Anthropogenic investigation for defining a framework and for conducting dynamic modeling of behavioral output in the context of environmental condition, intraspecies and interspecies interactions during ancestral evolution in order to define normality in the human lineage
The whole purpose of the research was to get to the bottom of the evolutionary process which manufactured the unique cognitive condition of humans which is observably abnormal.
In order to define normality in today’s exhibit behavior we have to look further down the lineage into the early evolution which can supply the apparatuses for the emergence of the unique cognition in the lineage that concluded in homo sapiens.
1 Principals, practices and methods of research:
The universe is a complex system and biological planetary system is even more complex, in order to analyze the dynamic systems which supports biological planetary system in general and individual organism system in particular, I took a similar approach as the science of physics does when it analyze the universe: a complex system must be broken down into simple principles and basic ideas that create a visualization or model. A theoretical model for biological planetary system must be useful in that it should approximate reality and make it understandable, measurable, and predictable.
2 The foundations of my data analysis
The foundations of my research framework and modeling systems are based only on universal laws (axioms) and not on theoretical assumptions
3 The first part of my research
The first part of my research was to facilitate a tool for running models that can validate evolutionary theories (including mine): Theory is a set of assumptions, and it can only be approved if it cannot be disproved (show that two contradictory conclusions can be drawn from it)
The scientific method to test the viability of a theory is to draw a necessary conclusion from the theory and then check it against actual phenomena as rigorously as possible. When assumptions become universally accepted as an established rule, they are called universal laws or axioms.
3.1 Utilizing universal laws, principals and research methods from theoretical physics
My research methods are based on utilizing universal laws and principals from theoretical physics with a cosmological approach in order to describe and assess individual organisms as a system of smaller systems that is a part of larger systems, which all together obeys to the same universal laws that govern the properties and interactions of energy and mass in a space over time.
Principals, laws, units of measurement and methods of calculations from classical mechanics, general relativity and special relativity such as:
- Euclidean space: mathematical abstraction and extension of ordinary three dimensional space (Cartesian system of coordinates)
- Motion of objects: gravity, acceleration, circular motion and rotational motion
- Mechanics: center of mass, inertia, momentum, force and energy
- Statistical mechanics: fluids, heat and temperature and thermodynamics
- Electromagnetism: electricity and magnetism and others
3.2 Data collection – create a multidiscipline database of historical information:
Collecting multidisciplinary “raw” data (not relaying on data from thesis and hypothesis based on aggregated multidisciplinary data) which include quantitative and empirical biological, ecological and paleontological data such as images and measurements of fossils (not reconstruction of skeletons from few fragments), documented observations of empirical natural phenomena, documentation of quantitative properties and behavioral observation of the living members of the primate lineage especially the members of the Hominidae lineage, historical statistical data that represent process and that can supply dating data such as genetic data, geologic and climatic data etc.
Sources of data: the data is collected from scientific papers directly from scientific data producer (universities and projects such as hgsc.bcm.edu, carta.anthropogeny.org, pin.primate.wisc.edu etc.) and via aggregators such as online publishing outlets (nature.com, pnas.org, researchgate.net, plos.org etc.).
3.3 Data organization – filter-out erroneous data and chronically and topically organize factual data:
Organizing all papers in two data groups:
- Physical properties data – functional potential (single disciplinary): such as genetic sequence, brain module, weight/size, biomechanical, molecular/chemical structure, sediment/ice core sample etc.
- Behavioral properties data – functional work (crossdisciplinary): such as genetic mutation process, interactions between brain modules, behavioral observation of organisms, energetic output of biomechanical work, molecular and chemical interactions, changes in biodiversity due to geologic and atmospheric changes etc.
Separating the data in each paper into three groups:
- Empirical data – materials, tables and graphs: to be used as the data source for the models, consisting of documented observation and quantities properties collected in research papers (materials and methods, tables and graphs, references etc.)
- Empirical data validation – practices, methods and references: to validate data sources and practices such as mathematic calculations, data sample size and properties, reference data size and properties, number of observations , first hand, second hand or third party observation and/or documentation, sources credibility as well as the ingenuity of the subject or the originality of the method (After a while you will have a list of credible researchers and primary producers of data which their theoretical input is worth considering).
- Theoretical data – abstract, introduction, conclusions and discussions sections: to filter researcher’s opinions and agendas which create the background for suggestive trends (using the abstract as reference only)
4.1 Paleontological timeline for environmental and ecological states, trends and major events in the locations and at the periods of our lineage evolution:
Circumstantial analysis that connect environmental events to evolutionary process:
Create detailed historic timeline of ecological and paleontological trends and events that will be the “apparatus” for key trends and events in our lineage evolutionary process.
Reconstructing a timeline from ~56MYA to ~10KYA that contain historical trends and properties of habitats and geographic areas by conducting comparative analysis of the collected quantitative data in order to extract all the crossdisciplinary data in the different papers that contain different aspects of interactions, junctions and correlations between environmental conditions and faunal evolution and states:
- Set a sequence of evidential markers (“anchor points”): points in time of which a cluster of multidiscipline data gives substantial evidential support for accurately reconstructing habitat. Based on the availability of data from credible sources that contain multiple sets (“data cluster”) of crossdisciplinary records confines to certain geographical area and concentrated in geological age that can be used to accurately reconstruct a snapshot of the habitat in such certain point of time at a certain territory.
- Establish historical timeline for global distribution of ecozones and the evolution of ecozones in local geographic areas: based on record of historic data from geographic, geologic, oceanographic, atmospheric (etc.) research papers and databases which can supply information for reconstructing the climatic conditions in a certain geographic area at a certain point in time (such as temperatures, precipitation, seasonality, elevation, tectonic setup and activity, ocean currents etc.) which determine the terrestrial ecozone which supply the plausible spectrum of potential for types of fauna, biomass productivity and biodiversity.
- Environmental events markers and phases where periods of stability recession or expansion of habitats started or concluded: based on evidential markers regarding a certain points in time where new environmental condition was introduced and consequently disrupts the statuesque and started new trend (e.g. decline in atmospheric CO2 started a cooling process which created a trend of increasingly drier climate, change in continental plates rearranged the ocean currents and mountain formation disrupts climate conditions in certain geographical area, which responsible for redistribution of ecozones and mark the points where a recession or expansion of habitats started or concluded)
- Evolutionary events markers and phases were and where a species of organisms and population emerged, spread, contract, disappeared or changed and the interactions between them: A taxonomic dating based on genetic clock and fossils to track chances in the web of life in ecological and geographical zones.