Home About us Contact
|
Home About us Contact | ||
|
|
||
Temperature Variables (temperature + variable)
Selected AbstractsEnvironmental determinants of amphibian and reptile species richness in ChinaECOGRAPHY, Issue 4 2007Hong Qian Understanding the factors that regulate geographical variation in species richness has been one of the fundamental questions in ecology for decades, but our knowledge of the cause of geographical variation in species richness remains poor. This is particularly true for herpetofaunas (including amphibians and reptiles). Here, using correlation and regression analyses, we examine the relationship of herpetofaunal species richness in 245 localities across China with 30 environmental factors, which include nearly all major environmental factors that are considered to explain broad-scale species richness gradients in such theories as ambient energy, water,energy dynamics, productivity, habitat heterogeneity, and climatic stability. We found that the species richness of amphibians and reptiles is moderately to strongly correlated with most of the environmental variables examined, and that the best fit models, which include explanatory variables of temperature, precipitation, net primary productivity, minimum elevation, and range in elevation, explain ca 70% the variance in species richness for both amphibians and reptiles after accounting for sample area. Although water and temperature are important explanatory variables to both amphibians and reptiles, water variables explain more variance in amphibian species richness than in reptile species richness whereas temperature variables explain more variance in reptile species richness than in amphibian species richness, which is consistent with different physiological requirements of the two groups of organisms. [source] Homogeneity analysis of Turkish meteorological data setHYDROLOGICAL PROCESSES, Issue 8 2010Sinan Sahin Abstract The missing value interpolation and homogeneity analysis were performed on the meteorological data of Turkey. The data set has the observations of six variables: the maximum air temperature, the minimum air temperature, the mean air temperature, the total precipitation, the relative humidity and the local pressure of 232 stations for the period 1974,2002. The missing values on the monthly data set were estimated using two methods: the linear regression (LR) and the expectation maximization (EM) algorithm. Because of higher correlations between test and reference series, EM algorithm results were preferred. The homogeneity analysis was performed on the annual data using a relative test and four absolute homogeneity tests were used for the stations where non-testable series were found due to the low correlation coefficients between the test and the reference series. A comparison was accomplished by the graphics where relative and absolute tests provided different outcomes. Absolute tests failed to detect the inhomogeneities in the precipitation series at the significance level 1%. Interestingly, most of the inhomogeneities detected on the temperature variables existed in the Aegean region of Turkey. It is considered that theseinhomogeneities were mostly caused by non-natural effects such as relocation. Because of changes at topography at short distance in this region intensify non-random characteristics of the temperature series when relocation occurs even in small distances. The marine effect, which causes artifical cooling effect due to sea breezes has important impact on temperature series and the orograhpy allows this impact go through the inner parts in this region. Copyright © 2010 John Wiley & Sons, Ltd. [source] The generation of monthly gridded datasets for a range of climatic variables over the UKINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 8 2005Matthew Perry Abstract Monthly or annual 5 km × 5 km gridded datasets covering the UK are generated for the 1961,2000 period, for 36 climatic parameters. As well as the usual elements of temperature, rainfall, sunshine, cloud, wind speed, and pressure, derived temperature variables (such as growing-season length, heating degree days, and heat and cold wave durations) and further precipitation variables (such as rainfall intensity, maximum consecutive dry days, and days of snow, hail and thunder) are analysed. The analysis process uses geographical information system capabilities to combine multiple regression with inverse-distance-weighted interpolation. Geographic and topographic factors, such as easting and northing, terrain height and shape, and urban and coastal effects, are incorporated either through normalization with regard to the 1961,90 average climate, or as independent variables in the regression. Local variations are then incorporated through the spatial interpolation of regression residuals. For each of the climatic parameters, the choice of model is based on verification statistics produced by excluding a random set of stations from the analysis for a selection of months, and comparing the observed values with the estimated values at each point. This gives some insight into the significance, direction, and seasonality of factors affecting different climate elements. It also gives a measure of the accuracy of the method at predicting values between station locations. The datasets are being used for the verification of climate modelling scenarios and are available via the Internet. © Crown Copyright 2005. