Significant Change Points Research Articles

Homogeneity tests and non-parametric analyses of tendencies in precipitation time series in Keszthely, Western Hungary

This study aims to investigate the precipitation trends in Keszthely (Western Hungary, Central Europe) through an examination of historical climate data covering the past almost one and a half centuries. Pettitt’s test for homogeneity was employed to detect change points in the time series of monthly, seasonal and annual precipitation records. Change points and monotonic trends were analysed separately in annual, seasonal and monthly time series of precipitation. While no break points could be detected in the annual precipitation series, a significant decreasing trend of 0.2–0.7 mm/year was highlighted statistically using the autocorrelated Mann-Kendall trend test. Significant change points were found in those time series in which significant tendencies had been detected in previous studies. These points fell in spring and winter for the seasonal series, and October for the monthly series. The question therefore arises of whether these trends are the result of a shift in the mean. The downward and upward shift in the mean in the case of spring and winter seasonal amounts, respectively, leads to a suspicion that changes in precipitation are also in progress in these seasons. The study concludes that homogeneity tests are of great importance in such analyses, because they may help to avoid false trend detections.

The spatial-temporal distributions of controlling factors on vegetation growth in Tibet Autonomous Region, Southwestern China

Due to cold and arid climate of Tibet Autonomous Region, vegetation growth is considered to be controlled by both moisture availability and warmth. In order to reveal the patterns of regional climate change and the mechanisms of climate-vegetation interactions, long term (1982–2013) datasets of climate variables and vegetation activities were collected from Climatic Research Unit (CRU) and Global Inventory Monitoring and Modeling System (GIMMS). Principal regression analysis and (partial) correlation analysis were conducted to reveal the contributions of controlling factors on vegetation growth. Study results showed that (1) Annual mean air temperature (TMP) had increased by 0.38 °C per decade (P = 0.00) and annual precipitation (PRE) had increased by 17.25 mm per decade (P = 0.15). A significant change point around the year 1997/1998 was detected by Mann-Whitney-Pettit test, coinciding with the occurrence of El Niño event. (2) Normalized Difference Vegetation Index (NDVI) had an insignificant positive trend. Spatially, pixels of high NDVI values, great NDVI trends and high inter-annual deviations are distributed in the densely vegetated eastern part. Principal regression analysis revealed that, alpine grassland (northern and western part) is mostly controlled by temperature, steppe meadow (middle and southern part) is mostly controlled by precipitation, and shrub/mixed needle leaved and broad leaved forest (eastern part) is mostly controlled by cloud coverage. (3) Partial correlation analyses showed that regions with high sensitivity to precipitation nearly overlapped with regions of high sensitivity to minimum temperature. And the high importance of cold index (CDI, accumulated negative difference between TMP and 5 °C) revealed in this study implied the effects of regional glacial melting and permafrost degradation. We concluded that the regional climate change can be characterized as warming and wetting. Different regions and vegetation types in Tibet Autonomous Region demonstrated different driving climate factors and climate-vegetation relationships.

Copy Number Variation Detection Using Total Variation.

Next-generation sequencing (NGS) technologies offer new opportunities for precise and accurate identification of genomic aberrations, including copy number variations (CNVs). For high-throughput NGS data, using depth of coverage has become a major approach to identify CNVs, especially for whole exome sequencing (WES) data. Due to the high level of noise and biases of read-count data and complexity of the WES data, existing CNV detection tools identify many false CNV segments. Besides, NGS generates a huge amount of data, requiring to use effective and efficient methods. In this work, we propose a novel segmentation algorithm based on the total variation approach to detect CNVs more precisely and efficiently using WES data. The proposed method also filters out outlier read-counts and identifies significant change points to reduce false positives. We used real and simulated data to evaluate the performance of the proposed method and compare its performance with those of other commonly used CNV detection methods. Using simulated and real data, we show that the proposed method outperforms the existing CNV detection methods in terms of accuracy and false discovery rate and has a faster runtime compared to the circular binary segmentation method.

