Statistical Extrapolation Methods Research Articles

Agrotechnical performance indicators of the asymmetric working body of a fallow cultivator

BACKGROUND: Obtaining sustainable and high-quality harvest is important for the production of agricultural products. It is known that up to 40-45% of all energy costs are spent on preparing the soil for sowing when cultivating agricultural crops. Surface-fallow tillage is a subtle technological process, it influences on normal distribution of the seed material in depth and, as a consequence, the further uniformity of seedlings. To ensure the process flow of pre-sowing preparation of the soil for sowing, a new asymmetric working body for a fallow cultivator was developed in the Donskoy Agrarian Scientific Center, the structural subdivision of the SKNIIMESKh, Zernograd. There is a task to conduct a comparative analysis of operation of the new working body with V-shaped sweeps when preparing the soil for sowing. AIM: Conducting a comparative analysis of operation of a serial V-shaped sweep with the new proposed asymmetric working body of a fallow cultivator by field research in the fields of the Donskoy ANC. METHODS: The research in the fields of Donskoy ANC was conducted according to the GOST 33687-2015 “Machines and tools for surface tillage” regional standard. Well-known statistical extrapolation methods implemented in the Microsoft Excel environment were used for data processing. RESULTS: The optimal operating parameters of the new proposed asymmetric working body have been determined in comparison with the serial working body of a fallow cultivator. CONCLUSIONS: According to the conducted laboratory and field studies, the parameters and operating modes of the new asymmetric working body were obtained.

Extreme load extrapolation and long-term fatigue assessment of offshore wind turbine tower based on monitoring data

Extreme load and fatigue damage are important parameters in the structural design of offshore wind turbines (OWTs). The purpose of this study is to obtain extreme loads and long-term fatigue damage assessment of OWT structures based on measured data. In the present study, a utility-scale OWT was monitored with a dynamic response monitoring system and long-term strains of the OWT tower were collected. Based on the monitoring strain and the operational conditions of the OWT, the load and fatigue characteristics of the OWT tower were discussed. Furthermore, statistical extrapolation of the extreme load of the OWT tower was performed and the applicability of different statistical extrapolation methods was studied. The results indicate that the same probability distribution model does not apply to all wind speeds. The maximum extreme load is extrapolated in the vicinity of the rated wind speed. Finally, the relationship between short-term fatigue damage and long-term fatigue damage of the OWT structure was discussed. Superimposing fatigue from a short calculation period underestimates the long-term fatigue of OWT structures due to significant calculation period impact. Therefore, an evaluation method for OWT structures' long-term fatigue was established to improve the accuracy of long-term fatigue calculation by superimposing short calculation periods.

Statistical Inference Methods for Clinical Medical Data with Missing and Truncated Data

Abstract In clinical medicine, due to some accidents will inevitably produce the situation of missing data, this study for its with missing and truncated data, the use of mathematical statistics methods for inference supplement. After classifying the types of incomplete data, the article utilizes the great likelihood and empirical likelihood to form a linear statistical model to infer such data. It verifies it through simulation experiments and example analysis. In the simulation experiment, for the case of the same missing probability, as the number of samples increases from 150 to 300, the bias, variance, and mean square error of this paper’s algorithm in parameter β 1 are reduced to 0.0122, 0.1435, and 0.1441, respectively. In the actual statistical inference analysis of cardiac disease and heart transplantation, the standard error of this paper’s method reduces by 0.0576 compared with that of CAA, and the inference The results are by the reality. In clinical medicine, this study proposes a practical statistical extrapolation method and a realization path for objective interpretation when incomplete data is present.

