Mainstreamism and self-fulfilling prophecies

By Joern Fischer

It’s good to be policy-relevant, and it’s good to get published in prestigious journals. But I’m concerned that the collective desire to attain these goals is taming science to a distinctly unhelpful middle ground that everyone can agree on. It’s like in politics, where major parties end up so similar you can’t really tell the difference anymore – in an effort to appeal to the largest number of people, almost by definition, distinctive elements and innovative ideas are filtered out.

This is annoying when it happens in politics, but it’s unacceptable when it happens in science. Science ought to be about expanding our understanding of the universe, not channeling it into the centre of status quo worldviews. And yet, I find there is more and more evidence that this is precisely what is happening.

Two things today inspired me to write this slightly impassioned rant. First, one of our papers got rejected due to its less-than-mainstream methods. The argument was in fact not that our methods were bad, but rather that they were unusual and may be difficult to accept by the readership of the journal. Second, a colleague pointed me to a paper that says we can’t really change values because they change slowly, and so there’s no point in trying. In combination, I feel these events are symptomatic of a new kind of “anti-sustainability” sustainability science – implying that we need innovation, but preferably without actually changing the world or the way we look at it.

In modern science then, it seems you must not rock the boat. You must not work towards paradigm shifts, or try to look at problems too broadly. Instead, you should look for clever, incremental improvements within existing ways of thinking. In sustainability science, you must look at societal problems, but only advocate for minor changes – no matter how deep the root causes are of the problems you are looking at.

Sustainable intensification, REDD+ payments, and the right kind of messaging to an audience with unalterable values – this is now the dominant way advocated to achieve sustainability improvements.

Those who point out that radical changes are not possible successfully get their stuff published – but to me, they lack creativity (and frankly, guts) to do what needs to be done. With everybody heading for the front of the mainstream, there will be no real innovation, and no major change. Or put more bluntly: we’d have the same values as decades ago, including slavery, racial discrimination and women not taking part in politics.

Think again: Of course things can change, if we want them to, including big things, and including human values. And from a sustainability perspective all of this can happen in relevant, short periods of time, too.

Trying to work for deep changes may not always work in the short term. But the growing zeal to not even try to think boldly strikes me as much more certain to lock us into a self-fulfilling prophecy of ever greater un-sustainability.

Managing time and expectations

By Joern Fischer

Our jobs as researchers are pretty nice in many ways — we get to work on stuff we’re truly interested in, we might get to enjoy the occasional sense of achievement, and we might even feel that we’re doing something good in the world. This good side of academic life has been emphasised by some; I’ve heard senior academics complain that we should stop complaining because really, our academic lives are so privileged.

While that’s probably true in general terms, many academics are also suffering from a sense of “too much”. Or, just as commonly, their families are suffering, or their collaborators, or students, because they have to engage with somebody who is stressed and evidently over-committed.

I’d like to make one simple point here: that we ought to do a good (or even excellent) job 100% of the time in which we work; but that we should not put up with pressures, incentives or norms to work more than 100% of time. When I worked in Australia, there was a pretty simple system regarding performance agreements. Once every two years,  you sat down with your boss and discussed how you would allocate 100% of your time to teaching, research and service. Teaching involved classes but also supervision of research students; research was, well, research; and service included committees and things like that within the university, but also communication engagement or editorial boards beyond the university.

There are three key benefits of institutionalising such performance agreements. One, nobody is expected to work more than 100%. Two, if you add a percentage to something (e.g. an increase from 40 to 50%), it’s clear that something else has got to be reduced. And three, not everybody has to be equal — some people might benefit their departments through service roles, others through teaching, others primarily through research. In extreme cases, an individual might drop one of the three components altogether.

