Assimilation Effects Research Articles

The effect of carbonate assimilation and nanoheterogeneities on the viscosity of phonotephritic melt from Vesuvius

Interaction between magma and carbonate plays a pivotal role in volcanic systems, yet its impact on magma transport properties remains inadequately explored. This study presents novel viscosity data on a leucite-bearing phonotephritic melt from the 472 CE Pollena eruption (Vesuvius, Italy), doped with varying amounts of CaO and CaO + MgO. The compositions match the chemistry of melt inclusions and interstitial glasses from skarns at Vesuvius, which have been interpreted as related to mixing of magma with different amounts of CaO and MgO derived from the host carbonates (limestone and dolostone). Viscosity measurements were conducted at both high (1150–1400 °C) and low temperatures (640–760 °C) by concentric cylinder viscometry, differential scanning calorimetry, and micropenetration methods. Through an integrated approach which combines Brillouin and Raman spectroscopy with the aforementioned techniques, we accurately predict the viscosity changes induced by magma‑carbonate interaction and identify the formation of nanoheterogeneities during low-temperature viscosity measurements. Notably, viscosity models from the literature fail to accurately reproduce our experimental data set at both high and low temperature. In the high-temperature regime, the addition of CaO induces a remarkable viscosity decrease, surpassing that produced by CaO + MgO addition. Furthermore, our findings reveal a significant viscosity/temperature crossover resulting from the addition of CaO and CaO + MgO to the melt phase. Undoped melt exhibits a higher viscosity compared to doped melts above 750 °C, with an inverse trend observed below this temperature threshold. Such rheological constraints may affect the mobility and mixing capability of melts exposed to different levels of carbonate assimilation.

Characterizing serial dependence as an attraction to prior response.

Serial dependence refers to a common misperception that can occur between subsequently observed stimuli. Observers misreport the current stimulus as being more similar to the previous stimulus than it objectively is. It has been proposed that this bias may reflect an attraction of the current percept to prior percept (Fischer & Whitney, 2014). Alternatively, serial dependence has also been proposed to be the result of an assimilative effect between observer decisions (Fritsche, Mostert, & de Lange, 2017; Pascucci, Mancuso, Santandrea, Libera, Plomp, & Chelazzi, 2019). Lying within this debate is the issue of how we quantify serial dependence. Should this be as a bias induced by prior stimuli or by prior responses? We investigated this by manipulating the orientation of the current stimuli such that they fell between previous stimulus and previous response. We observed an attraction to previous response and a concomitant repulsion from previous stimulus. This suggests that the attractive effect of serial dependence in orientation judgments is best quantified in relation to prior response.

Effect of microphysics scheme and data assimilation on hydrometeor and radiative flux simulations in the Arctic.

Although clouds are a major factor influencing atmospheric environments in the Arctic, numerical simulations of Arctic clouds are uncertain. In this study, the effects of microphysics scheme and data assimilation (DA) on the simulation of clouds, hydrometeors and radiative fluxes in the Arctic were investigated using the polar weather research and forecasting (WRF) model and three-dimensional variational DA. Compared with the WRF 5-class (WSM5) microphysics scheme, when the Morrison double-moment (Morrison) scheme was used, the simulated amount of cloud ice water decreased by approximately 68%. In contrast, the amount of water vapour, cloud liquid water, snow and rain in the atmosphere increased. With DA, the amount of water vapour increased, leading to increased hydrometeors. The cloud liquid water increased in the middle and low atmospheres when Morrison was used, whereas it increased in the low atmosphere when DA was used. The increase in cloud liquid water by using Morrison resulted in a decrease in the downward short-wave radiative flux at the surface, whereas using DA increased the downward long-wave radiative flux. Changing the microphysics scheme induced redistribution of the region and amounts of hydrometeors, whereas DA induced an increase in hydrometeors in specific regions by adding observation information to the model states.

