It is better to be broadly right instead of precisely wrong.

In this blog I will discuss a recent move by the National Trust to ‘macro-manage’ land in an attempt to get things broadly right over a large geographic scale.  Attempting to manage land for nature can be difficult because nature is so complex, in the face of such complex systems the National Trust’s strategy is not only cost efficient, it is extremely sensible.  To explain why I think this, I first need to write a little on the nature of randomness.  I will distinguish between three types of randomness, inherent, game and apparent randomness.  All three types of randomness are alike in a crucial way: they make the future uncertain.  Inherent randomness belongs in the domain of physics, more precisely quantum mechanics which states, amongst other things, that it is impossible to know both where a (sub-atomic) particle is and where it is going.  There is pure randomness at the root of reality.  Fortunately, as we move to larger scales e.g the size of a cell all of the randomness averages out in a predictable way hence this randomness has no influence on our lives.  Game randomness is the randomness we are most familiar with, the moment before the die is rolled we are uncertain about what the outcome will be, if we pick a card at random from a deck we do not know for certain which card we will pick.  Now, if the die is fair and the deck is a complete one then we can know with certainty the probability of rolling a ‘2’ (1/6) or picking an Ace (1/13), we know how uncertain the future is, how much we don’t know.  The last type of randomness, apparent randomness, is the most important to this topic.  Apparent randomness is the case of facing an uncertain future due to a lack of knowledge and understanding, it can be thought of trying to play cards with a weighted deck (say, one in which all clubs have been replaced by hearts) the composition of which the player does not know.  Here, if one knew the makeup of the deck then they would be able to predict the probability of different outcomes but the deck, the randomness generator, is not known to the player.  For example, though the weather may be determined by laws, just as the movement of a planet is determined by (Newton’s) laws of motion, our understanding of the weather laws is such that we are unable to predict it, thus, for all purposes, the future weather appears to us to be, at least slightly, random.  For another example consider the many precise (but often wrong) predictions made by the Bank of England regarding future inflation/interest rates/unemployment (see here for the result of a very quick Google search)

The weather is so difficult to predict because it depends upon many ‘units’ (water droplets, the solids around which they form, local air pressures and more) which can interact to form positive feedbacks.  The result is a system which is rendered hugely difficult to predict, in part because a tiny mis-estimation can have far reaching consequences.  In fact it was a study of the weather which gave birth to the mathematical field of ‘chaos theory’.  Chaos theory can be understood by imagining a tennis ball sat atop a large exercise ball in the middle of a sports hall.  If the perfectly balanced tennis ball is instead placed slightly to the right then it will roll away to the right, perhaps as far as the end of the sports hall and vice versa if the ball is placed slightly to the left.  Thus a tiny mis-estimation of the starting position of the tennis ball has far reaching consequences for predictions of the future position of the ball.  That the weather forms such an unpredictable system is a problem for ecology, conservation and agriculture because the weather plays such a large role in determining what happens at the very base of every foodweb.  Even if the weather was perfectly forecastable, predicting the precise impact of altering a complex foodweb via carrying out a conservation intervention would be nigh on impossible as is predicting the impact of a government’s economic intervention.

Conservation interventions (outside of academia) are normally carried out on the belief that doing A will result in a change in B.  If A is expensive then it will need to be justified.  The normal approach to this problem is to make a prediction about the change in B which will result from action A.  Unfortunately this usually means making predictions about complex systems which are not completely understood.  The more precise one attempts to be, the more likely one is to be wrong, herein lies the problem. 

There are two solutions to the difficulties of forecasting presents:

making vaguer predictions and making no predictions at all.

Both of these solutions run counter to our nature and also counter to the media’s handling of prediction making in the face of randomness.  Firstly we cannot help but attempt to predict the future by imagining various scenarios, not making predictions requires a great mental effort and self-restraint.  Secondly, when we cast our minds forwards we do so by imagining one possible scenario at a time.  Such a forecasting system is deeply flawed.  A useful forecast is not the sum of one or a few imagined scenarios, is the (weighted) average of all the possible scenarios which includes in it a measure of uncertainty.

