Tag Archives: biodiversity

Two Visions of Ecological Research

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Let us assume for the moment that the goal of scientific ecology is to understand the reasons for changes in the distribution and abundance of animals, plants, and microbes. If you do not think this is our main agenda, perhaps you should not read further.

The conventional, old paradigm to achieve this goal is to obtain a good description of the natural history of the organisms of interest in a population or community, define the food web they operate within, and then determine by observations or manipulations the parameters that limit its distribution and abundance. This can be difficult to achieve in rich food webs with many species, and in systems in which the species are not yet taxonomically described, and particularly in microbe communities. Consequently a prerequisite of this paradigm is to have good taxonomy and to be able to recognize species X versus species Y. A whole variety of techniques can be used for this taxonomy, including morphology (the traditional approach) and genetics. Using this approach ecologists over the past 90 years have made much progress in deriving some tentative explanations for the changes that occur in populations and communities. If there has been a problem with this approach, it is largely because of disagreements about what data are sufficient to test hypothesis X, and whether the results of manipulation Y are convincing. A great deal of the accumulated data obtained with this approach has been useful to fisheries management, wildlife management, pest control, and agricultural production.

The new metagenomics paradigm, to use one label, suggests that this old approach is not getting us anywhere fast enough for microbial communities, and we need to forget most of this nonsense and get into sequencing, particularly for microbial communities. New improvements in the speed of doing this work makes it feasible. The question I wish to address here is not the validity or the great improvements in genetic analysis, but rather whether or not this approach can replace the conventional old paradigm. I appreciate that if we grab a sample of mud, water, or the bugs in an insect trap and grind it all up, and run it through these amazing sequencing machines, we get a very great amount of data. We then might try to associate some of these kinds of data with particular ‘species’ and this may well work in groups for which the morphological species are well described. But what do we do about the undescribed sequences? We know that microbial diversity is much higher than what we can currently culture in the laboratory. We can make rules about what to call unknown unit A, unknown unit B, and so on. That is fine, but now what? We are in some sense back where Linnaeus was in 1753 in giving names to plants.

Now comes the difficult bit. Do we just take the metagenomics approach and tack it on to the conventional approach, using unknown A, unknown B, etc. instead of Pseudomonas flavescens or Bacillus licheniformis? We cannot get very far this way because the first thing we need to decide is does unknown A a primary producer or unknown B a decomposer of complex organic molecules? So perhaps this leads us to invent a whole new taxonomy to replace the old one. But perhaps we will go another way to say we will answer questions with the new system like is this pond ecosystem changing in response to global warming or nutrient additions? We can describe many system shifts in DNA-terminology but will we have any knowledge of what they mean or how management might change these trends? We could work all this out in the long term I presume. So I guess my confusion is largely exactly which set of hypotheses are you going to test with the new metagenomics paradigm? I can see a great deal of alpha-descriptive information being captured but I am not sure where to go from there. My challenge to the developers of the new paradigm is to list a set of problems in the Earth’s ecosystems for which this new paradigm could provide better answers more quickly than the old approach.

Microbial ecology is certainly much more difficult to carry out than traditional ecology on macroscopic animals and plants. As such it should be able to use new technology that can improve understanding of the structure and function of microbe communities. All new advances in technology are helpful for solving some ecological problems and should be so used. The suggestion that the conventional approach is out of date should certainly be entertained but in the last 70 years the development of air photos, of radio telemetry, of satellite imagery, of electrophoresis, of simplified chemical analyses, of automated weather stations, and the new possibilities of genetic analysis have been most valuable to solving ecological questions for many of our larger species. But in every case, at every step we should be more careful to ask exactly what questions the new technology can answer. Piling up terabytes of data is not science and could in fact hinder science. We do not wish to validate the Rutherford prediction that our ecological science is “stamp collecting”.

Why I am Bored with Biodiversity and Ecosystem Services

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Ecosystem services have become the flavour of the month and already it seems tired and bland.  “Biodiversity must be preserved for its ecosystem services” but making the tie between diversity and services has been elusive and will continue to be so. A body of literature has accumulated on the results of small-scale experiments in which plant diversity is manipulated and some service, let’s say productivity, is monitored. In some cases a relationship is found − more species more productivity; but not always. A rancher who wants to increase the productivity of her rangeland would be more inclined to plant to a monoculture of a highly productive grass. For example the introduced species, Crested Wheat Grass (Agropyron cristatum), was widely used in British Columbia in the early 20th century. Cheat grass (Bromus tectorum), another exotic species (if we are talking about North America) is expanding into rangeland and while it might increase the diversity, it reduces the productivity for forage.

Recently Mark Vellend (TREE 29(3): 138, March 2014) reviewed a book by Donald Maier, “What’s so Good about Biodiversity? A Call for Better Reasoning about Nature’s Value. “(Springer 2012). The take home message of this book is that the biodiversity−ecosystem services rationale for protecting biodiversity does not always hold and more species does not necessarily translate into more food or less disease.  It is time to get rid of platitudes and to confront our biases in a critical manner when it comes to biodiversity.

