Author Archives: Charles Krebs

Reducing Greenhouse Gases at the Local Scale

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This blog is devoted to the simple question of what we might do about climate change at a very small scale. As individuals we can do little directly about the big issues of fracking and oil extraction from tar sands and shale deposits. Of course we can and should vote about these large issues, but my question is what can we do at a local level to support the Paris Agreement?

This was all brought to my attention on a recent drive of 50 km from Haines Junction in the southern Yukon north to Kluane Lake. Along the side of the Alaska Highway on each side of the road for a perpendicular distance of perhaps 20 m the highways department had mowed down all the vegetation to the ground level along a stretch of about 25 km. Willows 1-2 m in height, small aspen, spruce and poplar trees up to 3 m in height were all mowed down and chopped into small pieces. This observation gave rise to two thoughts. First, highways departments have always done this kind of mowing so why worry about it? But second, why should we keep doing now what we always did in the past?

We have just signed the Paris Agreement to try to stop the increases of greenhouse gases in the atmosphere. This means we should be looking at everything we do to see if it is generating more greenhouse gases than necessary. Mowing down the edges of highways has two detrimental effects on our environment. First, diesel or petrol is used to run the machines that do the mowing, Second, we have now lost the only mechanism we currently have for taking CO2 out of the atmosphere, plant growth via photosynthesis. We mow down the plants, thus making compost that releases CO2 as it decays, and we lose the structure of the road edge that captures CO2 at no cost to us. But of course new plants will now start to colonize and re-grow along the road edge, capturing CO2, but the key point here is that in northern Canada it will take probably 20-30 years to have the vegetation recover to the point that it was before mowing. Thus on every score this mowing along the highway is a direct affront to the Paris Agreement.

The argument about road edges is always to protect vehicles from wildlife suddenly coming out of the forest on to the road and causing a collision. The frequency of this for the larger species would have to be measured, and the assumption that a mowed strip reduces collisions with wildlife would have to be quantified. In my observations a nicely mowed strip in northern Canada becomes green early in the spring and in fact then attracts large and small herbivores like moose, bison, and hares to the edges of the road. Thus mowing might actually increase the probability of collisions with wildlife. In Newfoundland Tanner and Leroux (2015) showed that moose browsed less in recently cut highway edges but this effect might be lost within a few years. The critical question if moose-vehicle collisions are to be reduced is to know exactly what actions produce fewer accidents (Jägerbrand and Antonson, 2016). Reducing speed limits has a strong effect on accident rates. No one has looked into the greenhouse gas issue regarding the cost and benefit of roadside clearing. Many authors (e.g. Meisingset et al. 2014) point out how little serious experimental work has been done on the wildlife collision issue, another opportunity for adaptive management.

The highways department would probably consider this all very silly to worry about. But it does raise the more general issue that many others have pointed out: should we somehow have a greenhouse gas indicator app that would tell us for our own houses, vehicles, and property what we are doing in our everyday actions to assist the reduction of greenhouse gases as mandated in the Paris Agreement. It cannot simply be business as usual.

Jägerbrand, A.K., and Antonson, H. 2016. Driving behaviour responses to a moose encounter, automatic speed camera, wildlife warning sign and radio message determined in a factorial simulator study. Accident Analysis & Prevention 86(1): 229-238. doi:10.1016/j.aap.2015.11.004.

Meisingset, E.L., Loe, L.E., Brekkum, Ø., and Mysterud, A. 2014. Targeting mitigation efforts: The role of speed limit and road edge clearance for deer–vehicle collisions. Journal of Wildlife Management 78(4): 679-688. doi:10.1002/jwmg.712.

Tanner, A.L., and Leroux, S.J. 2015. Effect of roadside vegetation cutting on moose browsing. PloS One 10(8): e0133155. doi:10.1371/journal.pone.0133155.

What do the Data Points Mean?

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In Statistics 101 we were told that each data point in a scatter plot should have a precise meaning. Hopefully all ecologists agree with this, and if so I proceed to ask two questions about the ecology literature:

  1. What fraction of scatter plots in ecology papers define what the dots on the plot mean? Are they individual measurements, are they means of several measurements? Are they predictions from a mathematical model?
  2. Given that we know what the dots are, are we shown confidence limits for the points, or do we assume they are absolutely precise with no possible error?

With these two simple questions in mind I did a short, non-random search of recent ecology journals. Perhaps if a graduate ecology class is reading this blog, they could do a much wider search so that we might even be able to tell some of the editors of our journals how they score on Statistics 101 Quiz # 1. I went through 3 issues of Ecology (2015, issues 4, 5, and 6), 3 issues of the Journal of Animal Ecology (2015, issues 4 to 6), and 3 issues of Ecology Letters (2016, issues 1, 2, and 3). I scored each figure in each paper. The first question above is harder to score, so I divided the answer into three groups: clearly defined in figure legend, not defined in figure legend but clear in the paper itself, and not clearly defined anywhere. I kept the second question above on a simpler scale by asking if there were or were not confidence limits or S.E. on the dots in the scatter diagram. I considered histogram bars as ‘data points’ equivalent to scatter plots and scored these with these same 2 questions. I scored figures with multiple plots in the same figure as just one data source for my survey. I ignored maps, simulation data, and papers with only models. I got these results:

    Data points Confidence Limits or S.E.
Journal Number of papers Clearly defined in figure legend Yes No
Ecology 80 179
(95%)		 98
(50%)		 96
(50%)
Journal of Animal Ecology 84 195
(98%)		 119
(60%)		 81
(40%)
Ecology Letters 33 64
(94%)		 29
(43%)		 39
(57%)

The good news is that virtually all the data points in figures that contained empirical data were clearly defined, so the first question was not problematic. The potentially bad news is that around half of the data figures did not contain any measure of statistical precision for the data points.

