Backyard bonanza: collating stats for a predator-free future

I've previously discussed how a lack of understanding of statistics can cause consumers to make poor choices, so it would seem that increasing the public's understanding of them can only be a good thing. Therefore, along the lines of New Zealand's annual garden bird survey, I decided to do a bit of citizen science. My aim was to record the highest number of each fauna species seen at one time, either actually in my garden or seen from my garden. The time frame was a calendar year, so as to take into account seasonal migrations and food availability. As an aside, it might have been easier to count flora (after all, it doesn't move very fast) but with Auckland being the weediest city in the world and my floral knowledge much weaker than my recognition of fauna, I opted for the easier option of any animal that I could see without using a microscope.

A meta-analysis released this month states that almost twenty-five percent of birds on the IUCN Red List of Threatened Species are being affected by climate change. In addition, with last years' announcement to make New Zealand predator-free by 2050, such surveys might be useful for locating concentrations of introduced pest species. In a way, I'm providing a guide that anyone can follow with the minimum of effort (hint, hint). So here are my results, followed by some more information:

Class/species	Native/self-introduced	Number seen
Insecta
Ant (unknown species)	Yes	Numerous
Asian paper wasp	No	3
Black field cricket	Yes	4
Bumble bee	No	1
Bush cockroach	Yes	14
Cabbage tree moth	Yes	7
Cabbage white butterfly	No	2
Cicada	Yes	2
Click beetle	Yes	2
Common bag moth	Yes	1
Crane fly	Yes	1
European earwig	No	1
Ground beetle	Yes	2
Honey bee	No	1
Housefly	No	7
Ladybird	Yes	2
Monarch butterfly	Yes	17
Shield bug	Yes	3
South African praying mantis	No	22
Tree weta	Yes	18
Arachnida
Bird dropping spider	Yes	1
Black cobweb spider	Yes	1
Black house spider	Yes	1
Daddy long-legs	Yes	3
Jumping spider	Yes	1
Nurseryweb spider	Yes	1
Slater spider	Yes	1
White tail spider	No	1
Annelida
Earthworm	No	5
Tiger worm	No	Numerous
Hexapoda
Springtail	No	Numerous
Chilopoda
Centipede	Yes	3
Mollusca
Common garden snail	No	9
Reptilia
Rainbow skink	No	2
Aves
Australasian hawk	Yes	1
Blackbird	No	2
Black headed gull	Yes	3
Eastern rosella	No	4
Fantail	Yes	2
Goldfinch	No	3
Greenfinch	No	2
House sparrow	No	14
Myna bird	No	4
Rock pigeon	No	5
Silvereye	Yes	7
Song thrush	No	1
Spotted dove	No	1
Starling	No	4
Tui	Yes	1
Mammalia
Cat	No	2
Chicken	No	1
Dog	No	1
Hedgehog	No	1
Mouse	No	1
Rabbit	No	1

The first thing that seems obvious is just how many non-native species I observed, some deliberate introductions whilst others accidentally brought to New Zealand, but all within the past two centuries.

Now for some interesting comments about how statistics can be (mis)interpreted:

1) The method I chose to order the table by could affect how easy it is to find key points of interest. Alphabetical order is familiar but is simply a well-known form of cataloging. Therefore it can be seen as a neutral form of presentation, not emphasising any particular pattern of the results. Had I ordered by native/non-native, it might have become more apparent how many of the latter bird species there are. If I had ordered all species in one list by this method, rather than in separate classes, the pattern would have been obscured again. So simply by selecting a certain order, results can appear to support a certain notion.

2) How useful is this data if it lacks supporting information? By this, I mean factors that might affect the count: Is it a common or garden (yes, that's a pun) location or an highly unusual one? Is the locale urban or rural? What are the surroundings? How big is the garden and how much vegetation is there? Is the vegetation primarily native or non-native? I could go on like for this ages, but clearly to get a more sophisticated understanding of the causes behind the figures, this information is necessary. Even then, two locations that are almost identical to a casual observer might appear profoundly different from the vantage point of say, earthworms. I will admit to (a) having built 2 weta motels and a bug motel; and (b) feeding silvereyes in winter; and (c) having made a tui sugar water feeder that has been totally ignored. Go figure!

3) Are there any other obvious factors that could affect wildlife? How managed is the location? Are chemicals such as weedkiller used or is the garden solely organic? Again, this can have a massive effect on wildlife, such as pesticides that remove insects at the base of food webs. On the one hand, if mine is an organic garden surrounding by neighbours who spray their foliage, then it could be an island of suitability in a comparatively barren terrain. But alternatively, if most of the neighbourhood isn't fauna-friendly, how likely would my garden get visited even on the off-chance by animals that can't live in the wider area?

4) Of course there's also contingency within natural selection. For example, quite by chance some species can survive on foods not native to their ecosystem. Although stick insect numbers in New Zealand were drastically reduced thanks to DDT, gardens don't need to contain their native food plants in order to support them. In the south-west of England, three species of accidentally-introduced New Zealand stick insect have flourished for decades on the likes of roses! Also, unusual events can affect populations: in this case, the two rainbow skinks appeared several months' after laying some ready lawn so I can only assume their eggs arrived with the turf, the previous five years having seen no skinks whatsoever.

