Short articles on conservation management practice & theory for professionals & students. We signpost resources for personal development, team development, research, seminar preparation, assignment & revision.
Any team needs to deliver the work that achieves its purpose. Getting people up to the right level of ability is important. This capability covers skills, awareness of the work, clarity on the goals and a sense of purpose that enables (i) prioritisation of effort, (ii) decision making and (iii) problem solving.
A recent study in Mauritius by Stebbings et al (2016) identified that operational teams made up of significant numbers of new starters (e.g. seasonal volunteers or incoming professionals) found that those new colleagues only achieved the desired level of performance part-way through the peak breeding seasons for working with endangered birds.
The arrangement for taking on new staff was historical and fitted a plan of when people would be at their busiest. However this study showed that taking people on earlier and training them to a higher level would make them more productive at the busiest times.
Reading:
Stebbings, E. , Copsey, J. , Tatayah, V. , Black, S. , Zuël, N. and Ferriere, C. (2016) Applying Systems Thinking and Logic Models to Evaluate Effectiveness in Wildlife Conservation. Open Journal of Leadership, 5, 70-83. doi:10.4236/ojl.2016.53007.
In conservation we are working in the business of change. We want to improve the situation for a species, or remove threats, or recover a landscape, or enable humans to co-exist with a sustainable natural environment.
As humans within human society and as biologists working with species and ecosystems we need to recognise that change is not a cause-effect process. Instead we should think of it as an emergent property – an outcome of many interventions and interactions with the things we are concerned about and their wider environment.
It is almost inconceivable that a rhino has recently been killed in a French zoo by poachers for its horn . Yet this is an outcome from changes in the system – the the need for income by criminals, the demand for horn, the depletion in accessibility to alternative wild supplies (due to better wildlife protection). We need to truly understand the dynamics in order to eliminate the threat and this takes constant learning – what worked before might not be relevant today. This sometimes seems too much to tackle.
We cannot do everything today. So how do we start?
The best processes of learning, improvement and innovation start small and grow big. This is also true in many cases within the conservation sector.
The Chatham Island Black Robin, Mauritius Kestrel and other species have been brought back from the brink by making initial steps, learning and continuing to make those steps. Start small and then build up. This strategy enables us to move fast and act, but most importantly learn, improve and upscale carefully. These examples are clearly not as complex or global as the system that impacts rhino conservation, but we must never be too afraid to learn how to innovate.
Further reading:
Gagliardo, R., Griffith, E., Mendelson, J., Ross, H., and Zippel, K. (2008). “The principles of rapid response for amphibian conservation, using the programmes in Panama as an example”. International Zoo Yearbook42 (1): 125–135.
Herrero, L. (2006) Viral Change, meetingminds, UK.
Martin, T. G., Nally, S., Burbridge, A. A., et al. (2012). Acting fast helps avoid extinction. Conservation Letters, 5, 274-280.
Traditional change management follows a linear approach, defining a goal, identifying a plan and delivering to that plan. The process is logical and surely unquestionable. However this is an example of linear thinking, which is rarely the appropriate way to consider complex conservation problems.
Ecosystems, landscapes, habitats, communities, species, populations do not act in a linear fashion, they are much more complex. This means that if you change one thing then something unexpected is likely to happen somewhere else – and what you had intended may or may not happen.
Of course understanding systems can be a difficult thing to do. Instead, managers either resort to ‘giving their view’ on things, or setting success measures based on those views. Having a view on why things are a problem is one thing, but it is better to get knowledge by collecting data (Deming 1993; Seddon 2005).
It is better to define the following:
Purpose is the definition of why we are here, best understood from the species or ecosystem perspective.
Measures allow us to understand what is likely to happen in future if the system (including human community interactions, commercial industrial or agricultural land use, wildlife trade etc) doesn’t change.
Method – can be addressed when we understand the data derived from our measures.
Manatee deaths due to watercraft collisions in Florida. Knowing the occurrence level (Measure) can we do anything (Method) to reduce unnecessary mortality of manatees (Purpose)?
Systems Theory tells us that Purpose, Measures and Method are fundamentally linked – it is a systemic relationship. This systemic relationship can either work for you or against you depending on how you set things up.
The paradox is that in this system, change requires no plan. For Seddon, change is simply an emergent property. It can only occur if you set things up that enable people to innovate with interventions in response to the real system of species and ecosystems – what happens.