There could be many reasons why confidence limits could not be applied to data points on graphs in papers. In some cases it would clutter the plot too much. In other cases the data points are completely accurate and have no error although this might be unusual in ecological data. Whatever the reason, some mention of the reason should be given in the text or the figure legend.

There were many limitations to this brief survey. It is clear that some subdisciplines of ecology adhere to Statistics 101 recommendations more carefully than others, but I did not tally these subdisciplines. One could make a thesis out of this sort of tally. Often I could not decipher if the data point was for an experimental unit or for a sampling unit but I have not analyzed for this error here.

So what do we conclude from this non-random survey? The take home message for authors is to make sure that the data points or histograms in their published figures are clearly defined in the figure legend and include if possible some measure of probable error. The message for reviewers and journal editors is to check that data points presented in submitted papers are properly identified and labeled with some measure of precision.

On Critical Questions in Biodiversity and Conservation Ecology

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Biodiversity can be a vague concept with so many measurement variants to make one wonder what it is exactly, and how to incorporate ideas about biodiversity into scientific hypotheses. Even if we take the simplest concept of species richness as the operational measure, many questions arise about the importance of the rare species that make up most of the biodiversity but so little of the biomass. How can we proceed to a better understanding of this nebulous ecological concept that we continually put before the public as needing their attention?

Biodiversity conservation relies on community and ecosystem ecology for guidance on how to advance scientific understanding. A recent paper by Turkington and Harrower (2016) articulates this very clearly by laying out 7 general questions for analyzing community structure for conservation of biodiversity. As such these questions are a general model for community and ecosystem ecology approaches that are needed in this century. Thus it would pay to look at these 7 questions more closely and to read this new paper. Here is the list of 7 questions from the paper:

  1. How are natural communities structured?
  2. How does biodiversity determine the function of ecosystems?
  3. How does the loss of biodiversity alter the stability of ecosystems?
  4. How does the loss of biodiversity alter the integrity of ecosystems?
  5. Diversity and species composition
  6. How does the loss of species determine the ability of ecosystems to respond to disturbances?
  7. How does food web complexity and productivity influence the relative strength of trophic interactions and how do changes in trophic structure influence ecosystem function?

Turkington and Harrower (2016) note that each of these 7 questions can be asked in at least 5 different contexts in the biodiversity hotspots of China:

  1. How do the observed responses change across the 28 vegetation types in China?
  2. How do the observed responses change from the low productivity grasslands of the Qinghai Plateau to higher productivity grasslands in other parts of China?
  3. How do the observed responses change along a gradient in the intensity of human use or degradation?
  4. How long should an experiment be conducted given that the immediate results are seldom indicative of longer-term outcomes?
  5. How does the scale of the experiment influence treatment responses?

There are major problems in all of this as Turkington and Harrower (2016) and Bruelheide et al. (2014) have discussed. The first problem is to determine what the community is or what the bounds of an ecosystem are. This is a trivial issue according to community and ecosystem ecologists, and all one does is draw a circle around the particular area of interest for your study. But two points remain. Populations, communities, and ecosystems are open systems with no clear boundaries. In population ecology we can master this problem by analyses of movements and dispersal of individuals. On a short time scale plants in communities are fixed in position while their associated animals move on species-specific scales. Communities and ecosystems are not a unit but vary continuously in space and time, making their analysis difficult. The species present on 50 m2 are not the same as those on another plot 100 m or 1000 m away even if the vegetation types are labeled the same. So we replicate plots within what we define to be our community. If you are studying plant dynamics, you can experimentally place all plant species selected in defined plots in a pre-arranged configuration for your planting experiments, but you cannot do this with animals except in microcosms. All experiments are place specific, and if you consider climate change on a 100 year time scale, they are also time specific. We can hope that generality is strong and our conclusions will apply in 100 years but we do not know this now.

But we can do manipulative experiments, as these authors strongly recommend, and that brings a whole new set of problems, outlined for example in Bruelheide et al. (2014, Table 1, page 78) for a forestry experiment in southern China. Decisions about how many tree species to manipulate in what size of plots and what planting density to use are all potentially critical to the conclusions we reach. But it is the time frame of hypothesis testing that is the great unknown. All these studies must be long-term but whether this is 10 years or 50 years can only be found out in retrospect. Is it better to have, for example, forestry experiments around the world carried out with identical protocols, or to adopt a laissez faire approach with different designs since we have no idea yet of what design is best for answering these broad questions.

I suspect that this outline of the broad questions given in Turkington and Harrower (2016) is at least a 100 year agenda, and we need to be concerned how we can carry this forward in a world where funding of research questions has a 3 or 5 year time frame. The only possible way forward, until we win the Lottery, is for all researchers to carry out short term experiments on very specific hypotheses within this framework. So every graduate student thesis in experimental community and ecosystem ecology is important to achieving the goals outlined in these papers. Even if this 100 year time frame is optimistic and achievable, we can progress on a shorter time scale by a series of detailed experiments on small parts of the community or ecosystem at hand. I note that some of these broad questions listed above have been around for more than 50 years without being answered. If we redefine our objectives more precisely and do the kinds of experiments that these authors suggest we can move forward, not with the solution of grand ideas as much as with detailed experimental data on very precise questions about our chosen community. In this way we keep the long-range goal posts in view but concentrate on short-term manipulative experiments that are place and time specific.