The Relative Importance of the Contrast and Assimilation Effects in Decisions Under Risk

ABSTRACTPast research on decisions under risk has documented two contradictory context effects: the contrast effect, where risk preferences in “target” tasks diverge from those in previous “surrounding” tasks, and the assimilation effect that implies the opposite bias. We present four web experiments (three preregistered) that clarify the conditions determining the relative prominence of these opposing effects. Our experiments focus on choice patterns in “target” tasks where participants choose between the status quo and a risky mixed gamble with an expected value of zero. Study 1 examines the impact of surroundings that differ from the target task with respect to the expected benefit from risk‐taking. The findings reveal a strong contrast effect: Decreasing the attractiveness of risk‐taking in the surrounding tasks increased the risk‐taking rate in the target tasks from 53.2% to 79.7%. Study 2 investigates the impact of surroundings that differ in the payoff domain. The findings indicate a strong assimilation effect: Decreasing the attractiveness of risk‐taking in the surrounding tasks decreased the risk‐taking rate in the target tasks from 74.7% to 36.5%. Additionally, the results revealed unpredicted and robust reversed loss aversion patterns which Studies 3 and 4 further clarify. Our findings (1) suggest that the isolated within‐task computations assumed by leading descriptive models overlook substantial contextual considerations, (2) clarify the factors determining the impact of the contrast and assimilation effects in decisions under risk, and (3) provide a theoretical framework for making useful predictions in various scenarios.

In Spiderman we trust: The influence of familiar media characters on the decision-making of primary school children

Children are increasingly active consumers in the media world and are thus confronted with a wide range of information. Making good decisions in such an environment is a major challenge. Weighting valid information in decision-making is an important skill that children must learn and apply. Yet, how do children weight information and which weights do they use? We developed a measuring instrument for children's weighting of advices by cue validity – the so-called Space Treasure Hunt. It is an easy to understand, child-friendly decision game. By anchoring it in the reality of children's media lives, we are able to assess the influence of familiarity and affect on children's decision making. During a treasure hunt in game situated in outer space, children are confronted with various characters who provide contradictory advice regarding where to find treasures. One of the advice-givers was an expert (valid cue), whereas the other advice-giver varied in terms of its media familiarity and affect. In our study (N = 372), we found that media familiar characters had a strong influence on children's decision-making. Media idols showed an assimilation effect, meaning that children followed the expert's advice the least often when it contradicted their media idol. Conversely, media familiar but less liked characters showed a contrast effect, meaning that children followed the expert's advice most often when it contradicted the media familiar, less liked character. Moreover, we found differences between children in terms of a three-way split: One third of the children, respectively, systematically followed the expert's advice, the media idol, or made their decisions unsystematically. We discuss how our results indicate the use of different weights in children's decision making.

Enhanced regional ocean ensemble data assimilation through atmospheric coupling in the SKRIPS model

We investigate the impact of ocean data assimilation using the Ensemble Adjustment Kalman Filter (EAKF) from the Data Assimilation Research Testbed (DART) on the oceanic and atmospheric states of the Red Sea. Our study extends the ocean data assimilation experiment performed by Sanikommu et al. (2020) by utilizing the SKRIPS model coupling the MITgcm ocean model and the Weather Research and Forecasting (WRF) atmosphere model. Using a 50-member ensemble, we assimilate satellite-derived sea surface temperature and height and in situ temperature and salinity profiles every three days for one year, starting January 01 2011. Atmospheric data are not assimilated in the experiments. To improve the ensemble realism, perturbations are added to the WRF model using several physics options and the stochastic kinetic energy backscatter (SKEB) scheme. Compared with the control experiments using uncoupled MITgcm with ECMWF ensemble forcing, the EAKF ensemble mean oceanic states from the coupled model are better or insignificantly worse (root-mean-square errors are 23% to −1.3% smaller), especially when the atmospheric model uncertainties are accounted for with stochastic perturbations. We hypothesize that the ensemble spreads of the air–sea fluxes are better represented in the downscaled WRF ensembles when uncertainties are well accounted for, leading to improved representation of the ensemble oceanic states from the new experiments with the coupled model. This indicates the ocean model assimilation will be improved with coupled models and may relax the need for operational centers to provide atmospheric ensembles to drive ocean forecasts. Although the feedback from ocean to atmosphere is included in this two-way regional coupled configuration, we find no significant effect of ocean data assimilation on the ensemble mean latent heat flux and 10-m wind speed over the Red Sea. This suggests that the improved skill using the coupled model is not from the two-way coupling, but from downscaling the ensemble atmospheric forcings (one-way coupled) to drive the ocean model.