Secondary sex ratio and trends in the associated gender-specific births near nuclear facilities in France and Germany: Update of birth counts

Increases in childhood cancer near nuclear facilities in France and in Germany as well as elevated human birth sex ratios after the atmospheric atomic bomb tests and after Chernobyl motivated the inspection of the secondary sex ratio and the corresponding gender-specific birth counts in the vicinity of nuclear facilities. Focus is on which changes in the birth counts go along with significant changes in the sex ratios. Official municipality-specific annual birth counts by sex for all of France and for whole Germany are updated until 2016 and 2017, respectively. Using logistic regression, we determine significant change-points (jumps) after distinct radiological events in sex ratio time-trends in circular areas around pertinent nuclear facilities. With Poisson regression, we quantify the corresponding change-points in the trends of absolute annual birth counts for boys and girls. In the 35-km vicinity of the ‘Centre de l’Aube Nuclear Disposal Facility (CSA)’ in France in the year 2000, we observe a jump in the sex odds (SO) with sex odds ratio (SOR) 1.101; 95% CI: (1.033, 1.175), p-value 0.0033. This jump in the sex odds can be associated with a drop in boys of 3.44% (−4.02, 10.37), p-value 0.3561, and a drop in girls of 8.44% (1.33, 15.04), p-value 0.0208. In the highly populated area around the nuclear power plant Philippsburg in Germany from 2001 onward, we see a similar effect: SOR 1.027 (1.008, 1.046), p-value 0.0045; drop in boys 5.56% (2.24, 8.76), p-value 0.0012; drop in girls 6.92% (3.62, 10.10), p-value <0.0001. The presented findings corroborate and specify earlier observations and call for intensifying bio-physical research in exposure mechanisms and exposure pathways of natural or artificial ionizing radiation including neutron radiation and neutron activation. Reinforced biological and epidemiological research should aim at clarifying the associated genetic and carcinogenic consequences at the population level.

No Significant Shift of Warming Trend over the Last Two Decades on the Mid-South of Tibetan Plateau

Climate warming on the Tibetan Plateau has been regarded as an important driving force of regional environmental change. Although several studies have analyzed the shift of warming trends on this plateau within the context of a recent global warming “hiatus” since 1998, their disparate findings have hindered a comprehensive and regional understanding. Based on the daily mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) collected from meteorological stations on the period of 1961–2017, we re-examined the timing and magnitude of temperature phase change using piecewise linear regression on the mid-south of Tibetan Plateau. The results show that among the trends in regional annual Tmean, Tmax and Tmin, the statistically significant change-point was observed only in annual Tmax (p &lt; 0.01). The warming trend of annual Tmax has accelerated significantly since 1992 and has exceeded that of annual Tmin after 2000, causing a remarkable reversal from decline to increase in diurnal temperature range (DTR) (p &lt; 0.01). Spatially, the occurrence time of change-points in Tmean, Tmax, and Tmin varied among stations, but most of them occurred before the mid-1990s. Besides, the trend shifts in Tmax/DTR during the cold season played a primary role in the significant trend shifts in annual Tmax/DTR. This study underscores that there is no significant shift of warming trends over the last two decades on the mid-south of Tibetan Plateau.

Analysis of hydrometeorological variables over the transboundary Komadugu-Yobe basin, West Africa

Abstract Spatiotemporal trends in daily observed precipitation, river discharge, maximum and minimum temperature data were investigated between 1971 and 2013 in the Komadugu-Yobe basin. Significant change points in time series are corrected using Adapted Caussinus-Mestre Algorithm for homogenizing Networks of Temperature series algorithm. Mann–Kendall test and Sen's slope are used to estimate the trend and its magnitude at dry, wet and annual season time scales, respectively. Preliminary results show an increasing trend of the observed variables. There is a latitudinal increase (decrease) in the basin temperature (precipitation) from lower to higher latitudes. The minimum temperature (0.05 °C/year) increases faster than the maximum temperature (0.03 °C/year). Overall, the percentage changes in minimum temperature range between 3 and 10% while that of maximum temperature ranges between 1 and 3%. Due to precipitation dependence on regional characteristics, the highest percentage change was recorded in precipitation with values between −5 and 97%. In all time scales, river discharge and precipitation have strong positive correlations while the correlation between river discharge and temperature is negative. It is imperative to advocate and support positive developmental practices as well as establishing necessary mitigation measures to cope with the effects of climate in the basin.