The National Trust’s Wicken Fen (Cambridge) (see here) and High Peak Moors (Peak District) (see here and here) projects are both attempts to manage land whilst making the minimal possible number of predictions.  The National Trust is doing this by utilising fairly unspecific tools (i.e. livestock graze land instead of fine scale intervention by hand in Cambridge and blocking ditches in the Peak District) in the hope that these will bring about broad benefits to the ecosystem.  Precisely what those benefits will be, there has been little attempt to precisely predict.  Instead the introduction of the livestock, ditch blocking and other broad-stroke interventions, are forming lessons from which the National Trust will learn in order to inform future efforts.

Restraining the extent of our meddling with nature, basing this meddling on minimal ecological theorising and instead looking for examples of what worked in the past may seem a non-scientific approach but it isn’t.  Learning what works is scientific.  If broad and approaches can be shown scientifically to work best, scientists are obliged to put aside any inherent preference for complexity and evaluate these approaches in the same way as more complex ones. 

Being broadly right means dealing with uncertainty, with vagueness, a situation which may not sit well with us at first but it is surely better than being precisely wrong.

QALYs and conservation

I am interested in what conservation can learn from other scientific disciplines as it strives to tackle two of its biggest problems, a lack of knowledge and a lack of funds.  Adopting an evidence based approach to selecting conservation interventions, as has been achieved in medicine, has been proposed as a solution to tackling the lack of knowledge conservation suffers from.  With regards to funds, conservation must generate more funds and use these funds as effectively as possible.  Here again, the NHS offers a lesson.  The NHS’ budget has long been insufficient to offer all treatments to all patients, as a solution a scientific method has been put in place to ensure that the resources are used optimally, to save the most lives and increase life quality as much as possible.  I will explore what conservation can learn from how the NHS achieves this.

Finite resources force tradeoffs.  Tradeoffs entail valuation, either implicit or explicit.

When utilising finite resources, a decision to pursue one course of action/invest in one intervention means deciding not to invest in another option.  Thus, the intervention which is chosen is valued (implicitly or explicitly) more highly than the option(s) not chosen.  When different interventions require different amounts of resources then the situation becomes more complicated but the principle remains, the option which is chosen is judged to be of greater value than the options not chosen.

The NHS’ finite budget forces it to make tradeoffs between different treatments.

The NHS has a finite budget which it can spend on treatments.  This budget is not large enough to provide every proven treatment.  As a result, according to the NICE (the National Institute for Health Care and Excellence) website ‘The enormous costs (of different treatments) mean that choices have to be made’.  These choices are tough choices, choosing between offering a drug to extend the life of a cancer patient by a few months or years and using this money to provide other treatments.  As stated on the NICE website ‘It makes sense to focus on treatments that improve the quality and/or length of someone's life and, at the same time, are an effective use of NHS resources’ (my emphasis).  It is because health and life are so important that these choices are so difficult and it is because these choices are so difficult that a rigorous and scientific system needs to be in place to ensure the correct decisions are made.  In this blog I will examine in more detail how the NHS does this, paying particular attention to the two phrases I’ve highlighted in bold, considering similarities in and lessons for conservation science.

‘Focus on treatments that improve the quality and/or length of someone’s life’:

The NHS’ finite budget means that choices must be made between different treatments for the same and different conditions.  This raises the question ‘how do you compare the cost of losing a leg against the cost of losing sight in one eye or both eyes against the cost of chronic back pain taking into account the effect of the treatment on the patient’s life expectancy?’  What is required is a common currency which allows the benefits of different treatments to be compared.  The currency used is the QALY (Quality Adjusted Life Year). 

To calculate the QALY for a treatment the quality of life of an individual with and without treatment must first be quantified as between 0 (death), and 1 (that of a healthy individual).  By multiplying the additional quality of life resulting from the treatment against the patient’s life expectancy, the Quality Adjusted Life Years resulting from the treatment is calculated (more information can be found here).  The resulting QALY is a standardised measure of the benefit of a treatment and can be compared to any other treatment.

 ‘It makes sense to focus on treatments that ... are an effective use of NHS resources’

Not all treatments offer equally high QALYs and not all treatments are equally expensive.  A treatment which resulted in a great increase in the patient’s quality of life and/or life expectancy may not be offered on the NHS if the price is too high.  Again, NICE use a simple and explicit method to overcome this problem: the cost of the treatment is divided by its QALY value to give £ per QALY (the chosen measure of cost effectiveness) as you can see on their website here. 

I believe that QALYs offer conservation two lessons:

1.       When choosing between different conservation options a common currency is required to compare these different options

2.       The calculation of the benefits of pursuing each option (expressed in the common currency) must be made explicit

I will explore these lessons throughout this blog.

