Long-term Mean Annual Precipitation Research Articles

Fine-root production in boreal peatland forests: Effects of stand and environmental factors

Fine roots are an important component of ecosystem carbon (C) cycling in boreal forests and peatlands. We aimed to estimate fine-root production (FRP) for a range of peatland forests, examine the patterns in, and develop models for estimating, the relationships between FRP and tree stand characteristics as well as environmental conditions.Fine-root production of 28 drained boreal peatland forest sites in Finland, representing different site types and soil water-table conditions, was measured using the ingrowth-core method. Total FRP and FRP of conifers decreased from south to north but long-term mean annual temperature sum and precipitation alone did not significantly explain this trend. Tree stand basal area predicted FRP better than any other stand variable alone, explaining 16 % of the variation in stand-level total FRP. Basal areas of pine and spruce correlated positively with the FRP of conifers. Total FRP varied considerably among the site types and, with the exception of the most fertile site type, decreased with decreasing fertility. A model that included stand basal area and site type accounted for 47% of the variation in stand-level total FRP. Total FRP was generally higher with a deeper water-table level (WT). Together, WT and basal area explained 25 % of the variation in stand-level total FRP. Most FRP occurred in the top 20-cm layer comprising 76–95% of total FRP. The most fertile site type showed lower FRP in deeper layers than the other site types. These results can be used for estimation of FRP with forest inventory data.

Differential sensitivity of above- and belowground plant biomass to drought and defoliation in temperate grasslands

Multi-year droughts combined with other stressors such as defoliation are likely to have substantial ecological impacts. However, grasslands vary significantly in their response to drought and defoliation, and interpretations rarely address the importance of roots despite evidence showing roots are likely to respond differently to drought and defoliation than shoots. Here, we conducted a three-year manipulative experiment, combining a reduction in rainfall treatment (drought, 45% of ambient) with each of a time-of-defoliation (early vs. late) and an intensity-of-defoliation (none, light, heavy) treatment at seven temperate grassland sites to test three a priori hypotheses: 1) defoliation early relative to late in the season would exacerbate drought impacts on aboveground net primary productivity (ANPP) and root biomass; 2) ANPP and root biomass would progressively decrease with increasing intensity of defoliation early in the growing season under drought; 3) drought and defoliation effects on ANPP and root biomass would vary along a gradient of long-term mean annual precipitation of study sites. Across all seven sites, the combined effects of drought and defoliation led to greater changes in root biomass than ANPP. Under drought conditions specifically, defoliation early in the growing season reduced root biomass, but not ANPP, compared to defoliation late in the growing season. The decline in root biomass under drought was more substantial when the intensity of early-season defoliation increased from none to heavy. Furthermore, variation in the timing and intensity of defoliation altered root biomass more in mesic than arid grasslands, while their effects on ANPP remained unchanged across the seven sites. These results indicate that root systems may be more responsive than ANPP to simultaneous drought and defoliation, and could lead to long-term changes in plant productivity.

Climate-Streamflow Relationship and Consequences of Its Instability in Large Rivers of Pakistan: An Elasticity Perspective

Precipitation elasticity provides a basic estimate of the sensitivity of long-term streamflow to changes in long-term precipitation, and it is especially useful as the first assessment of climate change impact in land and water resource projects. This study estimated and compared the precipitation elasticity (εp) of streamflow in 86 catchments within Pakistan over 50 major rivers using three widely used analytical models: bivariate nonparametric (NP) estimator, multivariate NP analysis, and multivariate double logarithm (DL) model. All the three models gave similar values of elasticity in the range of 0.1–3.5 for over 70–75% of the catchments. This signifies that a 1% change in the annual mean precipitation compared to the long-term historic mean annual precipitation will amplify the streamflow by 0.1–3.5%. In addition, the results suggested that elasticity estimation of streamflow sensitivity using the multivariate DL model is more reliable and realistic. Precipitation elasticity of streamflow is observed high at altitudes ranging between 250 m and 1000 m while the longitudinal and latitudinal pattern of εp shows higher values in the range of 70–75 and 32–36 decimal degrees, respectively. The εp values were found to have a direct relationship with the mean annual precipitation and an inverse relationship with the catchment areas. Likewise, high εp values were noticed in areas where the mean annual temperature ranges between 15 and 24 °C.

