Part 2: Exposing the over-inflated need for HBTs.
The excessive prescription outlined above can only seek justification with an over-inflated need for that prescription. And the DNRM responded accordingly. Foremost amongst recent efforts has been the very same Habitat Tree Technical Advisory Group as mentioned above.
The primary inputs for their work came from then QDNR’s Resource Science Centre with papers by Smith and Lees (9), called Density and distribution of habitat trees required to support viable populations of hollow dependent species, and by Ross (10) on Hollow bearing trees in native forest permanent inventory plots in SEQ.
More recently, this has been followed by a doctoral thesis by Wormington(11), under the supervision of the same D. Lamb above, on The habitat requirements of arboreal marsupials in the dry sclerophyll forests of SEQ. The unpublished paper was quoted by the HTTAG.
And the body of these works have the following flaws which, consequently, amount to flaws in the policy development process;1. None of the reports distinguish between hollow use and hollow dependence.
Many species that use tree hollows also use other forms of shelter and many are very adept at either building their own nests or using the nests of others. These are not “hollow dependent species.” Analysis of a core requirement for tree hollows must address partial dependence to focus on the extent to which species must have tree hollows to maintain their life cycles.
Of the arboreal mammals listed as hollow dependent, the Brushtail, the Mountain Brushtail, the Ringtail, the Sugar and Squirrel Gliders (essentially the one species as they interbreed with viable progeny) are known to use many other forms of shelter for some of the time. Feathertails rarely use hollows >6cm, use curled bark and nest in grass trees.2. They all assume some minimal number of hollows will produce species collapse.
The evidence from suburbia, orchards and regrowth forests proves that this is simply not true. Contrary to the efforts of the department to suggest otherwise, these areas produce surpluses of what has always been the primary determinant of species density and richness, food.
My suburban roof top is routinely the venue for noisy fighting and fornication of two so-called hollow dependent species (Ringtail and Brushtail Possums) that not only maintain their prefix, “Common”, but do so in densities well above those exhibited by forests under the so-called “protection” of the public sector. Their home range is less than half a hectare. They are outnumbered by feline predators but have been fruitful and have multiplied without a single hollow bearing tree. They have built one nest in my Macadamia tree, another in my Bamboo but, like students in a well misspent youth, sleep in a number of beds of opportunity.
The point at which these animals might experience ‘species collapse’ is obviously less than zero HBTs/ha.
A number of Foresters with experience predating the “habitat tree fetish” have observed that the greatest concentrations of Yellow Bellied Gliders were found in “extensively modified coupes”. This term generally meant no retained non-commercial stems and certainly no retained hollow bearing trees. They did, however, produce widely spaced stems with increased soil moisture reserves, improved and extended microbial soil fertility, more nutritious sap, bud and leaf material, for a greater part of the year, in vigorously growing stems that the Gliders simply knew as food.
Wormington(12) makes it very clear that population density is highly dependent on the nutritional value of eucalypts. And in the case of silviculturally neglected publicly owned Dry Sclerophyll forest this means the extent of E. citriodora in the stand. The results from private regrowth or remnant that has been well spaced, with weed control and Super-phosphate treatment is likely to be quite different.3. No surveys of sites without HBTs have been done to test the ‘species collapse’ theory.
If the species collapse theory has any basis in fact then forest stands without HBTs will have no arboreal mammals present. For these sites will have fallen below this theoretical threshold, whatever it is. But whenever it is suggested that such a survey should be conducted to clarify the matter we have always been told of the difficulty in gaining access to the private forest sites that are assumed to be the only places such a survey could take place.
But this is not the case. A close examination of the 390 Permanent Inventory Plots data used by Ross (13) reveals that there is an abundance of sites without HBTs in the public forest estate that could settle this question if the political and departmental will to do so was present. But one could be excused for not realising this fact.
For Ross has seriously misreported the proportion of plots without HBTs and when these errors are corrected we get a very different picture of this resource. In her Table 1 (14) the number of plots with hollows present was put at 323 when the actual records in her Appendix 1 came to only251. The number of plots without hollows was put at 67 when the actual records in her Appendix 1 came to 139 such plots. The numbers under the heading “Plot count” did not even add up, although the totals row did. The table below shows the actual area of plots without hollows to be 33.6%.Table 1. SEQ Permanent Inventory Plots without Hollow Bearing Trees
Revised from Table 1, of Ross; Stand density of trees & stags in SEQ permanent plots
Broad Plot count Plots Plot Hollows present Plot Hollows absent Plot %
forest Hollows Hollows Total fauna area plot size area plot size area without
type present absent survey (ha) 0.5 0.404 (ha) 0.5 0.404 (ha) Hollows
1 38 22 60 35 28.1 31 7 18.3 9 13 9.8 34.7%
2 92 30 122 25 57.6 72 20 44.1 15 15 13.6 23.5%
3 2 2 4 2 1.8 1 1 0.9 1 1 0.9 50.0%
4 82 25 107 23 50.0 61 21 39.0 10 15 11.1 22.1%
5 37 60 97 43.0 27 10 17.5 13 47 25.5 59.2%
Total 251 139 390 85 180.6 With hollows 119.84 Without hollows 60.76 33.6%
Broad Forest Type =
1 Coastal Dry Sclerophyll, 2 Inland Dry Sclerophyll, 3 Coastal Wet Hardwood, 4 Coastal Moist Hardwood, 5 Cypress
The fifth column(sic) lists the number of plots in each broad forest type that are reported to have had fauna surveys conducted on them. Clearly, there is sufficient number of plots without hollows to enable fauna surveys of an equally representative sample of these. And from this we can conclude that either;
a) an executive decision was made to avoid surveying these plots, or
b) a larger survey actually took place but these records have not been used or reported on for political reasons, or
c) the existing survey includes a number of plots without hollows but the results have been aggregated.