Optimally utilising a predetermined, finite budget.

So what would be the equivalent of a QALY in conservation?  I suggest that the simplest currency, which requires the least number of assumptions and arbitrary valuations, should be used to compare the costs and benefits of different options.  Take for instance a zoo deciding how best to use its resources.  The zoo may aim to maximise the number of different species in the zoo in which case the cost per extra species maintained in zoo could be used.  This might be adjusted to reflect preference for different species (in the same way different treatments are weighted depending on the change in quality of life they offer) e.g. an ape may be worth 3 (other) mammal species and each mammal may be worth 10 bird species (with the exception of penguins) which in turn may each be worth 10 invertebrate species.  Or perhaps, if the zoo’s aim was to reintroduce species to the wild, the zoo would use estimated cost per successful reintroduction of a species.  If the zoo aims to maximise visitor stay at the zoo then sum visitor time spent at enclosure per species could be used.  If education was the aim then a measure of change in knowledge and/or values resulting from visitors visiting the enclosure could be used.  I’m not suggesting how every zoo should be run, I’m trying to demonstrate that making your decision process explicit forces you to identify what it is that you base your decisions on and how you weight these decisions.  When public money is being spent then this is especially important.

Using economic valuation as the common currency

Suppose a conservation organisation has to choose between 3 projects, one will safeguard water quality, another will improve the health of pollinator populations and the third will increase carbon sequestration.  If all three projects cost the same, how should the organisation choose between the alternative uses of its resources?  I suggest that a common currency (like the QALY) is needed so that the projects can be compared.  This currency should require the minimal number of assumptions and arbitrary valuations.  The best attempt to achieve this so far is the Ecosystem Services approach which uses, as its common currency, monetary valuation.  For example, the avoided cost of building a new water treatment plant, the avoided cost of pesticide and benefit or larger crop yield and the avoided cost of climate change (calculated using carbon prices which already exist).  These conversions between different currencies, from water quality to avoided cost of a water treatment plant can be calculated scientifically, minimising the need for assumptions and arbitrary valuations whilst making those assumptions and arbitrary valuations explicit.

Comparing conservation to non conservation options, conservation must use the currency of decision makers.

Now suppose that a government has to decide between 3 project proposals concerning a plot of land, a large motorway verge for example.  The first project is a conservation one which will entail the planting native tree species leading to an increase in carbon sequestration and water quality, the second will build shops which will generate revenue via rent and VAT and the third will ensure that the land use, which has no net economic cost, does not change.  As when comparing different conservation options, a common currency is required to directly compare the 3 different projects.  The benefits of the second and third projects are easily estimated and expressed in monetary terms.  To compare these benefits to that of the first project either the economic benefit (or cost if the benefit is negative) of the second project must be converted into an equivalent amount of carbon sequestration and water quality improvement or vice versa.  As the first is very unlikely, the Ecosystem Services approach, by converting the value of the carbon sequestration and water quality improvement to monetary terms, allows comparison of all three projects such that the conservation option is included and well represented in the decision making process.

NICE doesn’t have to make decisions between increasing health or increasing GDP, that’s why they can stick to QALYs, a currency one step removed from explicit economic valuation.  But individuals and organisations comparing conservation with business opportunities use the currency of money.  Economic valuation is the language spoken.  This must be the QALY of conservation.  It is this which conservation must adopt in order to ensure the value of nature can be compared to the value of other options so that it may be included in the decision making process.  I acknowledge that occasionally, and only occasionally, the currency the government uses to make decisions is public support/protest.  In these instances public support for a conservation option/opposition to the alternative may influence a decision.  However, public support for conservation options has, historically, been hugely insufficient.  This is why I believe that economic valuation is required.

We are a long way off of accurately valuating Ecosystem Services.  In fact, before conservation ‘treatments’ can even been assigned a QALY value they must be demonstrated to be effective via a rigorous scientific valuation.  Many conservation ‘treatments’ are used without ever being effective; conservation’s knowledge problem.  This is why a transparent method, like that used by NICE, is so necessary.  By making our implicit valuations and assumptions explicit, we make criticism and adjustment in the face of new information simpler.  It is because nature, like our health, is so important, that a rational, scientific method is required when it comes to using our limited resources.  If you still disagree, if you believe that explicitly valuing nature is fundamentally wrong then please stop to consider that, if you live in the UK, every aspect of your health is valued relative to every other and has its value.  If you are unfortunate to contract renal cancer then the NHS won’t cover the full cost of treatment ‘sunitinib’, proven to be effective, because it is too expensive (http://news.bbc.co.uk/1/hi/health/7546879.stm).

