From the land of the free

From the legislature of the US state of Utah:

AGRICULTURAL OPERATION INTERFERENCE 2012 GENERAL SESSION STATE OF UTAH [... ... ...] This bill establishes the crime of agricultural operation interference ... ... ... [and] provides that a person is guilty of agricultural operation interference if the person, without the consent of the owner of the operation, records an image of, or sound from, an agricultural operation while on the property where the agricultural operation is located; and establishes penalties. [... ... ...]

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• Bill HB187. http://le.utah.gov/~2012/bills/hbillint/hb0187.pdf

Case in point

A collection of case studies from recent science literature highlight the importance of statistics...

• Beating the drought: using GenStat to investigate drought tolerance in chick peas.

• Reading the future: multivariate data analysis of brain patterns using IDL gives improved prognosis for improved reading in dyslexia sufferers.

• Committing fluicide: OriginPro analyses the viricidal potential of hydrophobic polycations.

• Fishy business: Statistica analysis of otolith microchemistry data illuminates population relationships amongst Atlantic herring.

• Wears the diamonds?: Multiple linear regression in SPSS offers a way to better prediction of wear rates in industrial cutting tools.

• Learning from past mistakes: Pursuing future geopolitics through historical data with Wolfram Mathematica.

Hurrah – the crabs are back!

Despite unavoidable absence from their natural habitat¹ on medical priority grounds, the crabs of Easton MD² are back.

The results of the 2011 Big Crab Contest have been announced. Congratulations to all participants on this year's magnificent crop of Pleocyematal artworks

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1. *addendum, twelve hours later ... just to confound me, a new sighting in natural habitat waters has now been verified.
2. **that's MD Maryland and MD Medicinæ Doctor, both.

Just deserts

According to Richard Lederer’s unnamed student^[1], deserts are defined by a climate "such that the inhabitants have to live elsewhere" and have to be "cultivated by irritation". Say the word desert to most people in the industrialised west, and they will visualise somewhere hot, sandy, and utterly devoid of any life except, possibly, Peter O’Toole and Omar Sharif striding (with or without camels) across photogenic dunes.

In the days when I was trying the patience of successive O-level geography teachers, we were given a more seductively precise and objective definition: annual mean rainfall of 250mm or less. That figure is still around, although it has generally been supplanted by more sophisticated relative concepts like relative moisture economy deficit (more water lost through evaporation and transpiration than is received in precipitation).

Generally speaking, the most widely used climatological classification systems go by distribution of vegetation, which both serves as an indicator of available water and decides the viability of other life. This approach naturally appeals to statistical data analytic bean counters like myself, though they do complicate matters by including temperature considerations. A desert, for my purposes here, is a region whose available water economy provides marginal (or nonexistent) support for life. It will usually be arid, but we won’t be too picky about semiaridity distinctions as many of the problems to be studied involve transition. It will often be megathermal, but not necessarily so.

Oceans cover about two thirds of the earth’s surface. Deserts account for roughly two thirds of what is left (and current trends, despite significant efforts at reversal, are towards net increase) so they are no small matter – either in themselves or in the computational challenges which they can present. It is not much of an exaggeration to say that only since the explosion of generally accessible scientific computing resources can they be realistically confronted at all. [More]

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1. Lederer, R., Anguished English : an anthology of accidental assaults upon our language. 1987, Charleston: Wyrick. 0941711048 (pbk.).

Less food for more future

In a comment to my Food for a future post (and the article from which it is extracted), Geoff Powell comments that “Eating less would help”.

He's right, of course.

So would discarding less. In Eire, more than a third of a tonne of edible food is thrown away per person per year; in the UK, more than one tonne; in the US, over a hundred tonnes.

Reduction in both consumption and waste fall into what I called in the article "the blue corner". Taken together, blue corner strategies in the developed world could reduce global food requirements by 40-90% (depending on definitions and assumptions) . Even just halving waste and overconsumption in the US and EU would significantly increase the net food supply in a world where one in three go hungry.

