Monthly Archives: October 2019

The Central Predicament of Ecological Science

Ecology like all the hard sciences aims to find generalizations that are eternally true. Just as physicists assume that the universal law of gravitation will still be valid 10,000 years from now, so do ecologists assume that we can find laws or generalizations for populations and ecosystems that will be valid into the future. But the reality for ecological science is quite different. If the laws of ecology depend on the climate being stable, soil development being ongoing, evolution being optimized, and extinction being slow in human-generation time, we are in serious trouble.

Paleoecology is an important subdiscipline of ecology because, like human history, we need to understand the past. But the generalizations of paleoecology may be of little use to understand the future changes the Earth faces for one major reason – human disturbance of both climate and landscapes. Climates are changing due to rising greenhouse gases that have a long half-life. Land and water are being appropriated by a rising human population that is very slow to stabilize, so natural habitats are continually lost. There is little hope in the absence of an Apocalypse that these forces will alleviate during the next 200 years. Given these changes in the Anthropocene where does ecology sit and what can we do about it?

If climate is a major driver of ecological systems, as Andrewartha and Birch (1954) argued (to the scorn of the Northern Hemisphere ecologists of the time), the rules of the past will not necessarily apply to a future in which climate is changing. Plant succession, that slow and orderly process we now use to predict future communities, will change in speed and direction under the influence of climatic shifts and the introduction of new plant species, plant pests, and diseases that we have little control over. Technological optimists in agriculture and forestry assume that by genetic manipulations and proper artificial selection we can outwit climate change and solve pest problems, and we can only hope that they are successful. Understanding all these changes in slow-moving ecosystems depends on climate models that are accurate in projecting future climate changes. Success to date has been limited because of both questionable biology and poor statistical procedures in climate models (Frank 2019; Kumarathunge et al. 2019; Yates et al. 2018).

If prediction is the key to ecological understanding, as Houlahan et al. (2017) have cogently argued, we are in a quandary if the models that provide predictions wander with time to become less predictive. Yates et al. (2018) have provided an excellent review of the challenges of making good models for ecological prediction. As such their review is either encouraging – ‘here are the challenges in bold type’ – or terribly depressing – ‘where are the long-term, precise data for predictive model evaluation?’ My colleagues and I have spent 47 years trying to provide reliable data on one small part of the boreal forest ecosystem, and the models we have developed to predict changes in this ecosystem are probably still too imprecise to use for management. Additional years of observations produce some ecosystem states that have been predictable but other changes that we have never seen before over this time frame of nearly 50 years.

In contrast to the optimism of Yates et al. (2018), Houlahan et al. (2017) state that:

Ecology, with a few exceptions, has abandoned prediction and therefore the ability to demonstrate understanding. Here we address how this has inhibited progress in ecology and explore how a renewed focus on prediction would benefit ecologists. The lack of emphasis on prediction has resulted in a discipline that tests qualitative, imprecise hypotheses with little concern for whether the results are generalizable beyond where and when the data were collected.  (page 1)

I see this difference in views as a dilemma because despite much talk, there is little money or interest in the field work that would deliver reliable data for models in order to test their accuracy in predictions at small and large scales. An example this year is the failure of the expected large salmon runs to the British Columbia fishery, with model failure partly due to the lack of monitoring in the North Pacific (https://globalnews.ca/news/5802595/bc-salmon-stocks-plunge/; https://www.citynews1130.com/2019/09/09/worst-year-for-salmon/ , and in contrast with Alaska runs: https://www.adn.com/business-economy/2019/07/25/bristol-bay-sockeye-harvest-blowing-away-forecast-once-again/ ). Whatever the cause of the failure of B.C. salmon runs in 2019, the lack of precision in models of a large commercial fishery that has been studied for at least 65 yeas is not a vote of confidence in our current ecological modelling.

Andrewartha, H.G. and Birch, L.C. (1954) ‘The Distribution and Abundance of Animals.’ University of Chicago Press: Chicago. 782 pp.

Frank, P. (2019). Propagation of error and the reliability of global air temperature projections. Frontiers in Earth Science 7, 223. doi: 10.3389/feart.2019.00223.

Houlahan, J.E., McKinney, S.T., Anderson, T.M., and McGill, B.J. (2017). The priority of prediction in ecological understanding. Oikos 126, 1-7. doi: 10.1111/oik.03726.

