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Avian mortality from pesticides used in agriculture in Canada


Abstract and Figures

A serious impediment to estimating the impact of pesticides on migratory birds is the lack of comprehensive pesticide use data. Canada is one of the few developed countries that do not collect such information. A clear recommendation of this report (and of many others) is that Canada should establish a pesticide use reporting system. Based on areas in various crop types and on low, average and high pesticide use patterns for those same crops in the US, our best estimate for the incidental take from pesticides in Canada is between 0.96 and 4.4 million bird annually. This estimate assumes a kill rate of approximately 0.52 - 2.4 birds per hectare - the range from several industry studies carried out in typical farmland. A very approximate expert opinion is that a nest could be lost for every 4 birds killed. Given average nest success rates, this would add 50% more individuals to the above total. The number of birds killed by pesticides has been decreasing as more toxic products are slowly being replaced for human health reasons. However, several potential impacts of pesticides, namely reproductive and indirect effects are not included in this total. Large kills of migrating birds are also not considered here although this would be more of a problem for a full accounting of pesticide impacts under US conditions than for Canada. Approximately half of the total estimated kill is in Saskatchewan. The impact from pesticides is thought to be a clear contribution to the steep decline shown by several of grassland/farmland species. Because birds are killed on the breeding grounds, and because both adults and nests are vulnerable, this impact is proportionately higher than similar estimates derived for other sources of mortality. Mitigation of kills is relatively easy. The products that have a high probability of causing avian mortality have been identified. In most cases, substitution products of lower toxicity to birds already exist. Regulatory inaction is the only impediment to a reduction of the direct incidental take. Chronic and indirect effects will be slightly harder to mitigate although here also, much information exists on which products carry the highest risk.
Annual mortality of Canadian birds due to human activities (log-scale). Panel A shows stage-specific estimates for each activity, according to whether entire nests, single eggs/nestlings, or mobile individuals were killed, as in original papers and reports. Values include both means and medians, and error bars represent both confidence limits (90% or 95%) and maximum/minimum ranges, as originally presented. Panel B shows converted mortality estimates for each activity (median with 90% confidence limits), where stage-specific kill totals have been converted to the equivalent number of potential adult breeders based on a stochastic model incorporating species-composition and demography. Hollow symbols indicate mortality only estimated for part of Canada or for a limited number of species, and thus where total Canada-wide cross-taxa mortality is likely much higher than these estimates. Panel C shows these same converted estimates (median with 90% confidence limits), pooled across related activities (cats: feral and pet; transportation: vehicle-collisions, road maintenance, and chronic ship-source oil; buildings: collisions with all 3 types; power: transmission-line collisions, hydro reservoirs, electrocutions, transmission-line maintenance, and wind energy; agriculture: haying and pesticides; harvest: migratory and nonmigratory birds; fisheries: all gear types; oil and gas: all terrestrial and marine sources; mining: both pits/quarries and metals/minerals), as well as the original single-source values for forestry and communication towers. Values in all panels are ranked in descending order according to the converted kill totals. See text and Appendix 2 for citations of papers and reports used as data sources.
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Copyright © 2013 by the author(s). Published here under license by the Resilience Alliance.
Calvert, A. M., C. A. Bishop, R. D. Elliot, E. A. Krebs, T. M. Kydd, C. S. Machtans, and G. J. Robertson.
