New mathematical model can help save endangered species

This is the cover photo for article. Credit: Blake Meyer on Unsplash

The risk of extinction varies from species to species depending on how individuals in its populations reproduce and how long each animal survives. Understanding the dynamics of survival and reproduction can support management actions to improve a specie's chances of surviving.

Mathematical and statistical models have become powerful tools to help explain these dynamics. However, the quality of the information we use to construct such models is crucial to improve our chances of accurately predicting the fate of populations in nature.

“A model that over-simplifies survival and reproduction can give the illusion that a population is thriving when in reality it will go extinct.”, says associate professor Fernando Colchero, author of new paper published in Ecology Letters.

Colchero's research focuses on mathematically recreating the population dynamics by better understanding the species's demography. He works on constructing and exploring stochastic population models that predict how a certain population (for example an endangered species) will change over time.

These models include mathematical factors to describe how the species' environment, survival rates and reproduction determine to the population's size and growth. For practical reasons some assumptions are necessary.

Two commonly accepted assumptions are that survival and reproduction are constant with age, and that high survival in the species goes hand in hand with reproduction across all age groups within a species.

Colchero challenged these assumptions by accounting for age-specific survival and reproduction, and for trade-offs between survival and reproduction. This is, that sometimes conditions that favor survival will be unfavorable for reproduction, and vice versa.

For his work Colchero used statistics, mathematical derivations, and computer simulations with data from wild populations of 24 species of vertebrates. The outcome was a significantly improved model that had more accurate predictions for a species' population growth.

Despite the technical nature of Fernando's work, this type of model can have very practical implications as they provide qualified explanations for the underlying reasons for the extinction. This can be used to take management actions and may help prevent extinction of endangered species.

###

The study is published in the journal Ecology Letters led by Associate Professor Fernando Colchero from Department of Mathematics and Computer Science and the Interdisciplinary Center on Population Dynamics (CPop) at the University of Southern Denmark. The study was carried out in collaboration with with CPop members Asoc. Profs. Owen R. Jones and Dalia A. Conde from the Biology Department at SDU, and Annette Baudisch from the Faculty of Social Sciences, together with collaborators from over 20 institutions around the world.

Media Contact

Majken Brahe Ellegaard Christensen
majken@sdu.dk

 @NATsdu

http://www.sdu.dk/en/om_sdu/fakulteterne/naturvide 

All latest news from the category: Ecology, The Environment and Conservation

This complex theme deals primarily with interactions between organisms and the environmental factors that impact them, but to a greater extent between individual inanimate environmental factors.

innovations-report offers informative reports and articles on topics such as climate protection, landscape conservation, ecological systems, wildlife and nature parks and ecosystem efficiency and balance.

Back to home

Comments (0)

Write a comment

Newest articles

Speaking without vocal cords, thanks to a new AI-assisted wearable device

The adhesive neck patch is the latest advance by UCLA bioengineers in speech technology for people with disabilities. People with voice disorders, including those with pathological vocal cord conditions or…

New yttrium-hydrogen compounds discovered

Researchers at the University of Bayreuth have made a significant scientific breakthrough by discovering new yttrium-hydrogen compounds having serious implications for the research on high-pressure superconductivity. High-pressure superconductivity refers to…

New AI model detects ninety percent of lymphatic cancer cases

Medical image analysis using AI has developed rapidly in recent years. Now, one of the largest studies to date has been carried out using AI-assisted image analysis of lymphoma, cancer…

Partners & Sponsors