5) When it comes to surveys, timing is also important. As you might expect, most of my observations took place during the day, with the only nocturnal ventures being on clear nights when using my telescope. The moths and hedgehogs were mostly seen at night, whilst had I included birds I could hear as well as see, then a morepork would have been added to the list. Again a simple prejudice, in this case sight over sound, has skewed the statistics. The large number of mantises were not adults but nymphs all hatching from a single ootheca. As for the monarch butterflies, they were a combination of caterpillars, chrysalis and adults, having appeared in much greater numbers this year than previous, despite no additional swan plants (their only food). Interesting, a clump of twenty or so mature swan plants a few streets away hasn't yielded any monarchs in any of the three stages. Presumably, predators such as wasps are responsible.

The sheer randomness of nature is exciting, but doesn't exactly help to uncover why populations are such as they are found via small-scale studies. Oh, and further to the damage invasive species have wrought on native wildlife, you may be interested to learn that none of the mammals belonged to me, the cats and dog being owned by friends and neighbours whilst the rabbit was an escapee from a dozen houses away!

6) Finally, there's the scale prejudice. Although I have a basic microscope, I didn't include such tiny wonders as tardigrades and bdelloid rotifers, even though garden moss and leaf litter respectively has revealed these wee critters. My page of nature photographs shows this prejudice, with microscopic fauna getting their own page.

So, what can we learn from this, apart from the large number of non-native species commonly found in Auckland? Perhaps that raw data can be presented in ways to obscure patterns or suggest others, should the publisher have an agenda. Furthermore, without access to highly detailed meta data, the statistics by themselves tell only a small part of the story and as such are open to wide-ranging interpretation by the reader. Therefore the next time you read about some percentage or other, remember that even without manipulation or omission, survey data is not necessarily pure, unsullied and free of bias.

Lies, damned lies and the dubious world of cosmetics advertising

Let's face it, most people's ability to analyse statistics is pretty poor. In fact we can consider ourselves lucky if we know anything beyond mean, median, and mode, and certainly left- and right-skewing isn't a popular topic of conversation. Perhaps that's why the multi-billion pound global beauty industry uses such bizarre examples in their advertising, on the grounds that few punters will understand any of it. Not being a regular reader of women's magazines most of what I pick up is via flicking between TV channels, occasionally spotting some famous actress or supermodel accompanied by such interesting statements as '83 out of 114 women agree' (although I made that one up).

Isn't it fairly obvious that there are two concerns here? Firstly, the figures aren't easy to simplify to lowest common denominators, lacking the nice, rounded character of say, 80 out of 120. Secondly, the numbers are so small. Following the MMR scandal and its case study group of 12, surely few could think such a low sampling as my fictional 114 could be taken as a worthwhile trial? Yet I cannot think of a single example from this sector where the study (if we can call it that) exceeded 200. Are the numbers parts of some elaborate in-joke by the cosmetics industry or are they based on genuine data, in which case are the polls conducted by marketing agencies with very short attention spans?

Despite recommendations that the UK's Cosmetics, Toiletries and Perfumery Association members are meant to adhere to, outsider knowledge of what the beauty product multinationals get up to is minimal. Most companies test their products on other animals before moving onto humans, but how scientific is the research conducted on the latter? If the advertising figures are based around how punters ‘feel' (surely a profoundly subjective word), there is more than a hint that the research hasn't involved standard scientific procedures such as double-blind or placebo experiments.

And of course, no information is given as to where the punters were found: in statistical terms, how random was the sampling frame? So despite the sophisticated research that often goes into developing the products, their marketing appears to offer the antithesis in the form of essentially worthless polls and neo-scientific yet nonsensical compound words. Even innocent-sounding phrases such as "natural looking skin" aren't worth anything; after all, isn't all skin natural looking if it is free of make-up and cosmetic surgery? A combination of genetics and lifestyle - I really hate that last word - are responsible for the condition of your skin, with few people nowadays failing to recognise that sunbathing smokers are unlikely to retain a youthful complexion even with the aid of pots of ground up chicken feet and the food of queen bees.

That the product manufacturers have kept one step ahead of the cynicism is perhaps not all that difficult to explain. Our popular culture and media are obsessed with youth (which is nothing new - take classical Greece as an example) but at least modern legislation prevents the use of obviously insane ingredients. After all, it is far less than a century since radium was used in hair cream and toothpaste. It seems we may have slightly less gullibility than previous generations, yet even a temporary improvement in our appearance is inviting enough to fork out vast sums of money for.

But is all this about to change? In the last few years a radically different range of beauty products has been in development that appears to be rather more than usual temporary Polyfilla. Trials are taking place involving skin cream that may be an early form of "cosmeceutical", able to restore the structure of skin rather than simply obscuring aging and damage. As for me, I'm watching with interest the research into mimicking the effect of enzymes that prevent loss of hair colour - or even reverse it. What, vain? Me? Surveys suggest that only 1 in 10 men don't mind the natural greying process. Okay, I made that one up too!