Category Archives: Judy Myers’ blogs

On Declining Insect Populations

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Judy Myers, Charles Krebs, Gergana Daskalova and Isla Myers-Smith

The rising concern about conservation issues is echoed in recent months by newspaper reports of collapses in insect populations world-wide: the “insect Armageddon”. As part of our general concern that the-devil-is-in-the-details, we want to discuss these reports within the general question of how we decide if this simple statement is correct or not, and what methods are needed to establish declining population trends.

We require four procedures to decide if a population or a series of populations are declining:

(1) Reliable census methods and appropriate statistical analyses must be used. This is not a trivial exercise. Results can be biased by the chance occurrence of particularly high numbers at the beginning of the data trend as in Seibold et al. (2019), the failure to correct for temporal pseudoreplication in data sets as pointed out by Daskalova et al. (2021) or by searching the literature only for studies of insect decline and then claiming to show widespread population declines as in Sánchez-Bayo et al. (2019). It is important to avoid biasing data toward a conclusion that declines are occurring. Increasing trends and examples showing no trend must be acknowledged and published to allow a true assessment.

(2) The taxonomic group of concern must be delineated since what applies to butterflies may or may not apply to carabid beetles. It can be difficult and time consuming to sort through samples to identify taxonomic groups. For this reason, the biomass of trap collections has been used as a surrogate for insect numbers in some studies (Hallman et al. 2019). This tells us nothing about population trends or diversity of different types of insects. Population data are required, and the biology of the focus group identified when considering causal mechanisms for population trends. For example, aquatic and terrestrial species are likely to respond to different environmental conditions and these must be separated (Van Klink et al., 2020).

(3) The scale of the study must be carefully outlined, whether it is 1 ha of grassland, a region, a country, or a continent. Lumping together results from studies done at different scales makes interpretation impossible. Accounting for scale in analyses is challenging, but detected trends in metrics such as species richness can differ markedly across scales (Vellend et al. 2017; Chase et al. 2019).

(4) The duration of the study must be related to the generation time of the insect group and population dynamics of those taxa. Many insects have a single generation a year and others multiple generations. Shorter time series are more variable (Daskalova et al. 2021), time trends in many insect populations are often more saw shaped than linear (Macgregor et al. 2019), and some insect species experience outbreaks or population cycles (Myers and Cory 2013).

These four requirements are not new, and many authors have discussed the details of these issues and how they play out in specific insect populations (Didham et al. 2020; Wagner 2020). A fifth requirement needs to be added when multiple studies are included in meta-analyses:

(5) All data inclusion must be scrutinized to determine if the four above requirements have been met before they are included in the meta-analysis.

Census methods for insect populations were presented long ago by Southwood (1966) in a classic book, updated in Southwood and Henderson (2000) and now reviewed recently in Montgomery et al. (2021). Montgomery et al. (2021) noted that even at this late date there is a general lack of standardization in insect monitoring methods, and that this standardization is essential if we are to track insect population or community changes. Statistical methods for time series data must be rigorous as pointed out by Daskalova et al. (2021).  The general message is that there is no one insect monitoring method that can apply to all species, and the scale of the study, along with the sampling effort needed for reliable inferences on population trends, must be decided well in advance of starting a monitoring study.

Newspaper articles dramatize the collapse of insect populations while the reality shown by detailed studies is much more nuanced. Much of the decline in insects could be traced to climate change, agricultural intensification, forestry, human population growth, urbanization and other factors (Wagner 2021). Consequently, it is important to state what the baseline for any evaluation is. The pure ecologist may wish to know how much insect populations have changed in areas where only one factor like climate change has operated. The agricultural insect ecologist may wish to know overall changes in the presence of all human and natural changes in the agricultural landscapes in which insects live (Laussmann et al. 2021). To find out the actual mechanisms behind the observed declines, a clear experimental protocol is necessary. As useful as monitoring is by itself, it can only provide weak evidence of mechanisms responsible for insect declines.

The restoration of individual species that are declining is more difficult than we might like. Warren et al. (2021) provide details of management changes that attempt to restore populations of the endangered British butterfly Hamearis lucina by landscape level habitat improvements. Funds for restoration will not be available at the scale needed for tropical and subtropical habitats losing insect diversity under stress from agricultural intensification (Raven and Wagner 2021).

The bottom line is that there are enough data now to be concerned about insect declines, but we must be careful not to cry that the “sky is falling” (Saunders et al. 2020). As in many issues with changes in populations and communities, census methods and experimental designs must be sharpened and standardized. Our take-home message is that any tests of insect population, abundance or biodiversity trends require rigorous methods of analysis before publication, or phoning the local newspaper.

