Tag Archives: conservation ecology

On Biodiversity Science

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With David Attenborough and all the amazing picture books on biodiversity there can be few people in the world who have not been alerted to the array of beautiful and interesting species on Earth. Until recently the subject of biodiversity, known to First Nations since long, long ago, had not entered the western world of automobiles, industry, farming, fishing, music, theatres, and movies. Biodiversity is now greatly appreciated by most people, but perhaps more as entertainment for western societies and more for subsistence food in less wealthy parts of our world.

There are many different measures of ‘biodiversity’ and when discussing how we should protect biodiversity we should be careful about exactly how this word is being used. The number of different species in an area is one simple measure of biodiversity. But often the types of organisms being considered are less well defined. Forest ecologists attempt to protect forest biodiversity, but logging companies are more concerned only with trees and tree size for commercial use. Bird watchers are concerned with birds and have developed much citizen science in counting birds. Mushroom connoisseurs may worry about what edible mushrooms will be available this summer. But in many cases biodiversity scientists recognize that the community of organisms and the ecosystem that contains them would be a more appropriate unit of analysis. But as the number of species in an ecosystem increases, the complexity of the ecosystem becomes unmanageable. A single ecosystem may have hundreds to thousands of species, and we are in the infant stage of trying to determine how to study these biological systems.

One result is that, given that there are perhaps 10 million species on Earth and only perhaps 10,000 biologists who study biodiversity, where do we begin? The first and most popular way to answer this question is to pick a single species and concentrate on understanding its ecology. This makes are researcher’s life fairly simple. If elephants in Africa are under threat, find out all about the ecology of elephants. If a particular butterfly in England is very rare, try to find out why and how to protect them. This kind of research is very valuable for conservation because it provides a detailed background for understanding the requirements of each species. But the single species approaches lead into at least two quagmires. First, all species exist in a web of other species and understanding this web greatly expands the problem. It is possible in many cases to decipher the effects other species have on our elephants or butterflies, but this requires many more scientists to assist in analysing the species’ food chain, its diseases, its predators and parasites, and that is only a start. The second quagmire is that one of the general rules of ecology is that most species on Earth are rare, and few are common. So that we must concentrate our person-power on the common species because they are easier to find and study. But it is often the rare species that are of conservation concern, and so we should focus on them rather than the common species. In particular, given that only about 10% of the species on Earth have been described scientifically, we may often be assigned a species that does not have any information on its food habits or habitat requirements, its distribution, and how its abundance might be changing over time, a lifetime research program.

The result of this general overview is that the mantra of our day – Protect Biodiversity – begins as a compelling slogan and ends in enormous scientific complexity. As such it falls into the category of slogans like ‘Reduce Poverty’ and ‘Peace on Earth’, something we can all agree on, but the devil is in the details of how to achieve that particular goal.

One way to avoid all these pitfalls has been to jump over the problems of individual species and analyse communities of species or entire ecosystems. The result of this approach is to boil down all the species in the community to a number that estimates “biodiversity” and then use that number in relating ‘biodiversity’ to community attributes like ‘productivity’ or ‘stability’. This approach leads to testing hypotheses like ‘Higher biodiversity leads to greater stability’. There are serious problems with this approach if it is used to test any such hypothesis. First, biodiversity in this example must be rigorously defined as well as stability. The fact that higher biodiversity of butterflies in a particular region is associated with a more stable abundance of these butterflies over time is worthy of note but not of generalization to global communities or ecosystems. And as in all ecological studies we do not know if this is a generalization applicable to all butterfly populations everywhere until many more studies have been done.

A second problem is that this community or ecosystem approach to address ecological questions about biodiversity is not very useful in promoting conservation which boils down to particular species in particular environments. It should force us back to looking at the population ecology of species that are of conservation concern. It is population ecologists who must push forward the main goals of the conservation of the Earth’s biota, as Caughley (1994) recognized long ago.

The practical goals of conservation have always been local, and this constraint is mostly ignored in papers that demand some global research priorities and global ecological rules. The broad problem is that the conservation of biodiversity is a gigantic scientific and political problem that is currently underfunded and in its scientific infancy. At the present too much biodiversity research is short-term and not structured in a comprehensive framework that identifies critical problems and concentrates research efforts on these problems (Nichols et al. 2019, Sutherland et al. 2018). One more important issue for a seminar discussion group. 