Kumarathunge, D.P., Medlyn, B.E., Drake, J.E., Tjoelker, M.G., Aspinwall, M.J., et al. (2019). Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale. New Phytologist 222, 768-784. doi: 10.1111/nph.15668.

Yates, K.L., Bouchet, P.J., Caley, M.J., Mengersen, K., Randin, C.F., Parnell, S., Fielding, A.H., Bamford, A.J., et al. (2018). Outstanding challenges in the transferability of ecological models. Trends in Ecology & Evolution 33, 790-802. doi: 10.1016/j.tree.2018.08.001.

On Planting Trees to Solve the Climate Emergency

Rising CO2 levels could possibly be stopped by planting lots of trees. In recent months the media have rejoiced in a proposal (The Bonn Challenge) to plant trees on 350 million ha of degraded forest land around the globe by 2030 and thereby stop or greatly slow the global increase in CO2. The Bonn Challenge was first proposed in 2011 at a meeting in Germany and to date 43 countries have made pledges to plant trees to cover about half of the proposed needs, perhaps a total of 1 billion trees. Lewis et al. (2019) recently reported on progress to date in meeting this challenge. The question that a flurry of letters to Nature and other journals have raised is whether this goal is ecologically feasible.

There has always been a cohort of scientists seeking a technological fix to the climate emergency by capturing greenhouse gases or changing the atmosphere. To date all these technological fixes fail the economic test. Can biologists ride to the rescue for the CO2 problem and save the world? Clearly many people as well as politicians are technological optimists who hope that we can continue our lifestyle with little change in the coming decades. No one likes nay-sayers but it is important to hear what problems might arise to achieve a forestry solution to the climate emergency.

Lewis et al. (2019) mapped the land areas potentially available for restoration by planting trees. To achieve the Bonn Challenge most plantings would need to be in tropical and subtropical areas where tree growth is rapid. Bond et al. (2019) concentrated their analysis on Africa where about 1 million km2 have been proposed for restoration with trees. But they point out that much of this proposed area is grassland and savannah which support high value biodiversity. Tanzania we might presume would not be happy if the Serengeti was converted to a closed forest ecosystem. If we proceed with the Bonn Challenge and grasslands and savannahs become closed forests, several unintended consequences would occur. Trees utilize more water to grow and given a fixed rainfall in an area, less water would go into rivers, streams and lakes. Trees also absorb more solar radiation so that the climate in the restored areas would warm, while a main objective of the Bonn Challenge is to reverse global warming.

The list of ecological problems is long. Plantations of monocultures typically capture less CO2 than natural forests on the same land area. Forest fires release large amounts of CO2 from both natural forests and plantations, and rising temperatures are increasing forest losses to fire. Carbon capture estimates depend critically on turnaround times which depend on tree growth rates and the uses to which wood is put after a tree is harvested. Smith et al. (2015) concluded in an earlier analysis that afforestation could not achieve the goal of limiting global warming below 2ºC.

All these problems should not stop the reforestation of closed forest areas that were degraded in historical time, as Bond et al. (2019) have pointed out. But unfortunately, this news that we cannot reverse climatic warming by planting large numbers of trees continues the negativity that bedevils the science of ecology – you cannot achieve this goal given the ecological constraints of the Earth. Politicians and the public at large do not want to hear these messages and prefer the belief that technology will come up with a simple inexpensive solution. To shout that “this will not work” is not a way to become popular.

We appear not to have progressed from what David Schindler said 22 years ago:

“Humans, including ecologists, have a peculiar fascination with attempting to correct one ecological mistake with another, rather than removing the source of the problem.”
                  (Schindler 1997, pg.4).

Bond, W.J., et al. (2019). The Trouble with Trees: Afforestation Plans for Africa. Trends in Ecology & Evolution (in press). doi: 10.1016/j.tree.2019.08.003.

Lewis, S.L., et al. (2019). Regenerate natural forests to store carbon. Nature 568, 25-28 (4 April 2019). doi: 10.1038/d41586-019-01026-8.

Schindler D.W. (1997). Liming to restore acidified lakes and streams: a typical approach to restoring damaged ecosystems? Restoration Ecology 5, 1-6. doi: 10.1046/j.1526-100X.1997.09701.x.

Smith, P. et al. (2016). Biophysical and economic limits to negative CO2 emissions. Nature Climate Change 6, 42-50 (January 2016). doi: 10.1038/nclimate2870.