The significance of this is in the implications of hollow tree density and animal and species density across the forest estate. For Ross’ Table 2 (15) averages the total number of recorded hollow trees and stags over the total area of plots to give a mean of 10.2/ha. But there are two very distinct forest classes within this set for which the number of HBTs has a major bearing on animal and species density.
For example, when we allocate the 301 recorded hollows in the Coastal Dry Sclerophyll (BFT1) class to the 18.3ha of plot area with hollows we get a mean of 16.45 hollow stems/ha (up from 10.5/ha) in this class and zero in the remainder. The 149 recorded live stems amounts to a mean of 8.14 hollow stems/ha (up from 5.1/ha) in this class. The 166 >10cm hollow trees and stags produce a mean of 9.07/ha (up from 5.9/ha) and the 67 live >10cm hollow trees produce a mean of 3.66/ha (up from 2.3/ha) and zero in the remainder.
Similar results are produced in the other broad forest types with mean hollow stems/ha, on actual sites with hollows, amounting to;
Broad Forest Type All hollows >10cm hollows
Coastal Dry Sclerophyll (BFT1) 6.45/ha, 9.07/ha,
Inland Dry Sclerophyll (BFT2) 12.66/ha, 7.44/ha,
Coastal Moist Hardwood (BFT4) 18.21/ha, 7.13/ha, and
Cypress (BFT5) 17.62/ha 10.74/ha .
And it is worth noting that this number of hollow stems is well into the zone that is apparent in the graphs of Smith & Lees (16) (Fig 5a & 5b p56) where mammal and bird density is in decline. It should also be noted that Wormington,(17) (p20) who measured all hollows not just >10cm ones, found that, “The number of species also declined when the number of hollow bearing trees was >13/ha” (these sites also had low proportions of C. citriodora).
Clearly, fauna surveys of the plots without hollows are no more problematic than the ones that have already been carried out. The absence of data from these plots represents an absence of information that is likely to be highly relevant to the decision on appropriate levels of HBT retention under any Code of Practice.4. They fail to conduct any research that would assist in identifying the threshold number of HBTs.
Both Smith & Lees and Wormington have speculated that species decline begins when HBTs are less than 4/ha but this is from a very limited sample. Wormington states, (18) (p20) “The maximum number of 5 arboreal species was found at sites with 3.67 to 13 hollow bearing trees/ha and higher proportions of the total stand C. citriodora”.
But examination of the plot records reveal a very limited sample of only 5 of the 38 (or possibly 76) records had five species present. And the composition of the species reveals that the fourth and fifth species at each site were all capable of using other nest sources.
Of the 10 encounters that made up these claimed examples of ‘maximum species diversity’;
3 were Feather tailed Gliders that according to Smith & Lees, make use of curled bark, old birds nests and possum Dreys. Strahan (19) (p264) reports of nests in the dried fronds of our abundant grass-trees, (Xanthorrhoea sp.) “and a wide variety of other niches”.
· 3 were Sugar Gliders that according to Smith & Lees, make use of Blackberry bushes, rock piles and Dreys. And Wormington (20) (p26) has pointed out that, “The density of Sugar Gliders did not appear to be correlated with the density of hollow bearing trees. The sites where Sugar Gliders were present spanned the range of HBTs from 2 to 20/ha. Instead, the density of understorey Acacia influenced the number of encounters with SG.” Absent Acacia, absent ‘maximum species diversity’.
· 2 were Common Ringtail Possums that according to Smith & Lees, make use of dense vegetation, aerial debris, hollow logs (on ground) peeling bark and, of course, possum Dreys. Other sites of relevance to the COP for freehold forests would include, sheds, power boxes, mailboxes, old vehicle panels, empty cans, Banana bunches and termite nests.
· 1 was a Mountain Brushtail that according to Smith & Lees, make use of stumps, logs and burrows and to which Strahan (21) (p271) adds epiphytes.
· 1 was a Squirrel Glider, essentially the same species as the Sugar Glider. Smith & Lees have not recorded other den sites but as they interbreed with Sugar Gliders we can reasonably assume that they are capable of utilising the same alternative den sites.
