Changes In Precipitation Variability Research Articles

Tropical Atlantic variability in EC-EARTH: impact of the radiative forcing

AbstractUnderstanding the impact of radiative forcing on climate variability and change in the Tropical Atlantic is crucial for different socio-economic sectors, given their substantial impacts in both local and remote regions. To properly evaluate the effect of a changing climate on the variability, the use of standard transient historical and scenario simulations requires very large ensembles. A computationally cheaper alternative implemented in this study consists of performing two 250-year-long atmosphere-ocean coupled simulations with EC-EARTH 3.3 (CMIP6 version) with fixed radiative forcing at the years 2000 and 2050, representative of present and future climate conditions, respectively. The changes in the leading modes of Tropical Atlantic variability (TAV), including the Atlantic Niño/Niña and the Subtropical North Atlantic pattern, have been assessed in three target seasons: spring (MAM), summer (JJ) and early winter (ND). While the change in sea surface temperature (SST) climatology shows homogeneous warming, the difference between future and present SST variability exhibits a distinct behaviour consistent along the seasonal cycle, with a decrease in the equatorial region and an increase at subtropical latitudes. This study explores the processes associated with the suppressed/enhanced TAV, with a particular focus on the less-explored early winter season. In agreement with previous studies, the Atlantic Meridional Overturning Circulation (AMOC) shows a weakening in strength, but the results also show an increase in variability. The AMOC-related deepening of the equatorial thermocline and the flattening linked to weakened trade winds are consistent with the suppressed SST variability of the Atlantic Niño/Niña. On the other hand, the enhanced SST variability at subtropical latitudes is mainly associated with an increase in turbulent heat flux variability, with a minor contribution of the mixed layer depth variability. Variability in turbulent heat flux is influenced primarily by latent heat flux, connected to changes in precipitation variability.

Increasing multiscale variability in extreme precipitation under global warming in the Tienshan Mountains, Central Asia

Changes in precipitation variability not only have a significant impact on water cycle processes, but also pose an additional challenge to society's climate resilience. Extreme precipitation is more severe, more abrupt, and more sensitive to temperature changes than mean-state precipitation. However, our understanding of the features of extreme precipitation variability over a broad range of temporal scales, as well as the differences between wet and dry seasons, is limited. In this study, we perform filtering on a daily (2–5 days) to an interannual (2–8 years) scale, using daily precipitation data from detrended APHRODITE and bias-corrected CMIP6 based on zero-phase Butterworth filters. We then analyze the changes in climatological extreme precipitation variability at different time scales, looking at the features along geographical gradients and in wet and dry seasons. At various warming levels, extreme precipitation variability is projected. The findings reveal that the longer the time scale, the higher the overall variability of both extreme and mean-state precipitation, with extreme precipitation showing greater variability. From daily to interannual scales, the variability of R95p increases from 142.79 mm to 875.05 mm, representing a 6.13-fold increase in volatility, but the variability in mean precipitation increases just 1.43-fold, from 2.27 mm to 3.24 mm. The variability in the eastern Tienshan Mountains (80°E ∼ 95°E) is greater than that in the western Tienshan Mountains (66°E ∼ 80°E). Furthermore, along longitudinal and latitudinal gradients, extreme precipitation variability exhibits considerable time-scale differences, with the more extreme the event, the greater the variability. R10mm variability increases from 15.28 d to 76.74 d on a daily to interannual scale. The variability increase (61.46 d) is roughly twice that for R5mm. Seasonally, the wet season is more variable than the dry. The total variability of R10mm was 4.57 days in the wet season and 1.78 days in the dry season. Compared with the reference period (1976–2005), there is an overall increase in extreme precipitation variability at different warming levels, along with an increasing sensitivity to temperature. With the exception of consecutive dry days, the degree of response of filtered extreme precipitation variability to temperature (absolute value of response rate) shows obvious increases with time scale and accounts for a greater proportion of the total variability response rate.

Soil and vegetation water content identify the main terrestrial ecosystem changes.

