Eureka Prize

A quick heads up that the IUCN Red List of Ecosystems team won the Eureka Awards for Environmental Research!! The Eureka Awards of the Australian Museum are considered the “Oscars” of Australian science, so I can’t get any better than that!

Thanks to all the team for their hard work over many years, and to many years of exciting research and implementation to come! Also well done on the 4:3 gender split.


New publication in Journal of Applied Ecology

A week after it’s initial publication, I am finally getting round to posting a link to my new article on the cost-effective assessment of extinction risk with limited information. I wrote this paper during my first visit to CEED in 2013, working with Emily Nicholson and Michael McCarthy.

The setting: one in six species on the IUCN Red List are assessed as Data Deficient, seriously limiting our capacity to monitor biodiversity and track our progress towards international targets. Given the costs of field surveys and Red List assessments, re-assessing all 12,000+ species would cost USD320 million.

So how can we make the most of limited conservation dollars when assessing the status of Data Deficient species? The answer is double sampling, a simple technique borrowed from a statistics paper from the 1970s by Tenenbein, and described more intuitively in Mick McCarthy’s blog.

To estimate the proportion of Data Deficient species at risk of extinction, we can use:

– field surveys and IUCN Red List assessments, which are a perfect ‘gold standard’ but expensive

– models of extinction risk, which are cheaper but can make mistakes when predicting the status of species

I built predictive models of extinction risk for mammals, reptiles, amphibians and crayfish. I correlated species information (life-history traits, environmental niche and threat exposure) with true IUCN Red List status for well-known species. These simple data are often available for Data Deficient species, and can be collected from museum specimens, museum records and freely-available GIS layers. Good news, the models based on simple data were able to predict true Red List status very well, and for a fraction of the cost! The cost ratio between Red List assessments and my own work on predicting species extinction risk turned out to be 1,500 – a bold statement on how cheap PhD students are in the UK! This means that we could rapidly and cheaply predict the status of Data Deficient species with models, rather than wait for Red List assessments.

The paper demonstrates that by using both Red List assessments and models of risk (hence double sampling), we can estimate the levels of extinction risk in Data Deficient species for a third of the original costs of Red List assessments. This is because the status of all Data Deficient species are predicted with cheap models, whilst 1-6% of the species are assessed with Red List assessments to reduce errors in classification. Double sampling has considerable potential for estimating the proportion of Data Deficient at risk of extinction, and reducing the uncertainty in the Red List and Red List Index.

This graph shows the proportion of threatened species in different animal groups, with error bars representing the uncertainty due to Data Deficient species. Double sampling could cheaply reduce this uncertainty and help monitor the global status of biodiversity.

We also published an easy-to-use Excel spreadsheet to calculate the possible reductions in cost with double sampling (Tip: it works for any situation comparing two sampling methods differing in cost and reliability).

European travels

Bye bye Aussie summer ... Hello Helsinki
Bye bye Aussie summer … Hello Helsinki

I recently embarked on a four week-long tour of six European countries, full of workshops, talks and collaborations. The trip started with a Red List of Ecosystems (RLE) Committee for Scientific Standards meeting, where 25 experts on ecosystems, risk assessment and remote sensing discussed the challenges and solutions for the application of the RLE criteria. Over three days, we covered topics ranging from building a global ecosystem typology, identifying new datasets for RLE assessments, to refurbishing the IUCN Threats classification. I believe we made a lot of progress, and the RLE Guidelines are set to be published by mid-2015! During our week in Helsinki we also had a one day workshop on red listing Finnish ecosystems (we learnt a lot about mires), and a further workshop on setting up an Arctic/Boreal thematic group. Having never attended a thematic group meeting before, it was extremely interesting to witness the different steps involved in setting up working plans and large-scale assessments. The IUCN CEM members were very enthusiastic and proactive, so we will hopefully be able to add Arctic/Boreal ecosystems to our increasing list of assessments.

IUCN Red List of Ecosystems Committee for Scientific Standards - blinded by the Nordic sun
IUCN Red List of Ecosystems Committee for Scientific Standards – blinded by the Nordic sun

After a brief week end in Stockholm I visited the Max Planck Institute for Biodemography in Odense, Denmark. The group is mostly formed of human demographers, and I had the pleasure to attend the lab’s morning presentations. Knowing very little about human demography, I was surprised by the abundance of data on human mortality and causes of death (something biologists can only dream of!), and the complexity of human demography models. The graphs reminded me of paleontological reconstruction graphs, which almost require an entire degree to get to grips with. We then got to work on DISKo (Demographic Index of Species Knowledge), and index which quantifies the amount of demographic information for the world’s vertebrates.

Next stop was Switzerland, with a visit to IUCN Headquarters in Gland. I had not set foot in IUCN since 2009, when I completed a summer internship in the Species Programme. I met with a few staff members and explored the relationship between RLE and IUCN programmes, such as Conservation Economics, Global Policy and Climate Change Adaptation. Given that I haven’t focused much on the applications of RLE, it was great to learn more about the intended uses for the ecosystem assessments. I also gave a talk on the scientific foundations of RLE – focusing on how to define ecosystem collapse. During question time we discussed the relationship between RLE and the Red List of Threatened Species, and how these two products can complement each other – something we are all very excited about.