Learning to play table tennis on a windy day, lessons for conservation

I have played table tennis from a young age and have received an amount of coaching.  The role of the coach is to ensure that the player does not improve their stroke in a manner which is beneficial in the short term but limits the potential of the player, the player is responsible for fine tuning the prescribed technique, gaining ‘feel’ in the process.  In this blog I will show that controlled, non random, conditions aid an individual’s attempt to gain feel, or its intellectual equivalent, expert intuition.  In a random environment the quality of feedback is reduced and the process of gaining intuition is disrupted.  Conservation is practiced in a random environment meaning that the intuition of individuals, resulting from their own experiences should not be trusted.  I will consider the consequences of this conclusion and whether a role analogous to that of the coach exists in conservation.

When purposefully practicing (training) with the aim of improving their stroke, a player will try to isolate one aspect of their stroke technique e.g. the extent to which one uses their wrist to generate power and spin.  Small adjustments will then be made to that aspect of the stroke and the player will take note of the relationship between the adjusted technique and the outcome (the flight of the ball).  Feel will be gained as the player gains positive feedback from the technique which results in good shots. 

Now suppose that the player is playing outside on a windy day.  The wind changes in direction (blowing either towards the player, their opponent or not at all) randomly from shot to shot.  A player trials a technique and plays a shot.  The ball flies into the net.  There are two possible explanations: 1) the technique was a bad one or 2) the technique was good but the wind caused the shot be a bad one.  Similarly, if the ball goes onto the table then there are two possible explanations: 1) the technique was a good one or 2) the technique was a good one or 2) the technique was bad but the wind caused the shot to be a good one.  The player would be much less able to gain feel and would have to trial each technique many more times to gain the same level of feel. 

There are many disciplines in which feel can be trusted, disciplines in which shot and outcome are closely linked in a non random environment (see chapter 22 of the fantastic ‘Thinking, fast and slow’).  If conservation was practised in such an environment it would not be a problem that, as Sutherland observed in his 2004 paper ‘much of conservation practice is based upon anecdote’.  However, every conservation intervention is carried out on a windy day.  Natural populations fluctuate according to the weather as well as other factors we are unable to predict.  A system we cannot predict is random.  For instance, I recently read that butterflies have benefited from the weather over the past few months, an effect which will continue to be important over the next year (link here).  The effect of the weather is so important that human actions could have degraded butterfly habitats over the past 5 year with butterfly numbers peaking this year, the year when habitat is at its lowest quality.  Any individual landowner who followed this trend (with their land lowering in value to butterflies over the past 5 years), who was also unaware of the effect of the good weather and who measured butterfly population sizes would conclude that the habitat was of the highest quality in the final year.  This is analogous to playing using a bad technique but obtaining a good outcome due to the effect of the wind when playing table tennis outdoors.

One partial solution is to simply play more shots and gain feel more slowly.  The effect of the wind will even out over many shots and good technique will result in a good outcome more often than bad technique.  Similarly, one cannot learn from one conservation intervention not carried out under controlled conditions.  To identify good and bad conservation interventions the outcome of many interventions must be compared.  It is here that conservation scientists have a role to play by comparing the results of many trials of a similar conservation technique across many different conservation strategies.  Every conservation practitioner, that is every individual who purposefully manipulates the land for a conservation charity, business, government or personal enjoyment has the potential to turn their ‘shot’ into a small piece of feedback by measuring the effect of this shot, by checking if this shot lands on the table.  Currently conservation practitioners are playing shots, carrying out interventions they hope will benefit nature, and turning around not bothering to check if the ball lands on the table, if the intervention is a good one.  This is the strategy adopted by Sutherland, founder of www.conservationevidence.com

Alternatively, or alongside this approach, scientists can exclude the random by conducting well designed experiments.  The feedback gained will only apply to a very precise set of conditions which may not be relevant in reality.  However, general principles can be tested and lessons learnt.  A framework of understanding can be built.  For instance, if you asked a coach why an overarm tennis serve is better than an underarm one then they may point out to you that by striking the ball above the height of the net with a fully extended arm the player is able to generate more power whilst ensuring that ball lands in the correct section of the court.  The coach can work from theory (a grasp of mechanics) to technique.  Likewise, an understanding of the factors determining algal growth can be used to predict the effect of fertiliser running into a lake, for example.  Using this understanding an intervention can be recommended, the effectiveness of which can then be measured as outlined above.