Daskalova, G.N., A.B. Phillimore, and I.H. Myers‐Smith. 2021. Accounting for year effects and sampling error in temporal analyses of invertebrate population and biodiversity change: a comment on Seibold et al. 2019. Insect Conservation and Diversity 14:149-154. doi: 10.1111/icad.12468.

Didham, R.K., Basset, Y., Collins, C.M., Leather, S.R., et al. (2020). Interpreting insect declines: seven challenges and a way forward. Insect Conservation and Diversity 13, 103-114. doi: 10.1111/icad.12408.

Chase, J.M., McGill, B.J., Thompson, P.L., Antão, L.H., Bates, A.E., et al. 2019. Species richness change across spatial scales. Oikos 128:1079-1091. doi: 10.1111/oik.05968

Hallmann, C.A., et al. 2017. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12, e0185809. doi: 10.1371/journal.pone.0185809

Laussmann, T., Dahl, A., Radtke, A., 2021. Lost and found: 160 years of Lepidoptera observations in Wuppertal (Germany). Journal of Insect Conservation (in press). doi: 10.1007/s10841-021-00296-w

Macgregor, C.J., J. H. Williams, J.R. Bell, and C.D. Thomas. 2019. Moth biomass increases and decreases over 50 years in Britain. Nature Ecology & Evolution 3:1645-1649. doi: 10.1038/s41559-019-1028-6

Montgomery, G.A., M.W. Belitz, R.P. Guralnick, and M.W. Tingley. 2021. Standards and best practices for monitoring and benchmarking insects. Frontiers in Ecology and Evolution 8: 579193. doi: 10.3389/fevo.2020.579193.

Myers, J.H., Cory, J.S., 2013. Population cycles in forest Lepidoptera revisited. Annual Review of Ecology, Evolution, and Systematics 44, 565–592. https://doi.org/10.1146/annurev-ecolsys-110512-135858

Raven, P. H., and D. L. Wagner. 2021. Agricultural intensification and climate change are rapidly decreasing insect biodiversity. Proceedings of the National Academy of Sciences 118 (2): e2002548117. doi: 10.1073/pnas.2002548117. 

Sánchez-Bayo, F., and K. A. Wyckhuys. 2019. Worldwide decline of the entomofauna: A review of its drivers. Biological Conservation 232:8-27. doi: 10.1016/j.biocon.2019.01.020

Saunders, M.E., Janes, J.K. and O’Hanlon, J.C., 2020. Moving on from the insect apocalypse narrative: Engaging with evidence-based insect conservation. BioScience, 70(1):80-89. doi: 10.1093/biosci/biz143

Seibold, S., M. M. Gossner, N. K. Simons, N. Blüthgen, et. al. 2019. Arthropod decline in grasslands and forests is associated with landscape-level drivers. Nature 574:671-674. doi: 10.1038/s41586-019-1684-3.

Southwood, T.R.E. (1966) ‘Ecological Methods.’ (Methuen: London.)

Southwood, T.R.E. and Henderson, P.A. (2000) ‘Ecological Methods.’ (Blackwell Science: Oxford.) 575 pp.  ISBN: 0632054778

van Klink, R., Bowler, D.E., Gongalsky, K.B., Swengel, A.B., et al. (2020). Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417-420. doi: 10.1126/science.aax9931.

Vellend, M., Baeten, L., Becker-Scarpitta, A., Boucher-Lalonde, V., McCune, J.L., Messier, J., Myers-Smith, I.H. and Sax, D.F., 2017. Plant biodiversity change across scales during the Anthropocene. Annual Review of Plant Biology 68:563-586. doi: 10.1146/annurev-arplant-042916-040949 .

Wagner, D. L. 2020. Insect declines in the Anthropocene. Annual Review of Entomology 65:457-480. doi: 10.1146/annurev-ento-011019-025151.

Wagner, D.L., Grames, E.M., Forister, M.L., Berenbaum, M.R., and Stopak, D. (2021). Insect decline in the Anthropocene: Death by a thousand cuts. Proceedings of the National Academy of Sciences 118, e2023989118. doi: 10.1073/pnas.2023989118.

Warren, M.S., et al. (2021). The decline of butterflies in Europe: Problems, significance, and possible solutions. Proceedings of the National Academy of Sciences 118 (2), e2002551117. doi: 10.1073/pnas.2002551117.

Hypothesis testing using field data and experiments is definitely NOT a waste of time

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At the ESA meeting in 2014 Greg Dwyer (University of Chicago) gave a talk titled “Trying to understand ecological data without mechanistic models is a waste of time.” This theme has recently been reiterated on Dynamic Ecology Jeremy Fox, Brian McGill and Megan Duffy’s blog (25 January 2016 https://dynamicecology.wordpress.com/2016/01/25/trying-to-understand-ecological-data-without-mechanistic-models-is-a-waste-of-time/).  Some immediate responses to this blog have been such things as “What is a mechanistic model?” “What about the use of inappropriate statistics to fit mechanistic models,” and “prediction vs. description from mechanistic models”.  All of these are relevant and interesting issues in interpreting the value of mechanistic models.

