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Poorly Known Species at Most Risk from Extinction

August 14, 2013

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The small-toothed sportive lemur is poorly known by science, a fact that increases its extinction risk. Photo: Edward E. Louis Jr. under a Creative Commons license.
The small-toothed sportive lemur is poorly known by science, a fact that increases its extinction risk. Photo: Edward E. Louis Jr. under a Creative Commons license.

Earlier this year, the University of Queensland played host to the first Student Conference on Conservation Science to be held in Australia. The Australian conference was modeled on a successful event that has been running at the University of Cambridge for well over a decade, and which I had the great pleasure to attend during my own PhD.

The conference brings together young conservation scientists from around the world, to share their work with each other, and to attend short workshops run by experienced conservation scientists. At the Australian conference there was an emphasis on supporting attendance of students from Asia and the Pacific.

The Nature Conservancy sponsored prizes for the best talks and poster presentation by students at the conference. All the students attending were doing fascinating and important conservation science, but the prize winners have also learnt the critical skill of communicating it well. We applaud them. They will be the future leaders of conservation science and the Conservancy is glad to be able to reward them in a small way.

We asked each of the prize winners to introduce themselves and share their research on Cool Green Science. We’ll be running a blog from three winners this week, beginning with this piece by first prize winner Lucie Bland.–Eddie Game, conservation planning specialist

The less we know about a species, the more at risk they are at extinction. This map shows the global distribution of Data Deficient mammals, with yellow-red-orange indicating progressively less data on species. Image: Lucie Bland
The less we know about a species, the more at risk they are at extinction. This map shows the global distribution of Data Deficient mammals, with yellow-red-orange indicating progressively less data on species. Image: Lucie Bland

Poorly Known Species at Most Risk from Extinction

By Lucie Bland, PhD candidate, Zoological Society of London & Imperial College London

A major obstacle for conservation is our incomplete knowledge of the biological world. Less than 10% of the world’s putative species have been described, and conservation knowledge is heavily biased towards terrestrial vertebrates and plants, and temperate rather than tropical regions.

Uncertainty in global conservation knowledge first aroused my interest during an internship at the IUCN headquarters in Switzerland in the summer of 2009. The IUCN Red List of Threatened Species is the most comprehensive tool for assessing species’ extinction risk, and is key to monitoring progress towards the targets of the Convention on Biological Diversity.

However, 1 in 6 of the 65,000+ species on the IUCN Red List of Threatened Species are classified as Data Deficient, due to paucity of information on their distribution and population status. Data Deficient species are of great conservation concern, as they distort global patterns of extinction risk and may be neglected by conservation programs due to their uncertain conservation status.

My PhD, based at the Zoological Society of London and Imperial College London, focuses on the effect of data deficiency on global conservation prioritization. Do data gaps influence global patterns of extinction risk, and if so, how can we reduce this uncertainty cost-effectively?

The Student Conservation Conference in Brisbane provided a great opportunity to share my recent work on predicting the conservation status of Data Deficient species. Large amounts of information available for Data Deficient species, such as life-history, ecological and remotely-sensed data, are currently not being used to inform their conservation status. Predicting conservation status from these data may provide a rapid and cost-effective approach for reducing uncertainty in global estimates of risk, and prioritizing Data Deficient species for monitoring.

Taking terrestrial mammals as a focal group, my presentation demonstrated that powerful statistical models can accurately predict species extinction risk. I predicted 64% of Data Deficient terrestrial mammals to be at risk, increasing the estimated proportion of threatened terrestrial mammals from 22% to 27% globally.

I also found that regions predicted to contain large numbers of threatened Data Deficient species were already conservation priorities, but showed considerably higher levels of species imperilment than previously recognized. I concluded that unless directly targeted for surveys and conservation action, poorly-known species were likely to slide towards extinction unnoticed. As a consequence, my current work focuses on effectively allocating limited conservation resources to the monitoring of Data Deficient species.

Lucie Bland’s  broader research interests lie at the crossroads between human knowledge, species traits and human impacts. She is particularly interested in patterns of species discoveries, rediscoveries and extinctions, and how these reveal how humans study biodiversity. She wishes to pursue a career in academia, extending ecological and conservation approaches to poorly-known species. Lucie even has a pet project on crayfish macroecology and macroevolution.

Eddie Game

Eddie Game is the lead scientist for The Nature Conservancy, Asia Pacific Region. He is responsible for ensuring that the Conservancy remains a world leader in making science based conservation decisions, can robustly report on our impact, and that we get the greatest return for our conservation investments. Eddie has worked on conservation projects in over 15 countries, helping to apply innovative methods and analyses to projects as diverse as community protected areas in the Solomon Islands, grazing management in northern Kenya, and catchment restoration in Colombia. More from Eddie

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