Assimilating multivariate remote sensing data into a fully coupled subsurface-land surface hydrological model

Hydrological models play a crucial role in tracking and predicting terrestrial water storage, yet they face challenges due to uncertainties and inaccuracies caused by various factors such as meteorological processes and data limitations. To refine these models, data assimilation has emerged as a valuable tool, utilizing a new source of data to update model states while considering associated uncertainties, thereby enhancing our comprehension and predictive capabilities in hydrological processes. In this context, satellite data are receiving increasing attention because they can cover large areas and are useful in detecting spatial and temporal variability of water.In most existing studies related to satellite data assimilation in hydrological models, one source satellite data is used in the analysis. This study focuses on improving subsurface water storage model accuracy by assimilating data from different satellite sources. In particular, we used data from the Soil Moisture and Ocean Salinity (SMOS) satellite and terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE). The data are assimilated into a fully coupled subsurface-surface hydrological model, developed with ParFlow-CLM (PARallel FLOW- Community Land Model). The investigation is conducted in Iran. Employing an Ensemble Kalman Filter, three assimilation scenarios are explored: (i) GRACE, (ii) SMOS, and (iii) the combined assimilation of both GRACE and SMOS data (joint). Findings are validated against the Soil Moisture Active Passive (SMAP) and in-situ groundwater data by using a novel probabilistic reliability framework, demonstrating the advantages of joint data assimilation.The study highlights the influence of assimilated remote sensing data type on the effectiveness of data assimilation. Assimilating GRACE data enhances groundwater level estimations. However, SMOS data positively impacts topsoil moisture estimations, but adversely affects groundwater level estimates. Importantly, the assimilation of both GRACE and SMOS data through multivariate (joint) data assimilation significantly improves accuracy for both soil moisture estimation and groundwater level estimation.

Being a big fish in a little pond: student group composition, perceived academic standing, and young people’s academic self-concept

Upper secondary school students with a strong academic self-concept are more likely to complete their studies and thus increase their well-being in the future. Previous research on the big-fish-little-pond-effect (BFLPE) has thoroughly established the negative contrast effect of average group academic achievement on students’ academic self-concept. Many of these studies have been criticised for assuming the underlying social comparison without testing it. Here, survey and registered data from 1,047 Icelandic adolescents are used to explore the role of social comparison in the BFLPE. Models of hierarchical regression showed that students’ ideas about their relative position within their group of students mediated the effect of group average achievement on academic self-concept. This strengthens the assumption of social comparison being the underlying factor of the BFLPE. No assimilation effect between the type of school and academic self-concept was found. Implications for educators, school authorities, and policymakers are discussed.

Context effects in cognitive effort evaluation.

When given a choice, people will avoid cognitively effortful courses of action because the experience of effort is evaluated as aversive and costly. At the same time, a body of work spanning psychology, economics, and neuroscience suggests that goods, actions, and experiences are often evaluated in the context in which they are encountered, rather in absolute terms. To probe the extent to which theevaluation of cognitive effort is also context-dependent, we had participants learn associations between unique stimuli and subjective demand levels across low-demand and high-demand contexts. We probed demand preferences and subjective evaluation using a forced-choice paradigm as well by examining effort ratings, taken both on-line (during learning) and off-line (after choice). When choosing between two stimuli objectively identical in terms of demand, participants showed a clear preference for the stimulus learned in the low- versus high-demand context and rated this stimulus as more subjectively effortful than the low-demand context in on-line but not off-line ratings, suggesting an assimilation effect. Finally, we observed that the extent to which individual participants who exhibited stronger assimilation effects in off-line demand ratings were more likely to manifest an assimilation effect in demand preferences. Broadly, our findings suggest that effort evaluations occur in a context-dependent manner and are specifically assimilated to the broader context in which they occur.