Caughley, G. (1994). Directions in conservation biology. Journal of Animal Ecology 63, 215-244. doi: 10.2307/5542

Nichols, J.D., Kendall, W.L., and Boomer, G.S. (2019). Accumulating evidence in ecology: Once is not enough. Ecology and Evolution 9, 13991-14004. doi: 10.1002/ece3.5836.

Sutherland, W.J., Butchart, Stuart H.M., Connor, B., Culshaw, C., Dicks, L.V., et al. (2018). A 2018 Horizon Scan of Emerging Issues for Global Conservation and Biological Diversity. Trends in Ecology & Evolution 33, 47-58. doi: 10.1016/j.tree.2017.11.006.

A Poem on the State of Agriculture in 1935

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After listening to me rant about the state of modern agriculture in the Anthropocene, a colleague in Australia sent me this poem by C.J. Dennis (1876 – 1938) written long before most of us were born. I reprint it here as a reminder that many of our ecological problems are not new, that we have perhaps made progress on some but that in many areas Dennis’s poem about agriculture could have been published today. A powerful poem that in a classroom discussion might lead us to second thoughts that we now live in the best of all possible worlds. Vale C.J. Dennis.

C.J. Dennis in the Herald in 1935 in Australia
THE SPOILERS

“Because overstocking and continuous grazing have denuded the land of vegetation and removed all resistance to wind and flood, it has now been suddenly realised that erosion in the Western districts of N.S.W. has reduced thousands of acres to little better than desert. A descendant of the original black inhabitants of this country might regard this as just retribution.

Ye are the Great White People, masters and lords of the earth,
Spreading your stern dominion over the world’s wide girth.
Here, where my fathers hunted since Time’s primordial morn,
To our land’s sweet, fecund places, you came with your kine and corn.
Mouthing your creed of Culture to cover a baser creed,
Your talk was of White Man’s magic, but your secret god was Greed.
And now that your generations to the second, the third have run,
White Man, what of my country?  Answer, what have you done?

Now the God of my Simple People was a simple, kindly God,
Meting his treasure wisely that sprang from this generous sod,
With never a beast too many and never a beast too few,
Thro’ the lean years and the fruitful, he held the balance true.
Then the White Lords came in their glory; and their cry was: “More!  Yet more!”
And to make them rich for a season they filched Earth’s age-old store,
And they hunted my Simple People — hunters of yester-year —
And they drove us into the desert — while they wrought fresh deserts here.

They ravaged the verdant uplands and spoiled wealth ages old,
Laid waste with their pumps and sluices for a gunny-bag of gold;
They raided the primal forests and the kind, rain-bringing trees
That poured wealth over the lowlands thro’ countless centuries;
They fed their kine on the grasslands, crowding them over the land,
Till blade and root in the lean years gave place to hungry sand.
Then, warned too late of their folly, the White Lords grew afraid,
And they cried to their great god Science; but Science could not aid.

This have you done to our country, lords of the air and the seas,
This to the hoarded riches of countless centuries —
Life-yielding loam, uncovered, unsheltered in the drought,
In the floods your hand unbridled, to the age-old sea drifts out.
You have sold man’s one true birthright for a White Man’s holiday,
And the smothering sands drift over where once green fields turn grey —
Filched by the White Man’s folly to pamper the White Lords’ vice;
And leave to your sons a desert where you found a paradise.”

Herald, 6 December 1935, page 6

http://www.middlemiss.org/lit/authors/denniscj/newspapers/herald/1935/works/spoilers.html

A Few Problems Ecologists Need to Face

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This is an overly simple attempt to look ahead, after a summer of extreme heat, extensive forest fires, overheated crops, and excessive flooding, to ask where we ecologists might be going in the next century. 

The first and most important point is that these disasters of the last several months can all be blamed on climate change, and despite what you hear, there is no stopping these changes in the next hundred years. CO2 enrichment is turning Earth into a hot planet. This is a simple fact of physics that the CO2 we have already emitted into our atmosphere will be there for hundreds to thousands of years. The politicians and the media will tell you that carbon-capture is coming soon to solve all our emission problems and cleanse the atmosphere of excess greenhouse gases. If you believe that, ask yourself if you would invest your capital and retirement account in a poker game for a decline in CO2 during the next 20 years.