This will not be easy. Birds are probably the best studied group of animals on Earth, and we now have many species that are changing in abundance dramatically over large spatial scales (e.g. http://www.stateofcanadasbirds.org/ ). I am sobered by asking avian ecologists why a particular species is declining or dramatically increasing. I never get a good answer, typically only a generally plausible idea, a hand waving explanation based on correlations that are not measured or well understood. Species recovery plans are often based on hunches rather than good data, with few of the key experiments of the type requested by Turkington and Harrower (2016). At the moment the world is changing rather faster than our understanding of these ecological interactions that tie species together in communities and ecosystems. We are walking when we need to be running, and even the Red Queen is not keeping up.

Bruelheide, H. et al. 2014. Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China. Methods in Ecology and Evolution, 5, 74-89. doi: 10.1111/2041-210X.12126

Turkington, R. & Harrower, W.L. 2016. An experimental approach to addressing ecological questions related to the conservation of plant biodiversity in China. Plant Diversity, 38, 1-10. Available at: http://journal.kib.ac.cn/EN/volumn/current.shtml

On Caribou and the Conservation Conundrum

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The central conundrum of conservation is the conflict between industrial development and the protection of biodiversity. And the classic example of this in Canada is the conservation of caribou. Caribou in the millions have ranged over almost all of Canada in the past. They are now retreating in much of the southern part of their range, have nearly gone extinct in the High Arctic, and are extinct on Haida Gwaii (Queen Charlotte Islands). The majority of populations with adequate data are dropping in numbers rapidly. The causes of their demise point to human habitat destruction from forestry, mining, oil and gas developments and roads (Festa-Bianchet et al. 2011). We march on with economic development, and caribou are in the way of progress.

The nexus of interactions underlying this crisis is reasonably well understood for boreal caribou and there is an extensive literature on the topic (Bergerud et al. 2007; Hervieux et al. 2013; Hervieux et al. 2014; Schaefer and Mahoney 2013; Wittmer et al. 2007). Caribou avoid human constructions like pipelines, mines, forestry operations, and roads. Forestry in particular opens up habitat that tends to favor deer and moose. Climate change makes winters less severe for deer. More prey makes more predators, and caribou are typically accidental, secondary prey from wolves that live largely off moose and deer. The habitats that humans open up with roads, seismic lines, and wellheads provide superhighways for wolves and other predators, so that predator access is greatly improved. Such access roads also allow hunters to access ungulates and potentially increase the harvest rate.

If predators are the key immediate factor reducing caribou populations, there seem to be two general solutions. Killing wolves is the most obvious management action, and much of wildlife management in North America has historically been based on the simple paradigm: “killing wolves is the answer, now what is the question?” But two problems arise. There are more predators than wolves (e.g. bears) and secondly killing wolves does not work very well (Hayes 2010). At best it seems to slow down the caribou decline at great expense, and it has to be continuous year after year because killing wolves increases the reproductive rate of those left behind and migration of wolves into the “control” area is rapid. So this management action becomes too expensive in the long run to work well and most people don’t want to see bears killed wholesale either. So the next option is to use fencing to protect caribou from contact with all predators. These fences could be on small areas into which pregnant female caribou are put in the spring to have their calves, and then released when the calves are a few months old and have a better chance of avoiding predators. Or the ultimate fence would be around hundreds of square kilometers to enclose a permanent caribou population with all the predators removed inside the fenced area. This would require continuous maintenance and is very costly. It turns caribou into a zoo animal, albeit on a large scale.

There is one other solution and that is to set aside very large areas of habitat that are not invaded by the forestry, mining, and oil industries, and to monitor the dynamics of caribou in these large reserves. Manitoba is apparently doing this, with reported success in stopping caribou declines.

Beyond these southern populations of caribou in the boreal forest zone, the problems of caribou population trends on the tundra are difficult to unravel, partly because of a lack of data arising from a shortage of funds (Gunn et al. 2011). Climate change is happening and the exact effects on tundra populations is unclear. Many barren-ground caribou herds show fluctuations in abundance with a period of about 50 years. Food supply exhaustion may be one factor in the fluctuations but harvesting is also involved. Local harvest data are often not recorded and with poor population data and poor harvest data we can rarely determine the trajectories of the herds or explain why they are changing in abundance. Peary caribou in the far north are suffering from climate change, rain events in winter that freezes their food supply of lichens under ice so they starve. No one knows how to alleviate the weather, and we only add to the problem with our greenhouse gas emissions. Peary caribou now survive in very low numbers but we cannot be sure that will continue.

All in all, we work hard to conserve large mammal ecosystems in tropical countries but seem far too unconcerned about our Canadian caribou heritage. To inform conservation actions, serious long-term population studies are sorely needed, including more frequent aerial census estimates for all the caribou herds, radio-collaring individuals for demographic data and movements, and complete harvesting data from all sources.

 

Bergerud, A.T., Dalton, W.J., Butler, H., Camps, L., and Ferguson, R. 2007. Woodland caribou persistence and extirpation in relic populations on Lake Superior. Rangifer 27(4): 57-78 (Special Issue No. 17). doi: http://dx.doi.org/10.7557/2.27.4.321

Festa-Bianchet, M., Ray, J.C., Boutin, S., Côté, S.D., and Gunn, A. 2011. Conservation of caribou (Rangifer tarandus) in Canada: an uncertain future. Canadian Journal of Zoology 89(5): 419-434. doi:10.1139/z11-025 .