The species that made up the fourth record on the five plots with four species also came from the above list so there is no basis for concluding that HBTs were essential in achieving more than 3 species per plot. HBTs are merely an association with maximum species diversity, not a pre-condition for it.
And given that there are 139 plots with no HBTs at all then it would seem that there is sufficient scope to create HBTs in some of them (more than 10 plots each), and modify some of the overstocked plots, to provide a sufficient sample of plots with 0.5,1, 2, 3 and 4 HBTs/ha to determine where this threshold might be. But that, of course, might involve an unencumbered departmental whit and the sacrifice of a few sacred cows.5. No attempt has been made to reconcile the HBT retention prescriptions with the actual animal density and range of densities found in the public forest estate.
The HTTAG (22) carefully avoided this issue by ensuring that this material was embedded in Smith & Lees’ work. Any references that would normally be expected to perform the essential informing role of statements of fact were ‘weaselled’ off to the model so that any resulting misstatements would be less easily traced to the HTTAG. A good example of this tenuously coherent bunkum can be found on p22 and 23 of their report. The clear purpose of technical advisory groups is not to find the truth but, rather, to obscure responsibility for un-truths. And HTTAG appears to be no exception.
Nowhere in the HTTAG terms of reference, and certainly not amongst the 11 “Reporting Requirements” questions that were asked of the group, is the absolutely critical question;
“What is the nature, size and distribution of the actual population we are seeking to provide adequate housing for?”
Question 3 gives the initial appearance of doing this but no such answer is forthcoming. The question goes on to request answers for the 5 broad forest types used by Smith & Lees but the answers from page 20 to 25, and particularly the Table 2 (23) data provided by Smith, uses different descriptions of only 3 types and fewer samples than the actual source material from Smith & Lees(24) (their table 3a & 3b, p47) This does not appear to be designed to inform.
The estimates of bird and mammal density provided by Smith and reproduced by HTTAG appear to be approximately double the numbers used in Smith & Lees’ Table 5. (25) and in their graphs (Figs 2a to 4b p52) This appears to have been done through (26) “our belief that densities of hollow dependent fauna are underestimates.” (p24) HTTAG put the range of mammals as 1.1 to 2.3/ha while the actual recorded average densities of hollow dependent fauna recorded by Smith & Lees was;
Broad Forest Type SG SqG YbG GG CBP MBP CRP All Species
Coastal Dry Sclerophyll 0.30 0.12 0.48 0.12 0.06 0.00 0.00 1.08
Inland Dry Sclerophyll 0.15 0.00 0.26 0.10 0.31 0.00 0.00 0.82
Coastal Wet Hardwood 0.34 0.00 0.00 0.00 0.00 0.00 0.67 1.00
Coastal Moist Hardwood 0.29 0.06 0.22 0.06 0.03 0.06 0.03 0.75 .
But it is at the top of HTTAG p23 where the real smoke and mirrors begins with the quote from Smith & Lindenmayer (27) which says, “the number of arboreal mammals in 3 hectare sample plots has been shown to increase approximately linearly (my emphasis) with both the number of habitat trees and the portion of quarter hectare sub-plots with habitat trees.”
This approximate linearity appears to be a new synonym for the more familiar term, “barely linear” or almost linear but not quite. And the term means nothing without information on the actual elasticity, or slope, (the degree of change in one variable caused by another variable) of this approximately linear relationship. Smith & Lees graphs (28) and, from memory Smith & Lindenmayers, reveal a linearity that is at first barely elastic (a very gentle upward slope) followed by a majority of zero elasticity (i.e., horizontal) and ultimately to negative elasticity (a downward slope indicating that more HBTs mean fewer mammals).
And in every other field of science this is generally regarded as indicating that the two elements are unrelated. This is especially the case when small samples are also involved. So the linear models that predicted that maximum arboreal mammal density occurs when there are 6 HBTs per hectare have modelled a relationship that barely exists.
As the HTTAG states (29) (p22)
“The concept of maximum habitat tree density is based on an assumption that the density of hollow dependent fauna increases with the density of tree hollows then plateaus once a level (maximum habitat tree density) has been reached above which populations are no longer limited by hollows, but by other habitat factors such as a shortage of food.”
One can have no problem with this. And one must agree with the next sentence by HTTAG that calls for “analysing the empirical relationships between the observed density of hollow dependent fauna and the density of tree hollows in a wide range of forest types”. The problem is that they are yet to do so.
The relationship is likely to exist but if it does exist it will take the form of a steep slope. And in the absence of a steep, elastic slope, one can only conclude that they have been modelling in the parts of the curve where the relationship does not exist. That is, they have been modelling in units that are too large to detect the change.
Smith & Lees (30) (Fig 5a & 5b p56) have modelled in units of 2 HBTs from 2,4,6 & 8 etc, and this precludes the possibility of detecting significant slope changes between zero and the first record at 2. And a simple examination of one of the mammals concerned will reveal why the relationship is not present in the modelling and why the outputs from the modelling are pure bunkum.