The critical question for we ecologists is this: How much of the accumulated ecological wisdom will be unchanged in 100 years? If we have only to deal with changing climate, we could develop an understanding of what the limiting factors are and express the anticipated changes in the climatic units of the future. But that becomes a problem when we recognize that food webs have many interactions in them that are climate affected but perhaps not climatically determined. So, for example if we have a simple food web of polar bears feeding on seals, both of which require an ice pack for survival at the present time, what should we expect in 100 years when there is virtually no polar ice to be found. A simple model will predict that the polar bear will go extinct and perhaps seals will learn to use land instead of ice packs, but the fish that are the main food of the seals may also change if they depend on zooplankton that have a water temperature niche boundary that is exceeded. So exactly what will happen to this simple food web cannot be easily understood from current ecological wisdom or models.

Another example is from the current changing dynamics of Stellar sea lions of the North Pacific, summarized in an excellent review by Andrew Trites (2021). Stellar sea lions occupy the coastlines of the North Pacific from the Sea of Okhotsk and the Bering Sea eastward down the west coast of North America to southern California. Forty years ago, scientists noted a decline beginning in the western sea lion populations in the Bering Sea and the Gulf of Alaska and at the same time an increase in sea lion numbers from Southeast Alaska to California. Two explanations compete among seal experts to explain this pattern. The ‘overfishing hypothesis’ suggested that the Alaskan and Russian fishery has removed too much of the sea lion’s favourite food items and thus caused starvation among western sea lions. The alternative to this explanation, the ‘junk-food-hypothesis’ suggested that sea lions in the west were consuming too many fish species of low fat and fewer calories, and that their starvation was self-limited and not caused by the human fisheries.

Here is a “simple” ecological problem with 2 competing hypotheses or explanations that has not yet been resolved after many years of research. Empirical ecologists will possibly argue that we need to monitor the sea lions and their prey and the fishing catches over this extensive area for the next decade or two to find the answer as to which of the two competing hypothesis is closest to being correct. But given climate change and ocean warming, neither of which are uniform over all parts of the Earth, we would expect large changes in the abundance and distribution of many fish species and consequently also in the predators that depend on them. But exactly which ones, and exactly where? Conservation ecology is dogged by this problem and subsists largely by ignoring it in favour of short-term studies in small areas and the effects of human population growth, and perhaps this is all we can do at present. So, should “watch and wait, look and see” become our model? Wildlife and fisheries management thus become short-term ‘watch and wait’ sciences, like passengers on the Titanic long ago, wondering what the future holds.

One way to suggest future paths is to model the various communities and ecosystems that we study, and this activity is now strong in ecology and conservation. But there are many difficulties with this approach boiling down to a ‘wait-and-see’ method of empirical investigation. A review by Furtado (2020) of two books on fisheries management provides an up-to-date view of progress in fisheries ecology and illustrates problems with bluefin tuna management and the modelling approach to fish ecosystems in general. The problem in assuming the modelling approach as an answer to our dilemma is shown clearly by the current Covid pandemic and the reversals in modelling and alternative views that have caused much confusion despite much important research. Whither ecology from this point in time?

Furtado, Miguel (2020). The Future of Bluefin Tunas: Ecology, Fisheries Management and Conservation. Conservation Biology 34, 1600-1602.

Trites, A.W. (2021). Behavioral Insights into the Decline and Natural History of Steller Sea Lions. In ‘Ethology and Behavioral Ecology of Otariids and the Odobenid, Ethology and Behavioral Ecology of Marine Mammals,’. (Ed. C. Campagna and R. Harcourt), pp. 489-518. (Springer Nature Switzerland.)  doi: 10.1007/978-3-030-59184-7_23  

Blaming Climate Change for Ecological Changes

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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.

 

On Detecting Rare Species with Camera Trapping

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If you are a conservation biologist and you wish to save all or as many species as possible, your first problem is detectability. Does the species of concern live in this habitat? If it is present how many are there, and is their abundance changing from year to year? These are fundamental questions in conservation science and there is accordingly a very large literature on how to answer these simple questions for animals in different taxonomic groups. I want to deal briefly here with rare species in which the issue of detectability is most critical.

There is a large array of papers on detection methods in the conservation literature (e.g. Brodie et al. 2018; Crates et al. 2017; Steenweg et al. 2016; Clement et al. 2016, Trolliet et al. 2014). Detection methods vary from live trapping marked individuals, visual sighting of unmarked individuals, camera photos of marked or unmarked individuals, sign data such as tracks or scats in snow, mud or sand, DNA fingerprinting, and many clever natural-history- derived methods to measure detection. These methods are well developed for common animals (Williams et al. 2002).

