Analysis of Spatial-Temporal Variations of Drought in Oklahoma

Drought is a recurrent natural hazard that has impacts on agriculture, hydrology, ecosystem, and social-economy. A comprehensive analysis of drought is valuable for drought assessment and mitigation. Oklahoma is a state that frequently experiences drought. The goal of this dissertation is to analyze the spatial-temporal patterns of drought in Oklahoma. Specifically, it developed a new drought index and evaluated it against a number of widely-used drought indices. Then, the spatial-temporal patterns of drought in Oklahoma were investigated using the most suitable drought index. Finally, the impacts of climate oscillations on the drought were quantified and used to develop drought forecasts. A new drought index called the Precipitation Evapotranspiration Difference Condition Index (PEDCI) was developed. It overcomes a number of the limitations of other drought indices. The comparison of PEDCI and six widely used drought indices (Palmer’s Drought Severity Index, Z-Index, Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index, percent normal, and percentiles) demonstrated that the performance of drought indices varies temporally and spatially. The SPEI is the drought index that is the most representative of soil moisture conditions. The correlations with winter wheat yield indicated that drought indices such as SPEI, Z-Index and PEDCI, which are based on precipitation and evapotranspiration, are most appropriate for representing the impact of drought conditions on crop yield. Oklahoma was divided into four regions (southeast, southwest, northeast, and northwest Oklahoma) for the spatial and temporal analysis of drought. Drought frequency in northwest Oklahoma is higher than in other regions, and the frequency in spring is higher than in other seasons. There is a decadal-scale drought cycle in Oklahoma. Droughts are caused by both decreases in precipitation and increases in evapotranspiration, especially in recent years. Finally, drought is influenced by multiple climate oscillations. Seven regression models were developed for producing drought forecasts. The CCA-based regression model using multiple teleconnections at different lags was more skillful than the other drought forecast models. While skill is limited in some seasons, this method has promise for providing drought early warning in Oklahoma

Identification of academic peer effects in college: Does data aggregation matter?

This study exploited random roommate assignments in a small Chinese college to estimate the causal effects of roommates’ scores on the national College Entrance Test (CET) on first-year students’ Grade Point Average (GPA). Analyzing data on an entire cohort of enrolled students, we found that the level of aggregation, for both the peer-ability measure and one’s own academic-outcome measure, matters for the identification of academic peer effects. Specifically, while roommates’ average CET score has a barely significant impact, the highest-scoring roommate’s CET score has a strong positive impact. Peer effects are also larger for one’s GPA for required courses than that of elective courses. Finally, peer effects in both types of courses decline over time while the effects of one’s own CET score increase over time, suggesting that students in this college tend to substitute their own ability for peer ability as they become more academically independent

How are Income and Non-Income Factors Different in Promoting Happiness? An Answer to the Easterlin Paradox

This paper develops a formal economic theory to explain the Easterlin paradox-average happiness levels do not necessarily increase as countries grow wealthier. The theory analyzes the different roles of income and non-income factors in promoting people's happiness, and provides a foundation for studying happiness from the perspectives of social welfare maximization and individuals' self-interested rationality. It is shown that, for a certain class of economies, whether Easterlin paradox appears depends on the level of non-income factors. Happiness rises with income only up to a critical point that is determined by the level of the non-income factors; but once the critical income level is achieved, raising income further will lead to Pareto ineffcient allocations and decrease people's happiness. One policy implication is that government should promote a balanced growth between income and non-income factors. The empirical analysis provides some preliminary evidence consistent with the theory's predictions