Environmental change is a consequence of many interrelated factors. How vegetation responds to natural and human activity still needs to be well established, quantified and understood. Recent satellite missions providing hydrologic and ecological indicators enable better monitoring of Earth system changes, yet there is no automatic way to address this issue directly from observations. Here, we develop an observation-based methodology to capture evidence of changes in global terrestrial ecosystems and attribute these changes to natural or anthropogenic activity. We use the longest time record of global microwave L-band soil moisture and vegetation optical depth as satellite data and build spatially explicit maps of change in soil and vegetation water content and biomass reflecting large ecosystem changes during the last decade, 2010-20. Regions of prominent trends (from [Formula: see text] to 9% per year) are observed, especially in humid and semi-arid climates. We further combine such trends with land cover change maps, vegetation greenness and precipitation variability to assess their relationship with major documented ecosystem changes. Several regions emerge from our results. They cluster changes according to human activity drivers, including deforestation (Amazon, Central Africa) and wildfires (East Australia), artificial reforestation (South-East China), abandonment of farm fields (Central Russia) and climate shifts related to changes in precipitation variability (East Africa, North America and Central Argentina). Using the high sensitivity of soil and vegetation water content to ecosystem changes, microwave satellite observations enable us to quantify and attribute global vegetation responses to climate or anthropogenic activities as a direct measure of environmental changes and the mechanisms driving them.

Projected Effects of Temperature and Precipitation Variability Change on Streamflow Patterns Using a Functional Flows Approach

AbstractStreamflow patterns are shifting with climate change, and these shifts pose increasing risk to freshwater ecosystems. These emerging changes must be linked with ecological functions of river systems to understand how climate change may affect freshwater biota. In this study we used a functional flows approach to analyze the ecological effects of changing streamflow patterns in snowmelt‐dominated watersheds of the Sierra Nevada mountains of California. Our climate change modeling method combined ensemble Global Climate Models (GCMs) and decision scaling methods to incorporate the effects of GCM‐projected changes in precipitation variability on streamflow patterns. Of climate parameters explored, air temperature causes the most change in functional flows, although precipitation variability compounds changes driven by air temperature. The greatest changes in ecologically‐relevant streamflow patterns manifest as longer and drier dry season conditions, earlier snowmelt recession, and higher‐magnitude peak flows. Although the directions of changes in functional flow metrics are largely consistent across models and watersheds, the magnitude of change depends strongly on human emissions levels. The analytical approach used in this study can serve as a model for integrating multiple approaches in hydroclimatic assessment of ecological change, and the results can help prioritize specific aspects of the flow regime for restoration efforts.

Changes in precipitation variability across time scales in multiple global climate model large ensembles

Anthropogenic changes in the variability of precipitation stand to impact both natural and human systems in profound ways. Precipitation variability encompasses not only extremes like droughts and floods, but also the spectrum of precipitation which populates the times between these extremes. Understanding the changes in precipitation variability alongside changes in mean and extreme precipitation is essential in unraveling the hydrological cycle’s response to warming. We use a suite of state-of-the-art climate models, with each model consisting of a single-model initial-condition large ensemble (SMILE), yielding at least 15 individual realizations of equally likely evolutions of future climate state for each climate model. The SMILE framework allows for increased precision in estimating the evolving distribution of precipitation, allowing for forced changes in precipitation variability to be compared across climate models. We show that the scaling rates of precipitation variability, the relation between the rise in global temperature and changes in precipitation variability, are markedly robust across timescales from interannual to decadal. Over mid- and high latitudes, it is very likely that precipitation is increasing across the entire spectrum from means to extremes, as is precipitation variability across all timescales, and seasonally these changes can be amplified. Model or structural uncertainty is a prevailing uncertainty especially over the Tropics and Subtropics. We uncover that model-based estimates of historical interannual precipitation variability are sensitive to the number of ensemble members used, with ‘small’ initial-condition ensembles (of less than 30 members) systematically underestimating precipitation variability, highlighting the utility of the SMILE framework for the representation of the full precipitation distribution.

