Category Archives: Political Ecology

Do We Need Commissioners for the Environment?

Canada has just gone through an election, the USA will next year, and elections are a recurring news item everywhere. In our Canadian election we were spared any news on the state of the environment, and the dominant theme of the election was jobs, the economy, oil, gas, and a bit on climate change. The simplest theme was climate change, and yes, we are all in favour of stopping it so long as we do not need to do anything about it that would cost money or change our lifestyles. Meanwhile the fires of California and Australia and elsewhere carry on, generating another news cycle of crazy comments about the state of the environment.

Is there a better way? How can we get governments of the world to consider that the environment is worthy of some discussion? There is, and New Zealand has led the way in one direction. New Zealand has a Parliamentary Commissioner for the Environment, an independent Officer of Parliament, whose job it is to provide Members of Parliament with independent advice on matters that may have impacts on the environment. The Office is independent of the government of the day and the Prime Minister, and consequently can “tell it like it is”. A few quotations for the 2019 report give the flavour of this recent New Zealand report:

“If there is one thing that stands out from [our] reports, it is the extent of what we don’t know about what’s going on with our environment.  

“…the blind spots in our environmental reporting system don’t represent conscious choices to collect data or undertake research in some fields rather than others. Rather, they represent the unplanned consequences of a myriad choices over decades. Ours has been a passive system that has harvested whatever data is there and done the best it can to navigate what’s missing.

“In some ways, the most important recommendations in this report are those that relate to the prioritising and gathering of data in a consistent way. Despite attempts over more than two decades, no agreement has ever been reached on a set of core environmental indicators. This has to happen. Consistent and authoritative time series coupled with improved spatial coverage are essential if we are to detect trends. Only then will we be able to judge confidently whether we are making progress or going backwards – and get a handle on whether costly interventions are having an effect.

https://www.pce.parliament.nz/publications/focusing-aotearoa-new-zealand-s-environmental-reporting-system

This report is full of ecological wisdom and would be a useful starting point for many countries. Canada has (to my knowledge) no Environmental Commissioner and although various provinces and cities provide State of the Environment Reports, they are largely based on inadequate data. In some cases, like commercial fisheries, Parliaments or Congress have mandated annual reports, provided the secure funding, and retained independence of the relevant director and staff. In many cases there is far too much bickering between jurisdictions, use of inadequate methods of data collecting, long time periods between sampling, and no indication that the national interest has been taken into account.

Most Western countries have National Academies or Royal Societies which provide some scientific advice, sometimes requested, sometimes not. But these scientific publications are typically on very specific topics like smoking and lung cancer, vaccine protection, or automobile safety requirements. We can see this problem most clearly in the current climate emergency. The Intergovernmental Panel on Climate Change (IPCC) of the United Nations provides excellent reports on the climate emergency but no government is required to listen to their recommendations or to implement them. So, we have local problems, regional problems and global problems, and we need the political structures to address environmental problems at all these levels. New Zealand has provided a way forward, and here is another quote from the 2019 report that ecologists should echo:

Given that many of the environmental problems we face have been decades in the making and that for nearly 30 years we have [made] specific reference to cumulative effects that arise over time…it is astonishing that we have so little data on trends over time.

….it takes time to assemble time series. If we start collecting data today, it may be a decade or more before we can confidently judge whether the issue being monitored is getting better or worse. Every year that we delay the collection of data in an area identified as a significant gap, we commit New Zealand to flying blind in that area. …..A lack of time series in respect of some environmental pressure points could be costing us dearly in terms of poorly designed policies or irreversible damage.

One example may be enough. Caribou herds in southern Canada are threatened with extinction (Hebblewhite 2017, DeMars et al. 2019). Here is one example of counts on one caribou herd in southern Canada:

2009 = 2093 caribou
2012 = 1003
2019 = 185

It would be difficult to manage the conservation of any species of animal or plant that has such limited monitoring data. We can and must do better. We can start by dragging state of the environment reports out of the control of political parties by demanding to have in every country Commissioners of the Environment that are fully funded but independent of political influence. As long as the vision of elected governments is limited to 3 years, environmental decay will continue, out of sight, out of mind.

There is of course no reason that elected governments need follow the advice of any independent commission, so this recommendation is not a panacea for environmental issues. If citizens have independent information however, they can choose to use it and demand action.

DeMars, C.A.et al. (2019). Moose, caribou, and fire: have we got it right yet? Canadian Journal of Zoology 97, 866-879. doi: 10.1139/cjz-2018-0319.

Hebblewhite, M. (2017). Billion dollar boreal woodland caribou and the biodiversity impacts of the global oil and gas industry. Biological Conservation 206, 102-111. doi: 10.1016/j.biocon.2016.12.014.

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.

Big Science – Poor Data?

The big global problems of our time are climate change, human population growth, and migration. From these emerge all the others that worry us from inequality leading to poverty, regional wars, emerging diseases, and biodiversity loss. As ecologists we typically worry about climate change and biodiversity loss. We can do little directly about climate change except to change our life style and replace our do-nothing-politicians. We can have some effect on biodiversity conservation, a subject of later discussions. But the elephant in the room is always climate change, and Bill McKibben (2019) has presented us with a synopsis of a positive evaluation from the viewpoint of fossil fuels and is currently bringing out a book on these issues (McKibben 2019a).