Rare species are the first problem faced by all these detection methods. Rare species range from those virtually impossible to detect with current technology to those that turn up infrequently in the designated detection device. The conservation challenge of rare species is difficult if they are hard to detect and difficult to study so that we have few natural history parameters to guide conservation actions. For these we can only set aside what we think are suitable areas and conserve them.

The technology of monitoring rare species that can be detected at some reasonable level has greatly improved with the advent of passive-infrared-cameras that can be deployed 24-7 to capture images of whomever walks or swims by. But this technology raises a whole set of methodological issues that must be addressed. The first and most obvious one is the skill of the observer both in setting up the cameras and in looking at the photos to identify correctly the species present. The second and more difficult question is what to count as a detection or ‘hit’. If your question is simply ‘occupancy’ seeing one photograph in the time period of the study provides a + for occupancy. But many ecologists wish to connect the dots from occupancy scores to abundance so that some index of population numbers can arise from these camera data. To make this leap of faith relies heavily on the experimental design of the camera placements, the number of cameras, the make of the cameras (Meek et al. 2014), and the exact placement of cameras on trees or stakes to cover a specific area of habitat. Clearly if cameras are placed too close to one another, the photos from the different cameras are not independent, as most of the models of occupancy assume (Brodie et al. 2018). If bait is used with the cameras the situation becomes even more complex because some species may be attracted while others are repelled by the bait. In general camera detections or ‘hits’ for a particular species are a measure of activity rather than a direct measure of abundance, and so often the assumption is made that activity = abundance, which must be justified. In the extreme case in which a density estimate is needed from camera data, the problem of ‘edge effects’ of the sampled area must be considered just as it does with grid trapping (e.g Thornton and Pekins 2015). New approaches for estimating density from camera data appear almost daily and must be evaluated for accuracy (Nakashima et al. 2018).

We are now in the exponential phase of camera trapping with cameras put up in all sorts of spatial designs for different lengths of time with the hope that someone will have time to look at the photos and some clever statistician can factor out all the potential biases and non-independence of the resulting data. So in a nutshell my simple advice is to use cameras to gather wildlife information but think carefully about what exactly you wish to achieve: occupancy?, an index of abundance?, actual numerical abundance? population density? Or simply beautiful photos of interesting animals? And in the end you may be envious of plant ecologists whose plants do not walk away when you census them.

 

Brodie, J.F., et al. (2018). Models for assessing local-scale co-abundance of animal species while accounting for differential detectability and varied responses to the environment. Biotropica 50, 5-15. doi: 10.1111/btp.12500.

Clement, M. J., J. E. Hines, J. D. Nichols, K. L. Pardieck, and D. J. Ziolkowski. 2016. Estimating indices of range shifts in birds using dynamic models when detection is imperfect. Global Change Biology 22:3273-3285. doi: 10.1111/gcb.13283

Crates, R., L. Rayner, D. Stojanovic, M. Webb, and R. Heinsohn. 2017. Undetected Allee effects in Australia’s threatened birds: implications for conservation. Emu 117:207-221. doi: 10.1080/01584197.2017.1333392

Meek, P.D., et al. (2014). Camera traps can be heard and seen by animals. PLoS ONE 9, e110832. doi: 10.1371/journal.pone.0110832.

Nakashima, Y., Fukasawa, K., and Samejima, H. (2018). Estimating animal density without individual recognition using information derivable exclusively from camera traps. Journal of Applied Ecology 55, 735-744. doi: 10.1111/1365-2664.13059.

Smith, D.H.V. and Weston, K.A. (2017). Capturing the cryptic: a comparison of detection methods for stoats (Mustela erminea) in alpine habitats. Wildlife Research 44, 418-426. doi: 10.1071/WR16159.

Steenweg, R., et al. (2016). Camera-based occupancy monitoring at large scales: Power to detect trends in grizzly bears across the Canadian Rockies. Biological Conservation 201:192-200. doi: 10.1016/j.biocon.2016.06.020

Thornton, D.H. and Pekins, C.E. (2015). Spatially explicit capture-recapture analysis of bobcat (Lynx rufus) density: implications for mesocarnivore monitoring Wildlife Research 42, 394-404. doi: 10.1071/WR15092.

Trolliet, F., et al. (2014). Use of camera traps for wildlife studies. A review. Biotechnology, Agronomy, Society and Environment (BASE) 18, 446-454.

Williams, B.K., Nichols, J.D., and Conroy, M.J. (2002) ‘Analysis and Management of Animal Populations.’ (Academic Press: New York.). 817 pp.