Final stop was England. I gave a talk at University College London and a talk at UNEP-WCMC in Cambridge. I received a lot of interesting feedback and spiny questions – How does the RLE treat urban and modified areas? Does the RLE reflect a perception of nature without people? How will the RLE link with ecosystem services and climate adaptation? The questions asked in the two environments differed drastically – from science to applied conservation policy – and stretched me at times. Working at the science-policy interface has its challenges, as it can be difficult to satisfy queries from both spheres simultaneously. Overall, giving these talks enabled me to consider the project from different angles, and take into account the future uses of RLE into my current work.


Böhm, M., Williams, R., Bramhall, H., McMillan, K., Davidson, A., Garcia, A, Bland, L. M., Bielby, J., Purvis, A. and Collen. B. The correlates of extinction risk in reptiles: the relative importance of biology, geography and threat (submitted).

Bland, L. M., Collen, B., Orme, C. D. L. and Bielby, J. Known unknowns: global patterns of conservation knowledge deficiency (submitted).

Bland, L. M., Collen, B., Nicholson, E., Orme, C. D. L., Bielby, J, and Mc Carthy, M. Cost-effective assessment of extinction risk with limited information, Journal of Applied Ecology (in revision).

Rodríguez, J. P., Keith, D. A., Rodríguez-Clark, K. A., Murray, N. J., Nicholson, E., Regan, T. J., Miller, R. M., Barrow, E. G., Boe, K., Brooks, T. M., Oliveira-Miranda, M. A., Spalding, M., Bland, M., and Wit, P. A practical guide to the application of the IUCN Red List of Ecosystems criteria, Philosophical Transactions of the Royal Society: Series B, 1662.

Bland, L. M., Collen, B., Orme, C. D. L. and Bielby, J. (2014) Predicting the conservation status of Data Deficient species, Conservation Biology (early view).

Bland, L. M., Collen, B., Orme, C. D. L. and Bielby, J. (2012) Data uncertainty and the selectivity of extinction risk in freshwater invertebrates, Diversity & Distributions 18(12) 1211-1220.

Bland, L. M. (2006) My donkey (Mon ane), Vigot Editions, Paris, France, 126 p.

New issue of Phil Trans

This monday a new issue of Phil Trans was published, which might mean my favourite papers of the year by my favourite people have already been published (and it’s only the 5th of January!).

First of all, A practical guide to the application of the Red List of Ecosystems criteria is a paper from the RLE team (incl. myself) expanding on the PLoS paper describing the RLE criteria. So, what’s new? The paper reviews the intended application of the RLE assessment process, summarize ‘best-practice’ methods for ecosystem assessments and outline approaches to ensure operational rigour.

I enjoyed reading Richman et al.’s paper on the global conservation status of crayfish. They found 32% of crayfish to be at risk of extinction, with large geographical variation in threat drivers. The majority of threatened US and Mexican species face threats associated with urban development, pollution, and water management. On the other hand, the majority of Australian threatened species are affected by climate change, harvesting, agriculture and invasive species. Congratulations to Nadia for seeing this project through!!

Distribution of: (a) all crayfish species; (b) (c) threatened species; (d) (e) data-deficient species. Linked from Royal Society Publishing.

I also enjoyed Owen et al.’s paper on the global phylogeny of crayfish. They created both a synthetic tree and a maximum likelihood dated phylogeny (with fewer nodes). This enabled them to created EDGE and HEDGE scores for a number of crayfish species.

New job and new paper

Many news this (new) side of the earth …

  • I have been awarded a PhD from Imperial College London in July 2014, after passing my viva with no corrections in May 2014. My thesis was entitled “Resolving the effects of Data Deficient species on the estimation of extinction risk” and comprised four data chapters. You can e-mail me to request a copy of the thesis (it’s a heavy file!).
  • I am now a Research Associate in ecosystem risk assessment at the University of Melbourne with the QAECO group. I will be creating process-based models of ecosystem collapse to inform the rules and criteria of the IUCN Red List of Ecosystems. I am working with Emily Nicholson and Tracey Regan. The project is supported by an ARC Linkage Grant, and involves collaborators from UNSW, UniMelb, Deakin, IUCN, NSW Office of Environment and Heritage, and the Government of South Australia.
  • My new paper is out in Conservation Biology: Predicting the conservation status of Data Deficient species.Download Early View from this link or ask me for a reprint!

It's not all work ... before the move to Australia I also dropped by the Great Blue Hole in Belize
It’s not all work … before moving to Australia I also dropped by the Great Blue Hole in Belize



Women in STEM

Women in Science Technology Engineering and Technology is a hot topic at the moment – even being covered in Animal Conservation and many blog posts. I just came across this graphic from explaining attrition in the sciences – why women drop out of the science ladder as they progress. It would be great to see it extended to postgraduate and research jobs, as female attrition reaches it peak post-PhD, allegedly due to conflicts between academic careers and child-raising. For example, around 46 % of those being awarded undergraduate science degrees in the USA are women, but this percentage drops to 39 % for masters degrees, 33 % for doctoral degrees and – at the end of the career spectrum – 6 % for full professorships. Clearly, today’s challenge is not only to get women into science, but to keep them.