Contrasting the Effects of X-Band Phased Array Radar and S-Band Doppler Radar Data Assimilation on Rainstorm Forecasting in the Pearl River Delta

Contrasting the X-band phased array radar (XPAR) with the conventional S-Band dual-polarization mechanical scanning radar (SMSR), the XPAR offers superior temporal and spatial resolution, enabling a more refined depiction of the internal dynamics within convective systems. While both SMSR and XPAR data are extensively used in monitoring and alerting for severe convective weather, their comparative application in numerical weather prediction through data assimilation remains a relatively unexplored area. This study harnesses the Weather Research and Forecasting Model (WRF) and its data assimilation system (WRFDA) to integrate radial velocity and reflectivity from the Guangzhou SMSR and nine XPARs across Guangdong Province. Utilizing a three-dimensional variational approach at a 1 km convective-scale grid, the assimilated data are applied to forecast a rainstorm event in the Pearl River Delta (PRD) on 6 June 2022. Through a comparative analysis of the results from assimilating SMSR and XPAR data, it was observed that the assimilation of SMSR data led to more extensive adjustments in the lower- and middle-level wind fields compared to XPAR data assimilation. This resulted in an enlarged convergence area at lower levels, prompting an overdevelopment of convective systems and an excessive concentration of internal hydrometeor particles, which in turn led to spurious precipitation forecasts. However, the sequential assimilation of both SMSR and XPAR data effectively reduced the excessive adjustments in the wind fields that were evident when only SMSR data were used. This approach diminished the generation of false echoes and enhanced the precision of quantitative precipitation forecasts. Additionally, the lower spectral width of XPAR data indicates its superior detection accuracy. Assimilating XPAR data alone yields more reasonable adjustments to the low- to middle-level wind fields, leading to the formation of small-to-medium-scale horizontal convergence lines in the lower levels of the analysis field. This enhancement significantly improves the model’s forecasts of composite reflectivity and radar echoes, aligning them more closely with actual observations. Consequently, the Threat Score (TS) and Equitable Threat Score (ETS) for heavy-rain forecasts (>10 mm/h) over the next 5 h are markedly enhanced. This study underscores the necessity of incorporating XPAR data assimilation in numerical weather prediction practices and lays the groundwork for the future joint assimilation of SMSR and XPAR data.

The distributed strategy for asynchronous observations in data-driven wildland fire spread prediction

Background Asynchronous observations refer to observations that are obtained at multiple moments. The observation moments of fire fronts may differ throughout an entire wildfire area. Asynchronous observations include historical data, which hinders the effectiveness of data assimilation due to the lack of timely updates on changing fire fronts. Aims This paper proposed a distributed strategy combined with the Ensemble Transform Kalman filter (ETKF-distributed) for asynchronous observations. It can assimilate fire fronts immediately at any location by using new matching schemes between prediction and observation. Methods The ETKF-distributed undergoes testing using a wildland fire generated based on real terrain, vegetation, and historical weather data from the local area. In addition, the ETKF and ETKF-centralised proposed in our previous work were employed as comparisons. Observing System Simulation Experiments were conducted to generate asynchronous observation fire fronts. Key results The benefit of immediate assimilation enables the new method to maintain high accuracy predictions. Conclusions The allocation of observation resources can be focused in regions with high rates of speed when employing ETKF-distributed. Implications The ETKF-distributed has high efficiency and adaptability, making it highly promising for implementation in wildfire prediction.