There is much discussion of these articles in reviews such as Diamond (2019) and in the social media. The negative concerns for the future have in recent years been getting more press than the positive possibilities and these negative views may cause the public to give up and say all efforts are hopeless. But these three references from McKibben and Diamond push the possibility of a positive outcome, premised partly on the growing concern of humans to the effects of climate change and the emerging technologies in energy capture that do not depend on oil and gas. I do not wish to question these statements but rather to raise the question of where ecological scientists should fit into this picture.

If natural capital is in decline and some to many species are at risk of extinction, what should be the reaction of a young ecologist just starting their ecological career? I can see two extreme responses to the current situation. One I will call the Carry-on-Regardless approach, and the other the Mad Panic approach. The Carry-on Regardless approach believes that we as one or a few scientists have little ability to change the global paradigm of environmental destruction. Certainly, we will use our own efforts to educate and give good environmental example to all we encounter. But as a scientist the most important achievement one can make is to do good ecological science, to understand in some small way how populations and communities of organisms interact and sustain themselves at the present time. In this way we can hopefully solve some immediate practical problems but more importantly collect some critical data for the next generations of ecologists to use in understanding the changes that will go on during the next several centuries. In a simple manner, future ecologists will be able to say, ‘so this is how system X was working in 2020”. We have no way to know now how much our hard-earned knowledge will be useful to our great-grandchildren, but we press on in the hope that it will be of some help in understanding the trace of the human footprint down the ages.

The Mad Panic approach at the other extreme argues that you should stop all the research that you are doing and become an advocate to try to convince the world to change course and prevent disaster. There is no time to do research, we ought to be out there shouting from the rooftops. If you wish to work at the research end of this school of thought you should perhaps be looking for an ecological disaster (e.g. plastics in the ocean) that you can investigate to beat politicians over the head about how we must change now to prevent further disaster. There is certainly a need for this sort of action.

The problem is how to advise ecologists starting their careers. There is no simple answer, and some are better at the first approach and others at the second. The key point is that we need both, and my concern (being a Carry-on phenotype) is that we need to have clear and precise data of how the planet is changing as a prerequisite for the second approach. We do not have this now except for a few species in a few locations. We have very little long-term data on biodiversity, and we only kid ourselves if we decide that a 3-year study can be classified as a long-term study, or that a list of species in a given area tells us something about ecosystem function. Consider how long it has taken to show clear trends in climate data, or in a more news-worthy area how little economic understanding has emerged from all the detailed minute-by-minute data on the stock market over the last 70 years.

So, we end up with big questions and poor data, and somehow hope that we can model the future changes in the world’s ecosystems to give the public guidance. To achieve this goal, we need more Carry-on Regardless ecologists doing good work and fewer, less strident Mad Panic environmentalists. Environmental warning bells are certainly going off, and we should listen to them and try to gather the data necessary to understand what is happening and how good management might counter negative environmental trends. It is good to be optimistic, but we must couple our optimism with strong ecological studies to understand how communities and ecosystems function. And we are a long way from having enough of these basic studies to be confident of future projections to guide the next generations.

Diamond, Jared. 2019. Striking a balance between fear and hope on climate change. New York Times, 15 April 2019.

McKibben, Bill. 2019. A Future Without Fossil Fuels? New York Review of Books, April 4, 2019, pp.

McKibben, Bill. 2019a. Falter: Has the Hunan Game Begun to Play Itself Out? Henry Holt and Company, 291 pp. ISBN:13: 9781250178268

Why do Scientists Reinvent Wheels?

We may reinvent wheels by repeating research that has already been completed and published elsewhere. In one sense there is no great harm in this, and statisticians would call it replication of the first study, and the more replication the more we are convinced that the results of the study are robust. There is a problem when the repeated study reaches different results from the first study. If this occurs, there is a need to do another study to determine if there is a general pattern in the results, or if there are different habitats with different answers to the question being investigated. But after a series of studies is done, it is time to do something else since the original question has been answered and replicated. Such repeated studies are often the subject of M.Sc. or Ph.D. theses which have a limited 1-3-year time window to reach completion. The only general warning for these kinds of replicated studies is to read all the old literature on the subject. There is a failure too often on this and reviewers often notice missing references for a repeated study. Science is an ongoing process but that does not mean that all the important work has been carried out in the last 5 years.

There is a valid time and place to repeat a study when the habitat for example has been greatly fragmented or altered by human land use or when climate change has made a strong impact on the ecosystem under study. The problem in this case is to have an adequate background of data that allows you to interpret your current data. If there is a fundamental problem with ecological studies to date it is that we have an inadequate baseline for comparison for many ecosystems. We can conclude that a particular ecosystem is losing species (due to land use change or climate) only if we know what species comprised this ecosystem in past years and how much the species composition fluctuated over time. The time frame desirable for background data may be only 5 years for some species or communities but for many communities it may be 20-40 years or more. We are too often buried in the assumption that communities and ecosystems have been in equilibrium in the past so that any fluctuations now seen are unnatural. This time frame problem bedevils calls for conservation action when data are deficient.