2013. A synthesis of human-related avian mortality in Canada. Avian Conservation and Ecology 8(2): 11.
Synthesis, part of a Special Feature on Quantifying Human-related Mortality of Birds in Canada
A Synthesis of Human-related Avian Mortality in Canada
Synthèse des sources de mortalité aviaire d’origine anthropique au
Anna M. Calvert, Christine A. Bishop 1, Richard D. Elliot 1, Elizabeth A. Krebs 1, Tyler M. Kydd 2, Craig S. Machtans 2
and Gregory J. Robertson 1
ABSTRACT. Many human activities in Canada kill wild birds, yet the relative magnitude of mortality from different sources
and the consequent effects on bird populations have not been systematically evaluated. We synthesize recent estimates of avian
mortality in Canada from a range of industrial and other human activities, to provide context for the estimates from individual
sources presented in this special feature. We assessed the geographic, seasonal, and taxonomic variation in the magnitude of
national-scale mortality and in population-level effects on species or groups across Canada, by combining these estimates into
a stochastic model of stage-specific mortality. The range of estimates of avian mortality from each source covers several orders
of magnitude, and, numerically, landbirds were the most affected group. In total, we estimate that approximately 269 million
birds and 2 million nests are destroyed annually in Canada, the equivalent of over 186 million breeding individuals. Combined,
cat predation and collisions with windows, vehicles, and transmission lines caused > 95% of all mortality; the highest industrial
causes of mortality were the electrical power and agriculture sectors. Other mortality sources such as fisheries bycatch can have
important local or species-specific impacts, but are relatively small at a national scale. Mortality rates differed across species
and families within major bird groups, highlighting that mortality is not simply proportional to abundance. We also found that
mortality is not evenly spread across the country; the largest mortality sources are coincident with human population distribution,
while industrial sources are concentrated in southern Ontario, Alberta, and southwestern British Columbia. Many species are
therefore likely to be vulnerable to cumulative effects of multiple human-related impacts. This assessment also confirms the
high uncertainty in estimating human-related avian mortality in terms of species involved, potential for population-level effects,
and the cumulative effects of mortality across the landscape. Effort is still required to improve these estimates, and to guide
conservation efforts to minimize direct mortality caused by human activities on Canada’s wild bird populations. As avian
mortality represents only a portion of the overall impact to avifauna, indirect effects such as habitat fragmentation and alteration,
site avoidance, disturbance, and related issues must also be carefully considered.
RÉSUMÉ. Au Canada, de nombreuses activités d’origine anthropique entraînent la mort d’oiseaux sauvages, mais l’ampleur
relative de la mortalité selon les diverses sources et leurs conséquences sur les populations d’oiseaux n’ont pas été évaluées
systématiquement. Nous avons compilé des estimations récentes de mortalité aviaire au Canada causée par des activités
industrielles et d’autres origines anthropiques afin de mettre en contexte les estimations calculées pour chacune des sources de
mortalité présentées dans ce numéro spécial. Nous avons évalué la variation géographique, saisonnière et taxinomique de
l’ampleur de la mortalité à l’échelle nationale, de même que les effets sur les populations d’espèces ou de groupes dans l’ensemble
du Canada. Nous avons ensuite combiné ces estimations dans un modèle stochastique de mortalité spécifique au stade de vie.
L’étendue des estimations de la mortalité par les diverses sources couvre plusieurs ordres de grandeur et les oiseaux terrestres
sont le groupe le plus affecté en termes de nombre. Dans l’ensemble, nous avons estimé qu’approximativement 276 millions
d’oiseaux et 2 millions de nids sont détruits chaque année au Canada, soit l’équivalent de plus de 188 millions d’individus
nicheurs. La prédation par les chats et les collisions mortelles avec les fenêtres, les véhicules et les lignes de transmission ont
été collectivement responsables de > 95 % de la mortalité; les sources industrielles de mortalité les plus importantes ont été les
secteurs de la production d’énergie et de l’agriculture. Par ailleurs, les sources de mortalité comme les prises accidentelles par
les pêcheries peuvent avoir d’importants impacts locaux ou propres à une espèce, mais ces impacts sont relativement faibles à
l’échelle nationale. Les taux de mortalité variaient selon les espèces et les familles au sein des principaux groupes d’oiseaux,
soulignant le fait que la mortalité n’est pas simplement proportionnelle à l’abondance. Nous avons aussi constaté que la mortalité
n’est pas uniforme dans l’ensemble du pays : les sources de mortalité les plus importantes coïncident avec les foyers de population
1Environment Canada, Wildlife Research Division, Wildlife and Landscape
Science Directorate, 2Environment Canada, Canadian Wildlife Service
Avian Conservation and Ecology 8(2): 11
humaine, alors que les sources industrielles sont concentrées dans le sud de l’Ontario, en Alberta et dans le sud-ouest de la
Colombie-Britannique. De nombreuses espèces sont donc vraisemblablement vulnérables aux effets cumulatifs des multiples
impacts de sources anthropiques. Notre évaluation confirme aussi les grandes incertitudes liées à l’estimation de la mortalité
aviaire d’origine anthropique en matière d’espèces touchées, d’effets potentiels sur le plan des populations et d’effets cumulatifs
de la mortalité à l’échelle du paysage. Les efforts doivent être poursuivis afin d’améliorer ces estimations et d’orienter les actions
de conservation pour minimiser la mortalité directe causée par les activités d’origine anthropique sur les populations aviaires
du Canada. Puisque la mortalité aviaire ne représente qu’une partie de l’ensemble des impacts sur l’avifaune, les effets indirects
tels que la fragmentation et la perturbation d’habitats, l’évitement de sites précis, le dérangement et autres enjeux connexes –
doivent également être considérés attentivement.