Urban net primary production: Concepts, field methods, and Baltimore, Maryland, USA case study.

Given the large and increasing amount of urban, suburban, and exurban land use on Earth, there is a need to accurately assess net primary productivity (NPP) of urban ecosystems. However, the heterogeneous and dynamic urban mosaic presents challenges to the measurement of NPP, creating landscapes that may appear more similar to a savanna than to the native landscape replaced. Studies of urban biomass have tended to focus on one type of vegetation (e.g., lawns or trees). Yet a focus on the ecology of the city should include the entire urban ecosystem rather than the separate investigation of its parts. Furthermore, few studies have attempted to measure urban aboveground NPP (ANPP) using field-based methods. Most studies project growth rates from measurements of tree diameter to estimate annual ANPP or use remote sensing approaches. In addition, field-based methods for measuring NPP do not address any special considerations for adapting such field methods to urban landscapes. Frequent planting and partial or complete removal of herbaceous and woody plants can make it difficult to accurately quantify increments and losses of plant biomass throughout an urban landscape. In this study, we review how ANPP of urban landscapes can be estimated based on field measurements, highlighting the challenges specific to urban areas. We then estimated ANPP of woody and herbaceous vegetation over a 15-year period for Baltimore, MD, USA using a combination of plot-based field data and published values from the literature. Baltimore's citywide ANPP was estimated to be 355.8g m-2 , a result that we then put into context through comparison with other North American Long-Term Ecological Research (LTER) sites and mean annual precipitation. We found our estimate of Baltimore citywide ANPP to be only approximately half as much (or less) than ANPP at forested LTER sites of the eastern United States, and more comparable to grassland, oldfield, desert, or boreal forest ANPP. We also found that Baltimore had low productivity for its level of precipitation. We conclude with a discussion of the significance of accurate assessment of primary productivity of urban ecosystems and critical future research needs.

PHENOLOGICAL SENSITIVITIES TO CLIMATE ARE SIMILAR IN TWO CLARKIA CONGENERS: INDIRECT EVIDENCE FOR FACILITATION, CONVERGENCE, NICHE CONSERVATISM, OR GENETIC CONSTRAINTS

To date, most herbarium-based studies of phenological sensitivity to climate and of climate-driven phenological shifts fall into two categories: detailed species-specific studies vs. multi-species investigations designed to explain inter-specific variation in sensitivity to climate and/or the magnitude and direction of their long-term phenological shifts. Few herbarium-based studies, however, have compared the phenological responses of closely related taxa to detect: (1) phenological divergence, which may result from selection for the avoidance of heterospecific pollen transfer or competition for pollinators, or (2) phenological similarity, which may result from phylogenetic niche conservatism, parallel or convergent adaptive evolution, or genetic constraints that prevent divergence. Here, we compare two widespread Clarkia species in California with respect to: the climates that they occupy; mean flowering date, controlling for local climate; the degree and direction of climate change to which they have been exposed over the last ∼115 yr; the sensitivity of flowering date to inter-annual and to long-term mean maximum spring temperature and annual precipitation across their ranges; and their phenological change over time. Specimens of C. cylindrica were sampled from sites that were chronically cooler and drier than those of C. unguiculata, although their climate envelopes broadly overlapped. Clarkia cylindrica flowers ∼ 3.5 d earlier than C. unguiculata when controlling for the effects of local climatic conditions and for quantitative variation in the phenological status of specimens. However, the congeners did not differ in their sensitivities to the climatic variables examined here; cumulative annual precipitation delayed flowering and higher spring temperatures advanced flowering. In spite of significant spring warming over the sampling period, neither species exhibited a long-term phenological shift. Precipitation and spring temperature interacted to influence flowering date: the advancing effect on flowering date of high spring temperatures was greater in dry than in mesic regions, and the delaying effect of high precipitation was greater in warm than in cool regions. The similarities between these species in their phenological sensitivity and behavior are consistent with the interpretation that facilitation by pollinators and/or shared environmental conditions generate similar patterns of selection, or that limited genetic variation in flowering time prevents evolutionary divergence between these species.