Yellow Bellied Gliders, for example, have a home range from 30 to 70ha. So in a theoretical forest where only YBGs existed, the point at which one house is provided to one household would be somewhere between 0.033 and 0.014 HBTs/ha. So any issues about how many hollows are needed by each household will only be resolved by a capacity to model in units as small as 0.01 of a habitat tree.
For birds, the demands on the accuracy of the model are even greater. The Powerful Owl has a home range from 300 to 1500ha so the point at which one house is provided to one Powerful Owl household is somewhere between 0.0033 and 0.0006 HBTs. So the number of hollows required by the full suite of hollow nesting species will only be resolved by a capacity to model in units as small as one divided by the largest home range (in hectares).6. No attempt has been made to incorporate the most basic of demographic tools, the known data on species households and breeding cycles, to determine the actual number of hollow dependent households per hectare.
It is on this issue that we regret to advise that all of the main publicly funded inputs to this policy process appear to have made serious misrepresentations of fact to this policy process.
Smith & Lees (31) have attempted to calculate two equations for the HTTAG;
Equation 1 - Hollows required per hectare for each individual of each species, and
Equation 2 – Hollows required per hectare for all individuals of all species on the land unit.
In the course of doing so they have made the following extraordinary statements under the headings of “assumptions” but which read more like rationalisations. They said,
· “Owing to simplicity of calculation, time constraints and our belief that densities of hollow dependent fauna are underestimates, we calculated hollow requirements based on the assumption that all species were solitary. Clearly this is not the case for communal nesting species, such as the Yellow-Bellied Glider (and Sugar Gliders, Squirrel Gliders, Feathertails and, to a lesser extent, the Brushtails and Ringtails). Equation 1 below will need to be modified when recognition is made (does this mean when the scam is uncovered?) of communal nesting or that one tree with multiple hollows may be used by a number of species simultaneously.”
· “Figures used for home range size and the number of hollows occupied per home range are independent of habitat type due to the limited information available.”
Armed with this blank cheque Equation 1 was determined as;
No hollows required/ha = No hollows used per individual per home range / home range size (ha)
That is, what they use is assumed to be what they must have. The number of hollows/ha for each species is then multiplied in Equation 2 by the average density of each species/ha and added up to get what is claimed to be the total requirement for hollows/ha. But this is also subject to the following assumptions or rationalisations;
“This is a cautious approach to cater for known inadequacies in sampling techniques and the possibility that wildlife densities are underestimated.”
· “Individual tree hollows are rarely shared between species
· Trees are rarely shared by individuals of the same or different species, despite the number of hollows they contain.”
And they then state, “In reality these assumptions are not necessarily true, but provide for a precautionary approach and simplicity in Equation 2 below.”
So we have a doubling of the initial input of estimated animal density as shown in point 5 above, followed by an assumption that all species were solitary in Equation 1 that clearly overstates the hollow needs of some species by a factor of 5 or more, followed by an assumption that no trees are shared in Equation 2 that also overstates hollow needs by a factor equal to the number of species present. They have adjusted for the perceived underestimate of numbers at every step in the process and have justified it under “a precautionary approach”.
This may not have been a problem if HTTAG had not then stated (32) (p23) that;
“Maximum habitat tree densities required by these groups have been estimated theoretically from their natural density in forest habitats after taking into account a range of factors (my emphasis) such as;
· Nest group size, or the average number of individuals occupying each hollow;
· Species territoriality and the ability to co-occupy hollows in the same tree or different trees in the same cluster;
· Species requirements for multiple hollows within their home range if any;
· Competition between and within species for access to hollows of different size and type; and
· The average numbers of useable hollows per tree.”
To this one can only say, these theoretical estimates have not taken nest group size into account very well. The “not necessarily true” assumptions used by Smith & Lees have not been properly modified for incorporation into the calculation. Indeed, Equation 2, with its incorporation of the actual density/ha of each species has been abandoned.
It was replaced by a generality, a rule of thumb that has supposedly been derived from the above mentioned modelling (of the inelastic portion of the curve). HTTAG said;
“These models can be used to derive a rule of thumb which states that 1.2 habitat trees are required for every arboreal mammal species present(including Antechinus) or 2 habitat trees are required for every large hollow using possum and glider present (excluding Antechinus, Acrobates (Feathertail) and Cercartetus (Pygmy Possum).”
And it is here where the logic stumbles into a worm hole and leaps to hyper space, perchance to orbit around the “Klingon Home World”, when HTTAG goes on to state,
“Thus, in a forest with the potential (my emphasis) to support 2 large possums and gliders per hectare, the maximum habitat tree density (for arboreal mammals only) should be 4 habitat trees per hectare.”
This is the last sign of the already tenuous relationship of HTTAG with actual animal density per hectare. In a single paragraph they have switched from actual animals present to potential animals and those partially present animals have become whole ones needing 2 HBTs each.
So the mere potential for the presence of one Yellow Bellied Glider that dens with its family unit on one or two HBTs somewhere on the surrounding 70 hectares, is assumed to require 2 HBTs on every one of those surrounding 70 hectares. An actual presence of 1/70th of an animal/ha (0.0143) has been “taken into account” as a whole animal on each hectare.