Conservation science throws up counterintuitive findings, findings that feel wrong.  This is not surprising and we should be wary of our sense of feel where that sense is based upon personal experience in a random environment.  Even in a non random environment it is a misconception that the correct theory or technique should ‘feel’ right when described or tried for the first time.  It doesn’t always.  I remember someone who coached me telling me how to adjust the position of my feet when playing a forehand shot, ‘it will feel odd and alien, like wearing shorts on a windy day’ he said.  He was right.  At first the new technique just felt wrong.  Similarly, when I learnt to juggle I had to trust the guy who had taken the time to make an instructional youtube tutorial.  When I tried to replicate what he showed me it felt wrong.  Now I can juggle and it feels right but if I try to learn a new trick, a new pattern of movement it feels wrong again

Conservation is practiced in a random and complex environment.  In an environment which does not lend itself to the acquisition of expert intuition.  We should be wary of trusting our own experiences too much.  As a profession conservation must realise the value of feedback and the limits of our understanding.  At best, by pooling the experiences of many conservation practitioners, conservation might succeed in being broadly right.

Listening to the Devil's advocate, not just preaching to the choir

When considering conservation I think it is useful to engage with someone playing Devil’s advocate.  For a long time individuals have worked in conservation because they believe that it is a good and worthy cause.  They believe that nature is priceless and deserves to be protected and enjoyed by people.  The challenge for professional conservationists is converting this personal belief into action, taken by the public, via their professional work. When considering this problem I bear in mind two very different attitudes.

Self righteous hippy:
This attitude can be summed up as follows: ‘ I value nature for its intrinsic value and I am correct in doing so.  You should also value nature in the same way as me.  If you do not value nature in the same way as me you are wrong.  If you chose to behave in a selfish manner which degrades nature (but benefits you) then you are doing wrong and you are a bad person’.

Selfish individual:
To take an extreme example to illustrate my point, consider an only child and do not wish to have to have children who feels: ‘I do not care about any damage I cause the world as long as it does not affect me.  I live in a developed nation and am therefore likely to be shielded from the effects of any natural degradation.  I will probably never travel to Africa so I don’t care if Lions become extinct.  I act selfishly, why shouldn’t I?’.

The self righteous hippy attitude leaves me extremely frustrated.  An intrinsic valuation of nature is a personal attitude or valuation.  A personal valuation, by definition, is not wrong or right.  If the evidence suggests that most people act selfishly then people should be expected to act selfishly.  Instead of wasting energy on being indignant a better option is to consider how to make conservation the selfish option or how to increase the number of people who hold a similar intrinsic valuation (in a morally acceptable, non brainwashing way).  I believe that the selfish individual is beyond the reproach of a professional conservationist.  It is this person that conservation must listen to.  If this person can be convinced to act in a way which benefits nature then conservation will have succeeded. 

If flights are cheap then don’t get angry at people for having a large carbon footprint and if farmers are subsidised to produce food unsustainably then don’t morally reproach the individual farmers.  It is largely the role of the state to correct these problems by taxing flights or listening to the National Farmer’s Union, scientists and economists and making an informed, logical decision regarding which actions farmers should be paid to carry out.

Live by the Sword; Die by the Sword

This blog will focus on one particular problem of viewing the ecosystem services valuation (E.S.) approach as a conservation panacea and possible solutions to this problem.  Whilst the E.S. approach, which aims to express the value of nature to humans in monetary terms, has the possibility to increase the price we currently put on nature, this price will not always be sufficient.  Sometimes the economic benefits arising from degrading the environment will outweigh the economically explicit costs.  In such instances the degradation of the natural environment will be explicitly rationalised (as supposed to implicitly rationalised as is currently the case).  When this occurs scientists can ensure that their valuation explicitly includes known unknowns, the value of nature not yet quantified but expected to be important.  If this is not enough then there are two broad options: conservationists can fall back on the moral arguments which have been largely unsuccessful for the past hundred years: each species unique, irreplaceable and should be protected for its intrinsic value or they can hold up their handsand state that they cannot currently justify safeguarding the relevant natural resource on the basis of the economic costs.  Recently the ‘The State of Natural Capital Report’ opted for the first option, but I will argue that the explicit valuation of nature requires one to forego the moral argument.  Even so, I believe intelligent utilisation of the ecosystem services approach will do more harm than good.