The biggest fallacy however in this blog post or at least the title of the blog post is the implication that field ecological data are collected in a vacuum.  Hypotheses are models, conceptual models, and it is only in the absence of hypotheses that trying to understand ecological data is a “waste of time”. Research proposals that fund field work demand testable hypotheses, and testing hypotheses advances science. Research using mechanistic models should also develop testable hypotheses, but mechanistic models are certainly are not the only route to hypothesis creation of testing.

Unfortunately, mechanistic models rarely identify how the robustness and generality of the model output could be tested from ecological data and often fail comprehensively to properly describe the many assumptions made in constructing the model. In fact, they are often presented as complete descriptions of the ecological relationships in question, and methods for model validation are not discussed. Sometimes modelling papers include blatantly unrealistic functions to simplify ecological processes, without exploring the sensitivity of results to the functions.

I can refer to my own area of research expertise, population cycles for an example here.  It is not enough for example to have a pattern of ups and downs with a 10-year periodicity to claim that the model is an acceptable representation of cyclic population dynamics of for example a forest lepidopteran or snowshoe hares. There are many ways to get cyclic dynamics in modeled systems. Scientific progress and understanding can only be made if the outcome of conceptual, mechanistic or statistical models define the hypotheses that could be tested and the experiments that could be conducted to support the acceptance, rejection or modification of the model and thus to inform understanding of natural systems.

How helpful are mechanistic models – the gypsy moth story

Given the implication of Dwyer’s blog post (or at least blog post title) that mechanistic models are the only way to ecological understanding, it is useful to look at models of gypsy moth dynamics, one of Greg’s areas of modeling expertise, with the view toward evaluating whether model assumptions are compatible with real-world data Dwyer et al.  2004  (http://www.nature.com/nature/journal/v430/n6997/abs/nature02569.html)

Although there has been considerable excellent work on gypsy moth over the years, long-term population data are lacking.  Population dynamics therefore are estimated by annual estimates of defoliation carried out by the US Forest Service in New England starting in 1924. These data show periods of non-cyclicity, two ten-year cycles (peaks in 1981 and 1991 that are used by Dwyer for comparison to modeled dynamics for a number of his mechanistic models) and harmonic 4-5 year cycles between 1943 and1979 and since the 1991 outbreak. Based on these data 10-year cycles are the exception not the rule for introduced populations of gypsy moth. Point 1. Many of the Dwyer mechanistic models were tested using the two outbreak periods and ignored over 20 years of subsequent defoliation data lacking 10-year cycles. Thus his results are limited in their generality.

As a further example a recent paper, Elderd et al. (2013)  (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3773759/) explored the relationship between alternating long and short cycles of gypsy moth in oak dominated forests by speculating that inducible tannins in oaks modifies the interactions between gypsy moth larvae and viral infection. Although previous field experiments (D’Amico et al. 1998) http://onlinelibrary.wiley.com/doi/10.1890/0012-9658(1998)079%5b1104:FDDNAW%5d2.0.CO%3b2/abstract concluded that gypsy moth defoliation does not affect tannin levels sufficiently to influence viral infection, Elderd et al. (2013) proposed that induced tannins in red oak foliage reduces variation in viral infection levels and promotes shorter cycles. In this study, an experiment was conducted using jasmonic acid sprays to induce oak foliage. Point 2 This mechanistic model is based on experiments using artificially induced tannins as a mimic of insect damage inducing plant defenses. However, earlier fieldwork showed that foliage damage does not influence virus transmission and thus does not support the relevance of this mechanism.

In this model Elderd et al. (2013) use a linear relationship for viral transmission (transmission of infection on baculovirus density) based on two data points and the 0 intercept. In past mechanistic models and in a number of other systems the relationship between viral transmission and host density is nonlinear (D’Amico et al. 2005, http://onlinelibrary.wiley.com/doi/10.1111/j.0307-6946.2005.00697.x/abstract;jsessionid=D93D281ACD3F94AA86185EFF95AC5119.f02t02?userIsAuthenticated=false&deniedAccessCustomisedMessage= Fenton et al. 2002, http://onlinelibrary.wiley.com/doi/10.1046/j.1365-2656.2002.00656.x/full). Point 3. Data are insufficient to accurately describe the viral transmission relationship used in the model.

Finally the Elderd et al. (2013) model considers two types of gypsy moth habitat – one composed of 43% oaks that are inducible and the other of 15% oaks and the remainder of the forest composition is in adjacent blocks of non-inducible pines. Data show that gypsy moth outbreaks are limited to areas with high frequencies of oaks. In mixed forests, pines are only fed on by later instars of moth larvae when oaks are defoliated. The pines would be interspersed amongst the oaks not in separate blocks as in the modeled population. Point 4.  Patterns of forest composition in the models that are crucial to the result are unrealistic and this makes the interpretation of the results impossible.

