Predicting Disease Outbreaks Using Environmental Changes

Below is a press release about the Methods paper ‘Environmental-mechanistic modelling of the impact of global change on human zoonotic disease emergence: a case study of Lassa fever‘ taken from the University College London.

The multimammate rat (Mastomys natalensis) transmits Lassa virus to humans. ©Kelly, et al.

The multimammate rat transmits Lassa virus to humans. ©Kelly, et al.

A model that predicts outbreaks of zoonotic diseases – those originating in livestock or wildlife such as Ebola and Zika – based on changes in climate, population growth and land use has been developed by a UCL-led team of researchers.

“This model is a major improvement in our understanding of the spread of diseases from animals to people. We hope it can be used to help communities prepare and respond to disease outbreaks, as well as to make decisions about environmental change factors that may be within their control,” said lead author Professor Kate Jones, UCL Genetics, Evolution & Environment and the Zoological Society of London. Continue reading

A Model Approach to Weed Management

Post provided by VANESSA ADAMS

Vanessa Adams in the field with gamba grass in the Batchelor region, NT. ©Amy Kimber (NERP Northern Australia Hub)

Vanessa Adams in the field with gamba grass in the Batchelor region, NT.
©Amy Kimber (NERP Northern Australia Hub)

Invasive weeds cause environmental and economic harm around the world. Land managers bear a heavy responsibility for the control of infestations in what is often a time-consuming and costly battle.

Fortunately, an increasing number of research-based solutions are giving land managers an advantage. This includes tools to determine the distribution of weeds and also the development of modelling approaches to predict their spread.

Understanding the current and future distribution of an invasive species allows managers to better direct their limited resources. However, the direct and strategic management of weeds is tricky and that’s why population models (in particular spatial dispersal models that can be applied without much data) are needed to inform and facilitate action on the ground. Continue reading

Being Certain about Uncertainty: Can We Trust Data from Citizen Science Programs?

Post provided by VIVIANA RUIZ GUTIERREZ

Citizen Science: A Growing Field

Thousands of volunteers around the world work on Citizen Science projects. ©GlacierNPS

Thousands of volunteers around the world work on Citizen Science projects. ©GlacierNPS

As you read this, thousands of volunteers of all ages and backgrounds are collecting information for over 1,100 citizen science projects worldwide. These projects cover a broad range of topics: from volunteers collecting samples of the microbes in their digestive tracts, to tourists providing images of endangered species (such as tigers) that are often costly to survey.

The popularity of citizen science initiatives has been increasing exponentially in the past decade, and the wealth of knowledge being contributed is overwhelming. For example, almost 300,000 participants have submitted around 300 million bird observations from 252 countries worldwide to the eBird program since 2002. Amazingly, rates of submissions have exceeded 9.5 million observations in a single month! Continue reading

The Delphi Technique: Unleashing the Power of Structured Collaboration in Anonymity

Post provided by Nibedita Mukherjee (author of The Delphi technique in ecology and biological conservation)

The quirky nature of decision making

Two heads are often better than one in decision making. Several heads might have an even higher probability of being better than one. However, people in a group often have different modes of thinking or problem solving, alternate reference frames, subjective biases and varying levels or domains of expertise. How do we harness these messy thought processes and channel them for effective decision-making for biodiversity management?

© Henry Martin (The New Yorker Collection/The Cartoon Bank)

© Henry Martin (The New Yorker Collection/The Cartoon Bank)

Continue reading