Firstly, to get a few points out of the way.  Nature has always had a price-tag, this price tag has been an implicit one.  As long as people have been able to buy land or pollute their surroundings, nature has had a price.  As long as conservation has had a finite budget which has necessitated trade offs between different conservation actions, nature has had a price.  This price tag has rarely, if ever, reflected the value of nature to humans.  The ecosystem services valuation approach aims to make the value of nature explicit in a currency (money) which allows trade-offs to be made between alternative options, e.g. organic and intensive farming.  Lastly, some ecosystem services are easier to value than others.  Those which can be sold (e.g. the ability to produce crops) have been well valued, some such as the value of increased water quality are now being more accurately priced and others, such as the value of the emotional wellbeing gained from being in a natural environment are much harder to value.  The ecosystem services approach does not have to ensure that the price we put on nature perfectly reflects the nature’s value to us to be effective, it only has to ensure that the price we put on nature is more accurate and that this increased accuracy is enough to alter decisions.

The short term aim of the ecosystem services approach is not to perfectly measure the value of nature to us, it is to identify the biggest and easiest to measures sources of value such as pollination services, carbon storage and water quality enhancement.  Often including these values will be enough to alter decisions but sometimes it won’t.  When, in light of this valuation, environmental degradation is still economically rational then it is important that the existence of known unknowns, such as the cultural value or any other unmeasured value are acknowledged.  In some circumstances, where the benefits narrowly outweigh the quantified costs, this may result in decision makers erring on the side of caution.  Even if this is not the case, making the known unknowns explicit is a useful tool for directing future research.  This approach would also incentivise conservationists to create accounting methods which allow new information to be incorporated, methods which are transparent and useful to policy makers.

When an ecosystem services argument, which makes the known unknowns explicit is insufficient, should conservationists throw down the ecosystem services tool and redouble their efforts to prevent this extinction by reverting to the moral argument?  ‘The State of Natural Capital’ chose this option writing ‘when thinking about natural capital, wild species and habitats require special treatment that reflects their irreplaceability’ (authors’ emphasis).  It is my opinion that a change of tack of this manner would undermine the ecosystem services (E.S.) approach.  I believe that the use of the E.S. approach is a recognition, by conservationists, that in order to contribute to decisions they must be perceived as a consistent, reliable and impartial contributor to decisions.  In resorting to the moral argument, one chooses a personal rather than impartial valuation of nature.  Who would want to engage with a conservation organisation/scientist knowing that the conservationist, upon losing an argument, would react in this way? 

If conservation needs to have a constant presence at the decision making table but the moral argument still has some value then the opportunity exists to split the use of economic and moral arguments between different individuals/organisations.  Undoubtedly academics are not the most effective at rallying large scale public opposition to environmentally degrading activities.  Instead of individuals leaving the table to pick up their placards when an argument based upon ecosystem services valuation is insufficient, they could stay at the table whilst those organisations and individuals best at rallying public opinion take on the moral argument.

The ecosystem services approach is not perfect and most of those who champion it became involved in conservation for moral reasons.  Conservation must not lose sight of these reasons which drive some of their number to the decision making table.  I am a fan of the ecosystem services approach and I believe that one who fights for nature with the ecosystem services sword must be willing to see nature die by this sword.  Ultimately, conservation needs collaboration, whatever tools conservationists use, they must not lose sight of their ultimate motivation and aims.

Skylark Patches and Behavioural Economics

In ‘Fighting for Birds’, and also on his blog, Mark Avery expresses frustration at a reluctance amongst farmers to take advantage of funding for skylark patches ( 16m² areas of arable land left unfarmed) under the Entry Level Stewardship Scheme.  Having recently read the fantastic ‘Thinking, fast and slow’ by Daniel Kahneman, ‘Nudge’ (Thaler and Sunstein) and ‘Predictably irrational’ (Dan Ariely) I am convinced that conservation can learn from behavioural economics, the study of the ways in which individuals act irrationally (from the perspective of classical economics).  In this blog I will outline a series of experiments to identify whether farmers are more concerned with maximising their profits or the size of their farm’s yield.  I will also present an idea for a way to address individuals’ overestimations of the size of skylark patches (if this is a problem as Mark Avery suggests).