Point 5 and conclusion. Because it can be very difficult to critically review someone else’s mechanistic model as model assumptions are often hidden in supplementary material and hard to interpret, and because relationships used in models are often arbitrarily chosen and not based on available data, it could be easy to conclude that “mechanistic models are misleading and a waste of time”. But of course that wouldn’t be productive. So my final point is that closer collaboration between modelers and data collectors would be the best way to ensure that the models are reasonable and accurate representations of the data.  In this way understanding and realistic predictions would be advanced. Unfortunately the great push to publish high profile papers works against this collaboration and manuscripts of mechanistic models rarely include data savvy referees.

D’Amico, V., J. S. Elkinton, G. Dwyer, R. B. Willis, and M. E. Montgomery. 1998. Foliage damage does not affect within-season transmission of an insect virus. Ecology 79:1104-1110.

D’Amico, V. D., J. S. Elkinton, P. J.D., J. P. Buonaccorsi, and G. Dwyer. 2005. Pathogen clumping: an explanation for non-linear transmission of an insect virus. Ecological Entomology 30:383-390.

Dwyer, G., F. Dushoff, and S. H. Yee. 2004. The combined effects of pathogens and predators on insect outbreaks. Nature 430:341-345.

Elderd, B. D., B. J. Rehill, K. J. Haynes, and G. Dwyer. 2013. Induced plant defenses, host–pathogen interactions, and forest insect outbreaks. Proceedings of the National Academy of Sciences 110:14978-14983.

Fenton, A., J. P. Fairbairn, R. Norman, and P. J. Hudson. 2002. Parasite transmission: reconciling theory and reality. Journal of Animal Ecology 71:893-905.

On Improving Canada’s Scientific Footprint – Breakthroughs versus insights

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

  1. Choose carefully.

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

  1. Aim for breakthroughs.

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

  1. Embrace risk.

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

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

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

  1. Recruit internationally.

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

  1. Resist incrementalism.

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

  1. Empower ambitious, risk-taking young scientists.

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

  1. Embrace diversity.

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

  1. Speak the truth.

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

  1. Consider the way funding agencies do business.

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

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

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

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

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

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

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

 

Bill 24 – A threat to biodiversity and ecosystems associated with agriculture in BC

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Bill 24 – a threat to biodiversity and ecosystems associated with agriculture in BC

buse 2010Agriculture has often been viewed as a threat to natural environments. This is clearly the case when forests are cut down to create pastures for grazing animals or fields for high value crops.  However, in a world already greatly manipulated by human activities, agricultural areas have increased in significance as refuges for organisms ranging from wildlife, birds, insects, plants, and soil microbes.  In addition agricultural lands can preserve wetlands, riparian habitats, streams, wind breaks and patches of forest.  These habitats and the organisms that dwell there benefit the agricultural industry and society in general by providing healthy, functioning ecosystems both on and adjacent to agriculture.

In British Columbia Canada, agricultural lands have been protected to some degree since 1973 by the Agricultural Land Reserve administered by the Agricultural Land Commission. Approximately 47,000 sq. km have been preserved for agricultural use either now or in the future. It has been a continual battle over the years to prevent lands from being removed from the land reserve and large tracts have been used in land claim settlements with First Nations and for a variety of development projects.  For the latter, the claim has been made that the land under contention is not sufficiently high quality for agriculture or the need for economic development is greater than the need for food security

A new threat to the ALR is currently before the BC Legislature, Bill 24.  The proposed act will make it easier for many non-agricultural uses to be developed on agricultural lands. It will seriously change the operation of the Agricultural Land Commission, and will allow changes in the classification of Agricultural lands to occur without a transparent, public process based on sound, scientifically derived information. This bill is deeply flawed and threatens the sustainability and security of agricultural production. It puts the survival of many species and ecosystems at risk. It is particularly ill timed as the future of agriculture will be greatly changed as the climate continues to warm and northern areas become more suitable for crops.

A number of ecologists have voiced their concerns about the impact of this proposed bill in a letter to Primer Christy Clark.  Their concerns are not only about the impacts on the sustainability of the agricultural industry, but also about the enormous threats to biodiversity, species at risk and the functioning ecosystems in British Columbia that would follow the reduction of the Agricultural Land Reserve. This letter is copied below.

From: The undersigned concerned scientist and naturalists

To: Premier Christy Clark

PO BOX 9041
STN PROV GOVT
VICTORIA, BC
V8W 9E1

Dear Premier Clark,

The British Columbia Government’s recently proposed changes to the Agriculture Land Commission (the Commission) Act greatly concerns many scientists for three reasons.