State and development prospects of the agricultural tractor fleet in the context of digital transformation of agriculture

BACKGROUND: The digital transformation of various sectors of the national economy including agriculture is one of the main tasks of economic development. The implementation of digital technologies in production processes helps to improve the technical and economic indicators of production by ensuring the timely adoption of optimal management decisions, increasing labor productivity, and reducing the impact of the human factor on production. To ensure the digital transformation of agricultural production, first of all, it is necessary to assess the state of machinery and technology provision for agriculture, in particular, the tractor fleet, in terms of the level of equipment readiness for being equipped with digital systems and the availability of standard technical solutions for equipment adaptation to digital agriculture.
 AIMS: Determination the expected values of indicators of the level of technical and technological state of agricultural production by developing a forecast for the development of the agricultural tractor fleet and the level of provision with these types of equipment for the period up to 2030 taking into account current trends.
 METHODS: For the tractor fleet state assessment, the data taken from specialized databases on the tractor fleet and the area of arable land retired from active agricultural circulation, statistical materials of the Rosstat and Avtoselkhozmash-Holding organizations were used. Statistical extrapolation methods implemented in the Microsoft Excel environment were used to predict the development of the tractor fleet.
 RESULTS: The forecast for the tractor fleet development was made according to two scenarios: pessimistic and optimistic, taking into account the use of digital technologies.
 CONCLUSIONS: The development forecast made it possible to assess the state of the tractor fleet by 2030 according to various scenarios.

Statistical extrapolation methods and empirical formulae for estimating extreme loads on operating wind turbine towers

The wind turbine tower is designed against extreme load during power production with the return period of 50 years. The statistical extrapolation method is widely used to estimate the extreme load of wind turbine tower and is recommended by the IEC Standard 61400–1. However, various statistical extrapolation methods were used in previous studies and their accuracy and efficiency have not been evaluated comprehensively, which is investigated in this research. The validation procedure is assessed by simulating the one-year load of the reference wind turbine. It is found the fitting before aggregation methods with peak loads extracted by block maxima or peak over threshold techniques and three-parameter Weibull fitting function have the best accuracy and robustness. 60 samples for each wind speed are enough and the data below rated wind speed can be neglected for the optimal statistical extrapolation methods. In addition, an empirical formula for the extreme load estimation of wind turbine tower is proposed considering both the mean and fluctuating moment caused by the thrust force on the rotor, drag forces on the tower and nacelle and the gravities of nacelle and rotor. The extrapolation factor is modelled based on the estimated extreme load by the statistical extrapolation method. The proposed empirical formula shows good accuracy for both short-term and long-term extreme loads of wind turbine tower at various wind conditions.

Derivation of water quality criteria for glyphosate and its formulations to protect aquatic life in China.

Extensive use of the herbicide glyphosate leads to a high detection rate in the environment and potential risks to nontarget aquatic life. China ranks first globally in the production and consumption of glyphosate, but there are no glyphosate water quality criteria (WQCs) for protecting aquatic life. Here, data on the acute and chronic toxicity of glyphosate and glyphosate-based formulations (GBFs) to freshwater aquatic life were collected and screened. Significant differences in species sensitivity distributions (SSDs) and toxicity values for acute or chronic toxicity were found between glyphosate and GBFs. The hazardous concentrations for 5% of species (HC5) of glyphosate or GBFs between native and nonnative species were different, and native species were found to be more sensitive to the toxicity of glyphosate. The acute and chronic WQCs derived with the SSD method for glyphosate based on the toxicity data for native species in China were 3.35 and 0.26mg/L, respectively, and those found for GBFs were 0.21 and 0.005mg/L, respectively. The WQCs in this study were quite different from those estimated using similar statistical extrapolation methods in other countries, which reflects the differences in species sensitivity to glyphosate toxicity in different regions. The hazard quotients (HQs) were calculated based on the WQCs and concentrations of glyphosate in some surface waters in China and indicated that glyphosate exhibits medium or high hazard risk in some samples of Tai Lake, surface water in Guiyang, fishpond water in Chongqing, rural drinking water, and surface water and reservoir water in Henan Province. The WQCs of glyphosate and GBFs have scientific significance for the exposure and pollution control of herbicide formulations and the protection of aquatic life in China.

