Tag Archives: genetics and ecology

On Evolution and Ecology and Climate Change

If ecology can team up with evolution to become a predictive science, we can all profit greatly since it will make us more like physics and the hard sciences. It is highly desirable to have a grand vision of accomplishing this, but there could be a few roadblocks on the way. A recent paper by Bay et al. (2018) illustrates some of the difficulties we face.

The yellow warbler (Setophaga petechia) has a broad breeding range across the United States and Canada, and could therefore be a good species to survey because it inhabits widely different climatic zones. Bay et al. (2018) identified genomic variation associated with climate across the breeding range of this migratory songbird, and concluded that populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected population abundance. This study by Bay et al. (2018) sampled 229 yellow warblers from 21 locations across North America, with an average of 10 birds per sample area (range n = 6 to 21). They examined 104,711 single-nucleotide polymorphisms. They correlated genetic structure to 19 climate variables and 3 vegetation indices, a measure of surface moisture, and average elevation. This is an important study claiming to support an important conclusion, and consequently it is also important to break it down into the three major assumptions on which it rests.

First, this study is a space for time analysis, a subject of much discussion already in plant ecology (e.g. Pickett 1989, Blois et al. 2013). It is an untested assumption that you can substitute space for time in analyzing for future evolutionary changes.

Second, the conclusions of the Bay et al. paper rest on an assumption that you have adequate data on the genetics involved in change and on the demography of the species. A clear understanding of the ecology of the species and what limits its distribution and abundance would seem to be prerequisites for understanding the mechanisms of how evolutionary changes might occur.

The third assumption is that, if there is a correlation between the genetic measures and the climate or vegetation indices, one can identify the precise ‘genomic vulnerability’ of the local population. Genomic variation was most closely related to precipitation variables at each site. The geographic area with one of the highest scores in genomic vulnerability was in the desert area of the intermountain west (USA). As far as I can determine from their Figure 1, there was only one sampling site in this whole area of the intermountain west. Finally Bay et al. (2018) compared the genomic vulnerability data to the population changes reported for each site. Population changes for each sampled site were obtained from the North American Breeding Bird Survey data from 1996 to 2012.

The genetic data and its analysis are more impressive, and since I am not a genetics expert I will simply give it a A grade for genetics. It is the ecology that worries me. I doubt that the North American Breeding Bird Survey is a very precise measure of population changes in any particular area. But following the Bay et al. paper, assume that it is a good measure of changing abundance for the yellow warbler. From the Bay et al. paper abstract we see this prediction:

“Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations.”

The prediction is illustrated in Figure 1 below from the Bay et al. paper.

Figure 1. From Bay et al. (2018) Figure 2C. (Red dot explained below).

Consider a single case, the Great Basin, area S09 of the Sauer et al. (2017) breeding bird surveys. From the map in Bay et al. (2018) Figure 2 we get the prediction of a very high genomic vulnerability (above 0.06, approximate red dot in Figure 1 above) for the Great Basin, and thus a strongly declining population trend. But if we go to the Sauer et al. (2017) database, we get this result for the Great Basin (Figure 2 here), a completely stable yellow warbler population for the last 45 years.

Figure 2. Data for the Great Basin populations of the Yellow Warbler from the North American Breeding Bird Survey, 1967 to 2015 (area S09). (From Sauer et al. 2017)

One clue to this discrepancy is shown in Figure 1 above where R2 = 0.10, which is to say the predictability of this genomic model is near zero.

So where does this leave us? We have what appears to be an A grade genetic analysis coupled with a D- grade ecological model in which explanations are not based on any mechanism of population dynamics, so that the model presented is useless for any predictions that can be tested in the next 10-20 years. I am far from convinced that this is a useful exercise. It would be a good paper for a graduate seminar discussion. Marvelous genetics, very poor ecology.

And as a footnote I note that mammalian ecologists have already taken a different but more insightful approach to this whole problem of climate-driven adaptation (Boutin and Lane 2014).

Bay, R.A., Harrigan, R.J., Underwood, V.L., Gibbs, H.L., Smith, T.B., and Ruegg, K. 2018. Genomic signals of selection predict climate-driven population declines in a migratory bird. Science 359(6371): 83-86. doi: 10.1126/science.aan4380.

Blois, J.L., Williams, J.W., Fitzpatrick, M.C., Jackson, S.T., and Ferrier, S. 2013. Space can substitute for time in predicting climate-change effects on biodiversity. Proceedings of the National Academy of Sciences 110(23): 9374-9379. doi: 10.1073/pnas.1220228110.

