A study tool that combines statistics, programming, biology and space technology. Known by various names such as "climate envelope modeling", "habitat modeling" or "niche modeling", species distribution models seek to propose a new point of view for various areas of study, from conservation to epidemiology, paleontology and ecology. The history of distribution modeling began in the 1970s with the introduction of personal computers in universities, the advancement of space programs and the consolidation of statistics, as well as the exponential increase in scientific publications from the 1980s onwards (Figure 1) (lobo et.al 2010).
Figure 1: Number of published articles (line) and variation in the number of accumulated articles (dots) on species distribution, modeling found in ISI Web of Science after searching by themes and authors (Source: lobo et.al 2010 )
The first question that usually comes up after this introduction is: "How does it work?”. To clarify how it works, we can divide its functions into 4 main stages: data collection and preparation, execution of the selected algorithm, verification of the suitability of the prediction and, finally, the final result. The first stage, as the name suggests, involves collecting data that can come from taxonomic collections, articles, satellite images, online databases and a multitude of possible sources depending on the objective of the study. This stage is undoubtedly the most crucial, as it requires greater attention on the part of the researcher in what we call "data cleaning". This step consists of removing "impurities" from the data set, which generally do not make sense with the biogeographical condition of the period analyzed, in order to avoid taxonomic, temporal and spatial biases, which increases the reliability of the study. The second stage is a little more complex, as it is based on passing this data through an algorithm that will put it into predictive mathematical theorems such as linear regression, logistic regression, regression trees, among other models. In a simplified comparison, it would be like a first-degree equation that generates a linear graph in which, with the data collected and following the equation "y = ax + b" we can predict a straight line. It is important to note that the theorem used can vary according to the form of analysis and research, which means that new algorithms are constantly being updated and created. The third stage is the scientist's validation of the prediction by the accuracy of the data, i.e. interpreting what the graphs and mathematical models mean and whether there were any possible errors in the model. The final stage will not be explored in depth, as it would require a specific framework.
Figure 2: Line resulting from a first-degree polynomial function (Source: Personal archive)
With the process briefly explained, we can now move on to the practical applications of this research tool. Because it is a predictive tool, it can be used to understand how extinctions occur, for example, the evolution of disease transmission and even the population dynamics of invasive species. However, one of the applications that has come to the fore in recent years is the prediction of ecological interactions between animals and the climate changes that have been taking place on our planet. An important read that demonstrates the use of these tools in this context is shown in "The fate of endemic birds of eastern Brazilian mountaintops in the face of the climate change" (Hoffman, 2020), in which the author obtained results that made it possible to infer that the habitats of endemic mountaintop species tend to decrease in the coming years and suggests places where the creation of preservation areas would be more effective in terms of the ecology of these biomes.
In conclusion, species distribution modeling is a useful tool in several areas and should undoubtedly be more present in national research, especially with the recent climate changes. It is worthwhile for students of veterinary medicine, biology, zootechnics and related areas within the field of ecology, the environment and wild animals to invest in learning how to use these tools to promote research that can help as a conservation tool in the future.
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