The fact that the HTTAG had full access to the work of Smith & Lees, and can reasonably be expected to have read and understand the significance of the assumptions to the role of animal density in hollow use, then there are grounds to conclude that the above statement is a false and misleading misstatement of fact, that appears to have been made with a knowledge of its untruth.
HTTAG had been properly informed of the significance of actual animal density and the relevance of family unit size. And they chose to ignore the issue.
For the record, the reported range of sizes of family units of the relevant arboreal mammals are;
Feathertail Glider – Strahan(33) (p263) advises groups up to 16 in the wild and 22 in captivity and reports that captive breeding will not take place if they are maintained in pairs but breeding will take place in a larger social group. Smith & Lees (p32) cite Agnew 1996 as claiming den sizes of only 1 to 6 animals. For this analysis we will assume a mean grouping of 8 per den.
Sugar Glider – Strahan (p230) advises groups of up to 7 adults and their young of the season (2 per female, and 2 litters in a good year) in one nest with adolescents dispersing into smaller transient groups when 7 to 10 months old. Some are members of 2 groups with high mortality in 1st year of independence. Smith & Lees cite Quinn 1995 and Suckling 1984 as claiming den sizes of 2 to 7 animals. Wormington also cites Quinn’s 7 adults in 4 age classes (3 M, 4 F) and, presumably the current years offspring. For this analysis we will assume a mean grouping of only 5 per den.
Squirrel Glider - Strahan (p234) advises “Typically, a family group comprises one mature male (2+yrs), one or more adult females and their associated offspring of the season. Occasionally one or more young males (>2 years old) may also be associated with a group of up to 10 animals, including as many as 5 adults.” He also advises that SqG and SG breeding times and growth and development are “strikingly similar” i.e., 2 young per female and 2 litters in a good year. Smith & Lees cite Goldingay & Possingham as indicating den sizes of 2 to 9 animals. Wormington (p167) also cites Quinn as indicating an average of 2.9 animals per den. For this analysis we will assume a mean grouping of 2.9 per den.
Yellow Bellied Glider - Strahan (p230) advises, “In the northern part (of its range, i.e., Qld) a male may associate with 2 or 3 adult females and up to 3 young.” He also indicates travel distances of 2 km per night which would appear to be inconsistent with home ranges of 30 to 70 ha. Smith & Lees cite Henry & Craig 1984 as indicating den size of 1 or 2 animals while Wormington (p167) suggests the high den numbers are only in North Qld. For this analysis we will assume a mean grouping of 5 per den.
Greater Glider - Strahan (p240) describes it as “essentially solitary” But then states, “Males and females normally share a den from the onset of the breeding season until the young emerge from the pouch (4mths) and become independent at 9 months. Smith & Lees and Wormington (p166) appear to assume they are continually solitary. For this analysis we will assume a mean grouping of 1.5 animals per household or den, consistent with 4 months with male & female in one den, 4 months with male in one of a number of dens and female and young in another and 4 months of male, female and adolescent in solitary dens.
Common Brushtail Possum - Strahan (p273) makes no reference to den size, nor does Smith & Lees. For this analysis we will assume the same mean grouping of 1.5 animals per household as described for the Greater Glider above.
Mountain Brushtail Possum - Strahan (p271) makes no reference to den size but indicates that young are suckled for 9 to 11 months with a degree of pairing between male and female. Smith & Lees (p32) also provide no indication of den size. For this analysis we will assume a mean den size of 1.75 animals. This is based on 6 months of male and female in one den, and 6 months of solitary male and female with young. (i.e., 0.5x 2 + 0.5 x (1 + 2)/2 = 1.75).
Common Ringtail Possum - Strahan (p254) makes no reference to den size but advise that the pair bond carries over into the following season. Two young are born to established pairs with a second litter in a good year. Smith & Lees (p32) cite Thomson & Owen 1964 indicating up to 8 animals per den. This would be consistent with 2 parents, 2 litters of the current year and 2 semi-detached adolescents. For this analysis we will assume a mean den size of only 4 animals.
These assumed mean den sizes are applied to the reported mean animal density records of Smith & Lees Table 5 (p49) and the actual site density records of Wormington (p19) in the attached spreadsheets. These spreadsheets adjust for den size and an assumed 50% propensity of some species to use other nest sites. They provide the number of dependent animal households/ha on each of the 38 sites and show the number of HBTs that are available to each dependent household on each site.
Additional sheets model the consequences of a lower number of HBTs/ha (down to 0.5 HBTs/ha) on each of the sites. This enables the impact of any hollow shortages to be assessed at both site and landscape scale.7. Smith & Lees extrapolated to two totally improbable extremes of HBT need to make the DNRM preferred prescription appear reasonable.
No discussion on the science behind the DNRM prescriptions can take place without specific critique of the extraordinary mathematical acrobatics that have gone into Smith & Lees’ Tables 4, 5 and 6 (p48-50). This was an attempt at reconciling species known range of hollow use with the known variation in home range sizes. And a very poor attempt it was.