What I see in Germany is starkly different. We are incentivised to be in more and more projects; raise more and more funds; “supervise” more and more students; travel a lot; sit on committees without reward; and teach a lot of hours — and all of us should be the same, in terms of teaching load especially. What this does is it causes immediate declines in quality in all activities (nobody can be great at everything, in more than 100% of the time), and you get a bunch of over-committed, unfocused professors, left, right and centre.

Since this is systemic, there is no easy solution. But I think we should be aware of such patterns, and fight them whenever we can. As I said before: it’s not about being lazy or unproductive. It’s about recognising  that ideas are created by people who are happy in the workplace, who are reflective, and who have retained the capacity to focus to get the job done to the best of their abilities. If “excellence” is the goal (and many institutions claim that it is), you can’t keep adding stuff to people’s schedules and get the same quality out at the other end.

Values, conservation and sustainability

By Joern Fischer

In 1992, Shalom Schwartz published a seminal paper entitled “Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries”. The paper has been cited something like 12,000 times, and the findings have been refined since then. In short, it summarises different value orientations held by individuals. On reading this paper, I began to wonder what the implications of this are for conservation and sustainability.

schwartz_spatial1

Source: valuesandframes.org

I’ll start with a disclaimer and a summary of what Schwartz found. First the disclaimer: perhaps everything I write below has long been known by people working on conservation and sustainability, and I’m very late in catching up. If so, I’m happy to be further educated, e.g. by people explaining to me and other readers how this has been applied to conservation and sustainability in the comments below. But if I’m somewhat “typical”, then this is not at all widely known, understood, or reflected upon within the conservation and sustainability fields. And if that is the case, there might be some pretty important implications that require our attention.

Second – a summary of what Schwartz found. In the original paper from 1992, Schwartz developed theory, and then tested it on a large sample of individuals from a number of different countries. His theory was largely confirmed, and went something like this. Different people hold different values. Some values are compatible, whereas others are oppositional. Compatible values are, for example, if I value the attainment of wealth, and if I value the achievement of social recognition. Oppositional values might be valuing tradition versus seeking excitement in life.

These kinds of constructs – compatible and oppositional values – can be depicted in a kind of circular wheel, as shown in the Figure above. This wheel was generated by a multivariate analysis of many people responding to the same questions about their values, so this is an empirically grounded theory . Adjacent sectors in this wheel are compatible values, whereas opposite sectors in the wheel are oppositional.

So far so good – how is this relevant to conservation and sustainability? I think it is in a number of ways.

A lot of the values associated with conservation and sustainability cluster in the sector on “universalism” (top right). For example, here, we find “protecting the environment”, “social justice”, and even “unity with nature”. Opposite of that, we find the sector “power”, with values such as “wealth” and “social recognition”.

We can now ask ourselves where in this wheel individuals belonging to different cultures might sit. This is relevant for conservation and sustainability, because we might pitch our messages differently, according to people’s values (e.g. see this comprehensive report, or here for a simpler summary; and here for additional materials).

But I think perhaps there is something even more interesting going on. Here, I present three testable hypotheses, which would have implications for conservation and sustainability action.

Hypothesis 1: A substantial proportion of the population (probably differing between jurisdictions) actually holds values that are compatible with universalist values (i.e. sustainability and biodiversity conservation).

Hypothesis 2: Despite this, we are seeing patterns of behaviour at an aggregate (societal) level that emphasise values that are largely oppositional to sustainability, such as achievement and power. That is, we have created institutions that foster values that are not inherently shared by people. We thus have a mismatch between the value sets fostered by institutions and the value sets held by people.

Hypothesis 3: If this is correct, the “solution” to sustainability problems becomes one of “simply” re-aligining institutions to what people actually want. This may be a major task, but is a relatively smaller problem than if people themselves actually did not hold values compatible with sustainability. In other words, we may not need to “re-educate people”, but rather draw out what people actually want, and ensure that institutions are reformed in ways that reflect the want of “the people”.