Interactions between species richness, herbivory and precipitation affect standing biomass in Mongolian rangelands

AbstractQuestionsLivestock management in rangelands depends on the production of plant biomass. Biomass production is driven by the temporal and spatial variability in precipitation, but our understanding of how precipitation variability mediates grazing effects on biomass production is still fragmented. Along a 600‐km precipitation gradient we extracted biomass data to ask the questions: (a) what are the effects of grazing intensity on biomass production; (b) does grazing intensity interact with plant species richness to affect biomass production; and (c) how do plant functional groups respond to grazing and precipitation?LocationMongolia.MethodsBiomass was sampled along 15 grazing intensity transects within the precipitation gradient over two consecutive years. We modeled spatial variability in above‐ground plant biomass using mixed‐effects models. Normalized difference vegetation index (NDVI) data were combined with field‐sampled biomass data to correct for inter‐annual precipitation variation. The effects of species richness were modeled with respect to possible interactions with grazing intensity, and the composition of plant functional groups was modeled with respect to possible interactions between grazing intensity and precipitation.ResultsBiomass was negatively correlated with grazing intensity and this effect increased as precipitation increased. Biomass was positively correlated with species richness in both years, but the strength of this effect and the interaction between species richness and grazing intensity differed between 2014 and 2015 in line with highly variable precipitation between both years. The plant functional groups grasses, sedges, legumes, wormwood and forbs had contrasting responses to grazing and precipitation.ConclusionBiomass production in drylands is more vulnerable to changes in precipitation variability and grazing intensities in relatively moist and productive rangelands than in dry and unproductive ones. Future rangeland management needs to address potentially increasing precipitation variability in order to promote desired forage plants, and to preserve the positive effects of biodiversity for biomass production.

Distinct response of gross primary productivity in five terrestrial biomes to precipitation variability

Climate change will impact precipitation variability, potentially accelerating climate-terrestrial carbon feedbacks. However, the response of ecosystems to precipitation variability is difficult to constrain due to myriad physiological and abiotic variables that limit terrestrial productivity. Based on a combination of satellite imagery and a global network of daily precipitation data, we present here a statistical framework to isolate the impact of precipitation variability on the gross primary productivity of five biomes that collectively account for 50% of global land area. The productivity of mesic grasslands and forests decreases by ~28% and ~7% (respectively) in response to more irregular rain within the year, while the sensitivity is halved in response to higher year-to-year variability. Xeric grasslands are similarly impacted by intra-annual rainfall variance, but they show an increase in productivity with higher interannual rainfall variability. Conversely, the productivity of boreal forests increases under higher variability on both timescales. We conclude that projected changes in precipitation variability will have a measurable global impact on the terrestrial carbon sink.

Urban signatures of sub-daily extreme precipitation events over a metropolitan region

Previous research on the relationship between urbanization and extreme precipitation has shown that regional and global anthropogenic changes have made extreme precipitation events more frequent. The purpose of this research was to explore changes in the variability of extreme precipitation in urban areas that underwent different degrees of urbanization intensity, and to explore the possible reasons using data from 7 meteorological stations in Shenzhen, China with hourly precipitation records dating back to the 60's. Shenzhen is one of the fastest growing metropolitan areas on earth with heavy urbanization occurring since 1979. We used k-means clustering to categorize areas of the city into steadily urbanized regions (SUR) or rapidly urbanized regions (RUR). Next, the variations in the linear trends of annual maximum precipitation (AMP) were analyzed, followed by water vapor analysis and the random forest algorithm to analyze the causes of the variation. The results showed that the severity of the urbanization process had a large and significant impact on extreme precipitation. The AMP analysis showed that at the higher temporal resolutions (< 6 h) extreme precipitation was only significant at RUR stations, while at low temporal resolutions precipitation did not significantly change at any station. An analysis of the diurnal patterns of precipitation and the water vapor analysis over Shenzhen showed that the increase in short-duration extreme precipitation events may be related to atmospheric instability caused by heat emitted as a byproduct of the urbanization process. Furthermore, the differences between the variations in the precipitation trends of SUR and RUR may be related to differences in thermal contrast between high and low altitudes. The results of the random forest analysis supported the correlations between the severity of urban development and changes in precipitation variability. Our findings have highlighted the need for a better understanding of the local and regional anthropogenic effects on the climate and the intensification of extreme climate events due to urbanization.