Modeling redistribution of α-HCH in Chinese soil induced by environment factors

This study explores long-term environmental fate of alpha-HCH in China from 1952 to 2007 using ChnGPERM (Chinese Gridded Pesticide Emission and Residue Model). The model captures well the temporal and spatial variations of alpha-HCH concentration in Chinese soils by comparing with a number of measured data across China in different periods. The results demonstrate alpha-HCH grasshopping effect in Eastern China and reveal several important features of the chemical in Northeast and Southeast China. It is found that Northeast China is a prominent sink region of alpha-HCH emitted from Chinese sources and alpha-HCH contamination in Southwest China is largely attributed to foreign sources. Southeast China is shown to be a major source contributing to alpha-HCH contamination in Northeast China, incurred by several environmental factors including temperature, soil organic carbon content, wind field and precipitation. (C) 2011 Elsevier Ltd. All rights reserved.This study explores long-term environmental fate of alpha-HCH in China from 1952 to 2007 using ChnGPERM (Chinese Gridded Pesticide Emission and Residue Model). The model captures well the temporal and spatial variations of alpha-HCH concentration in Chinese soils by comparing with a number of measured data across China in different periods. The results demonstrate alpha-HCH grasshopping effect in Eastern China and reveal several important features of the chemical in Northeast and Southeast China. It is found that Northeast China is a prominent sink region of alpha-HCH emitted from Chinese sources and alpha-HCH contamination in Southwest China is largely attributed to foreign sources. Southeast China is shown to be a major source contributing to alpha-HCH contamination in Northeast China, incurred by several environmental factors including temperature, soil organic carbon content, wind field and precipitation. (C) 2011 Elsevier Ltd. All rights reserved

Impact of Fish Farming on Phosphorus in Reservoir Sediments

Fish farming has seriously influenced the aquatic environment in Sancha reservoir in SW China since 1985 and has been strongly restricted since 2005. Thus, phosphorus speciation in a sediment core dated between 1945 and 2010 at cm-resolution and in surface sediments from Sancha reservoir may allow us track how fish farming impacts phosphorus dynamics in lake sediments. Fish farming shifts the major binding forms of phosphorus in sediments from organic to residual phosphorus, which mostly originated from fish feed. Sorption to metal oxides and association with organic matters are important mechanisms for phosphorus immobilisation with low fish farming activities, whereas calcium-bound phosphorous had an essential contribution to sediment phosphorus increases under intensive fish framing. Notwithstanding the shifting, the aforementioned phosphorus fractions are usually inert in the lake environment, therefore changing phosphorus mobility little. The use of fish feed and water-purification reagents, the most important additives for fish farming, introduce not only phosphorus but also large amounts of sand-sized minerals such as quartz into the lake, to which phosphorus weakly sorbs. The sand-sized minerals as additional sorbents increase the pool of easily mobilisable phosphorus in sediments, which will slow down the recovery of reservoir water due to its rapid re-mobilisation

Timber production assessment of a plantation forest: An integrated framework with field-based inventory, multi-source remote sensing data and forest management history

Timber production is the purpose for managing plantation forests, and its spatial and quantitative information is critical for advising management strategies. Previous studies have focused on growing stock volume (GSV), which represents the current potential of timber production, yet few studies have investigated historical process-harvested timber. This resulted in a gap in a synthetical ecosystem service assessment of timber production. In this paper, we established a Management Process-based Timber production (MPT) framework to integrate the current GSV and the harvested timber derived from historical logging regimes, trying to synthetically assess timber production for a historical period. In the MPT framework, age-class and current GSV determine the times of historical thinning and the corresponding harvested timber, by using a "space-for-time" substitution. The total timber production can be estimated by the historical harvested timber in each thinning and the current GSV. To test this MPT framework, an empirical study on a larch plantation (LP) with area of 43,946 ha was conducted in North China for a period from 1962 to 2010. Field-based inventory data was integrated with ALOS PALSAR (Advanced Land-Observing Satellite Phased Array L-band Synthetic Aperture Radar) and Landsat-8 OLI (Operational Land Imager) data for estimating the age-class and current GSV of LP. The random forest model with PALSAR backscatter intensity channels and OLI bands as input predictive variables yielded an accuracy of 67.9% with a Kappa coefficient of 0.59 for age-class classification. The regression model using PALSAR data produced a root mean square error (RMSE) of 36.5 m(3) ha(-1). The total timber production of LP was estimated to be 7.27 x 10(6) m(3), with 4.87 x 10(6) m(3) in current GSV and 2.40 x 10(6) m(3) in harvested timber through historical thinning. The historical process-harvested timber accounts to 33.0% of the total timber production, which component has been neglected in the assessments for current status of plantation forests. Synthetically considering the RMSE for predictive GSV and misclassification of age-class, the error in timber production were supposed to range from -55.2 to 56.3 m(3) ha(-1). The MPT framework can be used to assess timber production of other tree species at a larger spatial scale, providing crucial information for a better understanding of forest ecosystem service. (C) 2016 Elsevier B.V. All rights reserved.ArticleINTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION.52:155-165(2016)journal articl