Hopelessly optimistic? Actually, people are selfish and individualistic, and care about power and wealth and nothing else? Perhaps – convince me if you can. But at this stage I think it’s more likely that we are dealing with a mis-match between values fostered through institutions and values held by individuals. I speculate, in turn, that such a mis-match has probably arisen from power dynamics that go hand in hand with how we have organized societies (including economic principles); i.e. the whole thing is an institutional and power problem, not fundamentally one of values.

If I’m right, all of this points to us needing more conversations at a societal level about what it is that we truly value — and then working towards how to (re-)organise society accordingly. And then who knows, perhaps sustainability is within closer reach than we may have thought …

The eternal challenge: walking the talk

By Joern Fischer

Having recently come back from a short, long-distance trip halfway around the world in the name of sustainability science – and having blasted a vast amount of carbon into the air in the process – I couldn’t help to think, yet again, about the perpetual challenge of “walking the talk” in sustainability science. But how does one “walk the talk”? The following are some suggestions for how to think through this.

  1. If it’s work-related travel, carefully weigh the sustainability costs and sustainability benefits. Frankly, a lot of work-related travel is not needed. We have a culture of workshops and meetings, and a culture of attending lots of these even if they are far away. Travel is cheap, workshop papers (i.e. discussion blabla papers) sell well, and have become a business in their own right. Personally, I believe in (i) prioritizing fieldwork related air travel over workshop air travel, (ii) prioritizing close travel for workshops/conferences over far trips, and (iii) thinking through how much travel you are willing to do in a given year.
  2. With respect to work travel, question the difference between what is necessary versus expected versus something you simply feel like. It’s too easy to say “I was invited and so I went”. In a culture where we all travel around without a second thought on whether that is good or necessary, just travelling a lot because everyone else is doing it is a very poor argument. So, as a minimum, be honest with yourself about (i) what is necessary, (ii) what is expected of you, and by whom, and (iii) what is simply your personal preference. Things you classify as necessary, well, I guess they can’t be changed easily. For things you classify as expected you can think about whose expectations these are, and whether you need to meet these expectations. And regarding third, frankly, that might be a fine reason at times, but from a sustainability perspective you should be aware that a preference for personal gluttony is also what’s destroying the planet. So probably best to remain a bit critical with oneself on this last point!
  3. Is there a way to get there without flying? Air travel is fast, and cheap (because it does not account for externalities). But it’s not the only way to get around. For example, many trips within Europe are possible by train if you think about it a little bit in advance. Night trains exist to some places, too.
  4. Once you decide to fly somewhere, consider offsetting your carbon impact. Most likely, your workplace – even if it’s a sustainability department – won’t have an offsetting scheme (do any?? I’d be interested!). Still, you can consider offsetting your personal and work-related carbon emissions. People who fly a lot also tend to earn a lot, making this not as big a deal as it may sound. Obviously, in science, your ability to offset depends on your salary and/or career level.
  5. Beyond travel, differentiate between big-ticket items versus little things in your life. Little actions can be good because you can do many little things. But changing a few big things in meaningful ways may achieve even more in terms of sustainability. Big changes are, for example, to live somewhere where you can ride a bike to work, rather than drive every day. Or to cut down the amount of animal protein in your diet, or obtain your food more locally. Little things like turning off light bulbs are fine … But just leaving your car at home one day (when you normally drive) is like a lot, a lot of lightbulbs!
  6. Recognise that you’re part of a “system”, and work on personal change as well as systemic change. While some sustainability scientists do too little (in my, in this case, not-so-humble opinion) to walk the talk, others beat themselves up for not being perfect footprint-free creatures. I think it’s important we recognize that it’s both a personal and systemic issue. If you live in North America or Australia, it’s nearly impossible to have a lifestyle that is fully sustainable. Most likely, most things from the food you eat to the transportation systems you use, to the infrastructure you support through your taxes are unsustainable. That is why it’s worthwhile to think about what you can do, and do that – while at the same time working on systemic changes so that living more sustainably becomes mainstream. That is, the institutional and socio-cultural context we live in will ultimately need to change, but that won’t happen overnight.