Nitrogen deposition magnifies the sensitivity of desert steppe plant communities to large changes in precipitation

Abstract Precipitation alteration and nitrogen (N) deposition caused by anthropogenic activities could profoundly affect the structure and functioning of plant communities in arid ecosystems. However, the plant community impacts conferred by large temporal changes in precipitation, especially with a concurrent increase in N deposition, remain unclear. To address this uncertainty, from 2016 to 2017, an in situ field experiment was conducted to examine the effects of five precipitation levels, two N levels and their interaction on the plant community function and composition in a desert steppe in northern China. Above‐ground net primary production (ANPP) and plant community‐weighted mean (CWM) height significantly increased with increasing precipitation, and both were well fitted with a positive linear model, but with a higher slope under N addition. The ANPP increase was primarily driven by the increase in Artemisia capillaris, a companion forb sensitive to precipitation variation. The plant community composition shifted with precipitation enhancement—from a community dominated by Stipa tianschanica, a perennial grass, to a community dominated by Artemisia capillaris. Synthesis. The findings imply that the ecosystem sensitivity to future changes in precipitation variability will be mediated by two potential mechanisms: concurrent N deposition and plant community‐level change. It is suggested that we should consider the vegetation compositional shift and multiple resource colimitation in assessing the sensitivity of terrestrial ecosystems to climate change.

Precipitation variability increases in a warmer climate

Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle’s response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climate models increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21st century, we find that in the global, multi-model mean, precipitation variability increases 3–4% K−1 globally, 4–5% K−1 over land and 2–4% K−1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.

Out-phased decadal precipitation regime shift in China and the United States

In order to understand the changes in precipitation variability associated with the climate shift around mid-1970s, the precipitation regime changes have been analyzed over both China and the USA. Specifically, a new variable is designed based on Benford’s Law (BL) to detect precipitation regime shift by using only the first digit information of the datasets. This new variable describes the decadal precipitation regime shift more directly and clearly than the traditional variables, such mean or trend of yearly precipitation amount. It is found that there is an obvious out-phased relation for precipitation regime shift over China and the USA, i.e., a significant shift from the lower to the higher BL’s goodness of fit (weaker to stronger precipitation intensity) in the Southern China occurred in 1979, and a significant shift from the higher to the lower BL’s goodness of fit (stronger to weaker precipitation intensity) in the USA occurred around 1978.

Variations in precipitation and runoff from a multivariate perspective in the Wei River Basin, China

Investigation of the variations in precipitation and runoff and possible breakpoints of their relationship is of great value for local water resources planning and management. The Wei River Basin (WRB), as a typical arid and semi-arid region in China, was selected as the case study. The zonal and meridional moisture transport flux from the National Centers for Environmental Prediction (NCEP) reanalysis dataset were used to explore the possible causes of changes in precipitation variability. A Copula-based method was adopted to examine the changing relations between precipitation and runoff variabilities and identify possible breakpoints of their relationship. Results showed that: (1) a roughly decreasing precipitation trend was found for most months, especially in spring and autumn, which was mainly affected by the joint effects of the weakening East Asian summer and winter monsoons; (2) similar to precipitation changes, the runoff in most months in the WRB exhibited significantly decreasing trends, which are highly correlated with those of precipitation at the 95% confidence level; (3) two breakpoints of the relationship between precipitation and runoff were identified at Linjiacun station in 1972 and 1996 and at Zhangjiashan station in 1988 and 1997, whilst only one breakpoint was detected at Huaxian station in 1995, which were well consistent with the extensive human water use and soil conservation practices.

Modeling the Impacts of Future Climate Change on Irrigation over China: Sensitivity to Adjusted Projections

Abstract Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China.

Satellite precipitation in southeastern South America: how do sampling errors impact high flow simulations?

Satellite precipitation estimates are increasingly available at temporal and spatial scales of interest to hydrological applications and with the potential for improving flood forecasts in data-sparse regions. This study evaluates the effect of sampling error on simulated large flood events. Synthetic precipitation fields were generated in Monte Carlo fashion by perturbing observed precipitation fields with sampling errors based on 1, 2 and 6 h intervals. The variable infiltration capacity hydrological model was used to assess the impact of these errors on simulated high flow events in the Iguazu basin, a rain-dominated, subtropical basin in southeastern South America. Results showed that unbiased errors in daily error-corrupted precipitation fields introduced bias in the simulated hydrologic fluxes and states. The overall bias for error-corrupted daily streamflows was positive and its magnitude increased with larger sampling intervals. However, for high flow events, the bias was negative as a result of an increase in simulated infiltration and changes in precipitation variability. Errors in precipitation also affected the magnitude and volume of the peak events but did not change the first two statistical moments of the peaks indicating that non-linearities in the hydrological system preserve the statistical properties of high flows in the basin. Caution is needed when using satellite products for hydrological applications that require the estimation of large peaks and volumes.