Gunn, A., Russell, D., and Eamer, J. 2011. Northern caribou population trends in Canada. Canadian Biodiversity: Ecosystem Status and Trends 2010, Technical Thematic Report No. 10. Canadian Councils of Resource Ministers. Ottawa, ON. iv + 71 p. http://www.biodivcanada.ca/default.asp?lang=En&n=137E1147-1

Hayes, B. (2010) Wolves of the Yukon. Wolves of the Yukon Publishing, Smithers, B.C. ISBN: 978-1-4566-1047-0

Hervieux, D., Hebblewhite, M., DeCesare, N.J., Russell, M., Smith, K., Robertson, S., and Boutin, S. 2013. Widespread declines in woodland caribou (Rangifer tarandus caribou) continue in Alberta. Canadian Journal of Zoology 91(12): 872-882. doi:10.1139/cjz-2013-0123.

Hervieux, D., Hebblewhite, M., Stepnisky, D., Bacon, M., and Boutin, S. 2014. Managing wolves (Canis lupus) to recover threatened woodland caribou (Rangifer tarandus caribou) in Alberta. Canadian Journal of Zoology 92(12): 1029-1037. doi:10.1139/cjz-2014-0142 .

Schaefer, J.A., and Mahoney, S.P. 2013. Spatial dynamics of the rise and fall of caribou (Rangifer tarandus) in Newfoundland. Canadian Journal of Zoology 91(11): 767-774. doi:10.1139/cjz-2013-0132 .

Wittmer, H.U., McLennan, B.N., Serrouya, R., and Apps, C.D. 2007. Changes in landscape composition influence the decline of a threatened caribou population. Journal of Animal Ecology 76: 568-579. doi: 10.1111/j.1365-2656.2007.01220.x

On Gravity Waves and the 1%

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The news this week has been all about the discovery of gravity waves and the great triumphs of modern physics to understand the origin of the universe. There is rather less news on the critical ecological problems of the Earth – of agricultural sustainability, biodiversity collapse, pollution, climate change – not to mention the long recognized economic problems of poverty and inequality, globally and within our own countries. All of these issues converge to the questions of resource allocations by our governments that have failed to assess priorities on many fronts. Many see this but have little power to change the system that is continually moving to save and improve the fortunes of the 1% to the detriment of most people.

In scientific funding there has always been a large bias in favor of the physical sciences, as I have commented on previously, and the question is how this might be publicized to produce  a better world. I suggest a few rules for scientific funding decisions both by governments and by private investors.

Rule 1: For maximizing scientific utility for the biosphere including humans, we require a mix of basic and applied science in every field. Whether this mix should be 50:50, 30:70, or 70:30 should be an item for extended discussion with the implicit assumption that it could differ in different areas of science.

Rule 2: Each major area of science should articulate its most important issues that must be addressed in the short term and the long term (>50 years). For biodiversity, as an example, the most important short term problem is to minimize extinctions while the most important long term problem might be to maintain genetic variability in populations.

Rule 3: The next step is most critical and perhaps most controversial: What are the consequences for the Earth and its human population if the most important issue in any particular science is not solved or achieved? If the required experiments or observations can be delayed for 30 (or 50) years, what will it matter?

If we could begin to lay out this agenda for science, we could start a process of ranking the importance of each of the sciences for funding in the present and in the long term. At the present time this ranking process is partly historical and partly based on extreme promises of future scenarios or products that are of dubious validity. There is no need to assume that all will agree, and I am sure that several steps would have to be designated to involve not only young and older scientists but also members of the business community and the public at large.

If this agenda works, I doubt that we would spend quite so much money on nuclear physics and astronomy and we might spend more money on ocean science, carbon budgets, and sustainable agricultural research. This agenda would mean that powerful people could not push their point of view in science funding quite so freely without being asked for justification. And perhaps when budgets are tight for governments and businesses, the first people on the firing line for redundancy will not be environmental scientists trying their best to maintain the health of the Earth for future generations.

So I end with 2 simple questions: Could gravity waves have waited another 100 years for discovery? What is there that cannot wait?

(Finally, an apology. I failed to notice that on a number of recent blogs the LEAVE A REPLY option was not available to the reader. This was inadvertent and somehow got deleted with a new version of the software. I should have noticed it and it is now corrected on all blogs.)

On Conservation Dilemmas

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Conservation is a strange mix of science and politics. What exactly the fraction of the mix is I would not hazard a guess, but probably the science of conservation biology is a small part of the total. That is not an excuse for anyone not to go into conservation as a career but you need to realize what you are walking into.

Many people have written about this but the latest radio announcements about wolf killing in western Canada got me thinking again about the problem of killing one native species to possibly protect another native species. Wolves eat caribou, mountain caribou are endangered, wolves are not (at the moment) endangered, therefore a simple solution: shoot A to save B. But think about this a bit and first of all realize that this is certainly not a scientific decision. Science tests hypotheses but it does not decree policies of action. The scientific issue buried in this controversy is whether or not shooting wolves will save the mountain caribou. How far, as a conservation scientist, do you trace the causality of a problem like this? Wolves eat a lot of moose as well as caribou. Oil and gas companies make roads to their wells and gas fields, paving the way for easy wolf dispersal to catch more moose or caribou. Moose love successional landscapes, and forestry companies love to make moonscapes by logging, generating successional landscapes. Deer also love farmland and successional landscapes, and mountain lions increase when deer increase. Mountain lions also take the occasional jogger. Where do we stop the causal chain?

If causality stops at the farm gate, wolves eat caribou therefore shoot them, life is simple. But to an ecologist this is missing the elephant in the room, our human use of landscapes. We make landscapes better for some species and worse for others, but we typically refuse to bear any responsibility for these landscape changes. How many logging companies or oil companies have been prosecuted for making wolves more abundant? So we go back to the farm gate and argue that killing wolves will have no effect on dwindling caribou because there are other predators out there – bears for example – that also eat caribou. And an honoured law of conservation biology is that once you get to a low population for the most part you are doomed no matter what happens. You cannot in a limiting case save a caribou herd of n = 1. But let us be optimistic as ecologists and argue that killing wolves will save the caribou. We have to add “this year” to that statement because, as Bob Hayes (2010) so elegantly argued in his book, once you start killing wolves you can never stop if that is your management solution. Caribou are caught in a nexus of wolves, bears, moose, deer, and elk in parts of western North America, and there is as yet no clear way of analyzing this nexus in a predictive manner. Killing wolves is the answer, but what is the question?