Behavioural economics is based on the observation that humans are not economically rational.  An economically rational individual would always act to maximise their utility (or overall wellbeing).  In the case of the farmer, making the assumption that farmers attribute no benefit to increased on farm biodiversity resulting from the incorporation of skylark patches, a rational farmer would incorporate skylark patches if they increased his (or her) (predicted) profits.  It has been shown that skylark patches do increase profits, see Mark Avery’s blog.  So why, when presented with this evidence, do all farmers not rush to incorporate skylark patches?

The first possibility is that farmers are not interested in maximising their profits.  Instead they may be 

interested in either A)maximising the area of land which they use to produce crops or B) they may evaluate the success of their farming efforts by calculating the total yield of the farm each year.  If farming is a vocation and farmers care about producing crops then this would make sense.  To test between these hypothesises the following scenarios would be used; each scenario concerns a different fictional farm.

Scenario	Area (hectares)	Yield (tonnes Per Hectare)	Total Yield	Profit per tonne (£)	Total Profit (£)
1	40	8	320	400	128000
2	40	9	360	350	126000
3	45	8	360	350	126000
4	35	8	280	450	126000
5	40	7	280	450	126000
6	35	9	315	400	126000
7	45	7	315	400	126000

Farmers would be shown scenarios in pairs or threes (with and without the ‘Total Profit’ column, removed in different experiments) and would be asked which of the farms they would prefer to be theirs.  It would be explained that they will not be able to alter the yield, which reflects the quality of the land or the profit per tonnes which reflects a deal with a local crop buyer which cannot be altered.  An economically rational farmer, if presented with all scenarios would prefer scenario 1 to every other scenario but would not have no preference between other scenarios. 

Experiment A: the farmer would be offered scenario 1 and 2 (in a randomised order e.g. scenario 1 presented first 50% of the time).  If the farmer chose scenario two then this would signal that they would rather run a farm with higher yields.  Next scenario 1 and 3 would be presented.  If a farmer chose option 3 then this would signal that they would rather run a farm which had a larger area producing crops.  Both options 2 and 3 offer the same yield which is greater than that offered by scenario 1 but offer a lower total profit.  If farmers attempt to maximise the quantity of crop they produce they should prefer scenarios 2 and 3 over scenario 1.

Experiment B and C: individuals would be presented with scenario 1, 4 and 5 and then 1, 6 and 7.  This time individuals would be asked to rank the scenarios in order of preference (with the option of 2 or more scenarios being equally preferable).  If individual preferred 4 to 5 and 6 to 7 then it would be possible to conclude that individuals would rather maximise their yield than the area of their farm and vice versa for individuals who preferred 5 over 4 and 7 over 6.

Experiment D: farmers would be given the option of the following 4 farms and would be asked to rank them from highest to lowest preference with the option of applying equal preference to 2 or more scenarios.

Scenario	Area (hectares)	Yield (tonnes Per Hectare)	Total yield	Profit per tonne	Total Profit
A	40	8	320	400	128000
B	40	8	320	450	144000
C	40	9	360	400	144000
D	45	8	360	400	144000

These two sets of experiments would make it possible to see if farmers prefer to maximise the quantity of crops they produce when total profits are equal and, if this is the case, if farmers prefer to do this by maximising the area of land they farm or by maximising their yield per area.  If farmers do prefer to maximise the area they farm then this will help to explain reluctance to take up skylark patches.  The inclusion of skylark patches means a reduction in area farmed.  These experiments could be extended to offer scenarios in which the total area farmed, or yield per area, were increased but total profit decreases due to a decrease in profit per unit of crop.

If farmers do want to maximise the quantity of crops produced then conservation can learn from Thaler and Benartzi’s ‘Save more tomorrow’ scheme.  Thaler and Benartzi recognised that individuals should be saving more for their pensions than they were but did not like to see a drop in their paychecks.  The authors trialled an arrangement whereby upon receiving a payrise workers increased their monthly contribution to their pension (without seeing their paychecks shrink).  The scheme was highly successful but how does it apply to farmers?  Once the currency that farmers use to evaluate the wellbeing they gain from farming (area of farm, yield per area, profit per tonne of crop or total profit) has been identified then skylark patch scheme can advertised so that individuals increase the number of skylark patches when this does not result in a decrease to the relevant aspect of their farming.  For example, if farmers are most concerned about the size of their farm then skylark patch uptake may be highest when targeted at individuals increasing the total area of their farm.

