrogen-limited montado ecosystem.

To date the implications of greater intra-annual variability and extremes in precipitation on ecosystem functioning have received little attention. This study presents results on soil and vegetation carbon and water fluxes in the understorey of a Mediterranean oak woodland in response to increasing precipitation variability, with an extension of the dry period between precipitation events from 3 to 6 weeks, without altering total annual precipitation inputs. With prolonged dry periods soil moisture did breach the stress thresholds for ecosystem processes, which led to short-term treatment differences in photosynthesis, but not in system carbon losses, with subsequent short-term decreases in net ecosystem exchange. Independent of treatment, irrigation events rapidly increased carbon and water fluxes. However, contradicting the predictions drawn from the 'bucket model', over the course of the growing season no all-over treatment differences were found in system assimilation and respiration, nor in evapotranspiration and ecosystem water use efficiency. This lack of responsiveness is attributed to the ecosystem's resilience to low soil moisture during the growing season of the herbaceous understorey, with temperature rather than soil moisture controlling key ecosystem processes. Moreover, severe nitrogen limitation of the studied ecosystem may explain the lack of moisture effects on net system carbon dynamics. Thus, although the bucket model predicts changes in soil water dynamics with increasing precipitation variability, ecosystem responses to more extreme precipitation regimes may be influenced by additional factors, such as inter-annual variability in nutrient availability.

Water stress due to increased intra-annual precipitation variability reduced forage yield but raised forage quality of a temperate grassland

Due to climate change an increase in the intra-annual precipitation variability including extreme drought and heavy rainfall events is predicted to impact major ecosystem processes. Evidence suggests that crop and forage production will be affected by altered climate variability. Due to the growing human population and rising demand for high quality animal feed it is necessary to determine the consequence of increased precipitation variability on forage yield and quality in order to adapt or implement compensation strategies against possible negative effects.Here, we present data from a field experiment in which a temperate European grassland was subjected to altered intra-annual precipitation variability (low, medium, high) in interaction with management strategies namely fertilization and alteration of harvest date (delay by 10 days). We measured forage yield and root length, quantified parameters of forage quality (crude protein, crude fiber, crude ash, crude fat, sugar, neutral detergent fiber (NDF), acid detergent fiber (ADF), in vitro gas production) and estimated relative feed value, net energy for lactation and metabolizable energy. Additionally, we tested the influence of seasonality of extreme weather events on the responsiveness of forage yield and quality to management strategies.Increased intra-annual precipitation variability decreased forage yield of the grassland. Furthermore, the proportion of functional groups was altered toward less grass and more forb biomass with amplified precipitation variability. Increased crude protein content and reduced fiber content (crude fiber, NDF, ADF) with increasing precipitation variability improved the relative feed values. Crude protein content was enhanced by fertilization during drought but reduced by delayed harvest after the drought period. Fertilization reduced losses in grassland annual yield caused by extreme precipitation. Management strategies proved less effective if precipitation variability occurred later in the season than earlier in the season.A nitrogen dilution effect (decreased plant nitrogen concentration with increasing shoot biomass) likely influenced the grassland crude protein contents under altered precipitation regimes and might have masked possible effects of precipitation variability on plant nitrogen and therefore on quality of grassland species. Nevertheless, alterations in the plant community composition and plant senescence seem to be the main drivers of forage quality change. Fertilization during drought periods and harvest delay after drought periods were only partially successful as management strategies to sustain forage production in more extreme precipitation regimes of the future. Further strategies need to be developed that acknowledge the shift in plant species compositions as the main driver of changes in forage quality in the face of changing precipitation patterns.

Effect of precipitation variability on net primary production and soil respiration in a Chihuahuan Desert grassland