Comments on how you think about “walking the talk” are, as always, most welcome!

The illusion of doing a good job

By Joern Fischer

A little while ago, I published a bit of an outburst about academia’s obsession with quantity. Some people have interpreted this to be in favour of a lower output academia. However, that’s not quite what I meant: I’m not at all against productivity. Rather, what does concern me is the frantic, incoherent production of “stuff” at the expense of theoretical coherence, social relations and reflection.

It is possible to be productive and reflective – to a point. What troubles me is that most of us academics are evidently bad at judging when we take on too much. Hardly anyone will admit to being addicted to “quantity” at the expense of quality. Yet, it’s quite clear when taking a look around that there are many instances in which academic life is less pleasant than it ought to be, because someone, somewhere took on too much (and is now a nuisance to everyone else).

Since, collectively, as academics, we are apparently not very skilled at judging when we’re doing a good job, I thought I’d put up some indicators that we might treat as warning signals. If these things are going well, it means we’re probably working within our zone of meaningful productivity; if they are going badly, it might be a sign that we’re compromising the quality of our work. So, we might ask ourselves:

  • Are products of your work routinely well received by your colleagues?
  • Are the people you work with generally happy with your contributions?
  • Are you able to attend meetings you planned or do you frequently cancel them?
  • Do you generally respond to all emails within a few days?
  • Do you provide timely, quality input on papers you are a co-author on?
  • If someone asked your students to confidentially report on the quality of your supervision, would they praise you or criticize you?
  • Do your papers show consistent messages, or an evolution of your thinking – or are they mixed messages bouncing back and forth, depending on the paper?
  • Do you stop to talk to the people around you, or just rush past them?
  • Do you find time to read and think about what you read? (Or do you just read the titles of papers, their abstracts, or tweets about them?)

How we do with respect to these questions might be something we ask ourselves, or we might ask colleagues to tell us if we’re not doing a good job on these things. To me, quality is about focus, about knowing what’s important, and about delivering what we commit to – it’s about being meaningfully productive, not just busy.

 

Self-perpetuating hierarchies and their effects on knowledge flows

By Joern Fischer

I recently had two interesting experiences, both involving colleagues from less wealthy countries. The first experience was hearing a stakeholder from an African country say that his country needed more of our knowledge and technologies, so it could move forward. The second experience was a researcher from Asia telling me that in her country, people didn’t develop theories, but rather relied on theories from the Global North. Those, in turn, were implemented, but not questioned or criticised.

It struck me that something interesting is going on here. Instead of taking pride in their systems knowledge, both of these individuals saw their country’s knowledge as somehow inferior to what is produced in wealthy countries. This may be true for some kinds of technologies — e.g. Germans build better cars than Tanzanians (sorry, guys, it was the first random African country that came to mind). But for many other kinds of things, the local knowledge is more likely to be just different, not inherently less valuable. It’s not a big secret that often, people from the Global North have gone to the Global South — and implemented “solutions” that ended up causing more harm than good.

What I find particularly interesting then, is that this pattern is being perpetuated (1) in two directions, and (2) beyond the initial observation that I highlighted above.

First, the duality of “knowledge provider” versus “knowledge recipient” is perceived by many individuals in the Global South, as I outlined above. But this doesn’t come out of nowhere, but rather, is being reinforced through science from the Global North routinely telling people what they ought to do — assuming that such science knows best. Science from the Global North might, for example, tell people where to intensify their land, how to irrigate, or which improved varieties to grow. If this suits local people may be considered, but often as an afterthought.