 

Seven Prescriptive Principles for Ecologists

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After three of us put together a paper to list the principles of applied ecology (Hone, Drake, and Krebs 2015), I thought that perhaps we might have an additional set of general behavioural principles for ecologists. We might think of using these seven principles as a broad template for the work we do in science.

  1. Do good science and avoid opinions that are not based on facts and reliable studies. Do not cite bad science even if it is published in Science.
  2. Appreciate and support your colleagues.
  3. Because you disagree with another scientist it is not acceptable to be rude, and it is preferable to decide what experiment can solve the disagreement.
  4. Adulterating your data to remove values that do not fit your hypothesis is not acceptable.
  5. Alternative facts have no place in science. A Professor should not profess nonsense. Nonsense should be the sole prerogative of politicians.
  6. Help your fellow scientists whenever possible, and do not envy those whose papers get published in Science or Nature. Your contribution to science cannot be measured by your h-index.
  7. We have only one Earth. We should give up dreaming about moving to Mars and take care of our home here.

Many of these principles can be grouped under the umbrella of ‘scientific integrity’, and there is an extensive discussion in the literature about integrity (Edwards and Roy 2017, Horbach and Halffman 2017). Edwards and Roy (2017, pg. 53) in a (dis-) service to aspiring young academics quote a method for increasing an individual’s h-index without committing outright fraud. Horbach and Halffman (2017) point out that scientists and policymakers adopt different approaches to research integrity. Scientists discuss ‘integrity’ with a positive view of ‘good scientific practice’ that has an ethical focus, while policy people discuss ‘integrity’ with a negative view of ‘misconduct’ that has a legal focus.

The immediate problem with scientific integrity in the USA involves the current President and his preoccupation with defining ‘alternative facts’ (Goldman et al. 2017). But the problem is also a more general one, as illustrated by the long discussion carried out by conservation biologists who asked whether or not a scientist can also be an advocate for a particular policy (Garrard et al. 2016, Carroll et al. 2017).

The bottom line for ecologists and environmental scientists is important, and a serious discussion of scientific integrity should be part of every graduate seminar class. Scientific journals should become more open to challenges to papers that use faulty data, and maintaining high standards must remain number one on the list for all of us.

Carroll, C., Hartl, B., Goldman, G.T., Rohlf, D.J., and Treves, A. 2017. Defending the scientific integrity of conservation-policy processes. Conservation Biology 31(5): 967-975. doi: 10.1111/cobi.12958.

Edwards, M.A., and Roy, S. 2017. Academic research in the 21st century: Maintaining scientific integrity in a climate of perverse incentives and hypercompetition. Environmental Engineering Science 34(1): 51-61. doi: 10.1089/ees.2016.0223.correx.

Garrard, G.E., Fidler, F., Wintle, B.C., Chee, Y.E., and Bekessy, S.A. 2016. Beyond advocacy: Making space for conservation scientists in public debate. Conservation Letters 9(3): 208-212. doi: 10.1111/conl.12193.

Goldman, G.T., Berman, E., Halpern, M., Johnson, C. & Kothari, Y. (2017) Ensuring scientific integrity in the Age of Trump. Science, 355, 696-698. doi: 10.1126/science.aam5733

Hone, J., A. Drake, and C. J. Krebs. 2015. Prescriptive and empirical principles of applied ecology. Environmental Reviews 23:170-176. doi: 10.1139/er-2014-0076

Horbach, S.P.J.M., and Halffman, W. 2017. Promoting virtue or punishing fraud: Mapping contrasts in the language of ‘scientific integrity’. Science and Engineering Ethics 23(6): 1461-1485. doi: 10.1007/s11948-016-9858-y.

 

On Conservation

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The question of how ecology can guide decisions about conservation actions is a vexed one of which much has already been written with respect to conservation triage (Bottrill et al. 2009, Gerber 2016). The global question – what should we do now? – produces two extreme answers: (1) do nothing. The biodiversity on earth has gone through many climatic fluctuations imposed by geology and planetary physics and these forces are out of our hands. Or (2) we must protect all species because we do not know if they are important for ecosystem function. The government recognizes that (2) is impossible, and either reflects back to answer (1) or politely asks scientists to suggest what is possible to achieve with limited funding. John Wiens (2016) in an interesting discussion in the British Ecological Society Bulletin (December 2016, pp 38-39) suggests that two possible solutions to this conundrum are to get more funding for conservation to reduce this clear financial limitation, or secondly to move from the conservation of individual species to that of ecosystems. The problem he and many others recognize is that the public at large fall in love with individual species much more readily than with ecosystems. It is the same problem medical science often faces with contributions from wealthy people – attack individual diseases with my funding, not public health in general.