Further to this topic, in December 2013 the first meeting was held of the budding International Panel on Biodiversity and Ecosystem Services. It will focus on the following topics:

1) Task force on capacity building
2) Task force on indigenous and local knowledge systems
3) Task force on knowledge and data
4) Development of a guide to the production and integration of assessments from and across all levels
5) Assessment on pollination and pollinators associated with food production
6) Methodological assessment on scenario analysis and modeling of biodiversity and ecosystem services
7)  Methodological assessment on the conceptualization of values of biodiversity and nature’s benefits to people
8) Development of a catalogue of policy support tools and methodologies and providing guidance on how further development of such tools and methodologies could be promoted and catalyzed

Given the involvement of 115 countries it will be interesting to track the success of this panel.  Note that pollination and pollinators are identified as a specific ecosystem service. Critical experimental ecologists should be involved if this panel is to be productive in a meaningful way and, if not on the panel, they should track its progress and comment accordingly. Stay tuned for further updates.

On Biodiversity Science

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Biodiversity science features heavily in articles in Science and Nature and it is a good idea to look at the accumulated wisdom to date. We can begin with the Cardinale et al. (2012) paper in Nature (“Biodiversity Loss and Its Impact on Humanity”) which gives us six consensus statements:

Consensus statement one: There is now unequivocal evidence that biodiversity loss reduces the efficiency by which ecological communities capture biologically essential resources, produce biomass, decompose and recycle biologically essential nutrients.

Consensus statement two: There is mounting evidence that biodiversity increases the stability of ecosystem functions through time.

Consensus statement three: The impact of biodiversity on any single ecosystem process is nonlinear and saturating, such that change accelerates as biodiversity loss increases.

Consensus statement four: Diverse communities are more productive because they contain key species that have a large influence on productivity, and differences in functional traits among organisms increase total resource capture.

Consensus statement five: Loss of diversity across trophic levels has the potential to influence ecosystem functions even more strongly than diversity loss within trophic levels.

Consensus statement six: Functional traits of organisms have large impacts on the magnitude of ecosystem functions, which give rise to a wide range of plausible impacts of extinction on ecosystem function.

followed by four emerging trends:

Emerging trend one: The impacts of diversity loss on ecological processes might be sufficiently large to rival the impacts of many other global drivers of environmental change.

Emerging trend two: Diversity effects grow stronger with time, and may increase at larger spatial scales.

Emerging trend three: Maintaining multiple ecosystem processes at multiple places and time requires higher levels of biodiversity than does a single process at a single place and time.

Emerging trend four: The ecological consequences of biodiversity loss can be predicted from evolutionary history.

I encourage you to read this paper and consider how well it describes a blueprint of past and future research on biodiversity. Here I offer a few thoughts on why I think it consists of a set of worrisome generalizations.

First of all every biologist would like to think that biodiversity is important. But we should consider what the equivalent statement might be for chemistry – chemicals are important. Surely this is both true and of little use, since we can never define scientifically the word ‘important’. Biodiversity is so broadly defined as to be a rather poor noun to use in scientific statements unless it is strictly defined. But you can take any kind of biodiversity measure – species number (richness) for example, and you might find that species X is a terrible weed that is not desirable for farmers but is beautiful in your home garden or useful food for butterflies. Malaria-carrying mosquitoes are not particularly desirable members of the local biological community. But let us all agree that biodiversity is important because it is an ethical belief but not a scientific statement as it stands.

If we look at the consensus statements as scientific hypotheses (I note the word ‘hypothesis’ appears only once in this article), we can ask how you could test them and what the alternative hypotheses would be. For consensus 1 for example, what would be the result of finding a community that increased productivity if certain species were lost from the system? This finding would not be viewed as contrary to consensus one because it would be said that the increased productivity was not done efficiently. It is probably best to assume these statements are not hypotheses to be tested.

As we work our way through the consensus statements, we find they are filled with weasel words that are useful in eliminating contrary evidence. Thus for consensus statement 2 we can stop at biodiversity (many definitions) and then stability (perhaps 70 different metrics) and finally ecosystem functions (of which there are many) and time (weeks?, years?, centuries?). The consensus which sounds so solid is empirically rather empty as any guide to the world.

I am left with many questions. Could not all of these consensus statements have been written 30 years ago? All of them have contrary instances that could be given from the literature, if the terms were rigorously defined. But this many not matter. Let us concede that these generalizations may be right 90% of the time. The bottom line is that we should conserve biodiversity. But this is what everybody has been saying for decades so we are no farther ahead.

The singular problem that concerns me the most is that these kinds of consensus statements are of little use to the land manager or the wildlife manager or the politician who has to make applied decisions at the local level. If we wish to arrest the decline of a particular songbird, what is the utility of these kind of statements? I have concluded that these kinds of papers about biodiversity are a kind of pablum for conservation ecologists to show that Nature and Science really are concerned about conservation issues while at the same time they devote 97% of their issues to the technological fixes that will ‘solve’ all the problems conservation biologists continually point out. As such these kinds of papers are useful statements for political ecology.

The four emerging trends are themselves worthy of another blog. They are vague ideas expressing beliefs that cannot be considered scientific hypotheses without rigorous definitions, and in their present form are almost quasi-religious statements of belief. How they might ever be tested is unclear. I particularly enjoyed the fourth emerging trend since I think that one of the evolutionary laws is that evolutionary history is exactly that – history – not a predictive map of future changes. There is a certain irony of our time that some of the world’s most prestigious evolutionary biologists are anti-religion while biodiversity scientists are trying hard to set up a new religion of biodiversity beliefs.

Cardinale, B. J.et al. 2012. Biodiversity loss and its impact on humanity. Nature 486:59-67.