Table 4 recognised that the calculation of Hollows Required/ha, in Equation 1 above, involved two variables, hollows used and home range size. This used the data on home range size in Table 2a (p32) and the number of reported hollows used from the same table.
For example, Sugar Gliders have been reported to use from 1 to 5 hollows and have home ranges from 0.5ha to 7.1ha. So the lowest number of dens (1) was divided by the largest home range (7.1ha) to get the number 0.14 hollows/ha as the minimum in the range. Then the largest number of dens (5) was divided by the smallest home range (0.5ha) to get the number 10 hollows/ha as the maximum in the range. And it was between these two numbers that the actual need for hollows may be found.
The problem with this is that these are two highly improbable extremes. It is like looking for the definition of a reasonable man by reference to Hitler and Stalin. We all agree that the answer is somewhere in the middle but we are none the wiser from examining the extremes.
The greatest number of hollows used is most likely to be found on the largest hame range, not the smallest. The least number of hollows used is most likely to be on the smallest home range because the food supply is sufficient to justify a higher density of animals and they are willing to compromise on housing to enjoy the benefits of the abundant food supply.
The smallest home range of 0.5ha has a radius of only 40 metres so the den is only one jump from shelter from anywhere in the territory. The largest home range of 7.1ha has a radius of 150 metres in which five hollows spaced along a 90 metre radius within the territory would be 100 metres apart (113m on arc) and ensure that no part of the territory is more than a 50 metre jump from shelter.
Apply the same analysis to 5 dens on 0.5ha and we get a rather silly scenario where no part of the range is more than 15 metres from a hollow. This situation in a mature forest would negate the need for gliding altogether. Animals could jump from one tree to another as possums do. The maximum number of hollows on the minimum range is an absurd extreme.
But that didn’t slow Smith & Lees. Their Table 5 (p49) proceeded to do the same calculation for each species in each broad forest type and then sum these values as an overall requirement per hectare. Column 6 multiplied the maximum hollows by the maximum animal density to get 13.3 hollows/ha for Sugar Gliders and a total of 41.17 hollows/ha for all the arboreal mammals in Coastal Dry Sclerophyll. The minimum number of hollows multiplied by the maximum animal density came to only 0.8 hollows/ha for all species in the same forest type.
But once suitably gobsmacked by the 41.17 hollows/ha number, the reader was then well primed to accept the almost equally unreasonable calculation in Column 7. This multiplied the maximum hollows/ha (10 for SG) by the mean animal density (0.3/ha) to produce a requirement for 3 hollow/ha for Sugar Gliders and 7.24hollows/ha for all arboreal mammals in the forest type. The minimum requirement multiplied by the mean animal density came to only 0.14 hollows/ha for all species in the forest type.
Obviously, 7.24 hollows/ha is certainly less unreasonable than 41 hollows/ha but this still does not bestow any legitimacy to the number. A highly improbable hypothetical extreme is still being applied to the mean animal density. But this did not prevent Smith & Lees from reflecting on how these results coincided with the HBT retention targets under the Code of Practice. And having arrived at any sort of figure that could plausibly support the established departmental position, the brain appears to have shut down and gone home.
But before doing so there was one last (the fourth) opportunity for incorporating the above mentioned “precautionary approach.” Smith & Lees (p50) state,
“On the basis of the precautionary principle, and consistent with the uncertainty inherent in dealing with this type of data (in this way) it might be prudent (sensu Gibbons and Lindenmayer 1996, 1997a and b) to choose maximum values to insert into the formulae we outlined in section2.3.2, so that maximum numbers of hollows are retained.”
No attempt was made to multiply a mean value by another mean value to get a most probable and realistic picture. If we know that the median density of Sugar Gliders in Coastal Dry Sclerophyll is 0.3/ha then we can reasonably conclude that the mean home range of an assumed solitary animal is 3.3ha. A circular territory this size would have a radius of 102 metres and it would take only 3 dens on a 50 metre radius to ensure that most of the territory was less than 50 metres from shelter.
And multiplying this mean (3 dens) by the mean animal density (0.3) gives a most probable hollow requirement for Sugar Gliders of 0.9 hollows/ha. But even this is not good enough as it still assumes they are solitary animals which they are not. It also still assumes that any values less than the mean will lead to, or are symptomatic of, species collapse.8. They fail to consider how these species are known to respond to either short-term or long-term overpopulation or housing shortage.
Neither Smith & Lees nor Wormington have described the climatic conditions that were present during their fauna surveys. Both stressed their belief that the recorded data represents a significant underestimate of numbers and have incorporated “precautionary approaches” to the basic records. Smith & Lees’ efforts are mentioned above.
Wormington’s efforts in this respect was to only analyse the highest of the two records taken for each of his 38 sites. And his belief that this selected class, with 73% of all encounters, is the “true picture” is so strong that he has refused to provide me with the other data sets unless he had prior agreement to his vetting of any conclusions.