The Living Planet Report of 2018 has been widely quoted as stating that global wildlife populations have decreased 60% in the last 4 decades. They base their analysis on the changes in 4000 vertebrate species. There are about 70,000 vertebrate species on Earth, so this statement is based on about 6% of the vertebrates. The purpose of the Living Planet Report is to educate us about conservation issues and encourage political action. No ecologist in his or her right mind would question this 60% quotation lest they be cast out of the profession, but it is a challenge to the graduate students of today to analyze this statistic to determine how reliable it is. We all ‘know’ that elephants and rhinos are declining but they are hardly a random sample. The problem in a nutshell is that we have reliable long-term data on perhaps 0.01% or less of all vertebrate species. By long term I suggest we set a minimal limit of 10 generations. As another sobering test of these kinds of statements I suggest picking your favorite animal and reading all you can on how to census the species and then locate how many studies of this species meet the criteria of a good census. The African elephant could be a good place to start, since everyone is convinced that it has declined drastically. The information in the Technical Supplement is a good starting point for a discussion about data accuracy in a conservation class.

My advice is that ecologists should not without careful thought repeat studies that have already been carried out many times on common species . Look for gaps in the current wisdom. Many of our species of concern are indeed declining and need action but we need knowledge of what kinds of management actions are helpful and possible. Many of our species have not been studied long enough to know if they are under threat or not. It is not helpful to ‘cry wolf’ if indeed there is no wolf there. We need precision and accuracy now more than ever.

World Wildlife Fund. 2018. Living Planet Report – 2018: Aiming Higher. Grooten, M. and Almond, R.E.A.(Eds). WWF, Gland, Switzerland. ISBN: 978-2-940529-90-2.
https://wwf.panda.org/knowledge_hub/all_publications/living_planet_report_2018/

Blaming Climate Change for Ecological Changes

The buzz word for all ecological applications for funding and for many submitted papers is climate change. Since the rate of climate change is not something ecologists can control, there are only two reasons to cite climate change as a reason to fund current ecological research. First, since change is continuous in communities and ecosystems, it would be desirable to determine how many of the observed changes might be caused by climate change. Second, it might be desirable to measure the rate of change in ecosystems, correlate these changes to some climate variable, and then use these data as a political and social tool to stimulate politicians to do something about greenhouse gas emissions. The second approach is that taken by climatologists who blame hurricanes and tornadoes on global warming. There is no experimental way to trace any particular hurricane to particular amounts of global warming, so it is easy for critics to say these are just examples of weather variation of which we have measured much over the last 150 years and paleo-ecologists have traced over tens of thousands of years using proxies from tree rings and sediment cores. If we are to use the statistical approach we need a large enough sample to argue that extreme events are becoming more frequent, and that might take 50 years by which time the argument would be made too late to request proper action.

The second approach to prediction in ecology is fraught with problems, as outlined in Berteaux et al. (2006) and Dietze (2017). The first approach has many statistical problems as well in selecting a biologically coherent model that can be tested by in a standard scientific manner. Since there are a very large number of climate variables, the possibility of spurious correlations is excessive, and the only way to avoid these kinds of results is to be predictive and to have a biological causal chain that is testable. Myers (1998) reviewed all the fishery data for predictive models of juvenile recruitment that used environmental variables as predictors and data was subsequently collected and tested with the published model. The vast majority of these aquatic models failed when retested but a few were very successful. The general problem is that model failures or successes might not be published so even this approach can be biased if only a literature survey is undertaken. The take home message from Myers (1998) was that almost none of the recruitment-environment correlations were being used in actual fishery management.

How much would this conclusion about the failure of environmental models in fishery management apply to other areas in ecology? Mouquet et al. (2014) pointed out that predictions could be classified as ‘explanatory’ or ‘anticipatory’ and that “While explanatory predictions are necessarily testable, anticipatory predictions need not be…….In summary, anticipatory predictions differ from explanatory predictions in that they do not aim at testing models and theory. They rely on the assumption that underlying hypotheses are valid while explanatory predictions are based on hypotheses to be tested. Anticipatory predictions are also not necessarily supposed to be true.” (page 1296). If we accept these distinctions, we have (I think) a major problem in that many of the predictive models put forward in the ecological literature are anticipatory, so they would be of little use to a natural resource manager who requires an explanatory model.

If we ignore this problem with anticipatory predictions, we can concentrate on explanatory predictions that are useful to managers. One major set of explanatory predictions in ecology are those associated with range changes in relation to climate change. Cahill et al. (2014) examined the conventional hypothesis that warm-edge range limits are set by biotic interactions rather than abiotic interactions. Contrary to expectations, they found in 125 studies that abiotic factors were more frequently supported as setting warm-edge range limits. Clearly a major paradigm about warm-edge range limits is of limited utility.

