Dominant processes causing the formation of coastal sand masses, case study: western Makran coastal plain

The instability and mobility of sand dunes is a major concern for those involved in the planning processes and management of arid coastal plains. Dune systems are created due to several factors and elements. Regarding environmental planning and the management of coastal zones, the study of their formation and development processes is of great importance. The present study aims at identifying the most influential factors in the dispersion of sand masses in the western region of the Makran Plain. The data for this study consisted of spatial maps of landform distributions, wind velocities and directions, fetch lengths as well as dynamic waves. Thematic topographical and geological maps, satellite images, GPS, and software such as WRPLOT View, Freehand, and Arc GIS were used for data processing and analysis. After the generation of the Geomorphologic units map through the Molitor Equation in WRPLOT View, wind and wave rose diagrams were provided. Also, the elongation and direction of sand mass movements in the plain were obtained through multi-temporal and multisensory data. The main rivers’ monthly discharges were analyzed according to information gathered from previous studies as well as their relevant hydrometric water stations. Results indicated that the location and distribution of coastal sand masses are not affected by wind, but by the geomorphologic characteristics of foreshore and coastal hydrodynamics. Also, the distribution of internal sand masses on the coastal plain is affected mostly by the plain stretches relative to the prevailing wind direction and to the extent of old beds and floodplains that are exposed to the prevailing wind rather than the wind itself

Health Belief Model-based Intervention on Women's Knowledge and Perceived Beliefs about Warning Signs of Cancer

Objective: Early detection of cancers essentially depends on knowledge of the warning signs. This study, therefore, aimed at investigating the effect of Health Belief Model (HBM)-based educational intervention on the knowledge and perceived beliefs of women about the warning signs of cancer. Methods: This experimental study with intervention (n = 80) and control (n = 80) groups was performed at four urban health centers affiliated to the university. Data collection was done in two phases, before and one month after the educational intervention, using three instruments, a demographic-clinical information questionnaire, the awareness questionnaire on cancer warning signs, and the cancer warning signs-HBM questionnaire. Results: The results of the multivariate repeated-measures analyses of variance indicated that the hypothesis of this study was confirmed. It means that 'women's knowledge and their perceived beliefs of cancer warning signs' improved after HBM-based educational intervention in the intervention group, compared to the controls over time. Thus, the 'level of knowledge' and perceived beliefs of the women in the intervention group compared to the controls increased, in terms of perceived 'sensitivity,' 'severity,' 'benefits,' 'barriers,' 'cue to action,' and 'self-efficacy' over time (P < 0.001). Conclusions: It could be hoped that this intervention would be effective for improving the performance of women in health-promoting behaviors of cancer prevention. It is recommended that health-care providers plan for HBM-based educational interventions, based on educational needs of the target groups at different community levels

Assessment of climate change downscaling and non-stationarity on the spatial pattern of a mangrove ecosystem in an arid coastal region of southern Iran.

Mangrove wetlands exist in the transition zone between terrestrial and marine environments and have remarkable ecological and socio-economic value. This study uses climate change downscaling to address the question of non-stationarity influences on mangrove variations (expansion and contraction) within an arid coastal region. Our two-step approach includes downscaling models and uncertainty assessment, followed by a non-stationary and trend procedure using the Extreme Value Analysis (extRemes code). The Long Ashton Research Station Weather Generator (LARS-WG) model along with two different general circulation model (GCMs) (MIRH and HadCM3) were used to downscale climatic variables during current (1968–2011) and future (2011–2030, 2045–2065, and 2080–2099) periods. Parametric and non-parametric bootstrapping uncertainty tests demonstrated that the LARS-WGS model skillfully downscaled climatic variables at the 95 % significance level. Downscaling results using MIHR model show that minimum and maximum temperatures will increase in the future (2011–2030, 2045–2065, and 2080–2099) during winter and summer in a range of +4.21 and +4.7 °C, and +3.62 and +3.55 °C, respectively. HadCM3 analysis also revealed an increase in minimum (∼+3.03 °C) and maximum (∼+3.3 °C) temperatures during wet and dry seasons. In addition, we examined how much mangrove area has changed during the past decades and, thus, if climate change non-stationarity impacts mangrove ecosystems. Our results using remote sensing techniques and the non-parametric Mann–Whitney two-sample test indicated a sharp decline in mangrove area during 1972,1987, and 1997 periods (p value = 0.002). Non-stationary assessment using the generalized extreme value (GEV) distributions by including mangrove area as a covariate further indicated that the null hypothesis of the stationary climate (no trend) should be rejected due to the very low p values for precipitation (p value = 0.0027), minimum (p value = 0.000000029) and maximum (p value = 0.00016) temperatures. Based on non-stationary analysis and an upward trend in downscaled temperature extremes, climate change may control mangrove development in the future