Comparison of copper concentrations in liver and muscle of Squalius cephalus and Capoeta capoeta gracilis (Pisces: Teleostei) in Tajan River, Iran

The aim of this study was to determine and compare the concentration of copper (Cu) in liver and muscle of two fish species Squalius cephalus and Capoeta capoeta gracilis. The fish were caught in four sampling sites along Tajan River, Mazandaran Province, northern Iran. The concentration of Cu was determined using flame atomic absorption spectrometry. There were significant differences (P<0.05) between the sampling sites with regard to Cu concentration in both muscle and liver of fish species.Significant differences were also found (P<0.05) between S. cephalus and C. c. gracilis regarding Cu content in liver and muscle tissues. The content of Cu in the liver was greater (P<0.05) than that in the muscle in both species. Also, Cu content of liver in both species was higher than the standard limits declared by WHO. This study reports high loads of Cu in Tajan River and a high content of Cu in the muscle and liver of S. cephalus and C. c. gracilis

A model-based approach for mapping rangelands covers using Landsat TM image data.

Empirical models are important tools for relating field-measured biophysical variables to remotely sensed data. Regression analysis has been a popular empirical method of linking these two types of data to estimate variables such as biomass, percent vegetation canopy cover, and bare soil. This study was conducted in a semi-arid rangeland ecosystem of Qazvin province, Iran. This paper presents the development of a regression model for predicting rangeland biophysical variables using the original image data of Landsat TM nonthermal bands. The biophysical variables of interest within the rangeland ecosystem were percent vegetation canopy cover, bare soil extent, and stone and gravel which their correlations were analyzed in relation to Landsat TM original data. The results of applying stepwise multiple regression showed that there is a significant correlation between Landsat TM band 2 reflectance values and biophysical variables. The developed models were applied to Landsat TM band 2 and relevant maps were generated. We concluded that such problems as an inexact location of field samples on the image, small size of samples, vegetation heterogeneity may significantly affect the modeling of real rangeland Landsat TM data relationships

A model-based approach for mapping rangelands covers using Landsat TM image data

Empirical models are important tools for relating field-measured biophysical variables to remotely sensed data. Regression analysis has been a popular empirical method of linking these two types of data to estimate variables such as biomass, percent vegetation canopy cover, and bare soil. This study was conducted in a semi-arid rangeland ecosystem of Qazvin province, Iran. This paper presents the development of a regression model for predicting rangeland biophysical variables using the original image data of Landsat TM nonthermal bands. The biophysical variables of interest within the rangeland ecosystem were percent vegetation canopy cover, bare soil extent, and stone and gravel which their correlations were analyzed in relation to Landsat TM original data. The results of applying stepwise multiple regression showed that there is a significant correlation between Landsat TM band 2 reflectance values and biophysical variables. The developed models were applied to Landsat TM band 2 and relevant maps were generated. We concluded that such problems as an inexact location of field samples on the image, small size of samples, vegetation heterogeneity may significantly affect the modeling of real rangeland Landsat TM data relationships

The Impacts of Clay and Gypsum Mining on Vegetation and Soil Conditions in Arid Ecosystems (Case Study: Segzi-Isfahan)

This study evaluates the impacts of clay and gypsum mining on ecosystem structure and function using Landscape Function Analysis (LFA) in Segzi plain, Isfahan. The length and width of patches and inter-patches length were recorded along the 18 established 50-meters transects in mining and reference sites. Eleven soil surface indicators were evaluated using LFA method in these patches and inter-patches spaces. Thirty six soil samples were randomly collected from 0 to 15 and 15 to 30 centimetres of soil surface, and the amount of pH, CaCO3, CaSO4, electrical conductivity, organic matters and the percentage of clay, silt or sand of the samples were measured. According to the results, structural and functional characteristics of the reference sites, including infiltration, stability, and soil nutrient cycling are better than mining sites. In clay mine sites, except indicators of slake test; litter and surface roughness indices were not different statistically (&alpha; = 5%). In Gypsum mine sites, all indicators in mining sites were statistically different (&alpha; = 5%) from reference sites, but their indicators of cryptogam cover, nature and roughness of the soil surface and deposit material. The extent of degradation in soil and vegetation characteristics of mined sites indicates that there is a strong desertification trend in the study area