High‐quality sea surface temperature measurements along coast of the Bohai and Yellow Seas in China and their long‐term trends during 1960–2012

AbstractAs semi‐enclosed and shallow seas, the Bohai and Yellow Seas (hereafter, BYS) marine ecosystems are more easily affected by natural and anthropogenic climate changes than those in the open oceans. An accurate assessment of sea surface temperature (SST) change is crucial for the near‐shore water environment. In this work, new high‐quality monthly mean SST time series from 11 in situ coastal hydrological stations at BYS for the period of 1960–2012 have been generated. Monthly mean SST time series were initially subjected to penalized maximal t (PMT) test, using homogeneous monthly mean surface air temperature (SAT) series as references. Homogenized monthly mean SST series were obtained by adjusting all significant change points which have been supported by historic metadata. Our study shows that there are 29 significant change points in these 11 SST series. The majority of them are caused by instrument changes and station relocations—both account for about 51.7 and 31%, respectively. Then, homogeneous SST series are used to assess the long‐term trends. As the regional average, the annual mean homogeneous SST series shows a rapid warming trend, with the rate of 0.21°C/decade. Compared to the homogeneous SST series, the original SST series underestimate the long‐term trend (only 0.13°C/decade), indicating the artificial change points usually result in a warm‐bias in the early period measurements. Seasonally, the most significant warming occurs in boreal winter during the period analysed. The relationships of the significant warming in boreal winter and atmospheric circulation modes have also been investigated. Results reflect the remarkable and direct influence of the East Asian Trough (EAT) on SST along the coastal BYS.

BIRTH COHORT ANALYSIS OF TRENDS IN AMNESTIC MILD COGNITIVE IMPAIRMENT (MCI)

Prior work suggests that dementia incidence rates may be declining in western nations. However, data regarding temporal trends in amnestic mild cognitive impairment (aMCI) incidence are limited. The Einstein Aging Study (EAS) provided the opportunity to examine whether age specific aMCI incidence rates have declined over sequential birth cohorts from 1915 to 1935, and whether trends in aMCI rates have differed for white and black older adults. Age specific incidence of aMCI was examined by birth year for 1,233 individuals age ≥70 who were enrolled in EAS population based cohort between November 1, 1993 and February 22, 2016, did not have cognitive impairment at the time of enrollment and who had at least one annual follow-up clinic visit. aMCI was defined using the updated Petersen criteria as presence of objective memory impairment, subjective memory impairment, and absence of functional decline or clinical dementia. Poisson regression was used to model aMCI incidence as a function of age, sex, race, education and birth year. Profile likelihood was used to identify the timing of noticeable increases or drops in incidence rates, with a change point allowed to fall any time between 1915 and 1935. Additional models were adjusted for trends in self-reported history of diabetes, myocardial infarction and stroke. Analyses included 5,320.9 person years of follow-up. Poisson regression analyses did not yield any significant change point in aMCI incidence rates in the overall cohort (p-value for Likelihood ratio test controlling for age, sex, race/ethnicity and education = 0.76). This result was similar for Blacks and Whites, and among men or women born between 1915 and 1935. Although stroke history was an independent predictor of incident aMCI, inclusion of stroke, MI and diabetes in the models did not change the results

Flood occurrence change-point analysis in the paleoflood record from Lake Mondsee (NE Alps)

