Guessing the future has never been easy, not even being a scientist.

Guessing the future has never been easy, not even being a scientist.

It is difficult to make predictions, especially about the future

 (Nicholas, 2007)

We very much tend to use and believe in the argumentative fallacy of the truths of science, which is why the following phrases are often used: “science proves that …” “based on a scientific study it is concluded that …”, With the cloak of science, you say and have the absolute truth. Who could question science? Who believes himself above science? However, things are not quite like that.

Science is an activity with which knowledge is generated so, without a doubt, it is of great help for decision-making. Science is based on verifiable facts. Thus, scientists know that some places are flooded because there is evidence of these events on the ground or because there is evidence to suggest that floods could occur. In this example there is knowledge that is applied to assume an event. If greenhouse gases continue to rise, it stands to reason that the climate could change; if a pandemic comes, it is logical that people will suffer from diseases, deaths and the decrease in economic activities. There is no doubt about that, the problem is when will the pandemic occur? When will climate change occur? When will the flood be? When will the collapse be?

Scientists, technicians and data managers have and generate knowledge, but also “they tend to believe they know a little more than they really do”, that is to say, “what they know is not the same as what they think they know” (Nicholas, 2017) and that is usually a problem when it comes to generating alerts about climate change, for example.

Predicting means: announcing in advance (RAE, 2010), in other words, predicting something is “announcing by revelation, science or conjecture something that has to happen”.

Revelation comes from: a) the prefix “re-”, which can be translated as “backwards”; b) the noun “velum”, which is synonymous with “veil”; y c) the suffix “-cion”, which is used to indicate action and effect. So the word “revelation” means “The act of telling something that is secret, making the hidden visible, or anticipating a future event”.

In the same way, conjecture is defined as the “ judgment that is formed as a result of making observations or analyzing evidence, in other words ,“ judgment or opinion formed from incomplete or supposed indications or data ”. The term, which comes from the Latin coniectūra .

Well, allow me to quote another phrase “ scientists have no word of honor “, this is said like this because what is true today, another scientist will explain it better in the future, with more knowledge, with better tools With better data, better knowledge can be generated, without a doubt, or as one referee said in one of my articles: “ With more work it would be better “.

It must be said that humans, including scientists, are very bad at guessing the future. The weather can only be “predicted” for about five to seven days with certainty because we have satellite images that allow us to “see” the clouds, more or less estimate where they are moving, more time for prediction means greater uncertainty .

History allows us to “predict” that year after year during the rainy season there will be hurricanes that affect the east coast of North and Central America, because the trade winds move from east to west. When exactly will the hurricanes be in terms of days? How many will they be in the next year? With what intensity will they arrive? We do not know, there are no precise answers. I mean, we are not that good at predicting the future, we are scientists, not fortune tellers.

In the case of estimating economic growth by country, which is an activity in which a lot of money is spent, biased estimates have been made since the end of the previous year. For January the uncertainty is very, very large, with variations of units, as the year progresses the predictions are refined, there is more data for the prediction and less time for the end of the year but the uncertainty is tenths of the GDP, already for November there is a lot of data, evidence and the certainties are much greater, for December it is no longer a prediction, it is a fait accompli. However, in this example, the appearance of a black swan is latent at any time.

In examples like the previous one, there is always the possibility of the appearance of “black swans” at any time, those unforeseen events that throw away all predictions, forecasts or estimates, as you like to call them. No one predicted that in the year 2020 the world economy would fall dramatically due to the SARS-CoV-2 pandemic, but as always, once the fact is consummated, the “experts” come out to explain that it was clear that it could happen, that it had signs.

In conclusion, “ It is difficult to make predictions, especially about the future” said Nassim Nicholas Taleb (2007) in his very interesting and illustrative book “ The Black Swan ” translated into Castilian as “Black swan, the impact of the highly improbable”.

Your posts and comments from your “colleagues”

Your posts and comments from your “colleagues”

“Publishing is difficult, being recognized is even more”

 (Bautista, 2021)

When I saw my first article published, I got great satisfaction, great joy for accomplishing one of my goals, beginning to harvest the fruits of so much work and effort. I soon understood that with publications, recognition does not always come to work, at least not from all colleagues and friends. I comment on this, my dear future doctors of science so that you are aware of what awaits you, some comments to your publications will be:

  • Congratulations, but it is in Spanish and the language of science is English
  • How nice, it’s a shame that it was published in a national magazine and only recognized by CONACYT.
  • It’s good that you already publish in English, but the magazine is not JCR (Journal Citation Reports) and has no impact factor

  • What a shame that the magazine in which you publish has a low impact factor
  • That magazine, although it is JCR and has a high impact factor, I think, as it feels, that it is from a predatory publisher
  • Be careful where you publish because not all JCR and impact factor magazines are good
  • This topic is not important for the institution
  • Ok but you are not the first author
  • But you are not an expert on that subject
  • Publishing in high-impact JCR journals, but Open Access is academic colonialism

That is, they will question the topic, magazine, impact factor, editorial, type of publication (open access or by subscription), your place in the list of authors, and everything that is possible, you will not escape criticism. However, the post there is on your CV. Of course you will also receive sincere compliments and congratulations.

