Open-source data are information provided free online. It is gaining popularity
in science research, especially for modeling species distribution. MaxEnt is an
open-source software that models using presence-only data and environmental
variables. These variables can also be found online and are generally free. Using
all of these open-source data and tools makes species distribution modeling
(SDM) more accessible. With the rapid changes our planet is undergoing, SDM
helps understand future habitat suitability for species. Due to increasing interest
in biogeographic research, SDM has increased for marine species, which were
previously not commonly found in this modeling. Here we provide examples of
where to obtain the data and how the modeling can be performed and taught.
Key Words: open-source data; MaxEnt; species distribution modeling; whale shark.
Species distribution modeling (SDM) takes
occurrence data, from observation or abundant datasets, and combines it with environmental variables to provide insight to species
spatial distribution (Elith & Leathwick,
2009; Senay et al., 2013). SDM provides
great potential for conservation planning
and management (Elith et al., 2006; Fourcase et al., 2014; Marshall et al., 2014), especially for marine environments (Stirling
et al., 2016). Over the years, SDM has promoted conservation by mapping regional
and world patterns such as dispersal, change
in habitat suitability, and potential extinctions (Sinclair et al., 2010), and forecasting
species distribution (Araújo & Guisan,
2006; Elith et al., 2006; Guisan et al., 2013). A correlative SDM uses
occurrence data and environmental variables to model species habitat
suitability (Jarnevich et al., 2015). In recent years, interest in modeling
marine species has increased (Redfern et al., 2006; Valavanis et al.,
2008), although modeling of marine mammals is more common than
other species (Robinson et al., 2011).
Maximum Entropy (MaxEnt) is a statistical procedure that
allows the least biased predictions of probability when it comes to
distributions and distribution patterns (Harte & Newman, 2014).
An open-source software is available online, also called MaxEnt. It
effectively handles complex functions and most accurately predicts
habitat suitability (Sinclair et al., 2010; Fourcase et al., 2014; Porfirio
et al., 2014). It generates predicted habitat suitability maps, current
and future, using known or presence-only species occurrences with
environmental variables (Fourcase, 2016). Both the presence-only
and the environmental variables data can be found online through
numerous websites dedicated to creating and updating this data.
(For more specific details about MaxEnt, see Phillips et al., 2006,
and Elith et al., 2011).
The overall goal of an activity using this information is to have
students use technology to increase their awareness and understanding of habitat suitability
changes and the effects on threatened species,
and to increase their critical thinking about conservation methods to prevent future extinctions.
The case study provided here was designed to
meet biology standards; however, it can be implemented in environmental sciences, ocean sciences, geosciences, and geography classes. It covers
many of the key concepts and practices suggested
by the AP Biology curriculum (Table 1) and the
Next Generation Science Standards (Table 2).
Finding the Data
Open-source data for species can be found in
numerous websites including Global Biodiversity Information Facility
(GBIF), International Union for Conservation of Nature (IUCN), eBird,
Ocean Biogeographic Information System (OBIS), iNaturalist, among
Current issues, such as
climate change, give
students a more
understanding of the
society and nature.
The American Biology Teacher, Vol. 80, No. 6, pp. 457–461, ISSN 0002-7685, electronic ISSN 1938-4211. © 2018 National Association of Biology Teachers. All rights
reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press’s Reprints and Permissions web page,
www.ucpress.edu/journals.php?p=reprints. DOI: https://doi.org/10.1525/abt.2018.80.6.457.
THE AMERICAN BIOLOGY TEACHER USING OPEN-SOURCE DATA IN CORRELATIVE SPECIES DISTRIBUTION MODELING OF MARINE SPECIES
TIPS, TRICKS &
Using Open-Source Data in
Correlative Species Distribution
Modeling of Marine Species
• CARLOS A. MORALES-RAMIREZ,
PEARLYN Y. PANG