Knowledge about changes of flood occurrence patterns is important for risk estimation of the future. Robust and well-calibrated paleoflood records, derived e.g. from lake sediments, are excellent natural archives to investigate flood variability of the past and to use the data for further modelling. In this paper, we analyse a 7100 year summer flood record recovered from Lake Mondsee (NE Alps), using a statistical approach. We identify a point process of renewal type, with a significant change-point of the occurrence pattern around 350 CE, switching from the overlay of two mechanisms of event recurrences of 5 and 50 years before to 2 and 17 years after this change-point. This change-point approach enables a comparison to other flood records, and possibly to relate event frequencies to climatic conditions. We also highlight how lower temporal resolution of flood records can hamper the analysis of relations to climatic signals. Hence high-resolution records with robust chronologies and flood information (e.g. seasonality and event characteristics) are essential to improve the understanding of the interplay between climatic signals and flood occurrences, which is an important ingredient for proper risk estimation and risk management.

Trends in mortality from cutaneous malignant melanoma in Spain (1982-2016): sex-specific age-cohort-period effects.

Mortality from malignant cutaneous melanoma increased alarmingly during the second half of the 20th century in Spain and other European countries. The aim was to analyse sex- and age-specific trends in melanoma mortality in Spain in the period 1982-2016. European age-standardized melanoma mortality rates during the period 1982-2016 were calculated from mortality figures provided by the National Statistics Institute. Joinpoint regressions were used to identify significant points of change in trends and to compute average annual per cent change (AAPC). Age-cohort-period models were fitted to explore the effect of these variables on mortality. During the period 1982-2016, age-standardized melanoma mortality rates increased in Spain from 0.90 to 1.80 deaths per 100 000 people in men and from 0.64 to 1.11 per 100 000 in women, rising noticeably from 1982 to 1995 in both sexes and in all age groups. From the mid-90s different trends were observed depending on sex and age: there was a decrease in mortality in the population younger than 45 years (AAPC -2 in both sexes) and aged 45-64 years (AAPC -1 among men and -0.2 among women), but in the group over 64 years rates continued to increase (AAPC 1.7 and 0.2, respectively, for men and women). The mortality sex ratio decreased in the younger population but increased in older individuals. A cohort effect was observed with lower mortality in the cohorts born after 1943 in men and 1956 in women. There was also a period effect with decreased mortality rates at the beginning of the 1990s. Melanoma mortality rates in Spain increased during the last decades of the 20th century; however, later they stabilized in women and began to decrease in younger cohorts and middle-aged men. Promotion of primary and secondary prevention measures should continue, with particular emphasis on males over 65 years.

Identifying Changepoints in Biomarkers During the Preclinical Phase of Alzheimer's Disease.

Objective: Several models have been proposed for the evolution of Alzheimer’s disease (AD) biomarkers. The aim of this study was to identify changepoints in a range of biomarkers during the preclinical phase of AD.Methods: We examined nine measures based on cerebrospinal fluid (CSF), magnetic resonance imaging (MRI) and cognitive testing, obtained from 306 cognitively normal individuals, a subset of whom subsequently progressed to the symptomatic phase of AD. A changepoint model was used to determine which of the measures had a significant change in slope in relation to clinical symptom onset.Results: All nine measures had significant changepoints, all of which preceded symptom onset, however, the timing of these changepoints varied considerably. A single measure, CSF t-tau, had an early changepoint (34 years prior to symptom onset). A group of measures, including the remaining CSF measures (CSF Abeta and phosphorylated tau) and all cognitive tests had changepoints 10–15 years prior to symptom onset. A second group is formed by medial temporal lobe shape composite measures, with a 6-year time difference between the right and left side (respectively nine and 3 years prior to symptom onset).Conclusion: These findings highlight the long period of time prior to symptom onset during which AD pathology is accumulating in the brain. There are several significant findings, including the early changes in cognition and the laterality of the MRI findings. Additional work is needed to clarify their significance.

