The Greedy Clearing Algorithm and Conservation Policies

Environmental policies to retain natural vegetation do not work particularly well, and offer little long-term hope of expansion and restoration of natural vegetation. The reason for this is a pattern in the general logic of clearing applications that I call the ‘Greedy Clearing Algorithm’. It goes something like this:

The Greedy Clearing Algorithm
Whenever you are concerned with whether to conserve or destroy a place or thing, ask whether there still exist some remnant of that place or thing somewhere else. If there are remnants somewhere else (e.g. in a Reserve area), proceed to clear.

original (Craig Duncan).

The definition of a Reserve (or a protected space) is often simplified as a 2D space on a map, and that sets the boundaries for interference from the outside. Setting boundaries changes the way we interact with the environment. Decisions may end up being based on general rules, and less on local observation and sensitivities.

If you do not have the planning documents in front of you, the realisation of what is happening might be somewhat delayed by the fact that we do not jump immediately from position (1) to position (6). What’s also not apparent that as clearing proceeds, species will tend to flee the damaged areas on the periphery of the cleared area, or there simply won’t be any guaranteed habitat. All that happens is that it the ultimate clearing takes time to manifest itself.

No real protection by ‘self-designated’ reserves within a clearing zone

Most commonly, clearing decisions assessed by local authorities are being dealt with by considering only specific reasons for local restraint, like some concern related to threatened species, or some significant environmental impact. The policy is designed around only considering these issues after they seem to become an issue for an economically-focussed activity. For example, under Koala protection legislation and regulations (at least in the last decade or so), the protected areas might be determined on a case by case basis and only when development approvals were undertaken.

In some Australian States, it is up to the logging industry to manage a forest’s clearing, which effectively makes the local authority responsible for protection of the species within that environment. As a result, the evidence needed to set a local ‘protected area’ (unable to be cleared) may be gathered by people with little interest in doing so.

Not surprisingly, the observations about species and their habitats are not likely to be as thorough and well informed, or with consideration of confounding factors as those who do not have a vested interest in clearing. Confounding factors may be that anywhere near where clearing is occurring, the animals tend to hide or flee the interference. The logging activities can increase the evidence of ‘absence’, which in this bizarre world of needing to look for a reason not to clear habitats, just makes it easier to clear them.

In the absence of observations, or a genuine interest in time-consuming observations, it’s much easier for industry to put time into ‘desktop’ intelligence, which is a substitute for doing real science or genuine observations. This involves using a rule or scientific ‘model’ of where animals might live, and using that as the basis for decisions. The model involves a formula that tries to predict where animals will live, or how many there are, even though you don’t actually know. Unless these models are tested and shown to be useful (which would require observations anyway), they end up being worth very little, because they are not actually scientifically justified.

Within a clearing zone, leaving clearing to those who are ‘hungry’ for more clearing will tend to make them minimise the areas that they self-designate as ‘protected’. They adopt abstract, rigid boundaries for protected zones that are only symbols of protection, when they do not achieve that purpose, because they are too small and arbitrary. They do not answer the question – is there adequate protection for the actual extant population of the threatened species?

Example 1

Here is a recent example of how someone uses the Greedy Clearing Algorithm to justify clearing of an area that is visited by Black Cockatoos (obtained from looking up the EPBC Act notifications, as the EDO offices do).

Source: EPBC Act Referral 2020-8620

In paragraph 3.5 of that referral is states “The vegetation is not representative of a Threatened or Priority Ecological Community.” This illustrates the other trend in clearing applications – that the more common something is (whilst we consider it arbitrarily plentiful), the less concern there is about removing it.

The focus on the extreme (threatened species) means that there is a positive reinforcement for clearing whilst it remains within the ‘normal’ range of retained vegetation or fauna, whatever that means. That is, it is only when we impose a last-resort protection e.g. we reclassify a species as “Threatened”, that the inevitable clearing that would otherwise occur is restrained. There is no pre-emptive (precautionary) restraint on clearing, in non-emergency circumstances.

Example 2

Here’s a similar example of clearing over a short period of time (months) to the time-based comparisons given above, drawn from the recent NSW Legislative Council enquiry into Koalas ( page 37):

Figure 5, page 37. koala hub in Wang Wauk State Forest in May 2018
Figure 8, page 37. koala hub in Wang Wauk State Forest in Dec 2018

In the case of koalas, conservation mapping tools and ‘offsets’ are used to try and provide a more general planning tool, but do these work? Are the maps effective? The reality is that mapping is only the first stage in assessment, and that protections might not actually be sufficient if there is ambiguity or uncertainty in what areas could possibly count as reserves. The difference between policy and reality must always be borne in mind.

Back in 2015, concerns were raised about the paucity of mapping of Koala habitat in NSW.

In 2016 Koala protection was focussed on protection of Koala Habitat in NSW State Forests, rather than rural areas. Attempts to map Koala habitat within those forests commenced only in 2016, with a pilot study.

In NSW, there is now the concept of ‘Core Koala Habitat’ and “Koala Habitat Protection’ which essentially works in the same way as the ‘Reserves’ idea, but there is far less certainty of whether particular mapped areas qualify for higher protection.

But in the last 3 years, massive areas of Koala habitat have still been cleared in NSW and Queensland. Even more recent media reports suggest that State-based clearing of Koala habitat is still proceeding at a rapid rate. Last year, it was suggested that clearing decisions in Queensland by its EPA were being made based on precedents and not current information.

Some criticism has been directed to the fact that the protected areas are subject to exemptions that subvert the purposes of the planning regulations, including rural land exemptions. e.g. EDO. EDO observations in its “Submission on the Review of the Koala SEPP (State Environmental Planning Policy 44 – Koala Habitat Protection)” noted that the definition of koala habitat was complicated and might not be sufficient to capture all required areas. The definition “required evidence of a resident population of koalas, with such attributes as breeding females with young and a historical record of the population”. In some respects, it required the kind of proof of continuity that might arise in native title claims.

In March 2020 NSW issued a replacement of SEPP44 in which the definition of ‘core Koala habitat’ had been revised.

The NSW Legislative Council Enquiry (Koala populations and habitat in New South Wales) concluded, in its June 2020 Report, that one of the many problems in actually implementing these ideas was the fragmentation of areas of habitat, and the loss of habitat, particularly more mature trees through logging (paras 2.60-2.61). Compounding this was evidence that the Foresty Corp had repeatedly breached its logging requirements (paras 2.67-2.68). It is clear that private industry also contributes to decline, particularly where it takes pre-emptive mining activities in Koala habitats (paras 2.108-2.130)

In Queensland, there is also the concept of essential koala areas (Koala Priority Areas) and habitat mapping. One of the latest maps is the Koala Conservation Plan Map as provided for by the Nature Conservation (Koala) Conservation Plan 2017. The South East Queensland Koala Conservation Strategy includes details of this with the Koala Maps information.

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