Explanatory predictions are not always explicit. Mauck et al. (2018) for example developed a climate model to predict reproductive success in Leach’s storm petrel on an island off New Brunswick in eastern Canada. From 56 years of hatching success they concluded that annual global mean temperature during the spring breeding season was the single most important predictor of breeding success. They considered only a few measures of temperature as predictor variables and found that a quadratic form of annual global mean temperature was the best variable to describe the changes in breeding success. The paper speculates about how global or regional mean temperature could possibly be an ecological predictor of breeding success, and no mechanisms are specified. The actual data on breeding success are not provided in the paper, even as a temporal plot. Since global temperatures were rising steadily from 1955 to 2010, any temporal trend in any population parameter that is rising would correlate with temperature records. The critical quadratic relationship in their analysis suggests that a tipping point was reached in 1988 when hatching success began to decline. Whether or not this is a biologically correct explanatory model can be determined by additional data gathered in future years. But it would be more useful to find out what the exact ecological mechanisms are.

If the ecological world is going to hell in a handbasket, and temperatures however measured are going up, we can certainly construct a plethora of models to describe the collapse of many species and the rise of others. But this is hardly progress and would appear to be anticipatory predictions of little use to advancing ecological science, as Guthery et al. (2005) pointed out long ago. Someone ought to review and evaluate the utility of AIC methods as they are currently being used in ecological and conservation science for predictions.

Berteaux, D., Humphries, M.M., Krebs, C.J., Lima, M., McAdam, A.G., Pettorelli, N., Reale, D., Saitoh, T., Tkadlec, E., Weladji, R.B., and Stenseth, N.C. (2006). Constraints to projecting the effects of climate change on mammals. Climate Research 32, 151-158. doi: 10.3354/cr032151.

Cahill, A.E., Aiello-Lammens, M.E., Fisher-Reid, M.C., Hua, X., and Karanewsky, C.J. (2014). Causes of warm-edge range limits: systematic review, proximate factors and implications for climate change. Journal of Biogeography 41, 429-442. doi: 10.1111/jbi.12231.

Dietze, M.C. (2017). Prediction in ecology: a first-principles framework. Ecological Applications 27, 2048-2060. doi: 10.1002/eap.1589.

Guthery, F.S., Brennan, L.A., Peterson, M.J., and Lusk, J.J. (2005). Information theory in wildlife science: Critique and viewpoint. Journal of Wildlife Management 69, 457-465. doi: 10.1890/04-0645.

Mauck, R.A., Dearborn, D.C., and Huntington, C.E. (2018). Annual global mean temperature explains reproductive success in a marine vertebrate from 1955 to 2010. Global Change Biology 24, 1599-1613. doi: 10.1111/gcb.13982.

Mouquet, N., Lagadeuc, Y., Devictor, V., Doyen, L., and Duputie, A. (2015). Predictive ecology in a changing world. Journal of Applied Ecology 52, 1293-1310. doi: 10.1111/1365-2664.12482.

Myers, R.A. (1998). When do environment-recruitment correlations work? Reviews in Fish Biology and Fisheries 8, 285-305. doi: 10.1023/A:1008828730759.

 

Ecology as a Contingent Science

The Northern Hemisphere is working through a summer of very warm weather, often temperatures 10ºC above ‘normal’. Climate change should in these conditions be obvious to all. Yet despite these clear changes, all the governments of developed countries – including Canada, USA, Australia, Britain – are doing next to nothing about the causes of climate change. This bald statement will lead to a lot of noise about “all we are now doing…”, a carbon tax promoted loudly but that is so low it can have little effect on emissions, and endless talk in the media about “sustainable practices” that are far from sustainable. Why should this be? There are many reasons and I want to discuss just one that pertains to the science of ecology.

Imagine that you are a physicist or chemist and are studying a physical or chemical problem in a lab in Germany and one in Canada. You would expect to get exactly the same experimental results in the two labs. The laws of chemistry and physics are universal and there would be consternation if results differed by geographical locations. Now transform this thought experiment to ecology. You might expect the converse for ecological experiments in the field, and there is much discussion of why this occurs (Brudvig et al. 2017, Marino et al. 2018, Zhou and Ning 2017). We need to think more about why this should be.

First, we might suspect that the ecological conditions are variable by place. The soils of Germany or France or New York or Vietnam differ in composition. The flora and fauna vary dramatically by site even within the same country. The impacts of human activities such as agriculture on the landscape vary by area. Climates are regional as well as local. Dispersal of seeds is not a uniform process. All these things ecologists know a great deal about, and they provide a rich source of post-hoc explanations for any differences. But the flip side is that ecology does not then produce general laws or principles except very general ones that provide guidance but not predictive models useful for management.

This thought leads me back to the general feeling that ecology is not categorized as a hard science and is thus often ignored. Ecologist have been pointing out many of the consequences of climate change for at least 30-40 years with few people in business or local political power listening. This could simply be a consequence of the public caring about the present but not about the future of the Earth. But it might be partly the result of ecology having produced no generality that the public appreciates, except for the most general ecological ‘law’ that “Mother Nature takes care of itself”, so we the public have little to be concerned about.