Long-Term Monitoring of Cork and Holm Oak Stands Productivity in Portugal with Landsat Imagery

Oak stands are declining in many regions of southern Europe. The goal of this paper is to assess this process and develop an effective monitoring tool for research and management. Long-term trends of the Normalized Difference Vegetation Index (NDVI) were derived and mapped at 30-m spatial resolution for all areas with a stable land cover of cork oak (Quercus suber L.) and holm oak (Quercus ilex L.) forests and agroforestry systems in mainland Portugal. NDVI, a good proxy for forest health and productivity monitoring, was obtained for the 1984–2017 period using Landsat-5 TM and Landsat-7 ETM+ imagery. TM values were adjusted to those of ETM+, after a comparison of site-specific and literature linear equations. The spatiotemporal trend analysis was performed using only July and August NDVI values, in order to minimize the spectral contribution of understory vegetation and its phenological variability, and thus, focus on the tree layer. Signs and significance of trends were obtained for six representative oak stands and the whole country with the Mann Kendall and Contextual Mann-Kendall test, respectively, and their slope was assessed with the Theil-Sen estimator. Long-term forest inventories of six study sites and NDVI time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) allowed validating the methodology and results with independent data. NDVI has a good relationship with cork production at the forest stand level. Pettitt tests reveal significant change-points within the trends in the period 1996–2005, when changes in drought patterns occurred. Twelve percent of the area of oak stands in Portugal presents significant decreasing trends, most of them located in mountainous regions with shallow soils. Cork oak agroforestry is the most declining oak forest type, compared to cork oak and holm oak forests. The Google Earth Engine platform proved to be a powerful tool to deal with long-term time series and for the monitoring of forests health and productivity.

Is equatorial Africa getting wetter or drier? Insights from an evaluation of long‐term, satellite‐based rainfall estimates for western Uganda

Long‐term trends in equatorial African rainfall have proven difficult to determine because of a dearth in ground‐measured rainfall data. Multiple, satellite‐based products now provide daily rainfall estimates from 1983 to the present at relatively fine spatial resolutions, but in order to assess trends in rainfall, they must be validated alongside ground‐based measurements. The purpose of this paper is twofold: (a) to assess the accuracy of four rainfall products covering the past several decades in western Uganda; and (b) to ascertain recent, multi‐decadal trends in annual rainfall for the region. The four products are African Rainfall Climatology Version 2 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN‐CDR), and TAMSAT African Rainfall Climatology And Timeseries (TARCAT). The bias and accuracy of 10‐day, monthly, and seasonal rainfall totals of the four products were assessed using approximately 10 years of data from 10 rain gauges. The homogeneity of the products over multiple time periods was assessed using change‐point analysis. The accuracy of the four products increased with an increase in temporal scale, and CHIRPS was the only product that could be considered sufficiently accurate at estimating seasonal rainfall totals throughout most of the region. TARCAT tended to underestimate totals, and ARC2 and PERSIANN were in general the least accurate products. Only annual rainfall estimates from CHIRPS and TARCAT were significantly correlated with ground‐measured rainfall totals. TARCAT was the most homogeneous product, while ARC2, CHIRPS, and PERSIANN had significant negative change points that caused a drying bias over the 1983–2016 period. After adjusting the satellite‐based rainfall estimates based on the timing and magnitude of the change points, annual rainfall totals derived from all four products indicated that western Uganda experienced significantly increasing rainfall from 1983 to 2016.

Spatial and Temporal Evolution of Low Water Flows in the Sassandra River Catchment Area in Cote d’Ivoire

In a context of climate change and declining water resources, knowledge of low flow is essential. Present study deals with the spatial and temporal evolution of the streams low flow in Sassandra river. In the study, 12 stations of the Sassandra sub-basins (Sassandra, N’zo, Lobo, and Davo) were selected according to the availability and quality of long-term data. Annual, monthly and daily low flow data from twelve hydrological stations of the Sassandra watershed were used and cover the period from 1970 to 2015. The methodology used is concerned with extracting the low flow data and analyzing and evaluating the trends (Mann-Kendall) and change-point (cumulate sum) of low flow data. Statistical tests are applied to the mean and variance of the low-flow series. The results of the statistical tests show more trends and change points on the mean than on the variance. Significant trends show an increase in low flow waters. The significant change point detected by the cumulative sums test generally occurs between 1990-2007. In addition, tributaries are more affected by significant trends and change point detection than Sassandra river.