Precipitation regimes are predicted to become more variable with more extreme rainfall events punctuated by longer intervening dry periods. Water-limited ecosystems are likely to be highly responsive to altered precipitation regimes. The bucket model predicts that increased precipitation variability will reduce soil moisture stress and increase primary productivity and soil respiration in aridland ecosystems. To test this hypothesis, we experimentally altered the size and frequency of precipitation events during the summer monsoon (July through September) in 2007 and 2008 in a northern Chihuahuan Desert grassland in central New Mexico, USA. Treatments included (1) ambient rain, (2) ambient rain plus one 20mm rain event each month, and (3) ambient rain plus four 5mm rain events each month. Throughout two monsoon seasons, we measured soil temperature, soil moisture content (y), soil respiration (Rs), along with leaf-level photosynthesis (Anet), predawn leaf water potential (Cpd), and seasonal aboveground net primary productivity (ANPP) of the dominant C4 grass, Bouteloua eriopoda. Treatment plots receiving a single large rainfall event each month maintained significantly higher seasonal soil y which corresponded with a significant increase in Rs and ANPP of B. eriopoda when compared with plots receiving multiple small events. Because the strength of these patterns differed between years, we propose a modification of the bucket model in which both the mean and variance of soil water change as a consequence of interannual variability from 1 year to the next. Our results demonstrate that aridland ecosystems are highly sensitive to increased precipitation variability, and that more extreme precipitation events will likely have a positive impact on some aridland ecosystem processes important for the carbon cycle.

Assessing rangeland degradation using multi temporal satellite images and grazing pressure surface model in Upper Mustang, Trans Himalaya, Nepal

This study aims to map and discriminate rangeland degradation from the effects of precipitation variability and thereby identify the driving forces of degradation in the grazing areas of Ghiling in Upper Mustang, Nepal. Landsat MSS, TM, ETM, and SPOT images covering the years 1976–2008 were analyzed. 8 km resolution NOAA NDVI from 1981to 2006 were used to identify the long term interrelationship between vegetation greenness and precipitation variability. The use of time series residual of the NDVI/precipitation linear regression to normalize the precipitation effect on vegetation productivity and identify the long term degradation was extended at the local scale. A weighted grazing pressure surface model was developed combining information from satellite images, topography, forage availability and detailed field work data on points of livestock concentration, herders' ranking of forage quality and grazing pattern in each pasture unit. The grazing pressure of a given site was defined as the product of annual net stocking density and the inverse of the total friction of livestock movement. While annual precipitation was found as the dominant factor for the interannual vegetation variability, degradation in Upper Mustang was the result of grazing induced change and some localized natural processes.

The effect of precipitation variability on ENSO/precipitation teleconnections in the contiguous United States

An investigation of the spatiotemporal tendencies of the parameters of the probability density function describing precipitation in the last century in the contiguous United States reveals the existence of statistically significant local trends in both space and time. In such a case the distribution describing precipitation at a site is not constant in time, meaning that the population characteristics have not remained the same throughout the century. Here we show that when this variability is taken into account, it alters the effect of El Niño‐Southern Oscillation (ENSO) on precipitation significantly and may often lead to erroneous predictions of ENSO‐related precipitation patterns.

Effect of Precipitation Variability on Pollutant Concentrations in Soil: Implications for Exposure and Risk Assessments

Concentrations of toxic pollutants in surface soils must be predicted in order to assess exposures and risks that may arise from emissions at incinerators and other air pollution sources. At present, concentrations are predicted using deterministic models and time-averaged values of input parameters. This steady-state equilibrium approach does not address variability in the underlying transport and fate processes. This paper explores the variability of pollutant concentrations in surface soils that arises from precipitation, an intermittent process that governs wet deposition and leaching processes. Using long-term (45 to 50 years) historical records at 6 climato-logically diverse sites, concentrations predicted using the steady-state approach are compared to those predicted using a dynamic numerical model that simulates dry and wet deposition, leaching, and pollutant accumulation in the surface layer of soil using a daily time step. The models are compared for pollutants of low, medium, and high water solubility. Both models show that predictions depend strongly on the pollutant solubility and the precipitation pattern at the location. Average concentrations differed between locations by a factor of up to 4 due to precipitation patterns; the solubility of the pollutant had a much more pronounced effect. Both models produced similar long-term trends, for example, the duration of the period needed to achieve a quasi-steady-state pollutant concentration. However, for soluble pollutants, the dynamic model produced maximum 24-hr average concentrations that exceeded long-term averages by 4 to 8 times, and long-term predictions of the dynamic model exceeded predictions of the steady-state model by 1.9 to 3.6 times (depending on the site). These differences are caused by the steady-state assumption that deposition and leaching occur continuously. While the steady-state model can be used to estimate long-term trends of moderately to highly insoluble pollutants, the dynamic model should be used to predict short-term, maximum concentrations and both short- and long-term averages of soluble pollutants. Site-specific exposure and risk assessments should consider temporal variation and the use of a dynamic model if concentrations of soluble pollutants approach risk-based target levels.

The effect of precipitation variability on drainage basin morphometry

The effect of precipitation variability on drainage basin morphometry