The paradigm of stability is deeply embedded in most people (Martin et al. 2016), and we are in the process of inventing a non-equilibrium ‘theory’ of ecology in which the outcome of ecological processes leads us into new communities and ecosystems we can only scarcely imagine and certainly not predict clearly. Physicists can predict generally what a future Earth climate with +2ºC or + 4ºC will entail (IPCC 2013, Lean 2018), but we cannot do this so readily with our ecological knowledge.

Where does this get us? Ecology is not appreciated as a science, and thus in the broad sense not funded properly. Ecologists fight over crumbs of funding even to monitor the changes that are occurring, and schemes that might alleviate some of the major effects of climate change are not tested because they are expensive and long-term. Ecology is a long-term science in a world that is increasingly short-term in thinking and in action. Perhaps this will change but no politician wants to wait 10-20 years to see if some experimental procedure works. Funding that is visionary is stopped after 4 years by politicians who know nothing about the problems of the Earth and sustainability. We should demand a politics of sustainability for our future and that of following generations. Thinking long-term should be a requirement not an option.

Brudvig, L.A., Barak, R.S., Bauer, J.T., Caughlin, T.T., and Laughlin, D.C. (2017). Interpreting variation to advance predictive restoration science. Journal of Applied Ecology 54, 1018-1027. doi: 10.1111/1365-2664.12938.

Chapman, M., LaValle, A., Furey, G., and Chan, K.M.A. (2017). Sustainability beyond city limits: can “greener” beef lighten a city’s Ecological Footprint? Sustainability Science 12, 597-610. doi: 10.1007/s11625-017-0423-7.

IPCC (2013) ‘IPCC Fifth Assessment Report: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.’ (Cambridge University Press: Cambridge, U.K.) http://www.climatechange2013.org/images/report/WG1AR5_ALL_FINAL.pdf

Lean, J.L. (2018). Observation-based detection and attribution of 21st century climate change. Wiley Interdisciplinary Reviews. Climate Change 9, e511. doi: 10.1002/wcc.511.

Marino, N.A.C., Romero, G.Q., and Farjalla, V.F. 2018. Geographical and experimental contexts modulate the effect of warming on top-down control: a meta-analysis. Ecology Letters 21, 455-466. doi: 10.1111/ele.12913.

Martin, J-L., Maris, V., and Simberloff, D.S. (2016). The need to respect nature and its limits challenges society and conservation science. Proceedings of the National Academy of Sciences 113, 6105-6112. doi: 10.1073/pnas.1525003113.

Zhou, J. and Ning, D. (2017). Stochastic community assembly: Does it matter in microbial ecology? Microbiology and Molecular Biology Reviews 81, e00002-00017. doi: 10.1128/MMBR.00002-17.

On Culling Overabundant Wildlife

Ecologists have written much about the culling of wildlife from an ecological and conservation perspective (Caughley 1981, Jewell et al. 1981, Bradford and Hobbs 2008, Hampton and Forsyth 2016). The recommendations for culling as a method for reducing overabundant wildlife populations are typically scientifically well established and sensitive to animal welfare. The populations chosen for culling are classified as ‘overabundant’. But overabundant is a human-defined concept, and thus requires some form of social license to agree about what species, in which conditions, should be classified as ‘overabundant’. The problem of overabundance usually arises when humans make changes that permit a species to become so numerous locally that it is having an adverse effect on its food supply, its competitors, or the integrity of the ecosystem it occupies. Once overabundance is recognized, the management issue is to determine which methods should be used to reduce abundance to a suitable level. Culling is only one option for removing wildlife, and animals may be captured and moved elsewhere if that is possible or sterilized to prevent reproduction and further increase (Liu et al. 2012, Massei and Cowan 2014).

All these policy issues are subject to open public debate and these debates are often heated because of different belief systems. Animal rights advocates may push the assumption that we humans have no rights to kill any wildlife at all. News media often concentrate on the most stringent views on controlling populations that are overabundant, and public discussion becomes impossible. Two aspects need to be noted that are often lost in any discussion. First is the cost of alternatives in dollars and cents. As an example, most ecologists would agree that wild horses are overabundant on open range in western United States (Davies et al. 2014, Rutberg et al. 2017) but the question is what to do about this. Costs to reduce horse populations by capturing horses and penning them and feeding them are astronomical (the current situation in western USA, estimated at $25,000 per animal) but this method of control could be done if society wishes to spend money to achieve this goal. Culling would be much cheaper, but the killing of large animals is anathema to many people who speak loudly to politicians. Fertility control methods are improving with time and may be more acceptable socially, but costs are high and results in population reduction can be slow in coming (Hobbs and Hinds 2018). Models are essential to sort out many of these issues, whether it be the projected costs of various options (including doing nothing), the expected population trajectory, or the consequences for other species in the ecosystem.

The bottom line is that if overabundant wildlife populations are not reduced by some means, the result must be death by starvation or disease coupled with extensive damage to other species in these ecosystems. This type of “Plan B” is the second aspect not often considered in discussions of policies on overabundant species. In the present political scene in North America opposition to culling overabundant wildlife is strong, coherent discussion is rarely possible, and Plan B problems are rarely heard. Most overabundant wildlife result from human actions in changing the vegetation, introducing new species, and reducing and fragmenting wildlife habitats. Wishing the problems will go away without doing anything is not a feasible course of action.

