Good, better, best, never let it rest, ’til your good is better and your better best
Which is all very well, provided we all agree on what’s good, let alone better. Last week’s blog contained a poll that asked: If you wanted to compare changes in vegetation condition at a site, based on two surveys – the second undertaken many years after the first – should both surveys be done in similar climatic conditions? If the first survey was in a severe drought, should the second also be done in a drought? If you haven’t yet voted, please do, as the poll is open for another couple of weeks.
Based on the votes so far, if I was a tabloid journalist, I’d assert that, voters are deeply divided over this polarizing issue.
The two main alternatives – (1) surveys do and (2) surveys don’t need to be done in the same conditions – have run neck & neck all week, each receiving 37% of votes. Relatively few readers have voted for option (3), it doesn’t matter which approach is used (16%), or option (4), neither approach is suitable (11%). Importantly, readers have provided great justifications for all four options in the comments.
I find the diversity of votes fascinating. It suggests we use words like biodiversity, condition and even better in many, varied ways. Ecosystem condition must be biodiversity’s Tower of Babel.
Good, better, best, never let it rest
How can we tell what’s better, let alone what’s best?
A number of readers posted fantastic comments. Thanks to everyone who took the time to write. The votes and comments raise fascinating topics for future blogs – although I’m not sure that it’s possible to address all the complexities in breezy 1,000 word essays. For now, I thought it’d be useful to summarize the main themes from your comments. If I’ve misinterpreted – or worse still, ignored – something you wrote, my sincere apologies, please correct me in the comments section below.
Evidence, what evidence?
A number of readers commented on the need for good, strong evidence before we make conclusions about environmental changes. In particular, many noted that old air photos contain limited information. On the other hand, others noted that management decisions have to be based on whatever evidence we have to hand, which is often inadequate.
Unfortunately, I introduced the poll in an ambiguous way that promoted different responses. The quiz intentionally referred to ‘two surveys’ (not two air photos), but the blog began by describing two air photos, one old and one new. Consequently, some readers rightfully suggested that air photos don’t provide enough information to detect changes in vegetation structure, let alone condition. Additionally, the poor-quality 1945 photo that I used in the poll certainly justifies this view – I probably couldn’t have picked a worse example. Ambiguity aside, the question asked in the poll remains relevant, regardless of whether we use air photos, on-ground surveys, or any other data source to detect changes.
Has it really changed or is it just fluctuating?
A number of comments raised a great point. Two surveys may show us that the vegetation is different at each point in time. However, from two surveys alone, we can’t tell whether this change follows a persistent, directional trajectory. The system may fluctuate (or oscillate) between these two points repeatedly, over short or long time scales. If we did a third survey, the year after the second survey, we might find that the vegetation looks like it did in the first survey. The more surveys we do, the more confident we can be about the direction and persistence of changes.
If it did change, then why? What caused the changes?
This gets to the nub of the poll question. Ecosystems change continually. When we document changes, we invariably want to know what caused them. Climate, disturbances, competition, herbivory, humans, and time itself, cause ecosystems to change. One of the benefits of doing surveys under the same climatic conditions is that it reduces the number of factors that may have caused the changes. Some readers suggested that we don’t need to do both surveys under the same conditions to detect changes in ecological attributes (subject to the points above and below), but if we do, then it helps us to identify the processes that may have caused the changes.
It may be different, but is it any better?
Many of the points above are technical. But this one isn’t technical, it relates to our values, and we all have different values. What do we mean by better condition? How can we judge whether a change is good or bad? As one person commented,
… at the risk of getting all philosophical, ‘condition’ seems to necessitate conceptions of good and bad – but good for who? good for what? good for when?
A change that some of us deem acceptable, may be deemed absolutely horrendous by someone else. I suspect that this issue underpins much of the diversity in voting patterns.
What makes this really interesting is that, when we make judgements about ecosystem changes, our judgements aren’t based solely on the nature of the change itself. Our judgements depend, to some extent, on what we think caused the changes. If we think a change was caused by people, then (some of us) will value the change differently than if we think it was caused by ‘natural’ processes. No amount of technical refinement to the protocols that we use to measure changes can overcome this basic issue.
I’m not sure that we can describe changes to ecological attributes without invoking judgements about changes in ecological condition. Why go to the trouble of describing something if we don’t value it? From the outset, we record (or observe) particular attributes, and ignore others, because we make judgements on what things are, and aren’t, important. We’re the bouncers at the gates of biodiversity assessment.
What should we measure?
Biodiversity is a huge concept. It’s way bigger than we can measure. The United Nations defined biological diversity as:
the variability among living organisms from all sources, including, ‘inter alia’, terrestrial, marine, and other aquatic ecosystems, and the ecological complexes of which they are part: this includes diversity within species, between species and of ecosystems.
We can’t measure biodiversity. We can’t monitor changes in biodiversity. Whenever we try to assess changes in ecosystem ‘condition’ or ‘health’ we use simple, partial proxies; we measure a few things that (we hope) reflect the immense, unobserved, hidden diversity of living things and their interactions.
Often we record a small group of easily-observed species, such as mammals, birds or vascular plants. Sometimes we use functional approaches, by measuring attributes that are likely to support many unrecorded species. For example, species diversity is often high in structurally complex vegetation, and in large, connected habitats. Consequently, we can monitor changes in vegetation structure, or the spatial configuration and connectedness of remnants. Our challenge is that we make value judgements and management decisions based on these partial data sets.
Another reader succinctly noted,”The notion of ‘vegetation condition’ may need unpacking. Condition for what? may be a question.”
I guess this is the central issue really, isn’t it? No matter what we record, we’ll all make different value judgements. We all have different attitudes, values and beliefs, and access to different experiences and information. So it’s not surprising that we judge ecosystem quality differently. Given the diversity of votes from the readers of this blog, imagine how the rest of the world (the 99.99999% who don’t read ecology blogs) might assess ecosystem health.
I think I’ve covered – but certainly not resolved – the major comments that were posted last week. Feel free to peruse the comments in the last blog (many are hidden below the poll results) for more details than I can cover here. Thanks again to everyone who voted and commented. I hope I haven’t twisted your ideas too much. It’s amazing how many opinions can be summoned from such a ‘simple’ question.
Good, better, best, never let it rest,
’til we all agree what’s better, so we can save what’s best.