Water level characteristics of Lake Caizi, lower reaches of the Yangtze River during wintering period based on long-term hydrological alteration

湖泊生态水位过程对维持湖泊生态系统结构、过程和功能的完整性具有重要意义，也是当今湖泊科学领域面临的重要科学问题.基于菜子湖湖区水位站（车富岭水位站）1956-2018年日水位资料，采用pettitt突变检验法分析水位的突变性特征.结合年保证率法得到菜子湖车富岭水位站低水位值，并在此基础上分析了低水位发生时间及历时、候鸟越冬期水位变化速率及其生态水位的区间阈值.主要结论有：菜子湖车富岭水位站1956-2018年年均水位无显著突变.菜子湖车富岭水位站低水位发生时间均值为年内的344 d，年际标准差为27 d，低水位的年均历时为69 d，标准差为49 d，有6年（1978、1997、2015-2018年）未发生低水位事件.菜子湖候鸟越冬期水位变化速率的均值为-0.009 m/d，年均值为-0.034~0.009 m/d，日均值为-0.051~0.016 m/d.菜子湖低水位发生时间的区间阈值为332~351 d，历时的区间阈值为33~98 d，变化速率的区间阈值为-0.070~0.020 m/d.加强菜子湖候鸟越冬期湿地生境保护适应性调度试验研究及生态环境监测，为菜子湖输水水位优化控制和菜子湖湿地生态保护提供科学依据.;The ecological water level process of lakes is of great significance for maintaining the integrity of the lake ecosystem structures, processes and functions, and is also an important scientific issue of lake science field nowadays. Based on the daily water level data, pettitt test was used to analyze the abrupt change characteristics of water level of Lake Caizi at Chefuling Station from 1956-2018. The low water level of Lake Caizi at Chefuling Station was obtained using the annual guaranteed frequency method. The starting time and duration of low water level, the water level change rate during the overwintering period of migratory birds and the interval threshold of ecological water level were analyzed accordingly. The main conclusions are as follows:there is no significant abrupt change point in the average annual water level of Lake Caizi at Chefuling Station from 1956 to 2018. The average occurrence time of low water level of Lake Caizi at Chefuling Stations is day 344, with the inter-annual standard deviation 27 days. The average duration time of annual low water level is 69 days with the standard deviation 49 days. Among the calculated 63 years, there are 6 years (1978, 1997, 2015-2018) without low water level event. The average rate of water level change during the overwintering period of migratory birds is -0.009 m/d, the annual average rate is -0.034-0.009 m/d, and the daily average rate is -0.051-0.016 m/d. The interval threshold of the occurrence of low water level of Lake Caizi is 332-351 d, the interval threshold of the duration time is 33-98 d, and the interval threshold of water level change rate is -0.070-0.020 m/d. Strengthening experimental study on habitat adaptation and ecological environment monitoring during the overwintering period of migratory birds to provide scientific basis for water level regulation and wetland protection of the Lake Caizi.

Credentialing for robotic lobectomy: what is the learning curve? A retrospective analysis of 272 consecutive cases by a single surgeon.