Long-term Survival Benefit of Tafamidis in Patients with Transthyretin Amyloid Cardiomyopathy

Introduction In the pivotal ATTR-ACT study, tafamidis was associated with a 30% lower mortality risk than placebo (PBO) in patients with transthyretin amyloid cardiomyopathy (ATTR-CM) over 30 months. Because patients receiving PBO in ATTR-ACT switched to tafamidis in the ongoing, open-label long-term extension (LTE), the long-term efficacy of tafamidis cannot be directly compared with PBO. A statistical extrapolation method has been used to estimate between-group differences in survival beyond the 30-month trial duration. Hypothesis Comparing observed long-term survival with tafamidis in the LTE with estimated survival with PBO extrapolated from ATTR-ACT will allow fuller assessment of tafamidis survival benefits. Methods In ATTR-ACT, patients with ATTR-CM received tafamidis (80 or 20 mg) or PBO for 30 months. In the LTE, patients previously receiving tafamidis continued on the same tafamidis dose, and those previously receiving PBO were randomized to tafamidis 80 mg or 20 mg. Based on a protocol amendment (July 20, 2018), all patients in the LTE transitioned to tafamidis free acid 61 mg (bioequivalent to tafamidis 80 mg). All-cause mortality was assessed using a Cox proportional hazards model for tafamidis 80/61 mg or PBO/tafamidis in ATTR-ACT/LTE. A gamma model based on patient-level data for the PBO group in ATTR-ACT and best model fitting criteria (AIC, BIC) was used to extrapolate survival beyond 30 months. Results In this interim analysis of all-cause mortality, 75/176 (42.6%) and 108/177 (61.0%) patients in the tafamidis 80/61 mg and PBO/tafamidis groups, respectively, died (median follow-up: 51.9 and 51.4 months). Long-term continuous tafamidis treatment was superior to PBO/tafamidis treatment (Figure). Mortality risk was reduced by 41.1% with tafamidis 80/61 mg (n = 176) vs PBO/tafamidis (n = 177) (hazard ratio, 0.5888 [95% CI: 0.4370-0.7931]; P = 0.0004). In the extrapolated PBO group, the estimated median overall survival was 35.2 months, vs 35.8 months in the observed PBO/tafamidis group. The curves for PBO/tafamidis and estimated PBO diverged after ∼44 months in favor of tafamidis. Conclusions Extrapolation of PBO data from ATTR-ACT was a valuable tool allowing comparison of potential outcomes with and without tafamidis treatment. Although these extrapolated data suggest that delayed initiation of tafamidis may provide some survival benefit, early continuous treatment with tafamidis results in significantly better survival outcomes in patients with ATTR-CM.

Assessment of extreme stresses and deflections on wind turbine blades with stochastic material properties using statistical extrapolation methods

Since the introduction of the 3rd edition of the IEC Standard 61400-1, designers of wind turbines are required to apply statistical extrapolation techniques, to estimate the extreme (ultimate) load values corresponding to fifty-year return period. In the present paper, the certification procedure is assessed under the uncertainty of the material properties using simulated load time series of the NREL 5MW Reference Wind Turbine. The uncertainty of the material properties is introduced in the elastic properties of the composite blades by using input data from the OptiDAT composite material database. Comparison of the estimated extreme loads and deflections of the blades as well as maximum stresses, also in connection to the Tsai Wu failure criterion, is performed for different material sets. It is found that the variability of the material properties does not affect the estimated ultimate flapwise moments (difference <1.5%) but affects the maximum flapwise deflection (differences ∼8%). It is concluded that for the levels of variation considered in the composite material properties, the coefficient of variation of the extreme stresses and the Tsai Wu failure criterion are in the order of 2% and 8% respectively.