Second, a general attitude of dividing the world into “providers” versus “recipients” of knowledge is self-perpetuating beyond its origin. That is, the same academic from the Global South who accepts his role as “recipient” of better science coming from the North, is likely to also assume a role of “provider” of science to local people in this country. That is, a top-down extension model that is common in the Global South is in itself the same pattern of one-way knowledge transfer that can be observed between the Global North and the Global South. This gets a little bit ironic then when people from the Global North start to highlight that governance structures in the Global South (for example) do not take local people into account adequately!

So, what to do? Dualistic understandings of one-way knowledge flows need to be treated with great caution. Of course, sometimes one person primarily “provides” and the other primarily “receives” knowledge. But very often, mutual learning is possible and would arguably lead to better insights on both sides: Academics in the Global North can learn from those in the Global South. Scientists in the Global South can learn from smallholder farmers in their countries. Recognising that knowledge flows can go both ways breaks down traditional hierarchies that prevent innovative and holistic thinking.

I singled out this pattern with respect to the Global North and Global South, and with respect to academics versus on-ground stakeholders. That’s because this is the anecdote that made me think of it. But self-perpetuating hierarchies like this exist in many realms of life. To truly learn and generate insight, I argue that we will do best to break down such hierarchies much of the time.

Empires, credibility, and a happy workplace atmosphere

By Joern Fischer

Bigger is better in academic reward structures: more grants, more students, more papers, more impact factor. But is there a limit to how big research groups (or “labs”) ought to be? What are the pros and cons of big, medium, or large research groups in terms of producing quality science, scientific credibility, and a happy working environment?

I figured thinking through this could be interesting, but as you will see, I didn’t get very far! Let’s start with very small research groups. Small groups can produce very good science if the individual researchers are very good. This might be especially the case for subjects where it is not necessary to draw on many different kinds of expertise, or where individuals work largely on their own. Here, it’s really largely the quality of the individual researchers that matters. If they’re very good, the science produced will be very good – and nobody would have any doubts about its credibility. On the other hand, if the individuals are weak in some areas, there are few opportunities to buffer one another in such a situation (e.g. if there are three people, and none of the three is good at statistics, then the statistics ends up … well, just not very good!). And complex subject matters, which require multiple different perspectives probably can’t be dealt with very well in extremely small research groups.

Medium-sized groups then … the most obvious advantage here is individuals can buffer one another more effectively, and there are more opportunities for mutual learning and collaboration. There is also the chance of having the beginnings of a “critical mass” of people who collectively can push forward a common approach or idea. In medium-sized groups, communication within the group is still quite straightforward, and the potential for people to be happy (in a social sense) is quite high.

What about really big groups? Well, they are clearly the most prolific. A glance at google scholar suggests that several of the world’s leading conservation scientists now produce over 50 publications a year, for example. So, is this the way to go, something to be frowned upon – or just something that needs to be managed very carefully? To start with, I guess the benefit of having a critical mass cannot be denied in such big groups. They are basically “centres”, though often somewhat more coherent in subject area because they are run by a single senior academic. On the downside, various risks also increase in really large groups. There’s a risk that the quality of the individual researchers in the group can’t be consistently high – it’s more difficult to hire large numbers of truly excellent people all at the same time than to hire a small number of truly excellent people. And then there’s the risk that people will be impressed by, but at the same time cynical, about very large groups: can anyone really contribute meaningfully to more than 50 papers a year? (I’m not sure, but I am sure that many people would say “no”!) And finally, there’s also the risk that overall group cohesion is lower, partly because communication within a large group is much more difficult. And so, very large groups in reality often split into a number of smaller sub-groups.

In the end then, if such sub-groups are working well, there is no reason to believe that large groups should be inherently less pleasant to be part of than small ones. They might even be particularly nice because they have a critical mass of like-minded people. If their governance is organized sensibly, perhaps large groups are in fact the best research environments … ? Or perhaps it’s small groups for some purposes, and larger ones for other purposes?