Credentialing processes for surgeons seeking robotic thoracic surgical privileges are not evidence-based, and the learning curve has not been reported. The goal of this study is to review our experience with robotic lobectomies and provide evidence for the development of a more uniform credentialing process. We performed a retrospective review of the first 272 consecutive robotic lobectomies performed between 2011 and 2017 by a single surgeon with prior video-assisted thoracoscopic (VATS) experience. Primary outcomes were operative duration, blood loss, chest tube duration, length of hospital stay, intraoperative complication, and conversion to thoracotomy. The patients were subdivided by surgical date into two cohorts of 120 consecutive patients to compare differences in outcomes, thereby illustrating the learning curve. Between 2011 and 2017, 272 patients (median age 67.5years) underwent a robotic lobectomy by a single surgeon. The majority of patients (157/272) had early stage (T1N0) adenocarcinoma. For the entire cohort, median operative time was 160min (83-317min). The median blood loss was 75mL (10-4000mL). Median chest tube duration was 2days (1-23days) and median hospital stay was 3days (1-25days). Intraoperative complications occurred in seven patients. Only six patients required conversion to thoracotomy. Using multivariable logistic regression, it was found that the age, gender, and stage do not factor into conversion to thoracotomy, but BMI was found to be a significant covariate (p 0.043). As the surgeon performs more surgeries, there is a significantly shorter operative time (p < 0.001), decreased blood loss (p < 0.001), and shorter hospital stay (p < 0.014). When the first 120 and last 120 surgeries were compared, there was significantly less blood loss (234.6 vs 78.69cc, p < 0.001), shorter operative time (181.9 vs 147.4min, p < 0.001), shorter tube duration (3.49 vs 3.11 days, p 0.007), and shorter length of stay (4.03 vs 3.48 days, p < 0.001), respectively. More intraoperative complications were observed during the first 120 surgeries (6/120) compared to the last 120 surgeries (0/120; Fischer exact p = 0.029). Regression model plots did not show any apparent and significant change points, but rather a steady improvement. The more cases the surgeon does, the better is the outcome in terms of operative duration, blood loss, post-operative length of stay and intraoperative complications. The learning curve for robotic surgery for a surgeon with prior VATS experience is that of a continuous improvement with experience instead of a particular change point. Since most thoracic surgeons who perform robotic-assisted surgery have already gotten past their VATS learning curves, they no longer have a definable learning curve for robotic surgery. Hence, if a surgeon is already proficient and credentialed to perform VATS lung resections, he or she is no longer faced with a significant learning curve for robotic lung resections, and should be credentialed to do so once he or she has undergone the appropriate training with the equipment and technology.

Modeling multi-decadal mangrove leaf area index in response to drought along the semi-arid southern coasts of Iran

Leaf Area Index (LAI; as an indicator of the health) of the mangrove ecosystems on the northern coasts of the Persian Gulf and the Gulf of Oman was measured in the field and modeled in response to observed (1986–2017) and predicted (2018–2100) drought occurrences (quantified using the Standardized Precipitation Index [SPI]). The relationship of LAI with the normalized difference vegetation index (NDVI) obtained from satellite images was quantified, the LAI between 1986 and 2017 retrospectively estimated, and a relationship between LAI and SPI developed for the same period. Long-term climate data were used as input in the RCP8.5 climate change scenario to reconstruct recent and forecast future drought intensities. Both the NDVI and the SPI were strongly related with the LAI, indicating that realistic LAI values were derived from historic satellite data to portray annual changes of LAI in response to changes in SPI. Our findings show that projected future drought intensities modeled by the RCP8.5 scenario increase more and future LAIs decreased more on the coasts of the Gulf of Oman than the coasts of the Persian Gulf in the coming decades. The year 1998 was the most significant change-point for mean annual rainfall amounts and drought occurrences as well as for LAIs and at no time between 1998 and 2017 or between 2018 and 2100 are SPI and LAI values expected to return to pre-1998 values. LAI and SPI are projected to decline sharply around 2030, reach their lowest levels between 2040 and 2070, and increase and stabilize during the late decades of the 21st century at values similar to the present time. Overall, this study provides a comprehensive picture of the responses of mangroves to fluctuating future drought conditions, facilitating the development of management plans for these vulnerable habitats in the face of future climate change.