Statistical extrapolation methods for estimating extreme loads on wind turbine blades under turbulent wind conditions and stochastic material properties

According to the IEC Standard 61400-1, designers of wind turbines are required to apply statistical extrapolation techniques to estimate the extreme (ultimate) load. In the present article, the certification procedure is assessed under the uncertainty of the material properties using a simulated load time series of the National Renewable Energy Laboratory 5MW reference wind turbine rotor. The uncertainty of the material properties is introduced in the elastic properties of the composite materials based on the OptiDAT composite material database. The assessment relies on the comparison of the estimated blade extreme loads and deflections, obtained for the reference and the stochastically varied material properties. It is found that the variability of the material properties does not affect the estimated ultimate moments (differences &lt; 1.5%) but affects the maximum flapwise deflection (differences ~8%). It is concluded that the peak over threshold peak extraction technique and the three-parameter Weibull fitting functions outperform among those considered in the article.

Evaluation of survival extrapolation in immuno-oncology using multiple pre-planned data cuts: learnings to aid in model selection

BackgroundDue to limited duration of follow up in clinical trials of cancer treatments, estimates of lifetime survival benefits are typically derived using statistical extrapolation methods. To justify the method used, a range of approaches have been proposed including statistical goodness-of-fit tests and comparing estimates against a previous data cut (i.e. interim data collected). In this study, we extend these approaches by presenting a range of extrapolations fitted to four pre-planned data cuts from the JAVELIN Merkel 200 (JM200) trial. By comparing different estimates of survival and goodness-of-fit as JM200 data mature, we undertook an iterative process of fitting and re-fitting survival models to retrospectively identify early indications of likely long-term survival.MethodsStandard and spline-based parametric models were fitted to overall survival data from each JM200 data cut. Goodness-of-fit was determined using an assessment of the estimated hazard function, information theory-based methods and objective comparisons of estimation accuracy. Best-fitting extrapolations were compared to establish which one provided the most accurate estimation, and how statistical goodness-of-fit differed.ResultsSpline-based models provided the closest fit to the final JM200 data cut, though all extrapolation methods based on the earliest data cut underestimated the ‘true’ long-term survival (difference in restricted mean survival time [RMST] at 36 months: − 1.1 to − 0.5 months). Goodness-of-fit scores illustrated that an increasingly flexible model was favored as data matured. Given an early data cut, a more flexible model better aligned with clinical expectations could be reasonably justified using a range of metrics, including RMST and goodness-of-fit scores (which were typically within a 2-point range of the statistically ‘best-fitting’ model).ConclusionsSurvival estimates from the spline-based models are more aligned with clinical expectation and provided a better fit to the JM200 data, despite not exhibiting the definitively ‘best’ statistical goodness-of-fit. Longer-term data are required to further validate extrapolations, though this study illustrates the importance of clinical plausibility when selecting the most appropriate model. In addition, hazard-based plots and goodness-of-fit tests from multiple data cuts present useful approaches to identify when a more flexible model may be advantageous.Trial registrationJAVELIN Merkel 200 was registered with ClinicalTrials.gov as NCT02155647 on June 4, 2014.

Innovation cooperation between Ukraine and Scandinavian Countries under conditions of a new industrial revolution

The current experience of building up a global economic system in the context of a new industrial revolution proves that economic growth and the competitiveness of the leaders of the state are mainly conditioned by the strengthening of the role of innovation. Therefore, the study of innovation cooperation between Scandinavian countries, both technological leaders and Ukraine is extremely relevant. The purpose of the article is to assess the current state of cooperation between Ukraine and the Scandinavian countries and provide recommendations for its development. The article set out and solved the following tasks: to characterize features of innovative development and prospects of cooperation in this area of the specified countries; to estimate comparative advantages in high-tech trade between them; identify prospects and develop recommendations for innovative cooperation between Ukraine and the Scandinavian countries. The materials and methods used to achieve the research goal were: statistical method, comparative analysis, comparison and extrapolation method. As a result of the study, it was discovered that the main directions of innovation cooperation of these countries are innovation-investment projects, technical assistance initiatives, experience transfer and technologies. Cooperation is mainly implemented in energy, information technology, education, science and high-tech trade. Ukraine has competitive advantages in the export of goods in the aerospace industry, information and communication services to the Scandinavian countries. Conclusions In order to deepen innovation cooperation between Ukraine and Scandinavian countries, it is expedient: (1) to expand the areas of cooperation in joint infrastructure projects, in the aerospace and pharmaceutical industries, and the production of components for automobiles; (2) joint research on biotechnology and nanotechnology; (3) concluding agreements in order to establish partnerships between the universities of the specified countries; (4) the introduction of state support to the aerospace industry and the creation of scientific and production clusters in this field; (5) further development and diversification of the Ukrainian IT market and interaction with Scandinavian countries in this area.