Any attempt to plan change otherwise is fiction.
Reading
Deming, W.E. (1993) The New Economics, MIT CAES, Cambridge MA.
Seddon, J. (2005). Freedom from Command and Control. Buckingham: Vanguard Press.
One of the most important things for conservation practitioners to be able to do is to detect real improvement (or real declines) from otherwise random changes for a species or ecosystem (Black and Copsey 2013).
Systems behaviour charts allow you to identify the difference between random changes and non-random changes -to see whether the ‘system’ has fundamentally changed if we use the rules summarised by Black (2015)
If we take the example of the recovery of Puerto Rican Parrots, initially managed by Snyder et al (1987) in the 1970s and 1980s, we see phases of the parrot population going up and down over time, some points above a mean line and some below (as you would expect).
Where the pattern of data falls outside this expectation, the system has fundamentally changed. In the case of the Puerto Rican parrots, this occurred in 1978 and again more fundamentally in 1989. It even looks like a new breakthrough may follow on from 2009.
Even more important than the actual numbers however, is the insight from plotting natural limits and warning limits. For the parrots we see that although the population is generally improved it is not stable and could be expected throughout the 2000s to drop to less than 10 birds as much as rise to 65. Indeed today’s population could yet be vulnerable to extinction – with a projected lower natural limit appearing to be below zero using most recent year’s data .
Reading:
Black S.A. (2015) System behaviour charts inform an understanding of biodiversity recovery. International Journal of Ecology, 2015 (787925): pp6 http://dx.doi.org/10.1155/2015/787925
Black S.A. and Copsey J.A. (2014) Does Deming’s ‘System of Profound Knowledge’ Apply to Leaders of Biodiversity Conservation? Open Journal of Leadership 3(2) 53-65. DOI: 10.4236/ojl.2014.32006
Snyder,N. F. R. , Wiley, J. W. and Kepler, C. B. (1987) The Parrots of Luquillo: Natural History and Conservation of the Puerto Rican Parrot,Western Foundation of Vertebrate Zoology, Los Angeles, Calif, USA.
110 Success Stories for Endangered Species Day 2012: Puerto Rican parrot (Amazona vittata), March 2015, http://www.esasuccess.org/caribbean.shtml.
Endangered Species Act Works: Puerto Rican parrot Amazona vittata, 2015, http://www.biologicaldiversity.org/campaigns/esa works/caribbean.html.
The status of any situation cannot be best judged from an isolated point in time. It is also dangerous to judge one point in time versus another point in time (such as this year versus last year). Consider this in the case of a population of rare birds, or the status of your budget, or the number of volunteers in your organisation. The only meaningful understanding of a data point is where it sits in the context of the past, and ideally, the future. For example if we look at manatee boat-collision mortality (right) and we have an annual count of 50 manatee deaths, is that good., bad or indifferent?
Prediction of the future is one of the most important but elusive skills that a manager can possess. Of course no one can actually predict the future, but we can identify predictable elements, or degrees of predictability. The best methods for prediction are based on using empirical data. In management circles, rather than establishing complex predictive models, the most pragmatic approach is to establish a picture of the current system and then base expectations on the predictability of the patterns of data in that system. For example with the Florida Manatee (above) we see three (or four) systems – a stable low level of collision deaths (to 1983), then a higher level from 1984-1997, then an unstable period 1997-1999, then a new system thereafter. You have to loo at the right system to understand what might happen next.
It is also unhelpful to define a level of performance as ‘good’ or ‘bad’. They key thing is how to stabilise it and how to make it better. The system in the 1990s is driven by the higher numbers of watercraft on the river systems – so collisions are more likely. We cannot say things are worse than in the 1970s, just that the likelihood of collision deaths is greater – and we might want to do something about that (such as impose slower waterway speed limits).
Reading:
Black S.A. (2015) System behaviour charts inform an understanding of biodiversity recovery. International Journal of Ecology, 2015 (787925): pp6 http://dx.doi.org/10.1155/2015/787925
In conservation we are usually in the business of change – either changing the fortunes of a species, for example recovering a population, changing a landscape, changing the attitudes of people towards species and ecosystems, changing the impact of threats. The best leaders face these realities and then work out how to address the issues. This is an adaptive process, there may be no plan.