Nonstationarity-based evaluation of flood frequency and flood risk in the Huai River basin, China

Using monthly streamflow data from 9 gauging stations covering a period of 1960–2014 across the Huai River basin, China, the Pettitt method and GAMLSS model were used to quantify flood frequency and related implications for flood hazards. Results indicated that: (1) no significant change points were observed in flood flows at the Huangchuan, Hengpaitou and Bengbu stations. However, significant hydrological alterations were detected for flood flows at other 6 stations with change points during ∼2000; (2) flood flows at the Bantai, Jiangjiaji and Hengpaitou stations were nonstationary but stationary flood flows were detected at other 6 stations. The Weibull distribution was the appropriate probability distribution describing flood flows across the Huai River basin and the lognormal distribution is the second best distribution; (3) no significant difference was detected for 10- and 20-year flood frequencies using the Pearson III type distribution function under the stationarity assumption. However, significant and increasing differences were expected for 30-, 50- and 100-year floods. It can be concluded that the assumption of stationarity, if the flood flows are actually nonstationary, can produce biased flood frequencies using Pearson III type distribution, and this result provides a critical reference for flood frequency analysis under the nonstationarity and/or stationarity assumption; (4) after 30 years, the flood magnification factor at Hengpaitou and Bengbu stations increased from 1 to 1.12 and from 1 to 1.06, respectively, implying higher flood risks at the Hengpaitou station. In addition, after 30 years, the return period of 100 year flood decreased from 100 years to less 70 years at the Hengpaitou station and from 100 years to nearly 78 years, implying higher frequency of floods with return periods of 100 years. Moreover, significant relations were detected between annual peak flood flow and flood-affected crop areas, implying that annual peak flood flow can be taken as an indicator of flood disasters across the Huai River basin and even in the Anhui province.

Irrigation water management in arid regions of Middle East: Assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data

Spatial and temporal distribution of reference (ETo) and actual evapotranspiration (AET) over the central region of Saudi Arabia during 1950–2013 are estimated using remote sensing and GIS techniques. Firstly, the FAO Penman-Monteith method was used to model the spatial distribution of ETo on a grid-by-grid basis using data collected from meteorological stations and GIS techniques. Then, crop coefficients (Kc) were modeled as a function of 16-day time-series MODIS normalized difference vegetation index (NDVI). Next, using Kc maps and ETo as input, daily AET was simulated by the soil water balance (SWB) model and aggregated to monthly and annual AET. From empirical NDVI-Kc relationships developed and applicable at pixel level, Kc derived from the NDVI-Kc relationships agree well with Kc recommended by FAO over various crop growth stages in the field. The monthly AET maps for 1950–2013 show a gradual increase in AET during the crop-growing season in January to May but a subsequent decline as the season progresses from June to December. The AET estimated for January to June are arranged in descending order, which are May (3.67–44.7 mm/day), April (5.99–36.8 mm/day), March (2.96–32.7 mm/day), February (0.68–20 mm/day), June (2.42–17.7 mm/day) and January (1–11 mm/day), respectively. Statistical analysis shows that statistically significant change point in daily AET generally occurred in 1990, such that the long-term average daily AET of 1950–1990 at 3.6 mm/day increased to about 5.3 mm/day between 1990 and 2016 with a positive trend of 1.5 mm/decade. The annual AET estimated for irrigated cropland in northern and central regions of Riyadh, Al-Qassim province and Hail province range from 1200 to 2900 mm/year. In these regions, low AET values are found in shrubland, grassland, and other natural vegetation. The annual AET estimated by the SWB model are about 9–11% higher than modeled AET in the study area, where the long-term average daily AET estimated for 1950–2013 range from 2 mm/day to 30 mm/day. Representative AET maps derived from applying the NDVI-Kc relationships to the SWB model will be useful to achieve the planning and management of sustainable water use in arid regions of Middle East.

Nonparametric change point detection in multivariate piecewise stationary time series

ABSTRACTDetecting change points in multivariate time series is an important problem with numerous applications. We develop a nonparametric method to detect multiple change points in multivariate piecewise stationary processes when the locations and number of change points are unknown. Based on a test statistic that measures differences in the spectral density matrices through the norm, we sequentially identify points of local maxima in the test statistic and test for the significance of each of them being change points. In addition, the components responsible for the change in the covariance structure at each detected change point are identified. The asymptotic properties of the test for significant change points under the null and alternative hypothesis are derived. We illustrate the better performance of our method in comparison to some of the recent methods through a few simulation examples and discuss applications of our method in seismology and finance.