Ecologists face this dilemma with respect to their research agenda and research grants in general – what exactly can you achieve in 3-5 years with a small amount of money? If your research is species-specific, something useful can often be studied particularly if the threatening processes are partly understood and you adopt an experimental approach. If your research is ecosystem oriented and your funds are limited you must generally go to the computer and satellite ecology to make any short term research possible. This problem of larger scale = larger costs can be alleviated if you work in a group of scientists all addressing the same ecosystem issue. This still requires large scale funding which is not as easily obtained as ecologists might like. The government by contrast wishes more and more to see results even after only a few years, and asks whether you have answered your original question. The result is a patchwork of ecological data which too often makes no one happy.

If you want a concrete example, consider the woodland caribou of western Canada (Schneider et al. 2010). For these caribou Hebblewhite (2017) has clearly outlined a case in which the outcomes of any particular action are difficult to predict with the certainty that governments and business would be happy with. Many small herds are decreasing in size, and one path is to triage them, leaving many small herds to go extinct and trying to focus financial resources to save larger herds in larger blocks of habitat for future generations. The problem is the oil and gas industry in western Canada, and hence the battle between resources that are worth billions of dollars and a few caribou. Wolf control can serve as a short term solution, but it is expensive and temporary. Governments like action even if it is of no use in the long term; it makes good media coverage. None of these kinds of conservation decisions are scientific in nature, and must be policy decisions by governments. It flips us back into the continuum between options (1) and (2) in the opening paragraph above. And for governments policy decisions are more about jobs and money than about conservation.

The list of threatened and endangered species that make our newspapers are a tiny fraction of the diversity of species in any ecosystem. There is no question but that many of these charismatic species are declining in numbers, but the two larger questions are: will this particular species go extinct? And if this happens will this make any difference to ecosystem function? There is scarcely a single species of all that are listed as threatened and endangered for which ecologists have a good answer to either of these questions. So the fallback position to option (1) is that we have a moral obligation to protect all species. But this fallback position leads us even further out of science.

In the end we must ask as scientists what we can do with the understanding we have, and what more needs to be done to improve this understanding. Behind all this scientific research looms the elephant of climate change which we either ignore or build untestable computer models to make ‘predictions’ which may or may not occur, if only because of the time scales involved.

None of these problems prevents us from taking actions on conservation on the ground (Wiens 2016a). We know that, if we take away all the habitat, species abundances will decline and some will go extinct. Protecting habitat is the best course of action now because it needs little research to guide action. There is much to know yet about the scale of habitats that need preservation, and about how the present scale of climate change is affecting protected areas now. Short term research can be most useful for these issues. Long-term research needs to follow.

Bottrill, M.C., et al. (2009) Finite conservation funds mean triage is unavoidable. Trends in Ecology & Evolution, 24, 183-184. doi: 10.1016/j.tree.2008.11.007

Gerber, L.R. (2016) Conservation triage or injurious neglect in endangered species recovery. Proceedings of the National Academy of Sciences USA, 113, 3563-3566. doi: 10.1073/pnas.1525085113

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

Schneider, R.R., Hauer, G., Adamowicz, W.L. & Boutin, S. (2010) Triage for conserving populations of threatened species: The case of woodland caribou in Alberta. Biological Conservation, 143, 1603-1611. doi: 10.1016/j.biocon.2010.04.002

Wiens, J.A. (2016) Is conservation a zero-sum game? British Ecological Society Bulletin 47(4): 38-39.

Wiens, J.A. (2016a) Ecological Challenges and Conservation Conundrums: Essays and Reflections for a Changing World. John Wiley and Sons, Hoboken, New Jersey. 344 pp. ISBN: 9781118895108

University Conundrums

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Universities in Canada and the United States and probably in Australia as well are bedeviled by not knowing what they should be doing. In general, they all want to be ‘excellent’ but this is largely an advertising gimmick unless one wishes to be more specific about excellent in what? Excellent in French literature? Probably not. Excellent in the engineering that facilitates the military-industrial complex? Probably yes, but with little thought of the consequences for universities or for Planet Earth (Smart 2016). Excellence in medicine? Certainly, yes. But much of the advertisement about excellence is self aggrandisement, and one can only hope that underneath the adverts there is some good planning and thinking of what a university should be (Lanahan et al. 2016).

