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How AKF and Government got their Numbers

The Australian Koala Foundation Methodology 

 
 

Comparison graph
Click image for larger size

The Australian Koala Foundation Methodology

 

The AKF’s approach to estimating Koala numbers is underpinned by $15 million and 28 years of research. Teams of AKF researchers and volunteers have gone out to survey Koala habitat usage at over 2,000 field sites, individually assessing more than 100,000 trees. At the same time National Vegetation Information System (NVIS) data was used to map potential Koala habitat on the East coast of Australia (for more detail please see Bob’s Map). 

Using AKF field survey data and other published studies, we developed models to estimate some demographic parameters, such as:

a) the proportion of habitat occupied by Koalas, 

b) potential Koala densities in each class of habitat, and

c) home range sizes in each class of habitat. 

These models, combined with habitat mapping, were used to predict the number of Koalas in each area on the basis of available habitat and the quality of this habitat. The results were validated and adjusted if necessary using information provided by researchers and local community groups working in the area. A more detailed explanation is available here.

The AKF methodology is a practical and objective approach to estimating Koala numbers. Koalas are hard to see and can often be high up in the tree canopy, so are difficult to count. More importantly, they exist in low densities across the entire Eastern coast of Australia, some 1.5 million square kilometres, so it is practically impossible to count them all. Instead, our modeling approach takes the results of a number of studies from locations around the country and attempts to use statistics and probability to estimate what is going on in the rest of the country.

Bob's Map 2018
Bob’s Map 2018: Click image for larger size

 

The Federal Government Methodology

 

Government numbers (as we understand) are a product of a grant for $50,000 to fund two meetings over a six month period. A group of 19 researchers met to exchange knowledge and make predictions. Koala numbers are well known for some areas (e.g. South East Queensland) and the working group came up with estimates for the rest of the country. A more detailed look at this can be found in this government report.

For much of the country, the informed guesswork of this Government working group was used to estimate Koala numbers. There are a number of Koala experts working in study areas across the country, and the government group included most of these experts. Their research has provided good estimates of Koala abundance in these small areas. However, they have essentially relied on guesswork and consensus to fill in the gaps.

In certain areas, where there are fewer (or no) researchers operating, estimates are likely to be biased. For example, in Queensland a large number of researchers, from both government and universities, are working on Koalas. So a range of opinions are represented. In comparison, Koala research in Victoria is primarily driven through the state government, so numbers in Victoria are largely the opinion of a single researcher, and most likely biased towards the Government position that Koalas in Victoria are a pest.

 

 

Which approach do you think is best?

 

The AKF approach is objective, making use of field work, and as much mapping and research as we could get our hands on, plus the input from local Government and groups over the length of the project. It is underpinned by $15 million and 28 years of research. The Government approach however is based on two workshops over a six month period costing $50,000 with results being based primarily on the informed guesswork of a selected group of researchers.
 

A comparitive representation of how AKF and the Government got their numbers.
(AKF prepared this graphic on the information provided by the Australian Government in their document entitled
‘Conserving Koalas in the 21st Century: synthesising the dynamics of Australia’s Koala populations’​)
 
 

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