Key Words: bird mortality; cats; collisions; human impacts; incidental take; industry; population effects
Several billion birds from over 400 species breed each year in
Canada (Blancher 2002), in a wide variety of habitats.
Landbirds, i.e., songbirds, raptors, upland gamebirds,
represent most of the birds in Canada and tend to have large
and widespread populations. Aquatic birds, such as waterfowl,
seabirds, shorebirds, and inland waterbirds, occupy freshwater
and marine habitats across the country. Birds occupy diverse
niches across Canada that overlap substantially with human
activities, and so are vulnerable to a large range of human-
related stressors. The recent State of Canada’s Birds report
(NABCI-Canada 2012) highlighted conservation efforts that
have contributed to increases in waterfowl and raptor
populations, but shorebirds, grassland birds, and aerial
insectivores have experienced rapid declines, some of which
are attributed to human-driven habitat change and mortality
across North America over the past 40 years (NABCI-Canada
Direct mortality resulting from human activities may have
important consequences, particularly when it is additive to
natural mortality, i.e. if individuals killed would have
otherwise survived (Anderson and Burnham 1976).
Agricultural practices, for example, have been identified as a
factor in declines of Northern Pintail (Anas acuta; Miller and
Duncan 1999, Prairie Habitat Joint Venture 2008) and
Bobolink (Dolichonyx oryzivorus; COSEWIC 2010) as well
as U.S. grassland birds (Mineau and Whiteside 2013), while
reduced juvenile survivorship and population declines of
urban songbirds have been linked to predation by cats (Crooks
and Soulé 1999, Balogh et al. 2011). Quantification of the
magnitude of human-related avian mortality, and its
population-level effects on Canada’s birds, is essential for
directing management and conservation actions and for
prioritizing future research directions (Loss et al. 2012);
especially when considered in conjunction with indirect
stressors such as habitat alteration and climate change.
Preventing and minimizing human-related mortality to birds,
their nests, and eggs is widely supported by environmental
legislation in Canada. Federal and provincial governments are
responsible for the protection, conservation, and management
of birds under the federal Migratory Birds Convention Act (S.
C. 1994, c. 22), the federal Species at Risk Act (S.C. 2002, c.
29) and various provincial wildlife Acts. These laws generally
prohibit the destruction of nests and eggs, and the “take” or
killing of individual birds. Permitting systems exist to manage
direct mortality due to hunting or while preventing damage
and danger to the public, but provisions or systems to authorize
inadvertent destruction of nests or birds as a consequence of
anthropogenic activities, often called ‘incidental take,’ are
applicable only to limited species or circumstances. Activities
that may destroy nests or birds are currently managed through
compliance promotion and by providing relevant information,
e.g., timing of breeding seasons, key migration periods and
pathways, to industrial sectors. This information allows the
development and adoption of measures that minimize the risk
of inadvertent destruction of nests and eggs, or killing of
Some sources of human-related avian mortality are well-
quantified, such as the regulated sport harvest of game birds,
but the magnitudes of most sources are imprecise or unknown.