Warren Bennis talks about ‘mastery of the context’. You need to understand the context then work your way through it towards what you want to achieve.
John Seddon goes further – if you want to improve something do not build a plan. When you make a change the only plan should be to study the system – to get knowledge. That knowledge will inform you – you will be able to work out what you need to do. And working it out should not be based upon assumptions or experience of ‘how we did it before’. The working out requires the further acquisition of knowledge.
Once change is applied we should ask ‘is it working’ – and how do we find out? y seeking knowledge of the results.
This is, of course, the scientific process. In the scientific cycle we might experiment to test an idea, but we don’t plan far into the future assuming we know the outcome already. Rather we go through cycles of knowledge acquisition to enable us to make further decisions about action and testing. The investment in thought, resources and time is focused upon action-ing what is important. The time spent on ‘management’ (planning, delegating, setting targets, monitoring) is eliminated. Everyone is instead focused on the work.
Reading:
Bennis W. (1989) On becoming a leader. Addison Wesley, Reading MA.
Seddon, J. (2005) Freedom from Command and Control, Vanguard Press, Buckingham, UK.
The “mountain chicken” frogs on the Caribbean island of Montserrat are in a perilous and seemingly irredeemable situation. It’s worth questioning whether attempted recovery is even worth the effort. After all, this species, one of the world’s largest frogs, will have to recover from just two individuals.
Hunting, habitat destruction from the 1995 volcanic eruption, and the arrival of the recent fatal fungal infection, Chytridiomycosis (or “chytrid”), has devastated the population of these frogs.
Rarely has any species naturally recovered once reduced to a few individuals, without some sort of human assistance. The Seychelles kestrel is one exception. Species declines are largely caused by human activity, whether that be through direct killing, destruction of natural habitats, or the introduction of species like cats, rats or the chytrid fungus.
Mountain chicken frogs are surprisingly large. Jeff Dawson, DurrellSadly, even in recent times, extinctions occur in plain sight. China’s last Yangtze River dolphins, a male and a female, were separately held captive without being bred. Australia’s Christmas Island pipistrelle bat was confirmed extinct, frustratingly, during delayed attempts to rescue the last individuals. Similar late efforts failed to rescue the Po’ouli, a unique forest bird on Maui, Hawaii.
The lack of action in these cases was caused by bureaucracy, aversion to risk, politics, misplaced priorities, and professional bias; human rather than biological factors. Thankfully, other examples demonstrate a better way.
Bringing a species back from near-extinction
North America’s black-footed ferret was thought lost in the 1980s until several were discovered in Wyoming, which inspired a recovery programme. The California condor was reduced to 27 individuals sparking a controversial, but successful, captive-breeding initiative.
The Chatham Islands black robin: rescued from a single pair. leonberard/flickr, CC BY
In New Zealand, the Chatham Islands black robin was rescued from a single breeding pair. On Mauritius, once the island of extinction, the local kestrel was considered a lost cause by the mid 1970s and was then the rarest bird in the world, yet decades later the population has been recovered by active management and now hundreds of pairs of birds live free on the island.
These cases required pioneering innovations, such as double-clutching (removing eggs to encourage pairs to breed again), using common species as adoptive parents, and training captive-bred animals for wild release. Leaders such as Don Merton, Tom Cade, Noel Snyder and Carl Jones shared ideas with colleagues across continents, fuelling knowledge and experimentation. Actually getting on with the work is important. For Jones, too many people “talk about conservation…but we’ve got to do it rather than talk about it”.
Rare species are not just an interesting entry in the catalogue of life. They have a function in the natural world. Amphibians are important in controlling insects and other invertebrates. In Montserrat, for instance, some farmers have noticed increased levels of crop pests since the frogs disappeared.
In practice, action first means setting short-term goals. For the mountain chicken frog, this involves moving the female into the male’s territory, building artificial nests, and protecting locations from threats.
The work must also pursue a long-term vision. A sustainable wild population of frogs means that captive-breeding, already undertaken in bio-secure facilities, is not the sole answer. Threats like chytrid need to be understood first to inspire possible solutions. The disease will not disappear just by increasing the numbers of frogs (though frog population is of course critical).