Climate change induced declines in fuel moisture may turn currently fire-free Pyrenean mountain forests into fire-prone ecosystems

Fuel moisture limits the availability of fuel to wildfires in many forest areas worldwide, but the effects of climate change on moisture constraints remain largely unknown. Here we addressed how climate affects fuel moisture in pine stands from Catalonia, NE Spain, and the potential effects of increasing climate aridity on burned area in the Pyrenees, a mesic mountainous area where fire is currently rare. We first quantified variation in fuel moisture in six sites distributed across an altitudinal gradient where the long-term mean annual temperature and precipitation vary by 6–15 °C and 395–933 mm, respectively. We observed significant spatial variation in live (78–162%) and dead (10–15%) fuel moisture across sites. The pattern of variation was negatively linked (r = |0.6|–|0.9|) to increases in vapor pressure deficit (VPD) and in the Aridity Index. Using seasonal fire records over 2006–2020, we observed that summer burned area in the Mediterranean forests of Northeast Spain and Southern France was strongly dependent on VPD (r = 0.93), the major driver (and predictor) of dead fuel moisture content (DFMC) at our sites. Based on the difference between VPD thresholds associated with large wildfire seasons in the Mediterranean (3.6 kPa) and the maximum VPD observed in surrounding Pyrenean mountains (3.1 kPa), we quantified the “safety margin” for Pyrenean forests (difference between actual VPD and that associated with large wildfires) at 0.5 kPa. The effects of live fuel moisture content (LFMC) on burned area were not significant under current conditions, a situation that may change with projected increases in climate aridity. Overall, our results indicate that DFMC in currently fire-free areas in Europe, like the Pyrenees, with vast amounts of fuel in many forest stands, may reach critical dryness thresholds beyond the safety margin and experience large wildfires after only mild increases in VPD, although LFMC can modulate the response.

Differential responses of soil bacteria and fungi to altered precipitation in a meadow steppe

Soil microorganisms are essential participants in ecosystem processes, yet their composition, diversity, and function are affected by altered precipitation. The patterns and key processes driving the effects of changes in precipitation on soil bacterial and fungal communities remain unclear. To better understand how changes in precipitation may affect soil microorganisms, we conducted a three-year field precipitation manipulation experiment, with treatments ranging from 50% reduction to 50% increases in precipitation, in a meadow steppe located in northeast China. Our results demonstrated that the bacterial community was more sensitive to changes in precipitation than the fungal community. The fungal community was sensitive to inter-annual differences in precipitation, but not to the treatment-induced changes in precipitation. Increased annual precipitation shifted the dominance of the microbial community from bacteria to fungi. Over the precipitation range (200–280 mm) soil microbial biomass and diversity are maximal, below the long-term mean annual precipitation (430 mm) for this site. Soil water content, pH, and total phosphorus were the main factors related to the variance in soil microbial community diversity. Results show non-linear, time-dependent, and interacting responses of bacterial and fungal biomass and diversity to soil properties under gradients of altered precipitation magnitude in this semi-arid grassland.

Rainfall erosivity in South America: Current patterns and future perspectives

Rainfall erosivity is the driving factor for soil erosion and can be potentially affected by climate change, impacting agriculture and the environment. In this study, we sought to project the impact of climate change on the long-term average annual rainfall erosivity (R-factor) and mean annual precipitation in South America. The CanESM2, HadGEM2-ES, and MIROC5 global circulation models (GCMs) and the average of the GCMs (GCM-Ensemble) downscaled by the Eta/CPTEC model at a spatial resolution of 20 km in the representative concentration pathway (RCP) 8.5 were applied in this study. A geographical model to estimate the R-factor across South America was fitted. This model was based on latitude, longitude, altitude, and mean annual precipitation as inputs obtained from the WorldClim database. Using this model, the first R-factor map for South America was developed (for the baseline period: 1961–2005). The GCMs projected mean annual precipitation for three 30-year time periods (time slices: 2010–2040; 2041–2070; 2071–2099). These projections were used to run the R-factor model to assess the impact of climate change. It was observed that the changes were more pronounced in the Amazon Forest region (namely, the North Region, NR, and the Andes North Region, ANR) with a strong reduction in the mean annual precipitation and R-factor throughout the century. The highest increase in the R-factor was projected on the Central and South Andes regions (CAR and SAR) because of the increase in the mean annual precipitation projected by the GCMs. The GCMs pointed contradictory projections for the Central-South Region (CSR), indicating greater uncertainty. An increase in the R-factor was projected for this region, eastern Argentina, and southern Brazil, whereas a decrease in the R-factor was expected for southeastern Brazil. In general, the GCMs projected reductions in the R-factor and annual precipitation for South America, with the highest changes projected from the baseline to the 2010–2040 time slice.