These kinds of problems in wildlife management are soluble in an objective manner with careful planning of research and management actions (Hone et al. 2017). Ecologists have a moral duty to present all scientific sides of the management of overabundant species, and to bring evidence into the resulting social and political discussions of management issues. It is not an easy job.

Bradford, J.B., and N.T. Hobbs. 2008. Regulating overabundant ungulate populations: An example for elk in Rocky Mountain National Park, Colorado. Journal of Environmental Management 86:520-528. doi: 10.1016/j.jenvman.2006.12.005

Caughley, G. 1981. Overpopulation. Pages 7-19 in P.A. Jewell S. Holt, and D. Hart, editors. Problems in Management of Locally Abundant Wild Mammals. Academic Press, New York. ISBN: 978-0-12-385280-9

Davies, K. W., Collins, G. & Boyd, C. S. (2014) Effects of feral free-roaming horses on semi-arid rangeland ecosystems: an example from the sagebrush steppe. Ecosphere, 5, 127. doi: 10.1890/ES14-00171.1

Hampton, J. O., and D. M. Forsyth. 2016. An assessment of animal welfare for the culling of peri-urban kangaroos. Wildlife Research 43:261-266. doi: 10.1071/WR16023

Hobbs, R.J. and Hinds, L.A. (2018). Could current fertility control methods be effective for landscape-scale management of populations of wild horses (Equus caballus) in Australia? Wildlife Research 45, 195-207. doi: 10.1071/WR17136.

Hone, J., Drake, V.A. & Krebs, C.J. (2017) The effort–outcomes relationship in applied ecology: Evaluation and implications BioScience, 67, 845-852. doi: 10.1093/biosci/bix091

Jewell, P. A., Holt, S. & Hart, D. (1982) Problems in Management of Locally Abundant Wild Mammals. Academic Press, New York. 360 pp. ISBN: 978-0-12-385280-9

Liu, M., Qu, J., Yang, M., Wang, Z., Wang, Y., Zhang, Y. & Zhang, Z. (2012) Effects of quinestrol and levonorgestrel on populations of plateau pikas, Ochotona curzoniae, in the Qinghai-Tibetan Plateau. Pest Management Science, 68, 592-601. doi: 10.1002/ps.2302

Massei, G. & Cowan, D. (2014) Fertility control to mitigate human–wildlife conflicts: a review. Wildlife Research, 41, 1-21. doi: 10.1071/WR13141

Rutberg, A., Grams, K., Turner, J.W. & Hopkins, H. (2017) Contraceptive efficacy of priming and boosting doses of controlled-release PZP in wild horses. Wildlife Research, 44, 174-181. doi: 10.1071/WR16123

On Questionable Research Practices

Ecologists and evolutionary biologists are tarred and feathered along with many scientists who are guilty of questionable research practices. So says this article in “The Conservation” on the web:
https://theconversation.com/our-survey-found-questionable-research-practices-by-ecologists-and-biologists-heres-what-that-means-94421?utm_source=twitter&utm_medium=twitterbutton

Read this article if you have time but here is the essence of what they state:

“Cherry picking or hiding results, excluding data to meet statistical thresholds and presenting unexpected findings as though they were predicted all along – these are just some of the “questionable research practices” implicated in the replication crisis psychology and medicine have faced over the last half a decade or so.

“We recently surveyed more than 800 ecologists and evolutionary biologists and found high rates of many of these practices. We believe this to be first documentation of these behaviours in these fields of science.

“Our pre-print results have certain shock value, and their release attracted a lot of attention on social media.

  • 64% of surveyed researchers reported they had at least once failed to report results because they were not statistically significant (cherry picking)
  • 42% had collected more data after inspecting whether results were statistically significant (a form of “p hacking”)
  • 51% reported an unexpected finding as though it had been hypothesised from the start (known as “HARKing”, or Hypothesising After Results are Known).”

It is worth looking at these claims a bit more analytically. First, the fact that more than 800 ecologists and evolutionary biologists were surveyed tells you nothing about the precision of these results unless you can be convinced this is a random sample. Most surveys are non-random and yet are reported as though they are a random, reliable sample.

Failing to report results is common in science for a variety of reasons that have nothing to do with questionable research practices. Many graduate theses contain results that are never published. Does this mean their data are being hidden? Many results are not reported because they did not find an expected result. This sounds awful until you realize that journals often turn down papers because they are not exciting enough, even though the results are completely reliable. Other results are not reported because the investigator realized once the study is complete that it was not carried on long enough, and the money has run out to do more research. One would have to have considerable detail about each study to know whether or not these 64% of researchers were “cherry picking”.

