Which threatening processes should be research priorities to save more threatened species?

New research shows that removing uncertainty about threats could quadruple the gains in species persistence currently achieved by best practice threat management. Prioritising research to understand the effectiveness of managing fire, invasive predators and dieback would maximise species benefits.
Published in Ecology & Evolution
Which threatening processes should be research priorities to save more threatened species?

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Managing threatened species requires making tough decisions. The lists keep getting longer, and management agencies globally are increasingly required to prioritise limited resources to save species. With limited resources, it’s important to use resources efficiently. Unfortunately, species management outcomes are often uncertain, so we rarely know where to target efforts to improve management efficiency, nor how many additional species could be saved by more efficient management.

To understand the potential gains from removing uncertainty about threatening processes, we undertook a value of information analysis. Value of information is a decision-science technique that measures the potential gains from the collection of new information. In our case, it allows decision-makers to prioritise the investment in improving knowledge about management effectiveness of threatened species. Working with the New South Wales government’s innovative Saving our Species program in Australia, we analysed almost 1,000 threatened species and threatened ecological communities affected by 20 key threatening processes including some of the big threats impacting species globally, such as fire, invasive species, and diseases. Calculating the value of information for such large numbers of species and threats is challenging and hasn’t been attempted before. One of our biggest challenges was to evaluate the gains in reducing two sources of uncertainty: the effectiveness in management of threats and the response of the species to that management. To collect the data for our analysis, we asked species experts to estimate the effectiveness of best practice management and the expected persistence of species with and without each threat. 

We analysed the impacts of threats to almost 1000 listed species and threatened ecological communities in NSW, including (clockwise from top left): Grey-crowned babbler, koala, and Major Mitchell's cockatoo. Photos: May-Le Ng.

Across all threats, we found that the average gain in species persistence if managed under current uncertainty would be 3% per species. If uncertainty could be removed, the gains would jump to 12% per species. The potential gains from removing uncertainty about threat management effectiveness could quadruple the gain in persistence achieved by managing under current uncertainty.

The implications of this finding are that uncertainty is far more influential than we thought for some threats and there are big opportunities to improve species management if we target research investment towards particular threats. We found that managers were confident about controlling invasive plant threats, but very uncertain about the benefits of managing high frequency fire, invasive predators and the plant dieback pathogen Phytophthora cinnamomi. Uncertainty about how species respond to threats had greater value than uncertainty about management’s ability to reduce the threat itself: i.e. it’s always better to attempt management than to do nothing even when the effectiveness is uncertain; but there are large potential benefits from better understanding how species will respond to threat reductions.

Our study quantifies the opportunities from better understanding how threat management influences species persistence but also creates new questions about how to best capitalise on these opportunities. When we looked at the interactions between threats, we found that the threats with the greatest potential gains from management (fire, invasive predators, dieback) were also those that interacted most with other threats. How to disentangle these interactions to reduce uncertainty is an ongoing challenge. Our next project will use adaptive management algorithms from artificial intelligence to strategically learn how to improve threat management over time while managing the system.

Our study is the first to quantify the value of information about threat management at such a broad scale. While many previous value of information studies have focused on single species and found minor benefits from removing uncertainty, our approach showed that when small benefits are aggregated across the many species impacted by threats, there can be large potential gains to management from reducing those uncertainties.  


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