Food for a future

It’s fashionable to scoff at Thomas Robert Malthus’ predictions, two hundred years ago, that human populations would grow until stopped by famine, disease or ‘moral restraint’. He wrote before the arrival of modern scientific crop research or contraception, and it’s unfair to blame Malthus for not foreseeing those breakthroughs. However, he was essentially right: the food supply expanded but remains finite, and contraception has not fundamentally disrupted the shape of the population growth curve, which is asymptotically approaching the vertical.

What to do about it is a matter of vigorous debate. To simplify: in the red corner are those who focus on means of increasing supply; in the blue, those who emphasise a dietary shift away from inefficient use of that supply. An Isaac Asimov short story^[1] did suggest exploiting the ‘many worlds’ view of quantum physics to disperse a trillion-strong population by placing every family on its own otherwise uninhabited Earth, but that one is a little beyond the reach of even today’s scientific computing power. In the long run, if the upward population curve continues, neither red approach nor blue will do more than defer the problem; in the meantime, pragmatically, both are needed. [More]

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1. Isaac Asimov, “Living space”, in Science Fiction. 1956, New York (NY, USA): Columbia Publications.

Statistics and Esperanza

In the course of work, recently, I ran across the following paragraph:

“So, what does 107 million underweight children under the age of five really mean? Before you can answer that, make the child come alive. Give her a name. I call mine "Esperanza". It means that little Esperanza has probably gone to bed hungry for each or most of the 1825 nights that she has lived so far. And, there are 107 million Esperanzas in Asia.”

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• Rajat M. Nag ( Managing Director General, Asian Development Bank). Graduation ceremony commencement speech at the Asian Institute of Management Master in Development Management Program. 31 July 2009. Full text available here.

Birds, bees and growing things

[Bee on Rape image ©2007 by Judith Acland]

No area of work is more closely associated with data analysis than agriculture. Statistics as a concept grew out of the need to quantify agricultural production for taxation purposes. Modern statistics as a coherent, mathematically-based field was shaped by a need to quantify agricultural investigation. Most generic methods can be traced back to an agricultural point of origin. The great landmark adventure of recent years, the sequencing of the human genome, concludes an intellectual story line that started with a statistical view of inheritance in peas. Astronomy and mathematics owe most of their history to the need to better predict seasons and the flooding of farmlands.

And it is inevitably so. No other strategic concern of the human race is so much at the mercy of a statistical universe. Within the controlled environments of manufacturing, ever smaller numbers of components escape the ever-tightening loop of quality control. In the fields, we remain concerned with the percentage of crop that can be brought to usable yield.

Agriculture has, to be sure, done serious quality control loop tightening of its own; but fewer of the affecting factors are amenable to human control than is the case in manufacturing – and the degree of control is less complete by many orders of magnitude. If production quality for left-handed silicon widgets is temperature dependent then I can easily control the temperature of the manufacturing environment within a few degrees. If I am a wheat farmer, however, I am limited to modest and partial amelioration of what the climate throws at me. The individual ear of wheat cannot be protected; my aim has to be maximising the number of ears per hectare that survive to be harvested and eaten.

Some day, perhaps, all food will be synthetic: biomass grown in orbital tanks, on nutrient broth mined from the asteroids and Saturn’s rings, then knitted into palatable forms, all under quality control comparable to current silicon chip production. Perhaps. That day is a long way off, though. More modest industrialisations, such as greenhousing, polytunnel cloching and hydroponic production are with us already, but are generally focused on market value position or marginal capacity. In the foreseeable future, a rising population will for the most part depend upon nutrition grown in dirt, under sky, battered by weather. In improving the efficiency with which we discern and exploit the patterns within that environment, computerised methods are as important as in any other area of science.

In this battle to maximise yield, data analysis is applied across a range of scales, but they can be split crudely into tactical and strategic approaches. Strategic application seeks to refine global understanding of the factors that affect success; tactical use is aimed at specific application of that understanding to a particular area, location or context. Linking the two, embracing both, is a mesh of research and modelling cycles.

All of this makes for a huge subject, and trying to address agricultural data analysis in a few pages has more than a hint of hubris. All that anyone can hope to achieve is a representative lucky dip into diverse topics. [read more...]