Leaf Morphological Traits and Leaf Nutrient Concentrations of European Beech Across a Water Availability Gradient in Switzerland

Climate change and the expected increase in frequency of dry summers are likely to affect the growth of important tree species. We investigated relationships between morphological and chemical leaf traits of European beech (Fagus sylvatica L.) and environmental factors along a water availability gradient consisting of 12 sites located throughout Switzerland. We found that leaf dry mass and leaf area tended to decrease with increasing long-term mean annual precipitation (MAP) and actual to potential transpiration (AT/PT), two correlated variables that form the water availability gradient. These results contrast with those of several other studies, and might be explained by favourable temperature and humidity conditions during leaf formation in spring at the dry sites. Although the relationship was not linear over the whole gradient, the drier sites were characterized by beech with a lower specific leaf area, along with higher foliar potassium (K) and lower foliar nitrogen (N) concentrations. These patterns likely reflect strategies developed as an adaptation to reduced water availability, but they also result from variation in the availability of nutrients in soil across our sites. In the case of N, there are indications that atmospheric deposition plays a role in foliar concentrations.

Field exclusion of large soil predators impacts lower trophic levels and decreases leaf-litter decomposition in dry forests.

Shifts in densities of apex predators may indirectly affect fundamental ecosystem processes, such as decomposition, by altering patterns of cascading effects propagating through lower trophic levels. These top-down effects may interact with anthropogenic impacts, such as climate change, in largely unknown ways. We investigated how changes in densities of large predatory arthropods in forest leaf-litter communities altered lower trophic levels and litter decomposition. We conducted our experiment in soil communities that had experienced different levels of long-term average precipitation. We hypothesized that altering abundances of apex predators would have stronger effects on soil communities inhabiting dry forests, due to lower secondary productivity and greater resource overexploitation by lower trophic levels compared to wet forests. We experimentally manipulated abundances of the largest arthropod predators (apex predators) in field mesocosms replicated in the leaf-litter community of Iberian beech forests that differed in long-term mean annual precipitation by 25% (three dry forests with MAP<1,250mm and four wet forests with MAP>1,400mm). After one year, we assessed abundances of soil fauna in lower trophic levels and indirect impacts on leaf-litter decomposition using litter of understorey hazel, Corylus avellana. Reducing densities of large predators had a consistently negative effect on final abundances of the different trophic groups and several taxa within each group. Moreover, large predatory arthropods strongly impacted litter decomposition, and their effect interacted with the long-term annual rainfall experienced by the soil community. In the dry forests, a 50% reduction in the densities of apex predators was associated with a 50% reduction in decomposition. In wet forests, the same reduction in densities of apex soil predators did not alter the rate of litter decomposition. Our results suggest that predators may facilitate lower trophic levels by indirectly reducing competition and resource overexploitation, cascading effects that may be more pronounced in drier forests where conditions have selected for greater competitive ability and more rapid resource utilization. These findings thus provide insights into the functioning of soil invertebrate communities and their role in decomposition, as well as potential consequences of soil community responses to climate change.

Drought suppresses soil predators and promotes root herbivores in mesic, but not in xeric grasslands