In particular, those affecting a few birds at a time, e.g., cat
predation or building collisions, may often be overlooked
because their local effects are rarely extrapolated nationally.
Therefore, the number of birds killed annually in Canada as a
result of human activities is poorly known, as are any resulting
effects on populations. Despite limitations imposed by small-
scale studies, nonrandom sampling designs, and an absence
of experimental controls (Loss et al. 2012), preliminary
estimates of human-related bird mortality at national- or
continental-level scales can be highly informative. For
instance, mortality from collisions with communication
towers results in a total annual kill across the U.S. and Canada
of about 6.8 million birds (Longcore et al. 2012), include
disproportionately large impacts on certain species, many of
conservation concern (Longcore et al. 2013). These studies
can further highlight the susceptibility of particular bird groups
to certain mortality sources, such as the vulnerability of long-
distance or nocturnal migrants to collisions with towers and
buildings (Klem 2009, Manville 2009, Arnold and Zink 2011)
or of auks to bycatch in gill nets (Piatt et al. 1984).
The papers presented in this special feature of Avian
Conservation and Ecology reflect the current scientific
Avian Conservation and Ecology 8(2): 11
understanding of the magnitude of human-related bird
mortality in Canada, based on data collected from a variety of
industrial and other activities. Each paper reports an estimate
of the total annual loss of birds, nests, or eggs, and considers
the likelihood of population-level effects on species in Canada.
In this synthesis, we compare the relative contribution of each
source of mortality, including several estimates that are
unpublished or were published recently elsewhere, and
consider the implications of the total kill from all sources.
Specifically, this synthesis aims to (i) identify, quantify, and
compare sources of human-related avian mortality in Canada,
(ii) explicitly model the sources of uncertainty in the mortality
estimates, (iii) identify the remaining gaps in the current
knowledge of threats to Canadian bird populations, and (iv)
thereby help to prioritize research, policy, management, and
conservation actions aimed at understanding and reducing
human-related bird mortality in Canada.
Sources of mortality
We synthesized estimates of the magnitude of human-related
avian mortality in Canada from major industrial sectors and
nonindustrial or public activities that we believe kill
substantial numbers of birds. Initial estimates were developed
in a series of reports prepared for Environment Canada. Nine
of these are found in this special feature, namely mortality
caused by: collisions with vehicles (Bishop and Brogan 2013),
cats (Blancher 2013), marine industries, i.e., offshore oil and
gas, commercial fisheries (Ellis et al. 2013), commercial
forestry (Hobson et al. 2013), collisions with windows in
buildings (Machtans et al. 2013), collisions with power
transmission lines (Rioux et al. 2013), mechanical agricultural
activities such as haying or mowing, cultivation, and harvest
(Tews et al. 2013), terrestrial oil and gas (Van Wilgenburg et
al. 2013), and wind power (Zimmerling et al. 2013). Estimates
from communication towers appear elsewhere (Longcore et
al. 2012). Reports on several other anthropogenic activities
with more limited data are cited here as unpublished works
(roadside maintenance: D. Abraham, D. Pickard, and C.
Wedeles, unpublished manuscript; agricultural pesticides: P.
Mineau, unpublished manuscript; mining: J. Williams,
unpublished manuscript; electrical and hydro power
generation: J.-P. L. Savard and S. Rioux, unpublished
manuscript; Appendix 1). Unless otherwise specified, the
information for each source presented in this synthesis is
drawn directly from these papers and reports.