Applying adverse outcome pathways and species sensitivity-weighted distribution to predicted-no-effect concentration derivation and quantitative ecological risk assessment for bisphenol A and 4-nonylphenol in aquatic environments: A case study on Tianjin City, China.

Adverse outcome pathways (AOPs) are a novel concept that effectively considers the toxic modes of action and guides the ecological risk assessment of chemicals. To better use toxicity data including biochemical or molecular responses and mechanistic data, we further developed a species sensitivity-weighted distribution (SSWD) method for bisphenol A and 4-nonylphenol. Their aquatic predicted-no-effect concentrations (PNECs) were derived using the log-normal statistical extrapolation method. We calculated aquatic PNECs of bisphenol A and 4-nonylphenol with values of 4.01 and 0.721 µg/L, respectively. The ecological risk of each chemical in different aquatic environments near Tianjin, China, a coastal municipality along the Bohai Sea, was characterized by hazard quotient and probabilistic risk quotient assessment techniques. Hazard quotients of 7.02 and 5.99 at 2 municipal sewage sites using all of the endpoints were observed for 4-nonylphenol, which indicated high ecological risks posed by 4-nonylphenol to aquatic organisms, especially endocrine-disrupting effects. Moreover, a high ecological risk of 4-nonylphenol was indicated based on the probabilistic risk quotient method. The present results show that combining the SSWD method and the AOP concept could better protect aquatic organisms from adverse effects such as endocrine disruption and could decrease uncertainty in ecological risk assessment. Environ Toxicol Chem 2018;37:551-562. © 2017 SETAC.

The toxicity of molybdate to freshwater and marine organisms. III. Generating additional chronic toxicity data for the refinement of safe environmental exposure concentrations in the US and Europe

The freshwater and marine long-term ecotoxicity datasets used in the European REACH registration dossiers for molybdenum and molybdenum compounds resulted in the derivation of a HC5,50%,freshwater (38.2mgMo/L) and HC5,50%,marine (5.70mgMo/L) by means of the statistical extrapolation method. Both datasets, however, did not meet the US-EPA information requirements for deriving Final Chronic Values (FCV) that were based on chronic data. US-EPA compliance was achieved by generating chronic no-effect data for the freshwater benthic amphipod Hyalella azteca and the marine inland silverside fish Menidia beryllina, using sodium molybdate dihydrate as test substance. A 42d-EC10 of 44.6mgMo/L for reproduction was determined in a water-only exposure with H. azteca. For M. beryllina, a 37d-NOEC of 139mg mMo/L for standard length and blotted wet weight was found. Other endpoints (e.g., survival, hatching success) proved to be less sensitive. Data were added to the existing chronic toxicity datasets, together with new long-term no-effect values that were identified in open literature for brown trout Salmo trutta, the marine alga Isochrysis galbana, the marine snail Nassarius dorsatus and the marine barnacle Amphibalanus amphitrite. The updated data sets resulted in a freshwater and marine HC5,50% of 35.7 and 6.85mgMo/L, respectively. The same data sets were also used for the determination of US-EPA FCVs, where the FVCfreshwater was 36.1mg/L, and the FCVmarine was 3.85mgMo/L. As the Final Plant Values for both aquatic environments were higher than their respective FCVs, the Criterion Continuous Concentration (CCC) for molybdenum is equal to the FCV.