Precipitation changes among years and locations along gradients of mean annual precipitation (MAP). The way those changes interact and affect populations of soil organisms from arid to moist environments remains unknown. Temporal and spatial changes in precipitation could lead to shifts in functional composition of soil communities that are involved in key aspects of ecosystem functioning such as ecosystem primary production and carbon cycling. We experimentally reduced and increased growing-season precipitation for 2 y in field plots at arid, semiarid, and mesic grasslands to investigate temporal and spatial precipitation controls on the abundance and community functional composition of soil nematodes, a hyper-abundant and functionally diverse metazoan in terrestrial ecosystems. We found that total nematode abundance decreased with greater growing-season precipitation following increases in the abundance of predaceous nematodes that consumed and limited the abundance of nematodes lower in the trophic structure, including root feeders. The magnitude of these nematode responses to temporal changes in precipitation increased along the spatial gradient of long-term MAP, and significant effects only occurred at the mesic site. Contrary to the temporal pattern, nematode abundance increased with greater long-term MAP along the spatial gradient from arid to mesic grasslands. The projected increase in the frequency of extreme dry years in mesic grasslands will therefore weaken predation pressure belowground and increase populations of root-feeding nematodes, potentially leading to higher levels of plant infestation and plant damage that would exacerbate the negative effect of drought on ecosystem primary production and C cycling.

Plant Production Responses to Precipitation Differ Along an Elevation Gradient and Are Enhanced Under Extremes

The sensitivity of plant production to precipitation underlies the functioning of ecosystems. Studies that relate long-term mean annual precipitation and production across multiple sites (spatial relationship) or examine interannual linkages within a site (temporal relationship) can reveal biophysical controls over ecosystem function but have limited ability to infer responses to extreme changes in precipitation that may become more common under climate change. To overcome limitations of using a single approach, we integrated satellite- and ground-based estimates of production with a standardized, multi-site precipitation manipulation experiment across a grassland elevation gradient in the southwestern USA. The responsiveness of production to changes in precipitation followed the order: temporal (0.06–0.13 g m−2 mm−1) < spatial (0.21 g m−2 mm−1) < experimental relationship (0.25–0.42 g m−2 mm−1), suggesting that spatial and temporal relationships determined with satellite- and ground-based estimates cannot be extrapolated to determine the effect of extreme events. A strong production response to differences in mean annual precipitation across sites reinforces a regional control of water availability. Interannual sensitivity to precipitation was strongest at the low elevation grasslands, and the high elevation mixed conifer meadow had a large reduction in production in a drought year. Extreme experimental drought strongly reduced production in low elevation grasslands, but water addition had mixed effects. High elevation meadows were insensitive to both extreme drought and water addition. Our results highlight the importance of accounting for extreme climate regimes and site-level factors when scaling climate change effects up to regional and global scales.

Revisited rainfall network design: evaluation of heuristic versus entropy theory methods

Rain gauges are installed to measure pointwise precipitation and provide a comprehensive perspective of its spatiotemporal variations. Selection of an efficient and reliable rainfall monitoring network is a key role to reduce its maintenance and handling cost. The main purpose of the current paper is to compare efficiencies of various network design methods. The applied methods are entropy theory (as probabilistic multi-criteria decision-making) and genetic algorithm (as one of the heuristic methods) with three objective functions. Also, two classical (ordinary kriging; OK) and modern (Bayesian maximum entropy; BME) spatial simulation methods were undertaken to provide a comprehensive spatial simulation of precipitation. The proposed assessment was applied on spatial mean annual precipitation variability in the Namak Lake watershed located in the central part of Iran. The final efficiency of developed network design methods is evaluated in terms of three criteria known as mass estimation error, total error, and spatial bias of estimated rainfall. Based on the results, different network distributions have been proposed by the methods. Despite the reliability of the heuristic approach in nonlinear optimization due to its mathematical principle, the results indicated that the network design based on entropy theory can be used to estimate long-term mean annual precipitation more reliably and accurately. Results of the mass estimation error have shown 78 and 83% superiority of the entropy theory approach from the worst approach obtained from the OK and BME methods, respectively.