There are serious problems in the world today and the question is what should the universities be doing about these long-term, difficult problems. There are two polar views on this question. At one extreme, universities can say it is our mandate to educate students and not our mandate to solve environmental or social problems. At the other extreme, universities can devote their resources to solving problems, and thereby educate students in problem analysis and problem solving. But these universities will not be very popular since for any serious issue like climate change, many voters are at odds over what can and should be done, Governments do not like universities that produce scholarship that challenges their policies. So we must always remember the golden rule – “she that has the gold, makes the rules”.

But there are constraints no matter what policies a university adopts, and there is an extensive literature on these constraints. I want to focus on one overarching constraint for biodiversity research in universities – graduate students have a very short time to complete their degrees. Given a 2-year or 3-year time horizon, the students must focus on a short-term issue with a very narrow focus. This is good for the students and cannot be changed. But it is potentially lethal for ecological studies that are long-term and do not fit into the demands of thesis writing. A basic assumption I make is that the most important ecological issues of our day are long-term problems, at least in the 20-year time frame and more likely in the 50 to 100-year time frame. The solution most prevalent in the ecology literature now is to use short term data to produce a model to extrapolate short term data into the indefinite future by use of a climate model or any other model that will allow extrapolation. The result of this conundrum is that the literature is full of studies making claims about ecological processes that are based on completely inadequate time frames (Morrison 2012). If this is correct, at least we ought to have the humility to point out the potential errors of extrapolation into the future. We make a joke about this situation in our comical advice to graduate students: “If you get an exciting result from your thesis research in year 1, stop and do no more work and write your thesis lest you get a different result if you continue in year 2.”

The best solution for graduate students is to work within a long-term project, so that your 2-3 years of work can build on past progress. But long-term projects are difficult to carry forward in universities now because research money is in short supply (Rivero and Villasante 2016). University faculty can piggy-back on to government studies that are well funded and long-term, but again this is not always possible. Conservation ecology is not often well funded by governments either, so we keep passing the buck. Collaboration here between governments and universities is essential, but is not always strong at the level of individual projects. Some long-term ecological studies are led by federal and regional government research departments directly, but more seem to be led by university faculty. And the limiting resource is typically money. There are a set of long-term problems in ecology that are ignored by governments for ideological reasons. Some politicians work hard to avoid the many ecological problems that are ‘hot potatoes’ and are best left unstudied. Any competent ecologist can list for you 5 or more long-term issues in conservation biology that are not being addressed now for lack of money. I doubt that ideas are the limiting resource in ecology, as compared with funding.

And this leads us back in a circle to the universities quest for ‘excellence’. Much here depends on the wisdom of the university’s leaders and the controls on university funding provided by governments for research. In Canada for example, funding constraints for research excellence exist based on university size (Murray et al. 2016). How then can we link the universities’ quest for excellence to the provision of adequate funding for long-term ecological issues? As one recommendation to the directors of funding programs within the universities, I suggest listing the major problems of your area and of the world at large, and then fund the research within your jurisdiction by how well the proposed research matches the major problems we face today.

Lanahan, L., Graddy-Reed, A. & Feldman, M.P. (2016) The Domino Effects of Federal Research Funding. PLoS ONE, 11, e0157325. doi: 10.1371/journal.pone.0157325

Morrison, M.L. (2012) The habitat sampling and analysis paradigm has limited value in animal conservation: A prequel. Journal of Wildlife Management, 76, 438-450. doi: 10.1002/jwmg.333

Murray, D.L., Morris, D., Lavoie, C., Leavitt, P.R. & MacIsaac, H. (2016) Bias in research grant evaluation has dire consequences for small universities. PLoS ONE, 11, e0155876.doi: 10.1371/journal.pone.0155876

Rivero, S. & Villasante, S. (2016) What are the research priorities for marine ecosystem services? Marine policy, 66, 104-113. doi: 10.1016/j.marpol.2016.01.020

Smart, B. (2016) Military-industrial complexities, university research and neoliberal economy. Journal of Sociology, 52, 455-481. doi: 10.1177/1440783316654258

Biodiversity Conundrums

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Conservation ecologists face a conundrum, as many have pointed out before. As scientists we do not make policy. Most conservation problems are essentially a moral issue of dealing with conflicts in goals and allowable actions. Both the United States and Canada have endangered species legislation in which action plans are written for species of concern. In the USA species of concern are allotted some funding and more legal protection than in Canada, where much good material is written but funding for action or research is typically absent. What is interesting from an ecological perspective is the list of species that are designated as endangered or threatened. Most of them can be described colloquially as the “charismatic megafauna”, species that are either large or beautiful or both. There are exceptions of course for some amphibians and rare plants, but by and large the list of species of concern is a completely non-random collection of organisms that people see in their environment. Birds and butterflies and large mammals are at the head of the list.