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd. [source] Changes in seasonal and annual high-frequency air temperature variability in the Arctic from 1951 to 1990INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 9 2002Rajmund Przybylak Abstract A detailed analysis of intraseasonal (within season) and interannual (between years) temperature variability for the whole Arctic for the period 1951,90 is provided. For this purpose four temperature variables were used: average (TMEAN), maximum (TMAX) and minimum (TMIN) temperatures, and the diurnal temperature range (DTR). The source data for the analysis were the daily TMAX and TMIN for ten stations representing almost all climatic regions in the Arctic. The methods of calculation of temperature variability were mostly taken from Plummer (1996; Australian Meteorological Magazine45: 233). Thus the results presented for the Arctic can be fully compared with existing results for the other parts of the world (China, the former USSR, the USA and Australia). Regional trends in intraseasonal and interannual temperature variability were mixed and the majority of them were insignificant. Trends in intraseasonal variability were positive in the Norwegian Arctic and eastern Greenland and negative in the Canadian and Russian Arctic. Small increases in interannual variability for all temperature variables were observed annually in the Norwegian Arctic and eastern Greenland, and in the Canadian Arctic. These were largely a result of increases in winter and transitional seasons respectively. On the other hand, opposite tendencies, both on a seasonal and an annual basis, occurred in the Russian Arctic. Statistically significant negative trends in intraseasonal variability were noted mainly in the Canadian Arctic, whereas such trends in interannual variability were noted mainly in the Russian Arctic. The absence of significant changes in intraseasonal and interannual variability of TMEAN, TMAX, TMIN and DTR is additional evidence (besides the average temperature) that in the Arctic in the period 1951,90 no tangible manifestations of the greenhouse effect can be identified. Copyright © 2002 Royal Meteorological Society. [source] Modelling the distributions of Culicoides bluetongue virus vectors in Sicily in relation to satellite-derived climate variablesMEDICAL AND VETERINARY ENTOMOLOGY, Issue 2 2004B. V. Purse Abstract., Surveillance data from 268 sites in Sicily are used to develop climatic models for prediction of the distribution of the main European bluetongue virus (BTV) vector Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and of potential novel vectors, Culicoides pulicaris Linnaeus, Culicoides obsoletus group Meigen and Culicoides newsteadi Austen. The models containing the ,best' climatic predictors of distribution for each species, were selected from combinations of 40 temporally Fourier-processed remotely sensed variables and altitude at a 1 km spatial resolution using discriminant analysis. Kappa values of around 0.6 for all species models indicated substantial levels of agreement between model predictions and observed data. Whilst the distributions of C. obsoletus group and C. newsteadi were predicted by temperature variables, those of C. pulicaris and C. imicola were determined mainly by normalized difference vegetation index (NDVI), a variable correlated with soil moisture and vegetation biomass and productivity. These models were used to predict species presence in unsampled pixels across Italy and for C. imicola across Europe and North Africa. The predicted continuous presence of C. pulicaris along the appenine mountains, from north to south Italy, suggests BTV transmission may be possible in a large proportion of this region and that seasonal transhumance (seasonal movement of livestock between upland and lowland pastures) even in C. imicola -free areas should not generally be considered safe. The predicted distribution of C. imicola distribution shows substantial agreement with observed surveillance data from Greece and Iberia (including the Balearics) and parts of mainland Italy (Lazio, Tuscany and areas of the Ionian coast) but is generally much more restricted than the observed distribution (in Sardinia, Corsica and Morocco). The low number of presence sites for C. imicola in Sicily meant that only a restricted range of potential C. imicola habitats were included in the training set and that predictions could only be made within this range. Future modelling exercises will use abundance data collected according to a standardized protocol across the Mediterranean and, for Sicily in particular, should include non-climatic environmental variables that may influence breeding site suitability such as soil type. [source] Clinal variation of maxillary sinus volume in Japanese macaques (Macaca fuscata)AMERICAN JOURNAL OF PRIMATOLOGY, Issue 4 2003Todd C. Rae Abstract Macaques (genus Macaca) are unique among cercopithecids in that they possess a maxillary sinus, and among anthropoids in that they demonstrate a relatively weak relationship between the size of this sinus and the cranium. To test the hypothesis that extrinsic factors may contribute to maxillary sinus size variation, a sample of 46 Japanese macaque (M. fuscata) crania from known localities were subjected to computed tomography (CT) imaging, and sinus volume and nasal cavity area were analyzed relative to latitude and temperature variables. The results suggest that the environmental factors are significant determinants of nasal cavity size in Japanese macaques, but that the relationships between the environment and maxillary sinus volume (MSV) are probably a passive consequence of changes in the size of the nasal cavity. The sinus shrinks as the nasal cavity expands, due to an increased need to condition inspired air in colder climates. This in turn suggests that the sinus itself does not contribute significantly to upper respiratory function. Am. J. Primatol. 59:153,158, 2003. © 2003 Wiley-Liss, Inc. [source] | ||||||||||