As I’m approaching the end of this blog post, I have not reached a definitive conclusion on what to make of academic group sizes. Perhaps size is just not an interesting feature in its own right: perhaps it’s how the group is run that matters in terms of the quality of the science and the workplace atmosphere … I’d be interested in people’s thoughts! What do you think, and what are your experiences with small versus large research groups?

“Re-connecting people and nature”: wrong term, wrong goal?

By Joern Fischer

As part of our research on leverage points for sustainability transformation, we are investigating the potential to “re-connect” people and nature in order to advance sustainability. But does this framing just reinforce a false dualism between people and the environment?

In a recent paper, Karen Malone describes child-dog encounters in La Paz, Bolivia. Focusing on poor urban children, and dogs living in the streets, she challenges the simple notion of “re-connecting” people (here, children) and nature. First, street dogs de facto represent “nature”, but a very different kind of nature from the wild and romantic images Western scholars may hold when thinking about nature. Second, children talk about their relationships with dogs as friendships, rather than as subject-object relationships, which a dualistic human-nature view would suggest. Third, anthropocentrism and human exceptionalism – i.e. people being inherently more special than other living beings – are not supported by the narratives provided by the children.

So how problematic is the concept of re-connecting people and nature? How problematic is the term?

To me, the answer is twofold. On the one hand, we need a communication tool to reach those who do think of humans as separate from nature, or of humans as being somehow different (or more advanced) from other beings. It’s all very well to highlight the non-exceptionalism of humans in academic circles, but “post-humanism” is going to be one step too far for most people to be willing to go. In the meantime, however, we might still be able to get an important point across by talking about “re-connecting” with nature. Using an anthropocentric narrative thus can be a tool to be understood in a culture where more radical (post-humanistic) messages are unlikely to be heard. This intuitive appeal of anthropocentric framing is not new: it has, in fact, been a central tenet of the ecosystem services argument. As I highlighted quite a while ago on this blog, scholars like Gretchen Daily never intended to say that nature has no worth beyond that to humans – but they chose to highlight the values to humans because it’s these values that are likely to attract an audience. (Which worked, by the way.)

On the other hand then, just like with ecosystem services, some caution is warranted. It’s fine to use a simple metaphor in the first place, knowing the world is more complex – but metaphors have an annoying habit of taking on a life of their own. Ecosystem services are no longer being thought about critically by many users of the concept. And if we’re not careful, the nascent agenda of re-connecting people and nature may also be at risk of inadvertently reinforcing the human-nature divide, rather than closing it.

This suggests scholars like us ought to use the “re-connect” term carefully, and allow for at least a couple of sentences in any given paper that explain the value of the metaphor, while acknowledging that a metaphor is by necessity a simplification of reality.

We need conceptual models so we can communicate. And to communicate effectively, we need to meet our audiences on a level that they are receptive to. Interdependent origination of all phenomena may get closer to the ultimate truth of our existence – but for that truth to come within reach at a societal level, re-connecting people and nature could be a good first step, despite the dualism implicit to the term.

Trandisciplinarity in a messy world

By Joern Fischer

In pursuit of sustainability, many have argued for the need for “transdisciplinary” research. Such research, ideally, is meant to be co-defined, and carried out in close collaboration with stakeholders – who double-act as decision-makers and thus solution-implementers. This solution-orientation defines sustainability science. But in a messy world, does this work?

The more I have thought about this, the more critical I have become of the idea of transdisciplinarity as defined above. At the same time, I don’t believe we ought to throw out the baby with the bath water (such a horrible metaphor!), and I think there are many good things about transdisciplinarity that we ought to keep. So in this post, I want to highlight three problems with an overly rigid type of transdisciplinarity, and then give a short outlook of what I think is worth keeping.

Co-defining problems with stakeholders may mean scratching the surface. Stakeholders are often quite specific in their outlook. By definition, they are interested in a given problem from the perspective of how it affects their stake in it. As a result, many transdisciplinary projects appear to work on extremely tangible, but rather simple problems. Messy problems that cannot be resolved via a simple research process often aren’t even targeted because they are not the problems of choice, of either stakeholders or researchers.