Boutin, S., and Lane, J.E. 2014. Climate change and mammals: evolutionary versus plastic responses. Evolutionary Applications 7(1): 29-41. doi: 10.1111/eva.12121.

Pickett, S.T.A. 1989. Space-for-Time substitution as an alternative to long-term studies. In Long-Term Studies in Ecology: Approaches and Alternatives. Edited by G.E. Likens. Springer New York, New York, NY. pp. 110-135.

Sauer, J.R., Niven, D.K., Hines, J.E., D. J. Ziolkowski, J., Pardieck, K.L., and Fallon, J.E. 2017. The North American Breeding Bird Survey, Results and Analysis 1966 – 2015. USGS Patuxent Wildlife Research Center, Laurel, MD. https://www.mbr-pwrc.usgs.gov/bbs/

On Sequencing the Entire Biosphere

There is an eternal war going on in science which rests on the simple question of “What should we fund?” If you are at a cocktail party and want to set up a storm of argument you should ask this question. There may be general agreement among many scientists that we should reduce funding on guns and wars and increase funding on alleviating poverty. But then the going gets tough. It is easier to restrict our discussion to science. There is a clear hierarchy in science funding favouring the physical sciences that can make money and the medical sciences that keep us alive until 150 years of age. But now let’s go down to biology.

The major rift in biology is between funding blue sky research and practical research. In the discussions about funding, protagonists often confound these two categories by saying that blue sky research will lead us to practical research and nirvana. We can accept salesmanship to a degree. The current bandwagon in Canada is to barcode all of life on earth, at a cost of perhaps $2 billion but probably much more. Or we can sequence everything we can get our hands on with the implicit promise that it will help us understand these organisms better or solve practical problems in conservation and management. But all of this is driven by what we can do technically, so it is machine driven, not necessarily thought driven. So if you want another heated discussion among ecologists, ask them how they would spend $2 billion for research in ecology.

We sequence because we can. Fifty years ago I heard a lecture by Richard Lewontin in which he asked what we would know if we had a telephone book with all the genetic sequences of all the organisms on earth. He concluded, as I remember, that we would know nothing unless we had a purely ‘genetic-determinism’ view of life. There is more to life than amino acid sequences perhaps.

No one I know thinks that current ecological changes are driven by genetics, but perhaps I do not know the right people. So for example, if we sequence the genomes of all the top predators on earth (Estes et al. 2011, Ripple et al. 2014), would we know anything about their importance in community and ecosystem dynamics? Probably not. But still we are told that if in New Zealand we sequence the common wasp genome we will find new ways to control this insect pest. Perhaps an equally important area would be funding to understand their biology in New Zealand, and the threats and threatening processes in an ecosystem context.

We are back to the starting question about the allocation of resources within biology. Perhaps we cycle endlessly in science funding in search of the Promised Land. In a recent paper Richards (2015) makes the argument that genome sequencing is the key to biology and thus the Promised Land:

“The unifying theme of biology is evolutionary conservation of the gene set and the resultant proteins that make up the biochemical and structural networks of cells and organisms throughout the tree of life.”

“The absence of these genome references is not just slowing research into specific questions; it is precluding a complete description of the molecular underpinnings of biology necessary for a true understanding of life on our planet.” (p. 414)

There seems little room in all this for ecological thought or ecological viewpoints. It is implicit to me that these arguments for genome sequencing have as a background assumption that ecological research is rather useless for achieving biological understanding or for solving any of the problems we currently face in conservation or management. Richards (2015) makes the point himself in saying:

“While the author is fond of ‘stamp collecting’, there are many good reasons to expand the reference sequences that underlie biological research (Table 2).”

The table he refers to in his paper has not a single item on ecological research, except that this approach will achieve “Acceleration of total biological research output”. It remains to be seen whether this view will achieve much more than stamp collecting and a massive confusion of correlation with causation. It requires a great leap of faith that this approach through genome sequencing can help to solve practical ecological problems.

Richards, S. (2015) It’s more than stamp collecting: how genome sequencing can unify biological research. Trends in Genetics, 31, 411-421.

Estes, J.A., et al. (2011) Trophic downgrading of Planet Earth. Science, 333, 301-306.

Ripple, W.J., et al. (2014) Status and ecological effects of the world’s largest carnivores. Science, 343, 1241484.