Fieldwork requires painful attention to detail, literally sitting with the animals to prevent disturbances, then monitoring offspring survival, assessing and carefully improving habitats, and moving individuals to new, safe locations. Conservationists need patience and determination to overcome disappointments. They must seek to understand changing circumstances, keep open to ideas and be willing to develop new approaches if things do not go well. Carl Jones suggests that recovery requires about 20 breeding cycles. That means 20 years for species that breed annually. Improved understanding can however, accelerate recovery.
Recent efforts in the US with the California Channel Islands fox restored a handful of surviving individuals to a thriving population in just a decade. The near-extinct Mauritius kestrel bounced back to a free-living population from just four birds. India’s unique pygmy hog was reintroduced after successful breeding of a few animals taken from the wild. Conservation is getting smarter and more effective.
So on Montserrat, people must act fast while hope remains. A sustainable frog population must be a priority. If people carefully use their knowledge, this extraordinary giant, the mountain chicken frog might withstand threats of disease and habitat pressure on its tiny, volcanic island home.
The original version of this article appeared in The Conversation
1) to do the work (produce output, product, service), and
2) to improve the work.
If the person is clear about the purpose of their work, then 1 and 2 should be easy to deliver if they have the right resources, skills, and understanding of users’ (e.g. customers) needs.
But managers rarely leave it at that…
Traditionally, managers get people to do ‘better’ in their work by what John Seddon tags as ‘sweating the labour’ – getting the people to work harder or faster. The idea is that you get more output for the same hours work – essentially more for the cost (efficiency).
Of course the idea of the sweatshop is morally uncomfortable – exploitation to achieve a profit motive. Yet we still stick to the idea by setting targets: ‘You produced 100 widgets last month, let’s have you aim for 110 widgets this month‘.
It seems plausible – motivational even! What possibly could be the harm in setting a target?
Well, the widgets are being created for a purpose – presumably the purpose for which the customer buys them. And that purpose is associated with the design and quality if production in the widget that is produced.
If you create arbitrary targets (and measures of performance) you will create a de facto purpose in people’s mind which is to deliver those targets. This is different from actually delivering the purpose of the work.
Your worker will work to produce 110 widgets BUT not necessarily a widget that meets the customer needs, nor a widget that could be produced faster or at lower cost whilst still meeting the customers needs, other than by cutting corners (lowering quality or increasing risk). The worker is busy but has got his eye off the ball. This produces errors and lowers the quality of work – which will probably have to be redone – at greater cost.
Targets are not motivational. They might make people move, but that is not motivation. A dog that moves is just one looking to avoid the next kick. It is not a motivated, free thinking, creative, proactive animal. Why would we exect people to operate any differently?
Reading
Herzberg, F. (1968) “One more time: how do you motivate employees?”, Harvard Business Review, vol. 46, iss. 1, pp. 53–62
Seddon, J. (2005) Freedom from Command and Control, Vanguard Press, Buckingham, UK.
If we start to address these questions and filter out assumptions and preconceptions, we are able to make some sensible decisions about how to make effective changes that will have a positive effect on performance.
The world is not perfect and we are unlikely to always have the time and resources to gather the complete picture of what is happening. Nevertheless it is important that we seek out and analyse relevant data in order to make some reasonably robust assumptions about what we can do.
There are two common failures of action, lets call them type 1 and type 2 (which is what statisticians call them). Another definition would be a mistake in identification between ‘common causes’ and ‘special causes’ of variation; without understanding the difference we risk just ‘tampering’. What we want to avoid is the delusion that feel like we are doing something useful but actually only making things worse (Deming, 1982).
“Common Causes”
Common cause situations are those where performance goes up and down over time and if analysed properly can be seen to occur over a relatively predictable pattern: if we change nothing, the performance level will most likely continue. The problems arise when someone thinks they see a real difference between points of data when in fact no such thing exists. This a type 1 error: we observe a change which is really only a natural effect of background ‘noise’ yet we choose to act on that ‘change’. For example someone in the team achieves a great result whilst others do not achieve the same result. Is the difference because of the person, or something else in the wider context? Perhaps, as is often the case, they just got lucky and happened to be the one that achieved the good result. Next week it might be someone else. The analogy is a fire alarm going off indicating a fire when in fact there is no fire. It is easy to fall into type 1 errors assuming highs and lows of performance which don’t exist. This is a ‘mistake of commission’ – doing something that should not have been done (Ackoff et al 2006).