Improving winter wheat yield estimation by assimilation of the leaf area index from Landsat TM and MODIS data into the WOFOST model

To predict regional-scale winter wheat yield, we developed a crop model and data assimilation framework that assimilated leaf area index (LAI) derived from Landsat TM and MODIS data into the WOFOST crop growth model. We measured LAI during seven phenological phases in two agricultural cities in China’s Hebei Province. To reduce cloud contamination, we applied Savitzky–Golay (S–G) filtering to the MODIS LAI products to obtain a filtered LAI. We then regressed field-measured LAI on Landsat TM vegetation indices to derive multi-temporal TM LAIs. We developed a nonlinear method to adjust LAI by accounting for the scale mismatch between the remotely sensed data and the model’s state variables. The TM LAI and scale-adjusted LAI datasets were assimilated into the WOFOST model to allow evaluation of the yield estimation accuracy. We constructed a four-dimensional variational data assimilation (4DVar) cost function to account for the observations and model errors during key phenological stages. We used the shuffled complex evolution–University of Arizona algorithm to minimize the 4DVar cost function between the remotely sensed and modeled LAI and to optimize two important WOFOST parameters. Finally, we simulated winter wheat yield in a 1-km grid for cells with at least 50% of their area occupied by winter wheat using the optimized WOFOST, and aggregated the results at a regional scale. The scale adjustment substantially improved the accuracy of regional wheat yield predictions (R2 = 0.48; RMSE= 151.92 kg ha−1) compared with the unassimilated results (R2 = 0.23;RMSE= 373.6 kg ha−1) and the TM LAI results (R2 = 0.27; RMSE= 191.6 kg ha−1). Thus, the assimilation performance depends strongly on the LAI retrieval accuracy and the scaling correction. Our research provides a scheme to employ remotely sensed data, ground-measured data, and a crop growth model to improve regional crop yield estimates

Expression of a LINE-1 endonuclease variant in gastric cancer: its association with clinicopathological parameters

BACKGROUND: Long interspersed nuclear element-1 (LINE-1 or L1), the most abundant and only autonomously active family of non-LTR retrotransposons in the human genome, expressed not only in the germ lines but also in somatic tissues. It contributes to genetic instability, aging, and age-related diseases, such as cancer. Our previous study identified in human gastric adenocarcinoma an upregulated transcript GCRG213, which shared 88% homology with human L1 sequence and contained a putative conserved apurinic/apyrimidinic endonucleas1 domain. METHODS: Immunohistochemistry was carried out by using a monoclonal mouse anti-human GCRG213 protein (GCRG213p) antibody produced in our laboratory, on tissue microarray constructed with specimens from 175 gastric adenocarcinoma patients. The correlation between GCRG213p expression and patient clinicopathological parameters was evaluated. GCRG213p expression in gastric cancer cell lines were studied using Western blotting analysis. L1 promoter methylation status of gastric cancer cells was tested using methylation-specific PCR. BLASTP was used at the NCBI Blast server to identify GCRG213p sequence to any alignments in the Protein Data Bank databases. RESULTS: Most primary gastric cancer, lymph node metastases and gastric intestinal metaplasia glands showed positive GCRG213p immunoreactivity. High GCRG213p immunostaining score in the primary gastric cancer was positively correlated with tumor differentiation (well differentiated, p = 0.001), Lauren’s classification (intestinal type, p < 0.05) and a late age onset of gastric adenocarcinoma (≥65 yrs; p < 0.05). GCRG213p expression has no association with other clinicopathological parameters, including survival. Western blotting analysis of GCRG213p expression in gastric cancer cells indicated that GCRG213p level was higher in gastric cancer cell lines than in human normal gastric epithelium immortalized cell line GES-1. Partial methylation of L1 in gastric cancer cells was confirmed by methylation-specific PCR. BLASTP program analysis revealed that GCRG213p peptide shared 83.0% alignment with the C-terminal region of L1 endonuclease (L1-EN). GCRG213p sequence possesses the important residues that compose the conserved features of L1-EN. CONCLUSIONS: GCRG213p could be a variant of L1-EN, a functional member of L1-EN family. Overexpression of GCRG213p is common in both primary gastric cancer and lymph node metastasis. These findings provide evidence of somatic L1 expression in gastric cancer, and its potential consequences in the form of tumor