But the true picture is more complex still. Wormington’s (p16) surveys took place between August 1997 and September 1998. This was an extreme El Nino period with an extended dry period in 1996 as well. Both the forest and the wildlife within had shut down into survival mode. The trees had shed leaves and had released toxins into their remaining foliage to make it less digestible. Soil microbial activity was impaired by moisture deficit, producing lower nitrogen levels and less nutritious sap and leaf matter. And this had serious consequences for all arboreal fauna. And their density adjusted accordingly.
So if there has been any time in the past few decades when species were close to “species collapse”, it was when the survey took place. It would seem trite but apparently necessary to state that species collapse is highly unlikely in a run of good seasons.
This data is shown in the attached spreadsheet, [2 sample Data]. The average animal density over the 38 plots and two surveys was only 0.189/ha, just more than a sixth of the 1.08 animals/ha recorded by the DNRM sample in Smith & Lees. (Assuming the DNRM sample area really was only 3ha as stated, with any sightings beyond 100m radius being excluded).
Of more interest is the average number of occupied hollows/ha and the number of HBTs for each dependent mammal household, for each of the surveys. For this shows the actual use being made of the HBTs at any given time. Wormington’s sample had a mean of only 0.0736 occupied hollows/ha or 103.6 HBTs for each family that needed one. The DNRM sample had 0.2467 occupied hollows/ha or 43.41 HBTs for every family unit that needed one.
Sheet [7.625 HBT] shows Wormington’s highest data records with plots ranked from highest to lowest animal density. The plot with the highest density, Bau201, had 17 encounters but this was still only 0.708 animals/ha. Each species was divided by its average household size to get a total of 0.249 animal households/ha. After adjusting for partial use by nest builders etc, this amounted to 0.1953 occupied hollows/ha each day. This plot had 6.33 HBT/ha which translated into 32.4 HBT for each mammal household that needed one.
But this was not the plot with the shortest supply of HBTs. This honour went to Plot 7, Mar203, with 11 encounters and only 2.67 HBTs/ha. This was 0.458 animals/ha, 0.2667 animal households/ha, 0.1556 occupied hollows/ha and amounted to 17.2 HBTs for each mammal household that needed one.
At the other extreme was Plot 37, Mtw204, with only one encounter but with 20 HBTs/ha. This was 0.042 animals/ha, 0.0083 animal households/ha, 0.0042 occupied hollows/ha and amounted to a mind bending 4,800 HBTs for each mammal household that needed one. And this was the highest record out of the two for this plot.
In all, 75% of encounters took place on 50% of the plots. And while we do not have access to the lesser record for each plot we can compile an average by deducting the highest record from the total recorded encounters. We know that 252 (73%) of the total 344 encounters were in the highest record set while the missing lowest record set had only 92 encounters (27%). This is broken down in tables 2 and 3 at the bottom of sheet [7.625 HBT].
The highest sample set averaged 6.632 encounters per 24 ha plot with 7.625 HBTs/ha. This was 0.276 animals/ha, 0.1289 animal households/ha, 0.1036 occupied hollows/ha and a mean 73.6 HBTs for each mammal household that needed one.
The same plots, at another time of year when the missing lowest sample was taken, averaged only 2.421 encounters per plot with the same 7.625 HBTs/ha. This sample had only 0.101 animal/ha, 0.0550 animal households/ha, 0.0435 occupied hollows/ha and a mean 175.3 HBTs for each mammal household that needed one.
And this, folks, is a classic example of zero elasticity in the relationship between HBTs and animal density. There was almost a three fold change in animal numbers and zero change in HBTs/ha. More importantly, it is clear that when animals are at their most vulnerable, the last thing they are concerned about is a shortage of hollows.
It should be noted, however, that HBTs/dependent household in this analysis are overstated in bad years and understated in good ones by the use of a single assumed household size. Household size will obviously change with climatic circumstances. So the average household of Sugar Gliders in drought may only be 2 individuals who have not reproduced that season while the average household in a good season may be 8 individuals made up of 2 parents, 2 litters of 2 young each for the season and 2 lingering adolescents.
And if the good season continues into a second year then the adolescents will respond to any localised shortage of HBTs, or any comparative decline in food supply, by seeking a new home range in the less populated parts of the forest or by playing their part in the food supply of an expanding Powerful Owl population. Those who do not adapt, have the adaptation forced upon them by other species who have adapted.
But the analysis of this issue to date has not recognised the capacity of species to respond to change. And this has obscured the fact that, in the forests for which data is available, the only undersupply of HBTs, if any, is a temporary phenomenon, found in good seasons. Arguments for retention of high numbers of HBTs/ha are based on the extremely unrealistic assumption that, in Queensland over the coming decades, the good times will continue uninterrupted.
The element that is responsible for the ten fold variation between Wormington’s lowest sample and the DNRM sample from Smith & Lees is rainfall related food supply. As, indeed, it is for every other native and feral species in Australia. That, folks, is an example of high elasticity (a steep slope) in the relationship. And it is a disgrace that so much resources have been devoted to studying an irrelevant variable.9. They fail to examine how hollow deprived species collapse might actually happen and this allows the assumption of broad based collapse to remain unchallenged.