All of this is fine and useful because it is largely political ecology, but it raises the question of what will happen should these rescue plans for threatened or endangered species fail. This question lands ecologists in a rather murky area of ecosystem function, which leads to the key question: how is ecosystem function affected by the loss of species X? The answer to this question depends very much on how you define ecosystem function. If species X is a plant and the ecosystem function measured is the uptake of CO2 by the plant community, the answer could be a loss of function, no change, or indeed an increase in CO2 uptake if species X for example is replaced by a weed that is more productive that species X. The answer to this simple question is thus very complicated and requires much research. For a hypothetical example, plant X may be replaced by a weed that fixes more CO2, and thus ecosystem function is improved as measured by carbon uptake from the atmosphere. But the weed may deplete soil nitrogen which could adversely affect other plants and soil quality. Again more data are needed to decide this. If the effect size is small, much research could provide an ambiguous answer to the original question, since all measurement involves errors.

So now we are in a box, a biodiversity conundrum. The simplest escape is to say that all species loss is undesirable in any ecosystem, a pontification that is more political than scientific. And, for a contrary view, if the species lost is a disease organism, or an insect that spreads human diseases, we will not mourn its passing. In practice we seem to agree with the public that the species under concern are not all of equal value for conservation. The most serious outcome of this consideration is that where the money goes for conservation is highly idiosyncratic. There are two major calls for funding that perhaps should not be questioned: first, for land (and water) acquisition and protection, and second, for providing compensation for the people whose livelihoods are affected by protected areas with jobs and skills that improve their lives. The remaining funds need to be used for scientific research that will further the cause of conservation in the broad sense. The most useful principle at this stage is that all research has a clear objective and a clear list of what outcomes can be used to judge its success. For conservation outcomes this judgement should be clear cut. Currently they are not.

When Caughley (1994) described the declining population paradigm and the small population paradigm he clearly felt that the small population paradigm, while theoretically interesting, had little to contribute to most of the real world problems of biodiversity conservation. He could not have imagined at the time how genetics would develop into a powerful set of methods of analysis of genomes. But with a few exceptions the small population paradigm and all the elegant genetic work that has sprung from it has delivered a mountain of descriptive information with only a molehill of useful management options for real world problems. Many will disagree with my conclusion, and it is clear that conservation genetics is a major growth industry. That is all well and good but my question remains as to its influence on the solution of current conservation problems (Caro 2008; Hutchings 2015; Mattsson et al. 2008). Conservation genetic papers predicting extinctions in 100 years or more based on low levels of genetic variation are not scientifically testable and rely on a law of conservation genetics that is riddled with exceptions (Nathan et al. 2015; Robinson et al. 2016). Do we need more untestable hypotheses in conservation biology?

Caro, T. 2008. Decline of large mammals in the Katavi-Rukwa ecosystem of western Tanzania. African Zoology 43(1): 99-116. doi:10.3377/1562-7020(2008)43[99:dolmit]2.0.co;2.

Caughley, G. 1994. Directions in conservation biology. Journal of Animal Ecology 63: 215-244. doi: 10.2307/5542

Hutchings, J.A. 2015. Thresholds for impaired species recovery. Proceedings of the Royal Society. B, Biological sciences 282(1809): 20150654. doi:10.1098/rspb.2015.0654.

Mattsson, B.J., Mordecai, R.S., Conroy, M.J., Peterson, J.T., Cooper, R.J., and Christensen, H. 2008. Evaluating the small population paradigm for rare large-bodied woodpeckers, with Implications for the Ivory-billed Woodpecker. Avian Conservation and Ecology 3(2): 5. http://www.ace-eco.org/vol3/iss2/art5/

Nathan, H.W., Clout, M.N., MacKay, J.W.B., Murphy, E.C., and Russell, J.C. 2015. Experimental island invasion of house mice. Population Ecology 57(2): 363-371. doi:10.1007/s10144-015-0477-2.

Robinson, J.A., Ortega-Del Vecchyo, D., Fan, Z., Kim, B.Y., and vonHoldt, B.M. 2016. Genomic flatlining in the endangered Island Fox. Current Biology 26(9): 1183-1189. doi:10.1016/j.cub.2016.02.062.

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