Close Enough for Jazz: Statistical Extrapolation in Complex Litigation

This paper discusses how statistical extrapolation methods can be used to calculate damages in large, complex litigation cases. The basics of elementary statistics are briefly explained and then applied to the litigation context, including when statistics are generally used, the manner of use, and several common challenges to statistical sampling.There is also a federal circuit split in allowing the use of statistics to calculate damages between the 9th Circuit Court of Appeals and the Fifth Circuit Court of Appeals, and the paper discusses the two seminal cases at the center of that split (Ratanasen v. State of California Department of Health Services; Cimino v. Raymark Industries, Inc.). There are several public policy concerns with the use of statistical sampling, namely judicial efficiency and accuracy of litigation outcomes. Other areas of law, such as antitrust, Title VII, and welfare rights law, that use statistical sampling can offer insight on its expanded use in general complex litigation cases. The paper concludes with a call for universal acceptance of the use of statistical extrapolation in large, complex litigation cases where it would be logistically impossible to determine the case by examining individual claims. This would apply in cases where there number of individual claims was so high that making a determination on a claim-by-claim basis would be impractical, or in class actions where the number of plaintiffs was exceedingly high that making individual determinations would be overly burdensome for the court. In sum, using statistical extrapolation to calculate damages is simply another tool for the judiciary to use in efficient case management, rather than a usurpation of the judiciary's discretion, and its used should be encouraged to litigate large, complex cases more effectively.

Comparison of statistical extrapolation methods for the evaluation of long-term extreme response of wind turbine

Prediction of extreme responses with given mean recurrence intervals (MRIs) is an essential task for reliability-based design of wind turbines. It involves statistical extrapolation of extreme response distribution at very upper tail region for the estimation of long-term extreme responses from short-term field or simulation data. In this study, the accuracy and effectiveness of the global maxima method, translation process method and average conditional exceedance rate (ACER) method in evaluating extreme response distribution are examined through comparisons with the predictions from controlled Monte Carlo simulation (MCS). The controlled MCS combines the importance splitting (ISp) method with multivariate autoregressive (MAR) modeling of stochastic wind excitations, enables a direct simulation of long-term extreme responses with much reduced computational efforts. The extreme value distribution determined provides a valuable opportunity to verify the adequacy of different statistical extrapolation approaches. This study reconfirms the limitation of global maxima method that the predictions are greatly relying on the prescribed probability distribution model. This study also highlights the challenges in translation process method for strongly non-Gaussian response process when moment-based Hermite model is used for representing the translation function between non-Gaussian response process and underlying Gaussian process. An improved Hermite model that better represents the translation function at upper tail is proposed, and its improved performance in the estimated extreme value distribution of strongly non-Gaussian response process is achieved. The ACER method, which is essentially a method of extrapolating the process crossing rate, is also found to be able to well represent the tail behavior of the extreme value distribution.

Load Spectrum Compilation Based on Nonparametric Statistical Extrapolation

Considering the special load characteristics of the wheel loader, thispaper focus on compiling the load spectrum of the transmission of the wheelloader using the nonparametric statistical extrapolation method (NSEM). In thisprocess, the determination of the kernel function shape is the critical issue,which has been discussed in detail. Before extrapolating the sample loadspectrum, the signal denoising of the field-tested time-history load signals isperformed. After that, the sample load cycles are obtained using the rainflowcounting method and the corresponding kernel function shape is determined. Thenthe NSEM of rainflow matrix is proposed, by which the whole-life load spectrumis estimated. The proposed extrapolation method can well realize the estimationof the load cycles that do not appear in sample load cycles but may exist inthe whole-life load history.

Derivation of Ecological Protective Concentration using the Probabilistic Ecological Risk Assessment applicable for Korean Water Environment: (I) Cadmium