Form solid criteria for the selection of the journal, language, review times, costs, prestige, academic profile, think about who your audience will be. This depends on your line of research as well. The best advice I can give you is to verify that the magazine you selected is not on the black list of predatory magazines (predatory journals).

On the other hand, when you work it is only clear that you have to pay the price, in time, of the learning curve, the skills to be a rock star of the academy require a lot of time, dedication and learning with the best tutors. Traveling alone is possible, but it will be difficult, it will be very stimulating, rewarding and magnificent to show yourself that you can alone, but it will be hard.

On the contrary, you will reach the top in less time if you work as a team, where a few write the projects (and there is always money), where there are expert technicians who move in the laboratory like fish in water (and there is always data). There where the great lights are where lines of research, laboratories, undergraduate and graduate degrees are born.

Even better when working in networks, where you have the privilege of knowing other ways of doing science, other laboratories, other equipment, other cultures, so the world becomes small.

Select your path, the shoes, and to walk the path of science.

The new generation of hybrid soil maps, between tradition and modernity

The new generation of hybrid soil maps, between tradition and modernity

Patricia Fragoso, Alberto Pereira, Francisco Bautista  y Gonzalo Zapata

The aim of this work was to develop the digital map of soils for Quintana Roo for a printed scale 1:400000 with 1:50000 work scale data, initially with a geopedological approach and subsequently improved to a digital map.

The map was prepared with data from the formative factors of soils using mathematical methods to infer information in the places where these data are not available. Its elaboration included three stages, the first two following the principles of the geopedological approach consisted in the synthesis of the information generated in the characterization of the geomorphological landscapes (vertical dissection, karst geomorphometrics, failures, geology) and soils, in the third stage incorporating the environmental components (climate and vegetation) and related variables through various statistical analysis (cluster analysis, principal component analysis and classification analysis) the procedure allowed to obtain the pattern of distribution of the Soils to finally develop the model and get to the digital map of soils in the study area.

Vertical dissection, karstic forms (dolines, uvalas and poljes), karst faults densities, and the flooding regime for karstic, bodies of water, and age of parental materials, explain 65% of spatial distribution of soils from Quintana Roo, Mexico.

The analysis of classification denotes that above 83% of soil WRB group assignments are correct.

The soil WRB groups that occupies the territory is the Leptosol, Gleysol and Phaeozem, together occupy 75.6% of surface. Other soil WRB groups are Kastanozem, Regosol, Vertisol, Histosol, Solonchak, Arenosol and Fluvisol.

The map developed with data from the soil forming factors and associated with mathematical methods to infer information in the places where there are no data is an important input for the decision making process.

IVAKY: Index of vulnerability to pollution of yucatecan karstic aquifer

IVAKY: Index of vulnerability to pollution of yucatecan karstic aquifer

The index of the vulnerability of the Yucatecan karstic aquifer (IVAKY) is proposed.

The IVAKY was built based on a geomorphopedological map scale of 1:50 000, which contains the density and type of karst depressions and soil associations in each geomorphopedological unit. The climate factor is included through the length of the rainy period that considers amount, distribution and intensity of the rain.

The three factors (topography, soils and climate) were weighted with the process of hierarchical analysis (AHP) using ArcGis.

It was identified that the ring of sinkholes  and part of the northeast of Yucatan state have the extreme level of vulnerability, where dominated sinkholes in contact with the aquifer and soil as Nudilithic Leptosols, Lithic Leptosols and Rendzic Leptosols, occupying 19% of the state surface.

Low and very low levels of vulnerability are located in southern Yucatan in areas of equal or greater than 50 masl, with low to medium density of karstic depressions (uvala and poljes) and Luvisols, Vertisols and Stagnosols associated with Leptosols ( 12% of the state surface).

In areas with very high levels and high vulnerability, the general population – including producers, entrepreneurs and decision makers – must be informed and made aware that land use is adequately managed, because poor management or activities intensely productive would represent both potential threats and high risks of pollution.

By contrast, in areas with low levels and very low vulnerability, anthropic activities represent a lower risk of aquifer contamination.

Finally, the proposed approach is replicable and could be used to assess the vulnerability of aquifers in regions with similar environmental characteristics in Mexico, Guatemala, Belize, Cuba and the United States of America (Florida).

Aguilar, Y*., F. Bautista, M. Mendoza, O. Frausto, T. Ihl y C. Delgado. 2016. IVAKY: Índice de la vulnerabilidad del acuífero kárstico yucateco a la contaminación. Revisa Mexicana de Ingeniería Química, 15(3): 913-933.

