Uncertainties in Species Occurrence Data: How to deal with False Positives and False Negatives

Post provided by Gurutzeta Guillera-Arroita

Species Surveys: New Opportunities and Ongoing Data Challenges

Technologies, such as drones, open new opportunities for wildlife monitoring ©J. Lahoz-Monfort, UMelb.

Technologies, such as drones, open new opportunities for wildlife monitoring ©J. Lahoz-Monfort, UMelb.

Monitoring is a fundamental step in the management of any species. The collection and careful analysis of species data allows us to make informed decisions about management priorities and to critically evaluate our actions. There are many aspects of a natural system that we can measure and, when it comes to monitoring the status of species, occurrence is a commonly used metric.

Ecologists have a long history of collecting species occurrence data from systematic surveys and our ability to gather species data is only going to grow! This is partly enabled by the fact that citizen science programs are starting to gain a prominent role in wildlife monitoring. There’s a growing recognition that well-managed citizen science surveys can produce useful data, while scaling up monitoring effort thanks to the increased human-power from large numbers of committed volunteers. Continue reading

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Uncertainty in biological monitoring : An interview with Viviana Ruiz-Gutierrez

David Warton (University of New South Wales) interviews Viviana Ruiz-Gutierrez (Cornell University) about her recent paper Uncertainty in biological monitoring: a framework for data collection and analysis to account for multiple sources of sampling bias. They discuss the main contributions of the paper, the effect false positives can have on occupancy estimates (when not accounted for) and her current position at Cornell. They finish off (in Spanish!) discussing the next step in her research agenda.

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

Issue 7.1

Issue 7.1 is now online!

The January issue of Methods is now online!

As always, the first issue of the year is our sample issue. You can access all of the articles online free of charge. No subscription or membership is required!

We have two Open Access articles and two Applications papers in our January issue.

Recognizing False Positives: Environmental DNA (eDNA) is increasingly used for surveillance and detection of species of interest in aquatic and soil samples. A significant risk associated with eDNA methods is potential false-positive results due to laboratory contamination. To minimize and quantify this risk, Chris Wilson et al. designed and validated a set of synthetic oligonucleotides for use as species-specific positive PCR controls for several high-profile aquatic invasive species.

BiMat: An open-source MATLAB package for the study of the structure of bipartite ecological networks. BiMat enables both multiscale analysis of the structure of a bipartite ecological network – spanning global (i.e. entire network) to local (i.e. module-level) scales – and meta-analyses of many bipartite networks simultaneously. The authors have chosen to make this Applications article Open Access.

Gemma Murray et al. provide this month’s second Open Access article. In ‘The effect of genetic structure on molecular dating and tests for temporal signal‘ the authors use simulated data to investigate the performance of several tests of temporal signal, including some recently suggested modifications. The article shows that all of the standard tests of temporal signal are seriously misleading for data where temporal and genetic structures are confounded (i.e. where closely related sequences are more likely to have been sampled at similar times). This is not an artifact of genetic structure or tree shape per se, and can arise even when sequences have measurably evolved during the sampling period.

Our January issue also features articles on Monitoring, Population Ecology, Genetics, Evolution, Community Ecology, Diversity and more. 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