Showing posts with label tui. Show all posts
Showing posts with label tui. Show all posts

Wednesday, 15 February 2017

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.