First, the revised changes to the governance and decision-making structure of the Commission reduces the ability for science to inform land use decisions. Second, the shift to divide the decision-making process regarding land classification into southern and interior zones will increase pressure to remove land from the reserve at a cost to the general good. And finally, the rationale for the division of the province into two jurisdictions, based simply on the value of the crops, overlooks the importance of other values associated with agricultural lands such as habitat for wildlife, endangered species, and contributions to ecosystem services.

Agricultural lands that occur in all regions of the province hold many values other than simply crop production. These areas contain wetlands, streams, ponds, riparian areas, woodlands, hedgerows, and uncultivated grasslands that are either adjacent to or integral to farm operations. These areas are instrumental in protecting functioning healthy ecosystems and in many cases, these diverse services help boost agricultural production. Many of the ecosystems encompassed by the Agricultural Land Reserve are rare in British Columbia and they provide habitat for a number of the Province’s most threatened or endangered species such as the burrowing owl, American badger, yellow-breasted chat, sage thrasher, Nooksack dace, and west slope cutthroat trout.  Other more common species that occur on Agricultural Land Reserve land are integral to agricultural production. These species range from soil microbes that sequester carbon below pasturelands, to birds such as the western meadowlarks, swallows, and common nighthawks whose populations are already declining. Species prized for hunting such as deer and elk also use so called marginal agricultural lands.  These species decline when agricultural lands are removed from production, marginal lands are converted to more intensive uses, or nonagricultural developments are permitted on agricultural lands. Allowing more nonagricultural uses on ALR land and the release of more lands from reserves will have the unintended consequence of threatening many important ecosystems and, by extension, many valuable species including species-at-risk.

Changing the current structure of the Commission to one that does not incorporate scientifically-derived information is deeply-flawed. Additionally, making changes to such an important piece of provincial legislation without consultation with the public, the agricultural industry, or scientists in general prevents relevant information and viewpoints to factor into informed decision-making. Allowing the agricultural industry to move forward with alternatives that incorporate science-based decision making within the current legislative framework are valid alternatives to altering the current reserve framework. These and other options should be explored because failing to incorporate alternate view points and scientifically derived information into the Commissions’ decision-making framework threatens the health of British Columbia’s ecosystems and endangers its biodiversity. The lack of a process to access and incorporate science-based information into the proposed framework threatens the biodiversity of British Columbia’s ecosystems and the sustainability and security of agricultural production in a changing climate.

We call upon the government of British Columbia to include scientifically derived information in the evaluation of the impacts of changes to Agricultural Land Reserve that may impact the health of British Columbia’s ecosystems and species at risk.

Sincerely,

The undersigned concerned scientists and naturalists

Authors

William Harrower RP Bio, PhD Candidate UBC

Judith Myers Professor Emeritus UBC

Sarah Otto, Fellow Royal Society of Canada, Director of Biodiversity Research Centre, Professor, UBC

Eric Taylor, Director Beaty Biodiversity Museum, Professor UBCElizabeth Kleynhans PhD Candidate UBC

 

 

Signatories

 