It can be argued that a failure to fully exploit a good season can lead to species collapse in a bad season. But this ignores the extent of variation across the forest resource. We know that in Wormington’s highest sample, 50% of the plots had only 25% of the population. And this sparse population operates to protect the inhabitants from predators by expanding the area over which the hunt takes place. Once the target population drops to a certain level then it is the predator’s survival that comes into question.
The predator’s problems are exacerbated by a greatly expanded supply of hollows that can be exploited by the remaining arboreal mammals. It is nature’s magic at play, once again. When a species actually need lots of hollows for survival, there is plenty of them available. When their survival is not under challenge in a good year, there is less available to each one. And in such circumstances they adapt by fitting more of their expanded family into the shelters available and switch to a “safety in numbers” strategy.
It should also be noted that the various anecdotal reports of certain species using large numbers of hollows are likely to be based on seasonal overabundance of HBTs that are created by seasonal population decline. They should never be used as some sort of constant requirement or be applied to the expanded population in a good season.
We also know that animal density remains higher on good quality sites. In Wormington’s highest sample, 75% of the population were found on the better 50% of plots. These sites maintain the best capacity to respond to improved conditions when they arrive but the most potential for density expansion is likely to be found in the lower quadrats.
The current departmental view on HBT requirements assumes a static resource and a uniform response to change. Neither of which is true. The attached spreadsheets enable each plot to be examined for its sensitivity to various assumed HBT retention levels and to various levels of species population.
10. No attempt has been made to determine the sensitivity of species sightings to HBT requirements.
The belief that there are more animals present on a site than those that are encountered is widespread amongst researchers and has some validity, especially for the smaller mammals. So one of the most important tasks for any examination of the need for HBT retention prescriptions is to model for the sensitivity of the stand to various levels of under-reporting.
The attached sheet, [model 1Hbtha] can be used to assess the demand for hollows by any likely under-reported population, for any level of HBT retention. In default form it models the impact on the highest and lowest of Wormington’s samples, the average of the two, and the impact on each plot.
It shows the same reported average of 0.189 animals/ha and 0.0736 occupied hollows/ha which, if only one 1 HBT was retained per hectare, would still mean 13.6 HBTs for each mammal household that needed one. The highest sighting sample still had a mean 9.6 HBTs for each mammal household that needs one. And the lowest sighting sample had a mean of 23 HBTs for each mammal household that needs one.
This would enable an average 13.6 fold population increase to a point where every HBT is occupied, assuming no increase in den size, or co-occupancy of HBT, takes place. And this potential increase would appear to be greater than the 10 fold variation between the reported DNRM population of 1.08 animals/ha and Wormington’s lowest sighting average of 0.101 animals/ha. And this suggest that a level of 1 HBT/ha may be adequate for maintaining species capacity to fully exploit a good season or two.
When 1 HBT/ha was modelled for the range of plots, only 3 plots had less than 4 HBTs for each family that needed one. These 3 plots had the 2nd, 3rd and 4th highest animal density so significant population increase can take place before adolescents need to leave the area.
But this may not be so if there is some serious under-reporting of animals present. This is more likely to occur with the smaller animals, the Sugar, Squirrel and Feathertail Gliders, than the larger species. And this is where the model can assist in understanding the problem.
We can take the average number of sightings in Wormington’s two samples (172) and add an equal number of encounters that are spread between the above mentioned three species. So the sightings of each three would increase by 57/58 to cover an assumed 50% under-reporting. This doubling of encounters would show new values of 59.5 Squirrel Gliders, 76 Sugar Gliders and 62.5 Feathertail Gliders.
This would show a doubling of animal density from 0.189 to 0.337 animals/ha but, due to larger family sizes, average households/ha would only increase from 0.0919 to 0.1339/ha. And because they are all partial users of other nest types, average occupied hollows will only increase from 0.0736 to 0.0946/ha. And each mammal family that needs a hollow will still have 10.6 HBTs each instead of the original 13.6 HBTs each. So the impact of under-estimation of species present has only marginal impact on the actual need for HBTs.
When only 0.5 HBT/ha (1 for 2 ha) was modelled, the average of the two samples still showed 6.8 HBTs for every mammal family that needed one. The highest sighting sample had 4.8 HBTs each while the lowest sighting sample had 11.5 HBTs for each mammal family that needed one.
When 0.5 HBT/ha was modelled for the range of plots, only 3 plots had less than 2 HBTs for each family that needed one. These 3 plots still had the 2nd, 3rd and 4th highest animal density so significant population increase can still take place before adolescents leave the area but the point at which larger families will occur and when co-occupancy of different hollows in the same HBT takes place will be earlier in the climatic cycle.
But this earlier Diaspora of adolescents may actually increase the rate of formation of breeding pairs in the less populated parts of the forest. In so doing it could ultimately lead to a greater capacity to fully exploit a good season.
Continued next post. IM