An application of a small area procedure with correlation between measurement error and sampling error to the Conservation Effects Assessment Project

County level estimates of mean sheet and rill erosion from the Conservation Effects Assessment Project (CEAP) are useful for program development and evaluation. Since county sample sizes in the CEAP survey are insufficient to support reliable direct estimators, small area estimation procedures are needed. The quantity of water runoff is a useful covariate but is unavailable for the full population. We use an estimate of mean runoff from the CEAP survey as a covariate in a small area model with sheet and rill erosion as the response. As the runoff and sheet and rill erosion are estimators from the same survey, the measurement error in the covariate is important as is the correlation between the measurement error and the sampling error. We conduct a detailed investigation of small area estimation in the presence of a correlation between the measurement error in the covariate and the sampling error in the response. In simulations, the proposed predictor is superior to small area predictors that assume the response and covariate are uncorrelated or that ignore the measurement error entirely

Estudio etnobotánico de áreas del noroeste de la provincia de Isfahan, Iran

Iran is one of the countries which enormously used medicinal plants from the ancient times. In this study, we documented the ethnobotanical data of Golpayegan, and Shahin Shahr and Meymeh counties (Isfahan province) for the first time in Iran. Field study and plant collecting were done in different seasons in 2016–2017. Ethnobotanical data were analyzed using information of questionnaires gained from 27 inhabitants. Totally, 48 plants of 24 families were recorded from studied areas. Asteraceae (36%) and Lamiaceae (23%) are those containing the biggest numbers of cited plants. Moreover, leaves (45.83%) and seeds (18.75%) were the most used parts. This study indicated the importance of useful plants of studied areas and the necessity of doing this kind of research on other parts of country in order to preserve this valuable information of local inhabitants.Irán es un país que ha utilizado de manera destacada las plantas medicinales desde la antigüedad. En este estudio, documentamos los datos etnobotánicos de los condados de Golpayegan, Shahin Shahr y Meymeh (provincia de Isfahán) por primera vez en Irán. El estudio de campo y la recolección de plantas se realizaron en diferentes temporadas en 2016 y 2017. Los datos etnobotánicos se analizaron utilizando información proveniente de cuestionarios realizados a 27 informantes. En total, se registraron 48 plantas de 24 familias de las áreas estudiadas. Las familias Asteraceae (36%) y Lamiaceae (23%) son las que contienen un mayor número de plantas citadas. Las hojas (45,83%) y las semillas (18,75%) son las partes de planta más utilizadas. Este estudio indica la importancia de las plantas útiles de las áreas estudiadas y la necesidad de realizar este tipo de investigación en otras partes del país con el fin de preservar esta valiosa información de los habitantes locales

Epidermal micromorphology of floret parts in Aeluropus (Poaceae)

Aeluropus from Poaceae comprises 5 species in the world and 3 species in Iran. This halophytic perennial is distributed in salty and dry soils of Asia, Europe, and Africa. In addition to being used as fodder, it can stabilize the soil by its rhizome or stolon. These features make Aeluropus a valuable plant. In this study, lemma and palea of 10 populations of Aeluropus were studied micromorphologically by scanning electron microscope (SEM) to determine diagnostic features among species studied. Eight characters as micro-prickle, macro-hair, long cell outline, cork and silica cells, papilla, salt gland, and epicuticular wax were studied. The occurrence of salt glands and silica cells in populations/taxa studied showed the ability of Aeluropus to tolerate harsh habitats. Our result showed the taxonomic value of floret micromorphological features to separate Aeluropus species

An Unbiased Predictor for Skewed Response Variable with Measurement Error in Covariate

We introduce a new small area predictor when the Fay-Herriot normal error model is fitted to a logarithmically transformed response variable, and the covariate is measured with error. This framework has been previously studied by Mosaferi et al. (2023). The empirical predictor given in their manuscript cannot perform uniformly better than the direct estimator. Our proposed predictor in this manuscript is unbiased and can perform uniformly better than the one proposed in Mosaferi et al. (2023). We derive an approximation of the mean squared error (MSE) for the predictor. The prediction intervals based on the MSE suffer from coverage problems. Thus, we propose a non-parametric bootstrap prediction interval which is more accurate. This problem is of great interest in small area applications since statistical agencies and agricultural surveys are often asked to produce estimates of right skewed variables with covariates measured with errors. With Monte Carlo simulation studies and two Census Bureau's data sets, we demonstrate the superiority of our proposed methodology