“Special Causes”
Some special causes are obvious, for example a major increase or decrease in performance or a freak accident. However, sometimes hidden patterns of performance can indicate a real change which might easily go undetected if we consider each data point as a ‘one off’. This is a bit like a fire breaking out but the fire alarm not ringing. The fundamental problem is that these genuine changes are due to ‘Special Causes’ something real which is impinging on the system. The issue here is that the solution sits outside the system – don’t redesign what you have as it will not replicate the situation – that is just meddling and will make things worse. For example, cycles of deteriorating work output followed by improving work output by one person might indicate an underlying special cause which needs to be addressed (health for example), so meddling with the design of the work in itself would be counterproductive. Furthermore if the manager does not look at performance over time, these cycles might not be detected anyway – on average they might look like a reasonable level of output. Ackoff calls this a mistake of omission –not doing something that should have been done.
An example can been encountered in Human Wildlife Conflict. A ‘rogue’ animal may change its behaviour due to injury or illness and preferentially predate livestock for a period of time. If a decision is made to destroy the animal (or relocate it to a more remote area) should the same policy be applied to any animal which predates livestock? For the one-off animal a one-off intervention might succeed, but if it were to be repeated for every animal it would certainly be costly (relocation) and might make things worse (e.g. if destroying every animal). Clearly identifying whether the rogue animal is an ‘exception’ or a ‘common cause’ is important.
Of course to detect differences between special cause and common cause varuiations in performance requires new skills and disciplines of thinking. When you understand the organisation as a system, improving service starts with a leap of fact, not faith.
Reading:
Ackoff, R.L.; Addison, H. J. Bibb, S. (2006) Management f-Laws: How Organizations Really Work. Triarchy Press
Deming W.E. (1982) Out of the Crisis, MIT CAES, Cambridge MA.
Seddon, J. (2005) Freedom from Command and Control, Vanguard Press, Buckingham, UK.
A typical definition of management and leadership is:
“Managing: gets the most efficient utility from people & resources;
Leadership: gets people to do things they would not otherwise do.”
IS THIS REALLY TRUE, AND IF TRUE, DOES IT MAKE IT RIGHT?
In a nutshell those previous statements on management and leadership summarise conventional wisdom accrued since 1900, first through either traditional ‘scientific management’ methods or later ‘human relations’ approaches. The latter approach, pioneered by Elton Mayo, was apparently devised to counteract the rigidity and hierarchies of the former. Unfortunately both approaches have the same defective focus – ‘doing it to people’. They are both a reflection of a command-and -control mindset which many would percieve as ‘managerialism‘.
There are two basic reasons for hiring people – to do the work and to improve the work (a tag line which I attribute to the psychologist and author John Seddon). Managerialism involves neither activity – so why do we havemanagers and leaders? A leader’s job is to enable workers to do those two things and provide a context for understanding that activity.
Improvement comes from understanding the system and making meaningful improvements to ensure better outcomes. ‘Doing it to people’ does not achieve this, but simply adds new layers of new ‘work’ – appraisals, briefing meetings, writing reports, filling in forms. Worse still this work assumes that for people to be effective they need to have stuff ‘done’ to them – like an inoculation for inherent bad characteristics – perhaps laziness, lack of intelligence or (potential) insubordination. This is the darker side to a manager’s mindset.
Whilst most managers and leaders do not want to be working for the ‘dark side’ and genuinely want the better for their teams, they must understand that if they follow the scientific/human relations approach the consequences of their actions are: de-motivation, a loss of dignity, a diminished sense of purpose, and reduction of productivity in their staff. In other words the effect on their team is just as if they actually had a negative attitude towards those people. In other words their staff will not like it and work will be negatively affected.
In knowledge industries, additional contributions to the total cost of this disruption is hidden, for example losses of skilled workers, high staff turnover and recruitment and so on. In conservation projects these costs can be proportionally high and the impact on project continuity and sustainability huge.
The choice is clear: managers and leaders need to find a better way…
Reading:
Hanlon G. (2015) The Dark Side of Management: A secret history of management theory, Routledge
Roscoe, P. (2015) How the takers took over from the makers. Times Higher Education, 26 November, p48
Seddon, J. (2003). Freedom from Command and Control. Buckingham: Vanguard Press.
The best processes of learning, improvement and innovation start small and grow big. This is also true in many cases within the conservation sector.