Probabilistic ecological risk assessment (PERA) for deriving ecological protective concentration (EPC) was previously suggested in USA, Australia, New Zealand, Canada, and Netherland. This study suggested the EPC of cadmium (Cd) based on the PERA to be suitable to Korean aquatic ecosystem. First, we collected reliable ecotoxicity data from reliable data without restriction and reliable data with restrictions. Next, we sorted the ecotoxicity data based on the site-specific locations, exposure duration, and water hardness. To correct toxicity by the water hardness, EU’s hardness corrected algorithm was used with slope factor 0.89 and a benchmark of water hardness 100. EPC was calculated according to statistical extrapolation method (SEM), statistical extrapolation methodAcute to chronic ratio (SEMACR), and assessment factor method (AFM). As a result, aquatic toxicity data of Cd were collected from 43 acute toxicity data (4 Actinopterygill, 29 Branchiopoda, 1 Polychaeta, 2 Bryozoa, 6 Chlorophyceae, 1 Chanophyceae) and 40 chronic toxicity data (2 Actinopterygill, 23 Branchiopoda, 9 Chlorophyceae, 6 Macrophytes). Because toxicity data of Cd belongs to 4 classes in taxonomical classification, acute and chronic EPC (11.07 μg/l and 0.034 μg/l, respectively) was calculated according to SEM technique. These values were included in the range of international EPCs. This study would be useful to establish the ecological standard for the protection of aquatic ecosystem in Korea.

Judgmental Forecasting in the Dry Bulk Shipping Business: Statistical vs. Judgmental Approach

This paper investigates the accuracy of judgmental forecasting methods for dry bulk freight market. Judgmental forecasting is a method that implements the purely judgmental aspects of a system. The research investigates judgmental forecasting for the Baltic Dry Index, and compares it with statistical extrapolation methods. Post-sample forecasting accuracy indicates the superiority of the proposed approach over the conventional statistical methods. Empirical studies are performed with an expert group and the accuracy of judgmental point estimates is compared with exponential smoothing, the X12 ARIMA, and the TRAMO/SEATS algorithms. The results of expert predictions outperformed traditional time-series methods.

Species richness and complementarity of beetle faunas in a mediterranean-type biodiversity hotspot

Regions of mediterranean-type climate represent most extra-tropical biodi- versity hotspots, being both highly diverse and highly endangered. Though renowned for their plant richness, these regions' insects constitute the bulk of their alpha diversities. Data on insect distribution and rarity are generally lacking for such regions, and are often considered unattainable. Intensive field inventories combined with statistical extrapolation methods can provide a sufficient understanding of alpha, beta, and gamma diversity components for application to conservation planning. These are essential to assessing the adequacy of a regional reserve network for the conservation of insect diversity. Here the beetle faunas of three protected areas spanning three major ecoregions in the California Floristic Province were inventoried and analyzed for species richness, complementarity, and uniqueness. These surveys produced collectively nearly 1,200 species from all three sites, estimated to be about 80% of their total faunas. Diversity was highly partitioned among sites, no one site containing more than 60% of the species. Dissimilarity was moderate to high for all comparisons, and all sites contained >40% unique species. Comparison of these results with those based on species of co-occurring plants reveal incongruent species richness but congruent similarities among sites. These results provide quantitative support to the perception that mediterranean insect faunas show high spatial variability. Along with online specimen level data on distribution, rarity, and seasonality, these results will help speed the incorporation of insect data into serious conservation planning.

Estimating exceedance frequencies of extreme river discharges using statistical methods and physically based approach

In the Netherlands, the design discharge for the river Rhine may be exceeded on average once every 1250 years. Design discharges are currently estimated by fitting of probability distributions and extrapolation techniques. To this aim, reliable and homogeneous observations are needed. Unfortunately, time series of observed discharges are of a limited length. Consequently, different probability distributions lead to quite different extrapolated values, and the goodness-of-fit tests to select an appropriate probability distribution are usually inconclusive. The fact that the series of observations are short and physical knowledge about the catchment response is not included in this analysis, contributes to this inconclusiveness. Therefore, in the Netherlands, new methodologies are investigated. The new developments consist on one hand of a new statistical extrapolation method based on Bayesian approach, that takes account of statistical uncertainties. On the other hand, a methodology is being made to provide a better physical basis about the catchment response under extreme meteorological circumstances. This method consists of a statistical rainfall generator combined with hydrological and hydraulic models. Together with the current extrapolation method, these new developments are the subject of this paper.