Comparison of Chromatic Assimilation Effects Depending on Printing Substrate in the Munker-White Model

Understanding the influence of paper surface structures on color perception is crucial for the printing industry. This research investigates the impact of horizontal and vertical parallel lines on chromatic assimilation using the Munker-White grid model. The study employs the perceived ∆E00 metric to quantify color differences and determine whether these textures affect perceived color accuracy and consistency differently. Results reveal variations in color perception due to surface textures. The biggest color difference (ΔE00) occurred at 60% RTV coverage for cyan, where the vertical structure showed a significantly lower value than the horizontal. For the yellow primary stimulus, the greatest difference was observed at 20% RTV coverage, with both structures showing high initial values that decrease with increased coverage. These findings provide valuable insights for improving color management practices and enhancing the quality and reliability of color reproduction on various substrates, contributing to advancements in printing technology and color science.

Decolonising cultural policy: the cultural and linguistic rights of the Sámi in Finland

In this article, the writer considers the current state of the cultural and linguistic rights of the Sámi, how they are supported by cultural policy and how decolonising cultural policy could contribute to the ongoing struggles of realising the self-determination and cultural rights of the Sámi. The article stipulates that concrete steps need to be taken for decolonising cultural policy in Finland specifically concerning the cultural and human rights of the Sámi. Cultural policy should be based on cultural rights, thus introducing decolonial practices in support of the Sámi culture and languages and into the culture policy and funding is imperative. The article suggests creating decolonial practices of research and policymaking rooted in intersectional and participatory methods that recognise the many forms of discrimination, not only the current-day colonialism or the effects of assimilation but also the intersections of an indigenous identity with other forms of discrimination. Furthermore, contributing to decolonisation should include research on the effects of colonisation on cultural rights, cultural policy and the distribution of funds for promoting the Sámi culture and languages in the Sámi communities and Finland.

The effect of an organomineral chelate complex on the amylolytic activity of intestinal enzymes of some fish species

To date, there is a large amount of information regarding the effect of heavy metals on the hydrolases of the digestive tract. It has been established that even biogenic metals in high concentrations can have a toxic effect. The assessment of the activity of digestive hydrolases is relevant, since a change in their activity has a direct effect on the effectiveness of assimilation of food. Amylolytic hydrolases help to provide the body with carbohydrates (along with fats) – the main sources of energy for fish. A decrease in the intake of carbohydrates will lead to a violation of metabolic processes and, as a result, underdevelopment and death of fish. The aim of the study was to determine the effect of an organomineral chelate complex on the amylolytic activity of intestinal enzymes of some fish species. The research was conducted at the Department of Biochemistry and Physiology of the St. Petersburg State University of Veterinary Medicine and on the basis of two fisheries in the Leningrad Region. The fish of the experimental groups (n = 10) were given an additive for 30 days, the data were compared with the control (n = 10). The drug was given together with the feed once a day, at a concentration of 0.5 g / kg (feed weight). Fingerlings (0+) of 3 species of freshwater bony fish were used as research objects: Carassius auratus (n=20), Cyprinus carpio (n=20), Oncorhynchus mykiss (n=20). Amylolytic activity was determined in the total homogenets of the intestinal mucosa of fish. The activity was assessed by the increase in hexoses by the Nelson method in the modification of Ugolev, Jesuitova. The detection was carried out on a photoelectric KKK-3 photometer. Based on the studies obtained, it can be concluded that the use of an organomineral chelate complex in the studied dosage (previously worked out in conditions of determining acute and chronic toxicity for fish) does not have a negative effect on the amylolytic activity of intestinal enzymes. There was no significant decrease in amylolytic activity in all experimental groups. Based on this, it is possible to recommend the use of a chelate complex for fish in industrial aquaculture.

Determination of soil phenanthrene degradation through a fungal-bacterial consortium.

