Important Bird and Biodiversity Areas (IBAs), Conservation and Cloud Forests

A recent paper in the journal explains how remote sensing is being used to identify IBAs, sites of international significance for the conservation of birds (and other taxa), that are at greatest risk of deforestation.

The Challenge

For years, conservationists have been calling out for an easy-to-use method of monitoring land-cover change across sites of conservation importance. In 2013 Hansen et al. (Science 342, 850–853) produced a 30m resolution global map of tree cover, and tree cover change. Despite acknowledged limitations of the map, it provided an opportunity for conservationists to assess and visualise broad patterns of tree loss at a global scale.

Analysis of these data on sites of conservation concern would enable conservationists to identify conservation priorities to which effort could be targeted. Examination of correlates of change could enable conservationists to identify the characteristics of sites that make them susceptible to forest loss, enabling pro active conservation.  But how to do this for such a large data set? The solution turned out to be through a collaboration between a physicist eager to help conservation, the secretariat of BirdLife International, the global partnership of conservation NGOs, and the Royal Society for the Protection of Birds, the UK BirdLife partner. Oh, and a massive amount of help from Google Earth Engine’s staff and their cloud processing power…


Map from Google Earth showing forest cover change in Borneo

The Cloud Forest

Google Earth Engine is a cloud-computing environment dedicated to geospatial analysis that allows rapid processing of vast amounts of data. Best of all, it does not require the developer to be an expert on parallel programming paradigms. Basic knowledge of Python or Java Script language is enough to perform otherwise complicated analyses. Suffice to say that all our output was generated with little more than 40 lines of code!

From the petabytes of available on Google Earth Engine data sets, we focused on Global Forest Change map provided by Hansen et al. It allowed the assessment of tree-cover change between 2000 and 2012 within each of the 7,700 Important Bird and Biodiversity Areas (IBAs) which hold forest birds. These sites are a subset of the global network of over 12,000 IBAs.

Action and Reaction

After the extraction of these data, we identified correlates of forest loss. This enabled us to identify which characteristics of IBAs are associated with them being at greatest threat from deforestation. This knowledge can help target resources to sites with attributes that point to them being at greatest risk. Think active intervention. But the most urgent use for these data is in identifying IBAs being damaged and degraded now, in order to call in the cavalry before, fingers crossed, it is too late – reactive conservation. Conservation resources are limited, so it is important that the sites to which resources are targeted first are those in most immediate need of support.

Our data have already fed directly into BirdLife’s vital “IBAs in Danger” initiative (, which aims to highlight those IBAs around the world in direst need of conservation intervention if they, and the species that they support, are to survive. These represent the most threatened of the most important sites for birds and other biodiversity across the globe.

Point of use

These data have now been circulated to regional BirdLife secretariats in Southern America, Oceania, Europe, Asia and Africa where they are being used close to the point of use. As detailed in our paper, feedback from this process has highlighted some issues with these data. For example, it is widely recognised that the Hansen et al data do not differentiate between natural and plantation tree cover. It transpired that the site which experienced the highest proportional loss of trees in the study had recently had a plantation removed. Step the cavalry down.  Such local knowledge is essential if these data are to be exploited to their full potential.

In Australia the loss of forest confirmed concerns regarding the trends in natural habitat loss as a result of increasing occurrences of fire in two sites already identified as IBAs in Danger.  These data highlighted another six IBAs across Australia where over 25% of tree coverage had declined during the survey period.  BirdLife Australia staff are checking to see what impact this is likely to have on species at these sites.


Median percentage forest loss between 2000 and 2012 within Important Bird and Biodiversity Areas (IBAs) identified for forest dependent species, for each country. Each colour category contains equal numbers of countries

But caution is needed when using these data alone – field surveys are still needed. We found that the forest cover map for many parts of Fiji, including the third largest island Taveuni, appears unable to differentiate between forest and cultivated habitats. Consequently, the change in the extent of forest cover that we reported is unlikely to be an accurate assessment of what has happened to IBAs here.  Finally there is no information on forest cover for most of the Polynesian and Micronesian Islands.  While the area of forests in these countries is small the proportion of globally threatened species that they contain is disproportionately high. We have recently provided feedback to the data producers on these issues.

Despite these issues, the fact that these data have already been used to inform conservation priorities illustrates not only how important they are, but also how remote-sensing data can be used to serve the needs of the conservation community.  At last, the recognised potential of remote sensing to global conservation monitoring and priority setting is being realised.

By Graeme Buchanan, Lincoln Fishpool, Lukasz Tracewski and Mark O’Brien

Graeme Buchanan, Lincoln Fishpool and Łucasz Tracewski were authors on the paper. Mark O’Brien is the Regional Programme Co-ordinator, for BirdLife Pacific, and here provides a user perspective on the analysis.

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