Inter-Annual Precipitation Variability Decreases Switchgrass Productivity from Arid to Mesic Environments

Cellulosic biofuels are an important source of renewable biomass within the alternative energy portfolio. Switchgrass (Panicum virgatum L.), a perennial C4 grass native to North America, is widely studied as a biofuel feedstock for its consistently high yields and minimal input requirements. The influences of precipitation amount and temporal variability on the fertilizer response of switchgrass productivity are not fully understood. Moreover, global climate models predict changes in rainfall patterns towards lower and increasingly variable soil water availability in several productive areas worldwide, which may impact net primary production of biofuel crops. We conducted a meta-analysis of aboveground net primary production of switchgrass from 48 publications encompassing 82 different locations, 11 soil types, 52 switchgrass cultivars, fertilizer inputs between 0 to 896 kg N ha−1 year−1, and 1 to 6 years of annual productivity measures repeated on the same stand. Productivity of the lowland ecotype doubled with N rates > 131 kg N ha−1 year−1, but upland ecotype productivity increased only by 50%. Results showed an optimum N rate of 30 to 60 kg N ha−1 year−1 for both ecotypes, after which biomass gain per unit of N added decreased. Growing season precipitation (GSPPT) and inter-annual precipitation variability (inter-PPTvar) affected both ecotypes similarly. Long-term mean annual precipitation (MAP) differentially affected lowland and upland productivity, depending on the N level. Productivity responses to MAP and GSPPT were similar for both upland and lowland ecotypes at none or low N rates. When N increased beyond 60 kg N ha−1 year−1, lowland cultivars had a greater growth response to MAP than uplands. Productivity increased with increasing GSPPT and MAP and had a positive linear response to MAP ranging from 600 to 1200 mm year−1. One third of the variability in switchgrass production was accounted for by inter-PPTvar. After accounting for MAP, sites with higher inter-PPTvar had lower switchgrass productivity than sites with lower inter-PPTvar. Increased inter-annual variation in precipitation reduced production of both ecotypes. Predicted changes in the amount and timing of precipitation thus likely will exert greater influence on production of upland than lowland ecotypes of switchgrass.

Land Cover Change in Northern Botswana: The Influence of Climate, Fire, and Elephants on Semi-Arid Savanna Woodlands

Complex couplings and feedback among climate, fire, and herbivory drive short- and long-term patterns of land cover change (LCC) in savanna ecosystems. However, understanding of spatial and temporal LCC patterns in these environments is limited, particularly for semi-arid regions transitional between arid and more mesic climates. Here, we use post-classification analysis of Landsat TM (1990), ETM+ (2003), and OLI (2013) satellite imagery to classify and assess net and gross LCC for the Chobe District, a 21,000 km2 area encompassing urban, peri-urban, rural, communally-managed (Chobe Enclave), and protected land (Chobe National Park, CNP, and six protected forest reserves). We then evaluate spatiotemporal patterns of LCC in relation to precipitation, fire detections (MCD14M, 2001–2013) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and dry season elephant (Loxodonta africana) aerial survey data (2003, 2006, 2012, 2013). Woodland cover declined over the study period by 1514 km2 (16.2% of initial class total), accompanied by expansion of shrubland (1305 km2, 15.7%) and grassland (265 km2, 20.3%). Net LCC differed importantly in protected areas, with higher woodland losses observed in forest reserves compared to the CNP. Loss of woodland was also higher in communally-managed land for the study period, despite gains from 2003–2013. Gross (class) changes were characterized by extensive exchange between woodland and shrubland during both time steps, and a large expansion of shrubland into grassland and bare ground from 2003–2013. MODIS active fire detections were highly variable from year to year and among the different protected areas, ranging from 1.8 fires*year−1/km2 in the Chobe Forest Reserve to 7.1 fires*year−1/km2 in the Kasane Forest Reserve Extension. Clustering and timing of dry season fires suggests that ignitions were predominately from anthropogenic sources. Annual fire count was significantly related to total annual rainfall (p = 0.009, adj. R2 = 0.50), with a 41% increase in average fire occurrence in years when rainfall exceeded long-term mean annual precipitation (MAP). Loss of woodland was significantly associated with fire in locations experiencing 15 or more ignitions during the period 2001–2013 (p = 0.024). Although elephant-mediated damage is often cited as a major cause of woodland degradation in northern Botswana, we observed little evidence of unsustainable pressure on woodlands from growing elephant populations. Our data indicate broad-scale LCC processes in semi-arid savannas in Southern Africa are strongly coupled to environmental and anthropogenic forcings. Increased seasonal variability is likely to have important effects on the distribution of savanna plant communities due to climate-fire feedbacks. Long-term monitoring of LCC in these ecosystems is essential to improving land use planning and management strategies that protect biodiversity, as well as traditional cultures and livelihoods under future climate change scenarios for Southern Africa.