Angert Amy, Canada Research Chair in Conservation Ecology, Assistant Professor, University of British Columbia
Arcese Peter, FRBC Chair in Applied Conservation Ecology, Professor, University of British Columbia
Baker Sandra, Senior Environmental Assessment Specialist, RP Bio, n/a
Baute Gregory J. , PhD Candidate, University of British Columbia
Bears Heather, Wildlife Ecologist, PhD, Zoetica Wildlife Research Services
Bestbier Regina, Research Assistant, University of British Columbia
Beyers Rene, Associate Researcher, University of British Columbia
Bomke Art, Professor Emeritus, University of British Columbia
Bradfield Gary, Associate Professor, University of British Columbia
Brotz Lucas, PhD Student, University of British Columbia
Bunnell Fred, Professor Emeritus, University of British Columbia
Burton Philip J., NW Regional Chair, Associate Professor, UNBC
Burton Carla, Phd, Symbios Research and Restoration
Byers Sheila, Registered Professional Biologist, Beaty Biodiversity Museum
Cannings Richard, Senior Programs Biologist, Bird Studies Canada
Carefoot Tomas, Professor Emeritus, University of British Columbia
Christensen Villy, Professor, University of British Columbia
Clark Trisha, Research Technician, University of British Columbia
Cockle Kristina, NSERC Post-doctoral Fellow, Louisiana State University
Cooke James, Lecturer, University of British Columbia
Couch Brett, Instructor, University of British Columbia
Cumming Preston, Post-Doctoral Fellow, University of British Columbia
Davis Helen, Senior Wildlife Biologist, Artemis Wildlife Consultants
Doebeli Michael, Fellow of American Association for the Advancement of Science, Professor, University of British Columbia
Durand Ryan, Senior Ecologist, RP Bio. , Durand Ecological Ltd.
Dykstra Pamela, Master of Resource Management, RP Bio, PR Dykstra & Associates Resource Management Ltd.
Enns Katherine, MSc RP Bio., Delphinium Holdings Inc. (formerly Larkspur Biological Consultants Ltd.)
Fenneman James D., PhD Candidate, University of British Columbia
Fraser Lauchlan, Professor, Thompson Rivers University
Frid Leonardo, Systems Ecologist, Apex Resource Management Solutions Ltd.
Gibeau Pascale, RP Bio. PhD Student, Simon Fraser University
Gillis Elizabeth, Professor, Vancouver Island University
Gosselin Louis, Associate Professor, Thompson Rivers University
Hackinen Alisha, MSc Student, University of British Columbia
Halsey T. Gordon
Harrison Bruce, Registered Professional Biologist, Independent Practicing Biologist
Hauert Christoph , Associate Professor, University of British Columbia
Hehenberger Elisabeth, Post-Doctoral Fellow, University of British Columbia
Henry Greg, Professor, University of British Columbia
Hill Ryan, Professional Biologist, Azimuth Consulting Group Partnership
Hodges Karen, Associate Professor, University of British Columbia
Hoffos A Robin, Naturalist, Citizen
Houde Isabelle, MSc. RP Bio, Association of Professional Biology
Irwin Darren, Associate Professor, University of British Columbia
Javney Mohr Carmelle, Junior Fellow, The Chester Ronning Centre for the Study of Religion & Public Life
Jose Mereno Geraldes Armando, Research Associate, University of British Columbia
Kaytor Benita, MSc student, UNBC
Kerry Mara, Director of Science and Policy, David Suzuki Foundation
Koot Cathy, Research Coordinator, RP Bio, University of British Columbia
Krzic Maja, Professor, University of British Columbia
Ladell Jason, Registered Professional Biologist, Independent Practicing Biologist
Larsen Karl, Professor, Thompson Rivers University
Latimer Susan, Registered Professional Biologist, Independent Practicing Biologist
Lawson Julia, MSc student, University of British Columbia
Le Renard Ludovic, PhD Candidate, University of British Columbia
Leathem Jamie, MSc student, University of British Columbia
Leduc-Robert Genevieve, MSc student, University of British Columbia
Leering Gerry, Registered Professional Biologist, past President, Association of Professional Biology
Lehmann Crysta, n/a, University of British Columbia
Leskiw Leonardo, Senior Soil Scientist, Paragon Soil and Environmental Consulting
Letaw Alathea, PhD Candidate, University of British Columbia
Lewis Alan, Professor Emeritus, University of British Columbia
Lin Sherry, University of British Columbia
Lion Christine, Environmental Scientist, Stantec
Lussier Jason, University of British Columbia
Machmer Marlene M., Registered Professional Biologist, Pandion Ecological Research Ltd.
Mahon Todd, Wildlife Ecologist, RP Bio, Wildfor Consultants Ltd
Martone Patrick T., Associate Professor, University of British Columbia
Matthewson Lisa, Professor Emeritus, University of British Columbia
McCune Jenny L, Liber Ero Postdoctoral Fellow, University of Guelph
McGrath Kate , student, University of British Columbia
Millen Sandra, Sr. Instructor Emerita, University of British Columbia
Mobach Annmarie, self-employed
Moore Jonathan, Liber Ero Chair of Coastal Science and Management, Assistant Professor, Simon Fraser University
Morien Evan, Bioinformatician, MSc, University of British Columbia
Mosquin Daniel, Research Manager, University of British Columbia
Moyers Brook, PhD Candidate, University of British Columbia
Neill William E., Professor Emeritus, University of British Columbia
Neville John, President, BC Nature (Federation of BC Naturalists)
Osmond Matthew, PhD Candidate, University of British Columbia
Pollock Carol, Director of 1st Year Biology, Professor of Teaching, University of British Columbia
Power Damian, Registered Professional Biologist, Wolfhound Wildlife Services
Rahme Ann, Biologist, Fisheries and Oceans Canada
Reid Anya, PhD Student, University of British Columbia
Rieseberg Loren, Professor, University of British Columbia
Rodgers Thea, student, University of British Columbia
Rogic Sanja, Research Associate, Center for High-Throughput Sequencing
Rudman Seth, PhD Candidate, University of British Columbia
Ruskey Jennifer, MSc student, University of British Columbia
Salomon Anne, Assistant Professor, Simon Fraser University
Samuels Lacey, Botany Department Head, Professor, University of British Columbia
Scholer Micah, PhD Candidate, University of British Columbia
Seghers Ben, Lecturer (retired), Oxford
Shartau Ryan, PhD Candidate, University of British Columbia
Siegle Matthew, PhD Candidate, University of British Columbia
Smith Jackie, Senior Manager, RP Bio. P Ag., SLR Consulting Ltd
Snyder Joan, PhD, RP Bio. , Retired
Soto Marybel, MSc Student, University of British Columbia
Stafl Natalie, MSc Student, University of British Columbia
Starzomski Brain, Assistant Professor, University of Victoria
Steele Fiona, Senior Biologist, Diamond Head Consulting Ltd.
Suarez Adriana, PhD Candidate, University of British Columbia
Sullivan Tomas, Professor, University of British Columbia
Thiel Bryanna, MSc student, University of British Columbia
Thorley Joseph, PhD, RP Bio. , Poisson Consulting
Tonya Ramey, PhD Candidate, University of British Columbia
Turkington Roy, Professor, University of British Columbia
Wang Jessie, student, University of British Columbia
Wellwood Debbie, Wildlife Ecologist, RPBio, Raven Ecological Services
Werring John, Senior Science and Policy Advisor, MSc. RP Bio., David Suzuki Foundation
William Ramey, Professor of Teaching, University of British Columbia
Williams Jennifer, Assistant Professor, University of British Columbia
Worcester Robyn, Conservation Programs Manager, Stanley Park Ecology Society
Xue Xinxin, PhD Candidate, University of British Columbia
Zevit Pamela , Registered Professional Biologist, Adamah Consultants