Resilience of montado understorey to experimental precipitation variability fails under severe natural drought

Future climate scenarios for the Iberian Peninsula predict increasingly variable precipitation regimes, challenging key ecosystem processes in the Mediterranean biome. This study presents a large-scale water manipulation experiment, exposing the understorey vegetation in a Mediterranean oak woodland to simulations of precipitation variability. We hypothesized that, with no net changes in rainfall quantity, large infrequent precipitation events extend the period of soil moisture deficit, thereby decreasing productivity and soil nitrogen availability, accompanied by changes in plant community structure. However, the herbaceous understorey was highly resilient to increased precipitation variability. Extending the dry period between precipitation events from three to six weeks had no effect on productivity and community structure, this lack of responsiveness being attributed to phenotypic and physiological adaptations of the vegetation. However, vegetation senesced earlier, the shorter life cycle potentially influencing reproductive success. Additionally, experimental water manipulation did not affect soil nitrogen dynamics, with nitrogen being limiting in both treatments.In comparison, non-manipulated control plots experienced a severe natural wintertime drought, significantly reducing productivity and affecting species composition, but showed less indication of nitrogen limitation. Thus, although the understorey vegetation was resilient to changes in precipitation variability, long drought periods exerted highly negative effects, with the vegetation not being able to buffer the drought effects through adaptive strategies when the length of the dry period exceeded ∼10 weeks. Our results highlight the necessity for further studies investigating how climate change will influence the co-limitation of water and nitrogen availability, which in turn might affect plant productivity in Mediterranean ecosystems.

Precipitation variability does not affect soil respiration and nitrogen dynamics in the understorey of a Mediterranean oak woodland

Future climate scenarios for the Mediterranean imply increasing precipitation variability. This study presents a large-scale water manipulation experiment simulating changes in precipitation variability, aiming at a better understanding of the effects of rainfall patterns on soil C and N cycling and understorey productivity in a Mediterranean oak woodland. We used rain-out shelters to achieve (1) a normal dry period (7 days), and (2) a dry period increased three-fold (21 days), without altering total annual precipitation inputs. The temporal patterns of soil respiration (R s) and soil inorganic N were not affected by treatment. However, water infiltration and N leaching increased with large infrequent watering events. R s and soil NH4 +-N correlated with soil temperature, with soil NO3 −-N being influenced by leaching. The lack of significant treatment effects on either R s or soil inorganic N can be explained by (1) minor differences in plant productivity between the treatments, suggesting equal plant N demand, and (2) the absence of moisture dependence of R s and soil NH4 +-N. Increased N leaching with large infrequent precipitation events may have longer-term consequences for ecosystem functioning. Our results contribute to an improved understanding of possible climate change effects on key ecosystem processes in Mediterranean ecosystems.

Sensitivity of mean annual primary production to precipitation

AbstractIn many terrestrial ecosystems, variation in aboveground net primary production (ANPP) is positively correlated with variation in interannual precipitation. Global climate change will alter both the mean and the variance of annual precipitation, but the relative impact of these changes in precipitation on mean ANPP remains uncertain. At any given site, the slope of the precipitation‐ANPP relationship determines the sensitivity of mean ANPP to changes in mean precipitation, whereas the curvature of the precipitation‐ANPP relationship determines the sensitivity of ANPP to changes in precipitation variability. We used 58 existing long‐term data sets to characterize precipitation‐ANPP relationships in terrestrial ecosystems and to quantify the sensitivity of mean ANPP to the mean and variance of annual precipitation. We found that most study sites have a nonlinear, saturating relationship between precipitation and ANPP, but these nonlinearities were not strong. As a result of these weak nonlinearities, ANPP was nearly 40 times more sensitive to precipitation mean than variance. A 1% increase in mean precipitation caused a −0.2% to 1.8% change in mean ANPP, with a 0.64% increase on average. Sensitivities to precipitation mean peaked at sites with a mean annual precipitation near 500 mm. Changes in species composition and increased intra‐annual precipitation variability could lead to larger ANPP responses to altered precipitation regimes than predicted by our analysis.