In Karst, inventories of soil organic carbon should be reviewed

In Karst, inventories of soil organic carbon should be reviewed

Living almost 15 years in karst has allowed me to know the particularities of its soils, its diversity. For that reason, when I see the maps of soil organic carbon content I am horrified to see such great mistakes made by my colleagues, the same feeling causes me to hear or read that the Yucatan peninsula, is the largest store of organic carbon in the soil in Mexico.
The organic carbon inventories in the soil in karst areas should be done in a very different way to the way they are being carried out. Discontinuity and spatial heterogeneity should be taken into account at short distances of meters. Soil bulk Density data must be generated and the soil depth not to be used beyond the real depth.

The summary of the paper is:

The organic carbon stock in Leptosls with discontinuous distribution in the Peninsula  of Yucatan

The SOC estimation requires quantifying the coarse fraction(stones and gravels), bulk density and depth. The soils inventory realized for INEGI didn´t reports the first two parameters, then, the generated SOC maps have considerable doubt SOC.

The objective was to evaluate the spatial variability of soil organic carbon over short distances, as well as to report the contents of organic carbon per unit area in Leptosols from northern of Yucatan Peninsula.

102 samples were taken; organic carbon was analyzed by technique of potassium dichromate; and coarse fragments (coarse gravel, medium and fine gravel) were separated from the fine earth. The Color was recorded dry and wet, bulk density was measured using the amount of fine earth in a volume of 10×10 cm surface by a depth to find the rock.

Leptosols presented SOC values below 100 t ha-1 reported for this area, with mean values of 32.85, 37.57, 43.72, and 61.93 t ha-1, for dark brown soils, very dark brown, blacks and very dark grays respectively. Coarse fragments ranging from 6.7% to 96.4% with an average of71.15%.

The amount of edaphic organic carbon is in agreement with the values reported in percentage but lower than those reported in unit of surfaces, which is why it is being overestimated.

The spatial analysis of the soils at short distances reveals a high discontinuity and variability in the percentage of carbon, as well as in the depth and quantity of coarse fragments.

The comparison in the COS content between soils should consider the spatial discontinuity and the amount of COS in kilograms per hectare.
In the soil organic carbon inventories in the north of the Yucatán Peninsula, there has been an overestimation of the organic carbon of the soil that must be corrected considering the discontinuity of the soil and its shallow depth.

Delgado C, Bautista F, Calvo-Irabien LM, Aguilar-Duarte Y y Martínez-Tellez J. 2017. El carbono orgánico en Leptosols con distribución discontinua  en la península de Yucatán. Ecosistemas y Recursos Agropecuarios. 4(10):  31-38.

The magnetic increase in urban dust as an indicator of environmental pollution

The magnetic increase in urban dust as an indicator of environmental pollution

By A. Sanchez, F. Bautista, R. Cejudo, A. Goguichaishvili, J. Reyes, F. Solis and J. Morales

Many studies have shown that the magnetic increase in urban dust is related to the heavy metal pollution. Urban dust contains heavy metals circulating in the atmosphere of the cities. The skin contact, oral intake, and breathing of urban dust is related to serious health problems such as cancer. Chronic exposure of the population to urban dust is a public health problem. The objective of this work was the assessment of pollution using the magnetic increase in urban dusts.

Assessments of magnetic increase on urban dust samples collected on different surfaces, mostly paved and unpaved roads, were performed in order to evaluate the environmental contamination in Mexicali City (medium-sized city on the Mexico-USA border). Rock and mineral magnetic techniques consisted of systematic measurements of mass-specific magnetic susceptibility and isothermal remanent magnetization at 0.7 T.

Magnetic increase was estimated by comparing magnetic concentration for each sample relative to reference value obtained from the site with almost no human activity also known as conservation area in the suburb of town. Additional magnetic parameters as the S-200 ratio and Curie temperatures were used to identify predominant magnetic carriers.

Sánchez-Duque et al._Figura2

Figure 1. Magnetic susceptibility and Saturation Isothermal Remanent Magnetization in urban dust from divers soil urban uses
Sánchez-Duque et al._Figura6

Figure 2. Map of the mangnetic increace as pollution indicator.

Geostatistical analysis and interpolation techniques (experimental variogram and ordinary Kriging, respectively) were carried out in order to determine the spatial distribution of magnetic enhancement and relative levels of environmental contamination.

The results indicate that impure magnetic is the main mineral in most studied samples, other results are:

  1. The background values of the magnetic signal is located in the Conservation Area
  2. At sites with different levels of pollution, the magnetic signal was dominated by non-stoichiometric magnetite and grain coarse. Particles are essentially anthropogenic combustion product.
  3. The highest level of the magnetic increase occurred in areas of high traffic as well as in industrial, commercial and services areas.
  4. In the map we show the most polluted areas in which it should take remedial action.


Sánchez-Duque, A., F. Bautista, A. Gogichaishvili, R. Cejudo-Ruiz, J. Reyes-López, F. Solís-Domínguez  y J. Morales-Contreras. 2015. Evaluación de la contaminación ambiental a partir del aumento magnético en polvos urbanos – Caso de estudio para la ciudad de Mexicali, México. Revista Mexicana de Ciencias Geológicas,