 

 

 

Research funding for women

NSERC funding by gender

Success rates are similar, but women still get less

Judith Myers UBC

NSERC has over the years provided data on request for the Discovery Grant Program for Ecology and Evolution broken down by both gender and different categories of applicants, eg. established, new first renewals etc.  In 2008, I summarized these data for presentation at the Canadian Coalition of Women in Science, Engineering, Trades and Technology (CCWESTT). This can be found as “NSERC Discovery Grant Statistics for males and females 2002 – 2008 at http://ww.ccwestt.org/Home/tabid/36/Default.aspx. That analysis showed a consistent trend for women to receive smaller grants than men with the exception of new applicants in 2007 and 2008 for which grants for women were larger.

Here, I analyze the NSERC data from 2009 and 2013. I show that success rates for grant applications are similar between men and women; however, the trend for women to receive lower grant funding on average continues.

Figure 1

Figure 1. Proportion applicants successful in 2009 and 2013 competitions.  Numbers of applicants are given in the legend. “Renewal” is first time renewal and “first” includes those applying for the first time and applicants that were previously unsuccessful in their first attempt.  Horizontal lines indicate overall average success rate, 73% in 2009 and 63% in 2013. Number of applicants is at the top of the bar.

Figure 1 shows that the overall success rate in 2013 is approximately 10% lower than in 2009, the successes of males and females are similar, and the success rate across categories is similar although first renewal success is lower and is lowest for females. Given the importance of this stage for the establishment of the future careers of these applicants this trend is of concern.

Figure 2 nserc

Figure 2. Average grants of different categories of applicants for NSERC Discovery Grants in 2009 and 2013.  The horizontal line indicates the overall average grants grant size, $33 351 (grants $5028 less for females than males) in 2009 and $31 828 ($6650 less for females than males) in 2013.

Figure 2 shows that the trend seen in earlier data continues with grants of males being larger than those of females by a substantial amount.  A factor here is that there are no female high fliers who have substantially larger grants than the average, and overall median grants are about the same for males and females. I have not taken accelerator grants into consideration here.

Given that females are on average receiving approximately $6500 less than their male colleagues, it would be interesting to know how this is translated into productivity measured as the number of publications in one year.  For an indication of how publications relate to grant sizes, I selected individuals from the NSERC results for 2013 taking from a range of grant sizes but including those with the largest grants and a sampling from the lower grant sizes.  I then used Web of Science to determine the number of publications for the year 2012-2013 for each chosen individual.

Figure 3 nserc

Figure 3. Size of grant awarded in 2013 and number of publications in 2012-2013 for an arbitrary sample of grantees. Neither relationship is significant, but that for males is influenced by the high publication number for two of the male “high fliers”.