Money for management is yet another matter that enters the picture. Dollars spent on helicopter gunships cannot be spent on habitat improvements for other less charismatic species. So one needs value judgements here also, and this is not a scientific question but a policy one.

I think these conservation dilemmas are a general problem, and no doubt much is written about them. Do we kill an introduced species to save a native one? Do we forget about an introduced pest because a threatened bird species feeds on the pest? Do we get rid of an introduced weed that is poisonous to cattle but provides nectar for bees? Or in the present case do we kill one native species to potentially save another native species? Few of these questions are scientific questions and few can ever be sorted out by getting more data. So this is the problem I am not sure how to face. We go into conservation ecology to do science, but in the end we become a policy advisor that can be easily dismissed for political, social, or budget reasons. There is no way around this as far as I can see. If you think wolves are a valuable part of biodiversity, agitate not to kill them. If you think caribou will be preserved by killing wolves, go for the guns. All the arguments about the role of top predators in ecosystems (Ordiz et al. 2013, Ripple et al. 2014) can fall on deaf ears if society has a different value system than conservation biologists have.

Hayes, B. (2010) Wolves of the Yukon. Wolves of the Yukon Publishing, Smithers, B.C.

Ordiz, A., Bischof, R. & Swenson, J.E. (2013) Saving large carnivores, but losing the apex predator? Biological Conservation, 168, 128-133. doi: 10.1016/j.biocon.2013.09.024

Ripple, W.J., Estes, J.A., Beschta, R.L., Wilmers, C.C., Ritchie, E.G., Hebblewhite, M., Berger, J., Elmhagen, B., Letnic, M., Nelson, M.P., Schmitz, O.J., Smith, D.W., Wallach, A.D. & Wirsing, A.J. (2014) Status and ecological effects of the world’s largest carnivores. Science, 343, 1241484. doi: 10.1126/science.1241484

 

On Philanthropic Investment in Conservation – Part 2

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Here is an optimistic thought for the day. After writing my previous blog on philanthropy and conservation, it occurred to me that a single scenario might focus the mind of ecologists and conservation biologists as we think about relevant research:

Suppose you are sitting in your office and someone comes in and tells you that they wish to donate one billion dollars to your research in ecology. What would you tell them you would like to do?

This is of course ridiculous but let us be optimistic and think it may happen. There are a lot of very rich people around the world and they will have to do something with all their money. Some of it will be wasted but some could do much good for the development of strong science. So let us pretend for the moment that this will happen sometime in the future.

We need to think clearly what this money entails. First, if we want to live off the interest and we expect 5% return on investment, we end up with $ 50 million to spend per year. What are we going to do with all this money? The two options would seem to be to buy land and maintain it for conservation, or to set up a foundation for conservation that would support graduate student and postdoctoral fellows. Let us check these options out with a broad brush.

The first option is based on the belief that habitat loss is the key process driving biodiversity decline so we should use part of the money for land purchase or marine rights to areas. But we note that land purchases are not very useful if the land is not managed and protected so that some group of people need to be in charge. So suppose we spend half immediately on land acquisition, and land costs are $100 per ha, we could purchase about 50,000 km2, an area approximately the size of Denmark, slightly smaller than Scotland, and about the size of West Virginia. Then we can employ about 250 people full time to do research or manage the protected landscape at an overall cost of $100 K per scientist including salary and operating research costs. This is an attractive option and the decision that would need to be made is what areas are most important to purchase for conservation in what part of the world.

The second option is to establish a permanent foundation for conservation that would be devoted to supporting graduates and postdoctoral fellows worldwide. I am not clear on the costs for a foundation to operate but let us assume $ 2 million a year for staff and operating costs. This would leave $ 48 million for operating costs, supporting 480 students or postdocs at $100,000 each per year or 320 students if you wished to give each an average $150,000 per year for research and salary. If these were spread out over the 196 countries on Earth, clearly there would be about 2 scientists per country. If we spread them out evenly over the 148 million km2 of land area over the whole Earth, we would require each student or scientist to be in charge of about 300,000 km2, an area about the size of Norway, or Poland or the Philippines. Clearly one would not operate in such a fashion, and would concentrate person-power in the areas of greatest need.

There is considerable literature discussing the issue of how philanthropy can augment conservation in the most effective manner, and a few papers are given here that further the discussion.

Where does this theoretical exercise leave us? Clearly there would be many other ways to utilize these hypothetical funds for conservation, but the point that shows clearly is that the funds needed to achieve conservation on a global scale are very large, and even a billion dollars disappears very quickly if we are attempting to achieve solid conservation outcomes. The costs of conservation are large and there is the need to recognize that government funding is critical, so that an additional billion dollars from a philanthropist will only add icing on the cake and not the whole cake.

Not that anyone I know would turn down a billion-dollar donation as too little.

Adams, W., and J. Hutton. 2007. People, parks and poverty: Political ecology and biodiversity conservation. Conservation and Society 5:147-183.