There may be no interested stakeholders. The idea of transdisciplinarity often goes hand in hand with the idea of a “decision-maker”. What if there is not one decision maker, but instead, a complex governance system? Or what if the decision-makers are disinterested in what other stakeholders are interested in – or even work actively against it? Reducing oneself as a scientist to wanting to work with (decision-making) stakeholders means reducing oneself to situations where there are “benevolent dictators”. Where those situations exist, by all means, engaging with these good queens and kings and helping them make good decisions is great. But messy systems with a diversity of conflicting views are much more common. Complex problems, quite possibly, can’t be solved but only navigated (with thanks to Dave Abson for this point!).

Stakeholders may be uninformed about some of the most important problems. Related to the first limitation of only scratching the surface, stakeholders may simply not know about certain problems that scientists do know about. For example, scientists knew about climate change long before stakeholders starting being interested in climate change. Letting stakeholders define problems thus is empowering for them – but it can mean ignoring the fact that scientists do know certain things, very well, and possibly much better than many stakeholders. Especially for problems that are looming on the horizon, it’s entirely possible that you won’t find stakeholders to work with on these problems. Yet, those problems ought to be worked on.

So, with these three problems, what’s worth keeping about transdisciplinarity? I think deep down it’s its “vibe” (has anyone seen “The Castle”? Never mind …) that is worth keeping. Deep down, transdisciplinarity is about respecting non-research stakeholders, respecting their knowledge, engaging with them, and helping them do better through one’s research. It’s this moral basis of transdisciplinarity that I believe we can apply to just about all settings, because it’s grounded in something so deep that it makes sense irrespective of context. For processes of transdisciplinarity, this means they have to be flexible and tailored to a given situation. There’s no right way of doing transdisciplinary science, no right level of transdisciplinarity, and no inherently greater value in co-defining problems with stakeholders. Rather, if the motivation underpinning stakeholder engagement is right, the rest will probably follow.

Linear vs. non-linear ways of knowledge integration

By Joern Fischer

Just a few days ago, I spoke with a colleague about integration of research findings across scales of enquiry, and across disciplinary domains. We discussed this in the context of complex research projects that involve multiple components. It struck me there seemed to be two ways of knowledge integration that have different pros and cons.

The first is “linear” integration. You can picture this one as a flowchart, where one bit of knowledge flows to another, and where several boxes merge in one place. Such flowchart, or linear, integration is common in research projects. I see two main strengths for this. The first is intellectual rigour and transparency. Because you have mapped out an integration path from the beginning, you now collect the pieces of the puzzle, align them – and then you’re done. Anyone can follow this process because it’s transparent. The second advantage is that you can plan from the outset to have your data be in formats that fit together nicely. So, for example, your economic component can feed into the integration box, as can your ecological component – and if it’s planned well, you might find out something about the cost-effectiveness of alternative conservation methods. So, linear integration lends itself to integration via formal, quantitative models.

The second way of integration is “nonlinear”. This one may be pictured as a cloud of bits of knowledge about a system. Initially, you target the system of interest from a range of different perspectives. These could be disciplinary perspectives, or different scales, or a mixture of both. These perspectives may focus on the system in very different ways, including entirely different sets of methods. When it’s all said and done, all bits of knowledge thus generated can be visualized as points within a cloud. The system, in this analogy, is the whole cloud, and somehow, you never know the whole cloud. But if you have scattered your points nicely throughout it, when you step back and squint at your system, you start to see it nevertheless. This type of integration is non-linear, and difficult to plan. An advantage is that you might find things you could otherwise overlook, because you have no pre-conceived idea of how things might fit together. An obvious downside is that integration here is much more an art than a science (we’re squinting at a cloud, for crying out loud!).

Which is better? It probably depends on the purpose. My own research tends to favour the second approach, for better or worse.