TV Coverage of Cycling Races Can Help Document the Effects of Climate Change

Archive footage of the Tour of Flanders obtained by Flemish broadcaster VRT - Flanders Classics

Archive footage of the Tour of Flanders obtained by Flemish broadcaster VRT – Flanders Classics

Analysing nearly four decades of archive footage from the Tour of Flanders, researchers from Ghent University have been able to detect climate change impacts on trees. Their findings were published today in the journal Methods in Ecology and Evolution.

Focusing on trees and shrubs growing around recognisable climbs and other ‘landmarks’ along the route of this major annual road cycling race in Belgium, the team looked at video footage from 1981 to 2016 obtained by Flemish broadcaster VRT. They visually estimated how many leaves and flowers were present on the day of the course (usually in early April) and linked their scores to climate data. Continue reading

Using Focus Group Discussions in Conservation Research

Post provided by Christina Derrick

Focus Group Discussions: What are They and Why Use Them?

A focus group discussion with local farmers in Trans Mara district, Kenya, carried out by Tobias O. Nyumba (co-author)

A focus group discussion with local farmers in Trans Mara district, Kenya, carried out by Tobias O. Nyumba (co-author)

To paraphrase Nelson Mandela: ultimately, conservation is about groups of people. On a global scale it’s our collective human footprint that drives habitat destruction and species extinction, and the joint action of large groups that makes positive change. At a smaller scale, groups of people make decisions about conservation policy or management. In turn, communities of people feel the positive or negative effects of these actions, directly or indirectly. From global to local scales, groups of people make changes and groups of people feel the effects of those changes.

To improve conservation action and understand how decisions affect communities on the ground we need to talk to those communities. This is where focus group discussions become an asset to conservation research. They bring participants together in the same place where they can draw from their own personal beliefs and experiences, and those of other group members in a collective discussion. The researcher takes more of a backseat (facilitator) role in focus group discussions compared to interviews, allowing the group conversation to evolve organically. We can get a more holistic view of a situation from this method than from one-on-one interviews alone. Also, as respondents are interviewed at the same time and in the same place, travelling times and costs can be reduced for the researcher. 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

There’s Madness in our Methods: Improving inference in ecology and evolution

Post provided by JARROD HADFIELD

Last week the Center for Open Science held a meeting with the aim of improving inference in ecology and evolution. The organisers (Tim Parker, Jessica Gurevitch & Shinichi Nakagawa) brought together the Editors-in-chief of many journals to try to build a consensus on how improvements could be made. I was brought in due to my interest in statistics and type I errors – be warned, my summary of the meeting is unlikely to be 100% objective.

True Positives and False Positives

The majority of findings in psychology and cancer biology cannot be replicated in repeat experiments. As evolutionary ecologists we might be tempted to dismiss this because psychology is often seen as a “soft science” that lacks rigour and cancer biologists are competitive and unscrupulous. Luckily, we as evolutionary biologists and ecologists have that perfect blend of intellect and integrity. This argument is wrong for an obvious reason and a not so obvious reason.

We tend to concentrate on significant findings, and with good reason: a true positive is usually more informative than a true negative. However, of all the published positives what fraction are true positives rather than false positives? The knee-jerk response to this question is 95%. However, the probability of a false positive (the significance threshold, alpha) is usually set to 0.05, and the probability of a true positive (the power, beta) in ecological studies is generally less than 0.5 for moderate sized effects. The probability that a published positive is true is therefore 0.5/(0.5+0.05) =91%. Not so bad. But, this assumes that the hypotheses and the null hypothesis are equally likely. If that were true, rejecting the null would give us very little information about the world (a single bit actually) and is unlikely to be published in a widely read journal. A hypothesis that had a plausibility of 1 in 25 prior to testing would, if true, be more informative, but then the true positive rate would be down to (1/25)*0.5/((1/25)*0.5+(24/25)*0.05) =29%. So we can see that high false positive rates aren’t always the result of sloppiness or misplaced ambition, but an inevitable consequence of doing interesting science with a rather lenient significance threshold. Continue reading

In Defence of Satellite Data: The Perfect Companion to Ground-Based Research

Post provided by Dr Nathalie Pettorelli

Nathalie is an Institute Research Fellow at the Zoological Society of London. She heads the Environmental Monitoring and Conservation Modelling (EMCM) team and her main research involves assessing and predicting the impacts of global environmental change on biodiversity and ecosystem services. Nathalie was one of the presenters at the UK half of the Methods in Ecology and Evolution 5th Anniversary Symposium in April. You can watch her talk, ‘Harnessing the Potential of Satellite Remote Research’ here.

If there is one question I hear over and over again, it’s this: “why, oh why, do you use satellite data instead of ground-based data in your research?” People seem to think that I believe satellite data are better than ground-based data. Do I not value fieldwork? Do I not trust ground-based data? My answer to all of this is: you’ll never catch me preaching that satellite remote sensing can solve the entire data collection gap in ecological monitoring.

I use satellite data because a lot of my work happens at relatively large spatial and temporal scales, targets regions where ground-based data are simply unavailable or extremely difficult to gather and relies on being able to access data that have been collected in a systematic and scalable manner.

Yes, satellite-based techniques can address spatial and temporal domains inaccessible to traditional, on-the-ground, approaches, but I am the first to acknowledge that satellite remote sensing cannot match the accuracy, precision and thematic richness of in-situ measurement and monitoring.

©Clare Duncan

The New Generation of Ecologists in Action: Clare Duncan conducting field measurements in the Philippines to be combined with satellite remote sensing information to monitor ecosystem services delivery. ©Clare Duncan

In spite of this, data collected on the ground are currently difficult to use for mapping and predicting regional or global changes in the spatio-temporal distribution of biodiversity (a problem for those of us trying to tackle these kinds of issues). Ground-based data can also be expensive and tend to come from a single annual time period. This makes it difficult to gather information on temporal changes and phenology. Continue reading