Response of N2O emission to water and nitrogen addition in temperate typical steppe soil in Inner Mongolia, China

The Chinese steppe is undergoing a drastic increase in nitrogen (N) deposition, and the precipitation in this region is predicted to increase. However, the response of soil N2O emissions to the coupling changes of precipitation and N deposition in grassland ecosystem has been seldom discussed. A manipulative field experiment was conducted to investigate the individual and interactive effects of precipitation increase and N deposition on soil N2O efflux in semi-arid temperate grassland in Inner Mongolia during the growing seasons of 2010 and 2011.The treatments included four N addition levels [20gNm−2y−1 (N20), 10gNm−2y−1 (N10), 5gNm−2y−1 (N5), and a zero-N control (CK)] and two water application levels [natural precipitation for dry (D) and 15% increase of long-term mean annual precipitation for wet (W) treatments]. Results indicated that N and water addition both significantly increased soil N2O effluxes (P<0.01). The maximum N2O emissions were observed within 2–3 days after N addition to all treatments, and the N2O effluxes in W treatments were generally higher than in D treatments for the same N input level. For the treatments without N inputs, the N2O emission peak of WCK was 9.8% higher than DCK in 2010. The effect of water addition on N2O emission was more evident when more N fertilizer was applied. For the high N input treatments, the maximum N2O emission of WN20 treatment was 222.6% higher than DN20 in 2010. The changes in N and water availabilities accounted for 91.3% (2010) and 75.6% (2011) of the N2O cumulative efflux variation among different treatments (P<0.01). The N2O effluxes were significantly affected by the interactive effect between N and water in 2010 and 2011 (P<0.05). Significant interannual variability in the cumulative N2O emissions was observed, the cumulative N2O emissions in 2011 were significantly lower than those in 2010 even though the summer of 2011 experienced higher rainfall (P<0.01). Temperature also significantly influenced soil N2O emission apart from the effects of water and N. The temperature change accounted for 41.3% (W) to 47.2% (D) of the temporal variations in N2O emission during the relatively dry 2010. The combined changes in soil moisture, NH4+-N, and temperature accounted for 43.1% (D) to 54.5% (W) of the temporal variations in N2O emission in the relatively wet year of 2011.

Sensitivity of soil evaporation and reference evapotranspirationto climatic variables in South Korea

The quantification of evapotranspiration and soil evaporation is crucial for agricultural water management. The FAO-56 Penman-Monteith and E-DiGOR models were used to compute reference evapotranspiration (Eto) and bare soil evaporation, respectively, at 17 meteorological stations of South Korea, from 1980 to 2009. The same soil parameters were assumed for all stations in order to compare actual soil evaporation (Ea) rates jointly dominated by atmospheric evaporative demand and soil water availability, as well as the size of rainfall events. The sensitivity of Penman-Monteith type equations to the major climatic variables was determined based on 1-year dataset. The long-term mean annual precipitation and Eto calculated at selected stations over the country were 1339.7 mm and 1087.1 mm, respectively. Precipitation showed noticeable interyear fluctuations, and the annual Eto increased gradually during the study period. A strong correlation between pan evaporation (Epan) and Eto was observed (R = 0.808, P < 0.001), based on daily data of 30 years. Similarly, a significant correlation between Epan and potential soil evaporation (Ep) was existent (R = 0.622, P < 0.01). The Ep rates were lower than the Eto rates (Ep = 0.8 × Eto). The magnitude of Ea, as calculated with the model, reached a level of 63% of Ep. On the other hand, Ea accounted for 29.4% to 50.3% of the total precipitation over South Korea. Potential soil evaporation was more sensitive to net radiation, while reference evapotranspiration was mostly affected by the relative humidity. Wind speed was the less effective variable. The contribution of soil heat flux was negligible. The sensitivity of both Ep and Eto to the same climatic variables showed significant differences among seasons and locations. The aridity index ranged from 0.85 to 2.13, and all the study sites could be classified as humid areas. An aridity index of less than 1 appeared about once every 6 to 7 years, based on the station averages.

