Journal of Phylogenetics & Evolutionary Biology

Cranial dimensions and cranial indices are considered as simplest and most efficient way to indicate facial differences and age variations. Cranial morphology and dimensions are used to evaluate various aspects of growth and development thus helping in population differentiation.

Aim: the study is to investigate the craniometrical patterns in the Nigerian population based on three dimensional computed tomographic data, with the objectives of determining the age of individuals in the eastern part of Nigeria as well as determining if the skull of individual varies with age using computed tomography.

Methodology: involves a descriptive study design with age determined using standard ageing techniques. 150 dry adult human skulls cases (male and female both) constituted the material for the present study between age group of 25-60 years. Data were scanned in the radiology department and the CT data were processed in a computer workstation at the department. The CT scan acquisition was performed with 1.5mm slice thickness and reconstruction was done with 1.0 m 2 m slice thickness. All the CT data were recorded using DICOM 3.0 as a medical image file format into CD-ROM. The segmentation techniques were used to identify the region of interest of the computed tomography image based on Hounsfield unit. The selected region was calculated into 3-D modem based on the traditional definition with the modification into 3D model. The anatomical landmarks in craniometrics study were: Glabella (GL), Bregma (BR), Opisthocranium (OPC), Nasion (NA), Basion (BA). The measurements were interpreted using statistical analysis and reported in form of comparism of the mean values and mean difference, standard deviation, and confidence interval in respect to the various landmarks. Analysis of variance was utilized with p-value 0.005 alpha level of significant.

Result: the total number of sample for each landmark group is 1050 which covers the range value of 6 with a minimum number 1 and maximum number 7. The total sum of all Landmarks d is 4,200. The mean statistics of the seven groups is 4.00 with standard error of 0.62. The total number of length is 1050 with range of 119. The length attracts the minimum and maximum value of 80 and 199 with total sum of 132282. The mean statistics is 125.98 with standard error of 0.740.

Cranial dimensions and cranial indices are considered as simplest and most efficient way to indicate facial differences and age variations. Cranial morphology and dimensions are used to evaluate various aspects of growth and development thus helping in population differentiation. The aim of the study is to investigate the craniometric patterns in the Nigerian population based on three dimensional computed tomographic data, with the objectives of determining the age of individuals in the eastern part of Nigeria as well as determining if the skull of individual varies with age using computed tomography. Methodology involves a descriptive study design with age determined using standard ageing techniques. 150 dry adult human skulls cases (male and female both) constituted the material for the present study between age group of 25 - 60 years. Data were scanned in the radiology department and the CT data were processed in a computer workstation at the department. The CT scan acquisition was performed with 1.5 mm slice thickness and reconstruction was done with 1.0m 2m slice thickness. All the CT data were recorded using DICOM 3.0 as a medical image file format into CD-ROM.

Cranial dimensions and cranial indices are considered as simplest and most efficient way to indicate facial differences and age variations. Cranial morphology and dimensions are used to evaluate various aspects of growth and development thus helping in population differentiation. The aim of the study is to investigate the craniometric patterns in the Nigerian population based on three dimensional computed tomographic data, with the objectives of determining the age of individuals in the eastern part of Nigeria as well as determining if the skull of individual varies with age using computed tomography. Methodology involves a descriptive study design with age determined using standard ageing techniques. 150 dry adult human skulls cases (male and female both) constituted the material for the present study between age group of 25 - 60 years. Data were scanned in the radiology department and the CT data were processed in a computer workstation at the department. The CT scan acquisition was performed with 1.5 mm slice thickness and reconstruction was done with 1.0m 2m slice thickness. All the CT data were recorded using DICOM 3.0 as a medical image file format into CD-ROM.

The branching pattern of ancestor–descendant relationships among ‘Taxa’ (e.g., species or their genes) is named a ‘phylogeny’. ‘Phylogenetics’ is that the process of attempting to estimate these historical relationships by examining information like DNA, protein sequences, or morphological (shape) characters from extant taxa. This information is usually presented employing a mathematical tree – a structure wont to describe the evolutionary history of the taxa at a high level. These trees are available several different varieties and may be inferred in several alternative ways . there's an excellent amount of effort being put into methods of estimating trees, also as determining particular phylogenies for species of interest.

 

Behavioral ecology, also spelled behavioural ecology, is that the study of the evolutionary basis for animal behavior thanks to ecological pressures. Behavioral ecology emerged from ethology after Niko Tinbergen outlined four inquiries to address when studying animal behaviors: What are the proximate causes, ontogeny, survival value, and phylogeny of a behavior?

If an organism features a trait that gives a selective advantage (i.e., has adaptive significance) in its environment, then survival favors it. Adaptive significance refers to the expression of a trait that affects fitness, measured by a person's reproductive success. Adaptive traits are people who produce more copies of the individual's genes in future generations. Maladaptive traits are people who leave fewer. for instance , if a bird which will call more loudly attracts more mates, then a loud call is an adaptive trait for that species because a louder bird mates more frequently than less loud birds—thus sending more loud-calling genes into future generations.