Diallo, R. 2015. Conservation philanthropy and the shadow of state power in Gorongosa National Park, Mozambique. Conservation and Society 13:119-128. doi: 10.4103/0972-4923.164188

Ferraro, P. J., and S. K. Pattanayak. 2006. Money for Nothing? A call for empirical evaluation of biodiversity conservation investments. PLoS Biology 4:e105.
doi: 10.1371/journal.pbio.0040105

Jones, C. 2012. Ecophilanthropy, neoliberal conservation, and the transformation of Chilean Patagonia’s Chacabuco Valley. Oceania 82:250-263.
doi: 10.1002/j.1834-4461.2012.tb00132.x

 

On Log-Log Regressions

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Log-log regressions are commonly used in ecological papers, and my attention to their limitations was twigged by a recent paper by Hatton et al. (2015) in Science. I want to look at just one example of a log-log regression from this paper as an illustration of what I think might be some pitfalls of this approach. The regression under discussion is Figure 1 in the Hatton paper, a plot of predator biomass (Y) on prey biomass (X) for a variety of African large mammal ecosystems. I emphasize that this is a critique of log-log regression problems, not a detailed critique of this paper.

Figure 1 shows the raw data reported in the Hatton et al. (2015) paper but plotted in arithmetic space. It is clear that the variance increases with the mean and the data are highly variable, as well as slightly curvilinear, so a transformation is clearly desirable for statistical analysis. Unfortunately we are given no error bars on each of the point estimates, so it is not possible to plot confidence limits for each estimate.

Figure 1A

We log both the axes and get Figure 2 which is identical to that plotted as Figure 1 in Hatton et al. (2015). Clearly the regression fit is better that that of Figure 1 and yet there is still considerable variation around the line of best fit.

Figure 2A

The variation around this log-log line is the main issue I wish to discuss here. Much depends on the reason for the regression line. Mac Nally (2000) made the point that regressions are often used for predictive purposes but sometimes used only as explanations. I assume here one wishes this to be a predictive regression.

So the next question is if the Figure 2 regression is predictive, how wide are the confidence limits? In this case we will adopt the usual 95% confidence predictions for a single data point. The result is shown in Figure 3, which did not appear in the Science article. The red lines define the 95% confidence belt.

Figure 3A

Now comes the main point of my concerns with log-log regressions. What do these error limits really mean when they are translated back to the original measurements that define the graph?

The table given below gives the prediction intervals for a hypothetical set of 8 prey abundances scattered along the span of prey densities reported.

Prey abundance (kg/km2)

Estimated predator abundance (kg/km2)

Predicted lower 95% confidence limit

Predicted upper 95% confidence limit

Width of lower confidence interval (%)

Width of upper confidence interval (%)

200

4.4

2.46

7.74

-44%

+76%

1000

14.1

8.16

24.6

-42%

+74%

1500

19.0

11.0

33.2

-42%

+70%

2000

23.4

13.2

41.0

-44%

+75%

4000

38.7

22.4

69.0

-42%

+78%

8000

64.0

35.4

113.6

-45%

+78%

10000

75.2

43.6

134.4

-42%

+79%

12000

85.8

49.0

147.6

-43%

+72%

The overall average confidence limits for this log-log regression are -43% to +75%, given that the SE of the predictions varies little across the range of values used in the regression. These are very broad confidence limits for any prediction from a regression line.

The bottom line is that log-log regressions can camouflage a great deal of variation, which may or may not be acceptable depending on the use of the regression. These plots always visually look much better than they are. You probably already knew this but I worry that it is a point that can be easily overlooked.

Lastly, a minor quibble with this regression. Some authors (e.g. Ricker 1983, Smith 2009) have discussed the issue of using the reduced major axis (or geometric mean regression) when the X variable is measured with error instead of the standard regression method. One could argue for this particular data set that the X variable is measured with error, so that I have used a reduced major axis regression in this discussion. The overall conclusions are not changed if standard regression methods are used.

Hatton, I.A., McCann, K.S., Fryxell, J.M., Davies, T.J., Smerlak, M., Sinclair, A.R.E. & Loreau, M. (2015) The predator-prey power law: Biomass scaling across terrestrial and aquatic biomes. Science 349 (6252). doi: 10.1126/science.aac6284

Mac Nally, R. (2000) Regression and model-building in conservation biology, biogeography and ecology: The distinction between – and reconciliation of – ‘predictive’ and ‘explanatory’ models. Biodiversity & Conservation, 9, 655-671. doi: 10.1023/A:1008985925162

Ricker, W.E. (1984) Computation and uses of central trend lines. Canadian Journal of Zoology 62 (10), 1897-1905.doi: 10.1139/z84-279

Smith, R.J. (2009) Use and misuse of the reduced major axis for line-fitting. American Journal of Physical Anthropology, 140, 476-486. doi: 10.1002/ajpa.21090

On Philanthropic Investment in Biodiversity Conservation

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In the holiday season there is much talk and recommendations about donations to worthy causes, and this raises an interesting conundrum in biodiversity conservation. The question is relatively simple to answer if you have little money, but any reading of the business pages of our newspapers or a walk around the shopping centers of our large cities makes you realize that there are a great many people with more than a little money. What should you do with your excess cash?

Some people (but not all) will want to ‘make a difference’ with their accumulated wealth, at least until medical science can overcome the universal belief that “you can’t take it with you”. Peter Singer (2015) has addressed this question of how to spend your money most effectively when you donate. It comes down in the first instance of your time frame. If you wish to make a difference in the short term of a few years, your choices may differ fundamentally from those taken to make a difference in the long term of 100-500 years. The bulk of philanthropic donations now are in the short-term camp. We have poor people living on the street in most of our cities, people with curable diseases in less developed countries but no medical aid, and victims of wars, earthquakes and tsunamis who must rebuild their lives. So we must start with what I think is the biggest decision regarding philanthropy – do we worry only about people, or do we worry about the biological world as well? Most donations are directly related to improving the human condition, locally or globally.