Assessing the impact of interannual variability of precipitation and potential evaporation on evapotranspiration

The impact of interannual variability of precipitation and potential evaporation on the long-term mean annual evapotranspiration as well as on the interannual variability of evapotranspiration is studied using a stochastic soil moisture model within the Budyko framework. Results indicate that given the same long-term mean annual precipitation and potential evaporation, including interannual variability of precipitation and potential evaporation reduces the long-term mean annual evapotranspiration. This reduction effect is mostly prominent when the dryness index (i.e., the ratio of potential evaporation to precipitation) is within the range from 0.5 to 2. The maximum reductions in the evaporation ratio (i.e., the ratio of evapotranspiration to precipitation) can reach 8–10% for a range of coefficient of variation (CV) values for precipitation and potential evaporation. The relations between the maximum reductions and the CV values of precipitation and potential evaporation follow power laws. Hence the larger the interannual variability of precipitation and potential evaporation becomes, the larger the reductions in the evaporation ratio will be. The inclusion of interannual variability of precipitation and potential evaporation also increases the interannual variability of evapotranspiration. It is found that the interannual variability of daily rainfall depth and that of the frequency of daily rainfall events have quantitatively different impacts on the interannual variability of evapotranspiration; and they also interact differently with the interannual variability of potential evaporation. The results presented in this study demonstrate the importance of understanding the role of interannual variability of precipitation and potential evaporation in land surface hydrology under a warming climate.

Improving Bayesian maximum entropy and ordinary Kriging methods for estimating precipitations in a large watershed: a new cluster-based approach

The main purpose of this research is to investigate spatial variations of mean annual precipitation in a watershed. As a case study, the research focused on the Namak Lake watershed in Iran. Literature provides various techniques for studying spatial patterns of precipitation in a watershed. These techniques often require a large dataset. On the other hand, nonuniform data distribution in a watershed can reduce the accuracy and reliability of the predictions. To overcome these problems, this research applied the cluster method coupled with ordinary Kriging and Bayesian maximum entropy techniques. An estimated point was modified based on the distance from the point to the cluster center. The research considered elevation variations as a secondary variable. A cross-validation technique was used for evaluating the results of mean annual precipitations. The research compared the results of ordinary Kriging and Bayesian maximum entropy methods with and without the application of the clustering method. The research concluded that the cluster-based method can estimate the dynamics of long-term mean annual precipitation more reliably and accurately. The research also revealed more informative results for the cluster-based method.

Camelina: Adaptation and performance of genotypes

Camelina (Camelina sativa L. Crantz) has shown potential as an alternative and biofuel crop in cereal-based cropping systems. Our study investigated the adaption, performance, and yield stability among camelina genotypes across diverse US Pacific Northwest (PNW) environments. Seven named camelina genotypes and 11 experimental numbered genotypes were evaluated for seed and oil yield in trials at 18 location/year environments that spanned four annual precipitation zones. Locations were rainfed with long-term mean annual precipitation ranging from 242 to 1085mm. Thirteen trials were spring-planted and five were fall-planted. Oil content was determined on seed from seven trials, seed weight from five trials, plant height and grain density from four trials, and plant lodging from two trials. Yield stability index was determined and related to seed yield across trials and within each of four annual precipitation zones. Seed yields varied from a trial mean of 127kg/ha at Lind WA during a year of extreme drought to 3302kg/ha at Pullman WA with the grand mean 1213kg/ha. Seed yields among genotypes were significantly different (P<0.05) in 10 environments and ranged across environments from 913kg/ha for ‘GP07’ to 1349kg/ha for ‘Celine’. Spring planting produced higher yields than fall planting and named genotypes out-performed numbered genotypes overall. Between the two highest yielding genotypes, ‘Calena’ was more stable for yield than Celine. Stability index values varied among genotypes within each annual precipitation zone evaluated indicating adaptation differences among genotypes. Oil content varied from 29.6% to 36.8% across environments but varied less among genotypes – 30.8–32.9%. Oil content was negatively correlated to seed yield. Grand means for camelina performance characteristics in four trials were 1.25g/1000 seed weight, 92.4cm plant height, and 652kg/m3 seed density. Named genotypes were more productive than numbered genotypes across environments and can be grown is diversified environments when selected based on anticipated precipitation, seed yield, oil content, and other agronomic characteristics.