Alas the next problem is more serious. The 42% who are accused of “p-hacking” were possibly just using sequential sampling or using a pilot study to get the statistical parameters to conduct a power analysis. Any study which uses replication in time, a highly desirable attribute of an ecological study, would be vilified by this rule. This complaint echos the statistical advice not to use p-values at all (Ioannidis 2005, Bruns and Ioannidis 2016) and refers back to complaints about inappropriate uses of statistical inference (Armhein et al. 2017, Forstmeier et al. 2017). The appropriate solution to this problem is to have a defined experimental design with specified hypotheses and predictions rather than an open ended observational study.

The third problem about unexpected findings hits at an important aspect of science, the uncovering of interesting and important new results. It is an important point and was warned about long ago by Medewar (1963) and emphasized recently by Forstmeier et al. (2017). The general solution should be that novel results in science must be considered tentative until they can be replicated, so that science becomes a self-correcting process. But the temptation to emphasize a new result is hard to restrain in the era of difficult job searches and media attention to novelty. Perhaps the message is that you should read any “unexpected findings” in Science and Nature with a degree of skepticism.

The cited article published in “The Conversation” goes on to discuss some possible interpretations of what these survey results mean. And the authors lean over backwards to indicate that these survey results do not mean that we should not trust the conclusions of science, which unfortunately is exactly what some aspects of the public media have emphasized. Distrust of science can be a justification for rejecting climate change data and rejecting the value of immunizations against diseases. In an era of declining trust in science, these kinds of trivial surveys have shock value but are of little use to scientists trying to sort out the details about how ecological and evolutionary systems operate.

A significant source of these concerns flows from the literature that focuses on medical fads and ‘breakthroughs’ that are announced every day by the media searching for ‘news’ (e.g. “eat butter”, “do not eat butter”). The result is almost a comical model of how good scientists really operate. An essential assumption of science is that scientific results are not written in stone but are always subject to additional testing and modification or rejection. But one result is that we get a parody of science that says “you can’t trust anything you read” (e.g. Ashcroft 2017). Perhaps we just need to repeat to ourselves to be critical, that good science is evidence-based, and then remember George Bernard Shaw’s comment:

Success does not consist in never making mistakes but in never making the same one a second time.

Amrhein, V., Korner-Nievergelt, F., and Roth, T. 2017. The earth is flat (p > 0.05): significance thresholds and the crisis of unreplicable research. PeerJ  5: e3544. doi: 10.7717/peerj.3544.

Ashcroft, A. 2017. The politics of research-Or why you can’t trust anything you read, including this article! Psychotherapy and Politics International 15(3): e1425. doi: 10.1002/ppi.1425.

Bruns, S.B., and Ioannidis, J.P.A. 2016. p-Curve and p-Hacking in observational research. PLoS ONE 11(2): e0149144. doi: 10.1371/journal.pone.0149144.

Forstmeier, W., Wagenmakers, E.-J., and Parker, T.H. 2017. Detecting and avoiding likely false-positive findings – a practical guide. Biological Reviews 92(4): 1941-1968. doi: 10.1111/brv.12315.

Ioannidis, J.P.A. 2005. Why most published research findings are false. PLOS Medicine 2(8): e124. doi: 10.1371/journal.pmed.0020124.

Medawar, P.B. 1963. Is the scientific paper a fraud? Pp. 228-233 in The Threat and the Glory. Edited by P.B. Medawar. Harper Collins, New York. pp. 228-233. ISBN 978-0-06-039112-6

A Need for Champions

The World has many champions for the Olympics, economists have champions for free trade, physicists have champions for the Hadron Collider, astronomists for space telescopes, but who are the champions for the environment?  We have many environmental scientists who try to focus the public’s attention on endangered species, the state of agriculture, pollution of air and water, and the sustainability of marine fisheries, but they are too much ignored. Why do we have this puzzle that the health of the world we all live in is too often ignored when governments release their budgets?

There are several answers to this simple question. First of all, the ‘jobs and growth’ paradigm rules, and exponential growth is the ordained natural order. The complaint we then get is that environmental scientists too often suggest that studies are needed, and the results of these studies produce recommendations that will impede jobs and growth. Environmental science not only does not produce more dollar bills but in fact diverts dollars from other more preferred activities that increase the GDP.

Another important reason is that environmental problems are slow-moving and long-term, and our human evolutionary history shows that we are poor at dealing with such problems. We can recognize and adapt quickly to short-term problems like floods, epidemics, and famines but we cannot see the inexorable rise in sea levels of 3 mm per year. We need therefore champions of the environment with the charisma to attract the world’s attention to slow-moving, long-term problems. We have some of these champions already – James Hansen, David Suzuki, Tim Flannery, Paul Ehrlich, Naomi Klein – and they are doing an excellent job of producing scientific discussions on our major environmental problems, information that is unfortunately still largely ignored on budget day. There is progress, but it is slow, and in particular young people are more aware of environmental issues than are those of the older generation.