Impacts of changes in climate variability on regional vegetation in China: NDVI‐based analysis from 1982 to 2000

AbstractThree methods were used to distinguish the characteristics of changes in climate variability and normalized difference vegetation index (NDVI) during the period from 1982 to 2000 in China. Great changes in climate variability and an increased trend in NDVI were observed. The changes in precipitation variability were greater than the changes in temperature variability in each month, which is attributed to changes in the monsoon system in East Asia. The abrupt changes in climate and NDVI were more significant in 1983 than in the other years due to the impacts of El Niño/Southern Oscillation (ENSO). Using these results, the influences of changes in climate variability on vegetation were studied in the whole nation, and eight regions were defined according to the vegetation division map of China. The results show that abrupt climate changes at a small scale cannot cause abrupt NDVI changes directly. At a nationwide level, over a longer time scale the persistence of above/below average temperature determines the changes in NDVI; at a shorter time scale, changes in the magnitude of precipitation influence NDVI significantly. Such regional climate variability affects vegetation in different ways owing to the diversity of vegetation types, climatic conditions and topography of the land.

Short-term soil inorganic N pulse after experimental fire alters invasive and native annual plant production in a Mojave Desert shrubland

Post-fire changes in desert vegetation patterns are known, but the mechanisms are poorly understood. Theory suggests that pulse dynamics of resource availability confer advantages to invasive annual species, and that pulse timing can influence survival and competition among species. Precipitation patterns in the American Southwest are predicted to shift toward a drier climate, potentially altering post-fire resource availability and consequent vegetation dynamics. We quantified post-fire inorganic N dynamics and determined how annual plants respond to soil inorganic nitrogen variability following experimental fires in a Mojave Desert shrub community. Soil inorganic N, soil net N mineralization, and production of annual plants were measured beneath shrubs and in interspaces during 6 months following fire. Soil inorganic N pools in burned plots were up to 1 g m(-2) greater than unburned plots for several weeks and increased under shrubs (0.5-1.0 g m(-2)) more than interspaces (0.1-0.2 g m(-2)). Soil NO(3) (-)-N (nitrate-N) increased more and persisted longer than soil NH(4) (+)-N (ammonium-N). Laboratory incubations simulating low soil moisture conditions, and consistent with field moisture during the study, suggest that soil net ammonification and net nitrification were low and mostly unaffected by shrub canopy or burning. After late season rains, and where soil inorganic N pools were elevated after fire, productivity of the predominant invasive Schismus spp. increased and native annuals declined. Results suggest that increased N availability following wildfire can favor invasive annuals over natives. Whether the short-term success of invasive species following fire will direct long-term species composition changes remains to be seen, yet predicted changes in precipitation variability will likely interact with N cycling to affect invasive annual plant dominance following wildfire.

The influence of variable weather patterns on river water quantity and quality regimes

AbstractThere is growing awareness as to the potential sensitivity of hydrological systems to climate change. In particular long‐term changes in precipitation variability will have consequences for runoff regimes and thence solute transport. By utilizing the Lamb's Weather Type register in conjunction with observed 24 h rainfall totals it was possible to determine daily precipitation event probabilities and magnitudes for eight dominant synoptic classes. The stochastic rainfall series thus generated were then used to drive a robust hydrochemical model of an experimental catchment in the East Midlands, UK. The model results indicate that the frequencies of flood and drought are dependent upon the synoptic scenario, and especially the historical prevalence of both the anticyclonic and cyclonic patterns. Given that there have been marked fluctuations in the annual frequencies of these classes since the mid‐nineteenth century, long‐term variations in the severity and incidence of extreme flows may be anticipated. Clearly this will have major implications for the episodic export and dilution of solutes, sediments and microorganisms originating from both pristine and polluted hydrosystems.