But there is hope because more and more people are realizing that we cannot separate people from biodiversity because of ecosystem services. Without well-functioning ecosystems on Earth, all the medical advances of our time are for naught. This is an important message to convey to potential donors.

Conservation philanthropy is a curious mix of short term and long term goals. Many endangered species need action now to survive. But ecologists typically look at both the shorter and the longer term goals of conservation. The simplest goal is to set aside land for protection. Without habitat all is lost. But this goal must be paired with long term funding to hire rangers to protect the area from poachers and to monitor the status of the species within the protected zone. Relying on the government to do this by itself is not adequate and never has been. But beyond this primary goal of land protection, the conservation movement fractionates. There are arguments that without effective human population stabilization biodiversity loss must continue. So does this mean that effective donations should be earmarked for agencies that empower women and offer reproductive services? But this points out that we must not fall into the trap of thinking we can do only one thing at a time. Pandas or population – why not “both and”? Climate change is a similar ‘elephant in the room’ problem.

What are the long-term goals of conservation biology that would benefit from philanthropic investment? Start with pest control. Biological control of pests is a long-term issue par excellence (Goldson et al. 2015, Myers et al. 2009, Wyckhuys et al. 2013). But biological control programs are underfunded by governments and obtain little private philanthropy. Weed control, insect pest control, vertebrate pest control all fit in the same problem basket – long term problem supported only by short term funding. Invasive pest eradication on islands is one area of pest control in which both governments and private funding have been joining forces (http://www.islandconservation.org/ ) with good results.

Two other areas of conservation biology that are classically underfunded are taxonomy and monitoring. In many taxonomic groups the majority of the species on Earth are not yet identified and described with a scientific name. The nearest analogy would be having a bank with tons of coins of different sizes and shapes, but only a few of which had any engraving on them. Taxonomy which is so vital to biology suffers because physical scientists consider it “stamp collecting” and unworthy of scientific funding. Monitoring of ecological communities faces the same problem. Monitoring ecological communities is similar to monitoring weather, yet we support meteorological stations around the world but provide little support for ecological monitoring. At present ecological monitoring is done ad hoc by dedicated people but with little systematic organization. Monitoring of changes in the arctic is being coordinated globally (http://www.amap.no/ ) and specific programs have been outlined for example for northern Canada (https://www.ec.gc.ca/faunescience-wildlifescience/, but the funding levels are low considering the size of the areas under consideration. Tropical ecosystem monitoring is even less well funded, yet that is where much of global biodiversity is located (c.f. for example, Cardoso et al. 2011, Burton 2012).

So what can you do about this? Talk up the necessity and the advantages of conservation biodiversity. Imagine what would happen to any of these biodiversity problems if a foundation the size of the Bill & Melinda Gates Foundation devoted a large amount of its donations to conservation. Environmental stewardship is the key to the Earth’s survival, and a combination of problem solving of current biodiversity problems combined with a strong research component on how species interact and ecosystems operate to sustain themselves would be a legacy for future generations and a flagship for the next 100 years.

Burton, A.C. (2012) Critical evaluation of a long-term, locally-based wildlife monitoring program in West Africa. Biodiversity and Conservation, 21, 3079-3094. doi: 10.1007/s10531-012-0355-6

Cardoso, P., Erwin, T.L., Borges, P.A.V. & New, T.R. (2011) The seven impediments in invertebrate conservation and how to overcome them. Biological Conservation, 144, 2647-2655. doi: 10.1016/j.biocon.2011.07.024

Glen, A.S., Atkinson, R., Campbell, K.J., Hagen, E., Holmes, N.D., Keitt, B.S., Parkes, J.P., Saunders, A., Sawyer, J. & Torres, H. (2013) Eradicating multiple invasive species on inhabited islands: the next big step in island restoration? Biological Invasions, 15, 2589-2603. doi: 10.1007/s10530-013-0495-y

Goldson, S.L., Bourdôt, G.W., Brockerhoff, E.G., Byrom, A.E., Clout, M.N., McGlone, M.S., Nelson, W.A., Popay, A.J., Suckling, D.M. & Templeton, M.D. (2015) New Zealand pest management: current and future challenges. Journal of the Royal Society of New Zealand, 45, 31-58. doi: 10.1080/03036758.2014.1000343

Myers, J.H., Jackson, C., Quinn, H., White, S.R. & Cory, J.S. (2009) Successful biological control of diffuse knapweed, Centaurea diffusa, in British Columbia, Canada. Biological Control, 50, 66-72. doi: 10.1016/j.biocontrol.2009.02.008

Singer, P. (2015) The Most Good You Can Do. Yale University Press, New Haven. ISBN: 978-0-300-18027-5

Wyckhuys, K.A.G., Lu, Y., Morales, H., Vazquez, L.L., Legaspi, J.C., Eliopoulos, P.A. & Hernandez, L.M. (2013) Current status and potential of conservation biological control for agriculture in the developing world. Biological Control, 65, 152-167. doi: 10.1016/j.biocontrol.2012.11.010 http://www.islandconservation.org/where-we-work/

 

On Improving Canada’s Scientific Footprint – Breakthroughs versus insights

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In Maclean’s Magazine on November 25, 2015 Professor Lee Smolin of the Perimeter Institute for Theoretical Physics, an adjunct professor of physics at the University of Waterloo, and a member of the Royal Society of Canada, wrote an article “Ten Steps to Make Canada a Leader in Science” (http://www.macleans.ca/politics/ottawa/ten-steps-to-make-canada-a-leader-in-science/ ). Some of the general points in this article are very good but some seem to support the view of science as big business and that leaves ecology and environmental science in the dust. We comment here on a few points of disagreement with Professor Smolin. The quotations are from the Maclean’s article.