What can we do to change the existing dominant paradigm into a sustainable ecological paradigm? Begon (2017) argues that ecology is both a science and a crisis discipline, and his concern is that at the present time ecological ideas about our current crises are not taken seriously by the general public and policy leaders. One way to change this, Begon argues, is to reduce our reliance on specific and often complicated evidence and convert to sound bites, slogans that capture the emotions of the public rather than their intellect. So, I suggest a challenge can be issued to ecology classes across the world to spend some time brainstorming on suitable slogans, short appealing phrases that encapsulate what ecologists understand about our current problems. Here are three suggestions: “We cannot eat coal and oil – support agriculture”, “Think long-term, become a mental eco-geologist”, and “The ocean is not a garbage can”. Such capsules are not for all occasions, and we must maintain our commitment to evidence-based-ecology of course (as Saul et al. 2017 noted). That this kind of communication to the general public is not simple is well illustrated in the paper by Casado-Aranda et al. (2017) who used an MRI to study brain waves in people exposed to ecological information. They found that people’s attitudes to ecological messages were much more positive when the information was conveyed in future-framed messages delivered by a person with a younger voice. So perhaps the bottom line is to stop older ecologists from talking so much, avoid talking about the past, and look in the future for slogans to encourage an ecological world view.

Begon, M. 2017. Winning public arguments as ecologists: Time for a New Doctrine? Trends in Ecology & Evolution 32:394-396. doi: 10.1016/j.tree.2017.03.009

Casado-Aranda, L.-A., M. Martínez-Fiestas, and J. Sánchez-Fernández. 2018. Neural effects of environmental advertising: An fMRI analysis of voice age and temporal framing. Journal of Environmental Management 206:664-675. doi: 10.1016/j.jenvman.2017.10.006

Saul, W.-C., R.T. Shackleton, and F.A. Yannelli. 2017. Ecologists winning arguments: Ends don’t justify the means. A response to Begon. Trends in Ecology & Evolution 32:722-723. doi: 10.1016/j.tree.2017.08.005

 

On Politics and the Environment

This is a short story of a very local event that illustrates far too well the improvements we have to seek in our political systems. The British Columbia government has just approved the continuation of construction of the Site C dam on the Peace River in Northern British Columbia. The project was started in 2015 by the previous Liberal (conservative) government with an $8 billion price tag and with no (yes NO) formal studies of the economic, geological or environmental consequences of the dam, and in complete opposition by most of the First Nations people on whose traditional land the dam would be built. Fast forward 2 years, a moderate left-wing government takes over from the conservatives and the decision is now in their hands: do they carry on with the project, $2 billion having been spent already, or stop it with an additional $1-2 billion in costs to undo the damage to the valley from work already carried out? 2000 temporary construction jobs in the balance, the government in general pro-union and pro the working person rather than the 1%. They decided to proceed with the dam.

To the government’s credit it asked the Utilities Commission to prepare an economic analysis of the project in a very short time, but to make it simpler (?) did not allow the Commission to consider in its report environmental damage, climate change implications, greenhouse gas emissions, First Nations rights, or the loss of good agricultural land. Alas, that pretty well leaves out most things an ecologist would worry about. The economic analysis was sitting on the fence mostly because the question of the final cost of Site C is an unknown. It was estimated to be $8 billion, but already a few days after the government’s decision it is $10.5 billion, all to be paid by the taxpayer. If it is a typical large dam, the final overall cost will range between $16 to $20 billion when the dam is operational in 2024. The best news article I have seen on the Site C decision is this one by Andrew Nikiforuk:

https://thetyee.ca/Opinion/2017/12/12/Pathology-Site-C/

Ansar et al. (2014) did a statistical analysis of 245 large dams built since 1934 and found that on average actual costs for large dams were about twice estimated costs, and that there was a tendency for larger dams to have even higher than average final costs. There has been little study for Site C of the effects of the proposed dam on fish in the river (Cooper et al. 2017) and no discussion of potential greenhouse gas emissions (methane) released as a result of a dam at Site C (DelSontro et al. 2016). The most disturbing comment on this decision to proceed with Site C was made by the Premier of B.C. who stated that if they had stopped construction of the dam, they would have to spend a lot of money “for nothing” meaning that restoring the site, partially restoring the forested parts of the valley, repairing the disturbance of the agricultural land in the valley, recognizing the rights of First Nations people to their land, and leaving the biodiversity of these sites to repair itself would all be classed as “nothing” of value. Alas our government’s values are completely out of line with the needs of a sustainable earth ecosystem for all to enjoy.

What we are lacking, and governments of both stripes have no time for, is an analysis of what the alternatives are in terms of renewable energy generation. Alternative hypotheses should be useful in politics as they are in science. And they might even save money.

Ansar A, Flyvbjerg B, Budzier A, Lunn D (2014). Should we build more large dams? The actual costs of hydropower megaproject development. Energy Policy 69, 43-56. doi: 10.1016/j.enpol.2013.10.069

Cooper AR, et al. (2017). Assessment of dam effects on streams and fish assemblages of the conterminous USA. Science of The Total Environment 586, 879-89. doi: 10.1016/j.scitotenv.2017.02.067

DelSontro T, Perez KK, Sollberger S, Wehrli B (2016). Methane dynamics downstream of a temperate run-of-the-river reservoir. Limnology and Oceanography 61, S188-S203. doi: 10.1002/lno.10387