Fungal-bacterial consortia enhance organic pollutant removal, but the underlying mechanisms are unclear. We used stable isotope probing (SIP) to explore the mechanism of bioaugmentation involved in polycyclic aromatic hydrocarbon (PAH) biodegradation in petroleum-contaminated soil by introducing the indigenous fungal strain Aspergillus sp. LJD-29 and the bacterial strain Pseudomonas XH-1. While each strain alone increased phenanthrene (PHE) degradation, the simultaneous addition of both strains showed no significant enhancement compared to treatment with XH-1 alone. Nonetheless, the assimilation effect of microorganisms on PHE was significantly enhanced. SIP revealed a role of XH-1 in PHE degradation, while the absence of LJD-29 in 13C-DNA indicated a supporting role. The correlations between fungal abundance, degradation efficiency, and soil extracellular enzyme activity indicated that LJD-29, while not directly involved in PHE assimilation, played a crucial role in the breakdown of PHE through extracellular enzymes, facilitating the assimilation of metabolites by bacteria. This observation was substantiated by the results of metabolite analysis. Furthermore, the combination of fungus and bacterium significantly influenced the diversity of PHE degraders. Taken together, this study highlighted the synergistic effects of fungi and bacteria in PAH degradation, revealed a new fungal-bacterial bioaugmentation mechanism and diversity of PAH-degrading microorganisms, and provided insights for in situ bioremediation of PAH-contaminated soil.IMPORTANCEThis study was performed to explore the mechanism of bioaugmentation by a fungal-bacterial consortium for phenanthrene (PHE) degradation in petroleum-contaminated soil. Using the indigenous fungal strain Aspergillus sp. LJD-29 and bacterial strain Pseudomonas XH-1, we performed stable isotope probing (SIP) to trace active PHE-degrading microorganisms. While inoculation of either organism alone significantly enhanced PHE degradation, the simultaneous addition of both strains revealed complex interactions. The efficiency plateaued, highlighting the nuanced microbial interactions. SIP identified XH-1 as the primary contributor to in situ PHE degradation, in contrast to the limited role of LJD-29. Correlations between fungal abundance, degradation efficiency, and extracellular enzyme activity underscored the pivotal role of LJD-29 in enzymatically facilitating PHE breakdown and enriching bacterial assimilation. Metabolite analysis validated this synergy, unveiling distinct biodegradation mechanisms. Furthermore, this fungal-bacterial alliance significantly impacted PHE-degrading microorganism diversity. These findings advance our understanding of fungal-bacterial bioaugmentation and microorganism diversity in polycyclic aromatic hydrocarbon (PAH) degradation as well as providing insights for theoretical guidance in the in situ bioremediation of PAH-contaminated soil.

Experimental Evidence That Demand Characteristics Do Not Play a Dominant Role in the Evaluative Conditioning Effect

The evaluative conditioning (EC) effect has been documented in many experiments: Participants typically prefer stimuli that co-occurred with positive stimuli over stimuli that co-occurred with negative stimuli. The present research attempted to test whether demand characteristics are a dominant cause of the EC effect. In three experiments, we informed participants of the research hypothesis, sometimes indicating an expectation of a contrast effect, rather than an assimilative effect. That manipulation hardly moderated the EC effect. The manipulation influenced participants’ beliefs regarding the research hypothesis, although participants generally believed that an assimilative effect is a more plausible research hypothesis than a contrast effect. Even participants who believed that the researchers expected a contrast effect or assumed that stimulus co-occurrence typically causes a contrast effect still showed an assimilative effect. The results suggest that although demand characteristics might influence the EC effect, the overall influence of that factor is minor.