Mark Avery also writes that the patches look as if they occupy more space than they do.  I suggest offering farmers the feedback they need to improve their estimation of the area of skylark patches.  This could be achieved as follows:  Using aerial photographs or the following type of diagrams (with labelled axis), ask individuals to estimate the size of the red squares and the proportion of the total (blue) area which they occupy:

If mark is right then individuals will over estimate the proportion of the total area occupied by the red shapes, if I am right then repeated feedback (providing individuals with correct answers instantly after they make their estimations) will result in individuals’ skills increasing.  Subsequently, individuals will be better able to imagine the difference that 0.5, 1 or 5% of their land being used as skylark patches will really look like.

Other thoughts:

People don’t deal with percentages rationally and overestimate small percentages.  Individuals should be expected (on the basis of current research) to be more in favour of incorporating skylark patches when they are advertised as ‘leaving 98% of farm land area as arable' than as ‘taking only 2% of total farm land area').

Is expert intuition good enough for conservation?

I am currently reading the excellent ‘Thinking, fast and slow by Daniel Kahneman, in this blog I will consider Daniel’s observations regarding the conditions necessary for the attainment of excellence.  Throughout the book Kahneman persuasively argues the merits of using statistical analysis to make rational decisions rather than basing decisions on intuition.  However, Kahneman also provides conditions under which expert judgement, a form of intuition, can be trusted.  Do the actions taken by conservationists meet these criteria or would individuals’ decisions improve if they were based on cold statistics instead of intuition?

The criteria:
According to Kahneman, when an expert makes decisions

·         ‘In an environment that is sufficiently regular to be predictable

·         With an opportunity to learn these regularities through prolonged experience’

‘When both of these conditions are satisfied, intuitions are likely to be skilled.’

One factor which affects the efficiency with which an expert can learn from an effect is the coupling of cause and effect.  For example, if you were learning to play chess and played a move which resulted in your queen immediately being taken then it would be fairly easy to learn from that mistake.  In contrast, if a move you made set in sequence a series of moves by you and your opponent which resulted in your queen being lost 4 moves later then it would be harder to link the cause (your initial move) and effect (loss of queen). 

How do the environments in which conservation practitioners compare to these criteria? 

Every university course in Ecology or Population Biology will draw the attention of the students to stochasticity (randomness) in determining the state of any habitat or ecosystem at any one time.  In highly random environments (e.g. those subject to a highly variable climate), if not all environments, the first criteria is violated.  For this reason experts should be wary of basing decisions on their intuition, on what they ‘feel’ to be right

Secondly, for experts to learn they must make similar decisions many times (to account for stochastic effects) with the effects of these actions closely spatially and temporally coupled (the effects must occur close by both geographically and in time) to the action.  The consequences of conservation actions such as: the planting of trees, the protection of young trees from deer and/or other browsers, reintroduction projects, habitat creation and others are not felt for many years.  Not only does this make it harder for individuals to learn from their actions, most don’t try as long term funding is sacrificed in the face of financial pressures.  Furthermore, many actions have effects which occur at a large geographical distance from their cause rendering what one intuitively feels to be right, wrong.  A good example of this comes from Chinese Lanterns which fall as debris a long way from where they are released, if the lantern fell a metre away from where it was released then I’m confident the person who released the lantern would make an effort to remove that waste (at least if it was released at home.  As it is, pollutants which cause an effect out of sight are left out of the mind of the polluter.  In order for conservation practitioners to be confident about the effects of an intervention they must be confident that no significant effects will be felt outside of the geographical area they have considered (the possible effect of badger culls increasing badger movement is one such example).

I am therefore sceptical of any ‘expert’ who sites intuition as the grounds on which they made a decision regarding decision.  As Kahneman explains the solution is objective statistical analysis.  Pool all the available data regarding the proposed conservation decision, acknowledging uncertainty.  Unfortunately, all too often the pool of available data is too small.  Conservation evidence is an organisation set up to address this problem.  It is a problem which will most easily be addressed with conservation practitioners recognising the limits of their intuition and sharing their knowledge with other practitioners with other experience.  This should not be taken as an attack on the knowledge of practitioners, rather as a comment on the irregularity of ecological systems in which effect is often spatially and/or temporally distance cause.