  1. Choose carefully.

“Mainly invest in areas of pure science where there is a path to world leadership. This year’s Nobel prize shows that when we do this, we succeed big.” We suggest that the Nobel Prizes are possibly the worst example of scientific achievement that is currently available because of their disregard for the environment. This recommendation is at complete variance to how environmental sciences advance.

  1. Aim for breakthroughs.

“No “me-too” or catch-up science. Don’t hire the student of famous Prof. X at an elite American university just because of the proximity to greatness. Find our own path to great science by recruiting scientists who are forging their own paths to breakthroughs.” But the essence of science has always been replication. Long-term monitoring is a critical part of good ecology, as Henson (2014) points out for oceanographic research. But indeed we agree to the need to recruit excellent young scientists in all areas.

  1. Embrace risk.

“Learn from business that it takes high risk to get high payoff. Don’t waste money doing low-risk, low-payoff science. Treat science like venture capital.” That advice would remove most of the ecologists who obtain NSERC funding. It is one more economic view of science. Besides, most successful businesses are based on hard work, sound financial practices, and insights into the needs of their customers.

  1. Recruit and invest in young leaders-to-be.

“Be savvy and proactive about choosing them…. Resist supporting legacies and entitlements. Don’t waste money on people whose best work is behind them.” We agree. Spending money to fund a limited number of middle aged, white males in the Canadian Excellence in Research Chairs was the antithesis of this recommendation. See the “Folly of Big Science” by Vinay Prasad (2015). Predicting in advance who will be leaders will surely depend on diverse insights and is best evaluated by giving opportunities for success to many from which leaders will arise.

  1. Recruit internationally.

“Use graduate fellowships and postdoctoral positions as recruitment tools to bring the most ambitious and best-educated young scientists to Canada to begin their research here, and then target the most promising of these by creating mechanisms to ensure that their best opportunities to build their careers going forward are here.” This seems attractive but means Canadian scientists have little hope of obtaining jobs here, since we are < 0.1% of the world’s scientists. A better idea – how about Canada producing the “best-educated” young scientists?

  1. Resist incrementalism.

“If you spread new money around widely, little new science gets done. Instead, double-down on strategic fields of research where the progress is clear and Canada can have an impact.“ Fortin and Currie (2013) show that spreading the money around is exactly the way to go since less gets wasted and no one can predict where the “breakthroughs” will happen.  This point also rests on one’s view of the world of the future and what “breakthroughs” will contribute to the sustainability of the earth.

  1. Empower ambitious, risk-taking young scientists.

“Give them independence and the resources they need to develop their own ideas and directions. Postdocs are young leaders with their own ideas and research programs”. This is an excellent recommendation, but it does conflict with the recommendation of many universities around the world of bringing in old scientists to establish institutes and giving incentives for established senior scientists.

  1. Embrace diversity.

“Target women and visible minorities. Let us build a Canadian scientific community that looks like Canada.” All agreed on this one.

  1. Speak the truth.

“Allow no proxies for success, no partial credit for “progress” that leaves unsolved problems unsolved. Don’t count publications or citations, count discoveries that have increased our knowledge about nature. We do research because we don’t know the answer; don’t force us to write grant proposals in which we have to pretend we do.” This confounds the scientists’ code of ethics with the requirements of bureaucracies like NSERC for accounting for the taxpayers’ dollars. Surely publications record the increased knowledge about nature recommended by Professor Smolin.

  1. Consider the way funding agencies do business.

“We scientists know that panels can discourage risk-taking, encourage me-too and catch-up science, and reinforce longstanding entitlements and legacies. Such a system may incentivize low-risk, incremental work and limit the kind of out-of-the-box ideas that….leads to real breakthroughs. So create ambitious programs, empower the program officers to pick out and incubate the brightest and most ambitious risk-takers, and reward them when the scientists they invest in make real discoveries.” What is the evidence that program officers in NSERC or NSF have the vision to pick winners? This is difficult advice for ecologists who are asked for opinions on support for research projects in fields that require long-term studies to produce increases in ecological understanding or better management of biodiversity. It does seem like a recipe for scientific charlatans.

The bottom line: We think that the good ideas in this article are overwhelmed by poor suggestions with regards to ecological research. We come from an ecological world faced with three critical problems that will determine the fate of the Earth – food security, biodiversity loss, and overpopulation. While we all like ‘breakthroughs’ that give us an IPhone 6S or an electric car, few of the discoveries that have increased our knowledge about nature would be considered a breakthrough. So do we say goodbye to taxonomic research, biodiversity monitoring, investigating climate change impacts on Canadian ecosystems, or investing in biological control of pests? Perhaps we can add the provocative word “breakthrough” to our ecological papers and media reports more frequently but our real goal is to acquire greater insights into achieving a sustainable world.

As a footnote to this discussion, Dev (2015) raises the issue of the unsolved major problems in biology. None of them involve environmental or ecological issues.

Dev, S.B. (2015) Unsolved problems in biology—The state of current thinking. Progress in Biophysics and Molecular Biology, 117, 232-239.

Fortin, J.-M. & Currie, D.J. (2013) Big science vs. little science: How scientific impact scales with funding. PLoS ONE, 8, e65263.

Prasad, V. (2015) The folly of big science. New York Times. October 2, 2015 (http://www.nytimes.com/2015/10/03/opinion/the-folly-of-big-science-awards.html?_r=0 )

Henson, S.A. (2014) Slow science: the value of long ocean biogeochemistry records. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 372 (2025). doi: 10.1098/rsta.2013.0334.