Effects of open boundary bias correction and data assimilation in a regional ocean circulation model for the East Sea

Effects of open boundary bias correction and data assimilation in a regional ocean circulation model for the East Sea

Examining blockchain adoption determinants and supply chain performance: an empirical study in the logistics and supply chain management industry

PurposeThe purpose of this study is to explore the potential impact of blockchain technology on supply chain performance (SCP). This study further delves into the enablers of blockchain adoption (BA) in SCM and investigates both the direct and mediated effects of blockchain assimilation on garnering a competitive edge in the supply chain and bolstering innovation proficiency, ultimately enhancing SCP.Design/methodology/approachThis study used a quantitative approach, leveraging partial least squares structural equation modelling. Empirical data were sourced from 500 validated data sets obtained through questionnaires.FindingsThe results indicate that technological readiness and knowledge sharing are key drivers for integrating blockchain into supply chains, with technology readiness displaying a substantially stronger influence. Furthermore, BA significantly enhances supply chain innovation capabilities (SCIC), competitive performance (CP) and overall supply chain efficiency. Notably, both SCIC and CP mediate and amplify the positive effects of blockchain on SCP, emphasising the vital role of innovation and competition in optimising the benefits of blockchain.Originality/valueTo the best of the authors’ knowledge, this study is the first to bridge the gap in the literature connecting SCM and blockchain. The established model augments the theoretical discourse on the SCM-blockchain, offering scholars a validated framework that can be adapted and built upon in future studies.

Development and preliminary validation of a land surface image assimilation system based on the Common Land Model

Abstract. Data assimilation is an essential approach to improve the predictions of land surface models. Due to the characteristics of single-column models, assimilation of land surface information has mostly focused on improving the assimilation of single-point variables. However, land surface variables affect short-term climate more through large-scale anomalous forcing, so it is indispensable to pay attention to the accuracy of the anomalous spatial structure of land surface variables. In this study, a land surface image assimilation system capable of optimizing the spatial structure of the background field is constructed by introducing the curvelet analysis method and taking the similarity of image structure as a weak constraint. The fifth-generation ECMWF Reanalysis – Land (ERA5-Land) soil moisture reanalysis data are used as ideal observation for the preliminary effectiveness validation of the image assimilation system. The results show that the new image assimilation system is able to absorb the spatial-structure information of the observed data well and has a remarkable ability to adjust the spatial structure of soil moisture in the land model. The spatial correlation coefficient between the model surface soil moisture and observation increased from 0.39 to about 0.67 after assimilation. By assimilating the surface soil moisture data and combining these with the model physical processes, the image assimilation system can also gradually improve the spatial structure of soil moisture content at a depth of 7–28 cm, with the spatial correlation coefficient between the model soil moisture and observation increased from 0.35 to about 0.57. The forecast results show that the positive assimilation effect could be maintained for more than 30 d. The results of this study adequately demonstrate the application potential of image assimilation system in short-term climate prediction.

Effects of Nitrate Assimilation in Leaves and Roots on Biomass Allocation and Drought Stress Responses in Poplar Seedlings

Knowledge of tree biomass allocation is fundamental for estimating forest acclimation and carbon stock for global changes in the future. Optimal partitioning theory (OPT) and allometric partitioning theory (APT) are two major patterns of biomass allocation, and occurrences have been tested on taxonomical, ontogenetic, geographic and environmental scales, showing conflicting results and unclear ecophysiological mechanisms. Here, we examine the biomass allocation patterns of two young poplar (Populus) clones varying greatly in drought resistance under different soil water and nitrogen availabilities and the major physiological processes involved in biomass partitioning. We found that Biyu, a drought-sensitive hybrid poplar clone, had significant relations among biomass of leaf, stem and root, showing allometric partitioning. Xiaoye, a drought-tolerant poplar clone native to semi-arid areas, on the contrary, showed tightly regulated biomass allocation following optimal partitioning theory. Biyu had higher nitrate reductase activity in the fine roots, while Xiaoye had higher nitrate reductase activity in the leaves. Biochemical analyses and measurements of fluorescence and gas exchange showed that Xiaoye maintained more stable chloroplast membranes and photosystem electron flow, showing higher water use efficiency and a higher resistance to drought. A nitrogen addition could improve leaf photosynthesis and growth both in Biyu and Xiaoye seedlings under drought conditions. We concluded that the two poplar clones showed different biomass allocation patterns and suggest that the site of nitrate assimilation may play a role in biomass partitioning under varying water and nitrogen availabilities.