The lack of relationship between yearly publication rates and grant size shows that productivity does not relate strongly to funding success. No female received a grant of more than $50 000 in 2013 so the range of the data is less for them.  For males, high publication numbers for two “high fliers” cause a weak upward trend in the relationship of publications to funding, but average publication numbers for four “high fliers” pulls this relationship down.  For these selected data the average number of publications for males was 10.5 and for females 9.1.  Removing the data for “high fliers” in the male data sets results in a slightly higher grant size for males than for females but only 7 publications on average for males compared to 9 for females for similar funding levels. Although this is a small and selected data set, it likely reflects the overall pattern for little relationship between grant size and publication numbers.  Similarly Lortie et al. 2012 (Oikos 121: 1005–1008) found that for the mostly highly-funded North American ecologists and environmental scientists, citations per paper were not related to increased levels of funding although for NSERC funded researchers there was a weak relationship. Fortin and Currie (2013) found that the number of papers, highest times cited, and number of high impact articles were only weakly related to NSERC funding levels for Animal Biology, Chemistry and Ecology and Evolution (PLOS ONE, DOI: 10.1371). Missing from these analyses are the data for individuals who receive no funding.  Thus the reduced proportion of successful renewals in the current funding environment, and the slightly reduced success of first time renewals are not reflected in these evaluations of research productivity. A recent study of global patterns of publications and citations shows that women publish less than men particularly in areas in which research is expensive, they are less likely to participate in international collaborations and are less likely to be first or last authors on papers (Larivière et al. 2013. Nature 504:211 – 213). There are many factors involved here.

We do not have data on HQP numbers, a metric that is heavily weighted in the NSERC Discovery Grant evaluation.  It is likely that the reduced funding level for females results in fewer HQP for them and this could have a strong impact on average funding from NSERC and publication numbers in the future.

In conclusion the new system of Discovery Grant evaluation appears to result in more similar levels of funding across categories but does not remove the bias towards larger grants on average for males. The impact on research productivity of the 37% of applicants that receive no funding as a result of the lower success rate is not easy to evaluate, but data do not support the hypothesis that higher funding for fewer individuals increases Canada’s research productivity.

Models need testable predictions to be useful

2 Replies

It has happened again.  I have just been to a seminar on genetic models – something about adaptation of species on the edges of their ranges.  Yes this is an interesting topic of relevance to interpreting species’ responses to changing environments.  It ended by the speaker saying something like, “It would be a lot of work to test this in the field”. How much more useful my hour would have been spent if the talk had ended with “Although it would be difficult to do, this model makes the following predictions that could be tested in the field,” or “The following results would reject the hypothesis upon which this model is based.”

Now it is likely that some found these theoretical machinations interesting and satisfying in some mathematical way, but I feel that it is irresponsible to not even consider how a model could be tested and the possibility (a likely possibility at that) that it doesn’t apply to nature and tells us nothing helpful about understanding what is going to happen to willow or birch shrubs at the edge of their ranges in the warming arctic (for example).

Recommendation – no paper on models should be published or talked about unless it makes specific, testable predictions of how the model can be tested.

Why I am Bored with Biodiversity and Ecosystem Services

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Ecosystem services have become the flavour of the month and already it seems tired and bland.  “Biodiversity must be preserved for its ecosystem services” but making the tie between diversity and services has been elusive and will continue to be so. A body of literature has accumulated on the results of small-scale experiments in which plant diversity is manipulated and some service, let’s say productivity, is monitored. In some cases a relationship is found − more species more productivity; but not always. A rancher who wants to increase the productivity of her rangeland would be more inclined to plant to a monoculture of a highly productive grass. For example the introduced species, Crested Wheat Grass (Agropyron cristatum), was widely used in British Columbia in the early 20th century. Cheat grass (Bromus tectorum), another exotic species (if we are talking about North America) is expanding into rangeland and while it might increase the diversity, it reduces the productivity for forage.

Recently Mark Vellend (TREE 29(3): 138, March 2014) reviewed a book by Donald Maier, “What’s so Good about Biodiversity? A Call for Better Reasoning about Nature’s Value. “(Springer 2012). The take home message of this book is that the biodiversity−ecosystem services rationale for protecting biodiversity does not always hold and more species does not necessarily translate into more food or less disease.  It is time to get rid of platitudes and to confront our biases in a critical manner when it comes to biodiversity.

Further to this topic, in December 2013 the first meeting was held of the budding International Panel on Biodiversity and Ecosystem Services. It will focus on the following topics:

1) Task force on capacity building
2) Task force on indigenous and local knowledge systems
3) Task force on knowledge and data
4) Development of a guide to the production and integration of assessments from and across all levels
5) Assessment on pollination and pollinators associated with food production
6) Methodological assessment on scenario analysis and modeling of biodiversity and ecosystem services
7)  Methodological assessment on the conceptualization of values of biodiversity and nature’s benefits to people
8) Development of a catalogue of policy support tools and methodologies and providing guidance on how further development of such tools and methodologies could be promoted and catalyzed

Given the involvement of 115 countries it will be interesting to track the success of this panel.  Note that pollination and pollinators are identified as a specific ecosystem service. Critical experimental ecologists should be involved if this panel is to be productive in a meaningful way and, if not on the panel, they should track its progress and comment accordingly. Stay tuned for further updates.