Published mortality estimates for three other activities are also
presented for comparison. Sport-hunting totals for migratory
game birds in Canada from years 2000-2011 were obtained
from the National Harvest Survey data base (http://www.cws- Data on total annual
harvest of nonmigratory game birds, mainly Galliformes, were
obtained from provincial and territorial government web sites
and representatives. We also include an estimate of seabird
mortality from chronic ship-source oil pollution in the
northwest Atlantic from the late 1990s (Wiese and Robertson
We were unable to include several additional sources of
human-related mortality that may be important to Canadian
bird populations. A recent assessment of livestock impacts (B.
Bleho, N. Koper, and C. S. Machtans, unpublished
manuscript) found both positive effects of vegetation
management and negative effects of trampling on bird nests,
estimating a loss of ~1.5% of nests at a local scale, but is not
included here because it did not quantify total mortality. We
also did not calculate mortality and nest destruction from forest
harvesting on private lands. Canada’s National Forestry
Database ( indicates that private land
harvest accounts for ~19% of the total annual volume of wood
harvested from all lands in Canada, but we did not assess
whether harvest timing or bird densities were similar to those
calculated for commercial harvest. We found little published
information on the magnitude of avian mortality in Canada
from aircraft-strikes, and impacts from large-scale tailings
ponds remain uncertain (Timoney and Ronconi 2010),
although the number of birds killed annually by these sources
is expected to be small. Recent evidence also indicates
potentially important population-level effects of rodenticides
on birds of prey (Thomas et al. 2011), but this source of
mortality was not considered here. Effects of the aquaculture
industry were initially assessed because entanglements with
exclusion nets or nets associated with farms are potential
sources of mortality (Price and Nickum 1995). However, this
mortality source has not been documented in Canada, and the
consensus was that aquaculture currently causes very limited
direct bird mortality. Information on indirect impacts of
aquaculture development on marine bird populations is also
limited, and shellfish aquaculture may sometimes benefit
certain waterfowl species (Zydelis et al. 2006, 2009). As a
result, aquaculture is not considered further. Finally, we do
not include estimates of bird bycatch in freshwater fisheries
although the documentation of large kills suggests this is an
important information gap (e.g., Ellarson 1956).
Comparing mortality estimates between sources
Human activities can affect birds at different stages of their
annual cycles. Activities that alter habitat during the breeding
season, such as forestry and agricultural mowing, tend to
destroy nests, eggs and young. Many other sources cause direct
mortality of breeding adults, subadults, and juvenile birds,
such as fishing or collisions with cars or buildings. We present
total mortality estimates by the life stage where it occurs, to
highlight differences among sources.
We used the methodology of Hobson et al. (2013) and Van
Wilgenburg et al. (2013) to develop a stochastic simulation
model that expresses stage-specific losses as an equivalent
Avian Conservation and Ecology 8(2): 11
loss of potential adult breeders. This enabled a comparison of
the effects of mortality affecting species at different life stages.
In addition to allowing comparison of mortality across
sources, this model explicitly quantified and combined the
various sources of uncertainty in current mortality estimates.
An advantage of this modeling approach is that it allowed us
to combine data with various measures of central tendency
and spread (means, medians, min-max ranges, confidence
limits). These modeled values were also used to assess
population-level effects of mortality.
The stochastic model controlled both for effects at differing
life stages and for variation in life history strategies by
converting all individuals to the potential breeding adult stage.
However, we were unable to control for variation in time
needed to reach those stages because longer lived and low-
fecundity species take longer to reach breeding age, making
populations slower to recover from perturbations. Our analysis
also did not assess the effects of activities reducing future
productivity through habitat loss or alteration, e.g.,
unreclaimed oil and gas clearings in forest, which may be a
significant consequence of some of the industrial activities
considered here. Our analysis does enable direct comparisons
of mortality across various sources, which should be most
reliable when focused on comparisons of sources that affect
groups of species with similar life history characteristics. Most
importantly, these comparisons of numbers killed do not take
into account differences in population sizes of species, or
species groups.
Stochastic model to derive estimate of potential adult
breeders killed
Converting estimates of stage-specific losses to potential adult
breeders using the stochastic model involved the following
steps. First, we compiled estimates of stage-specific mortality
(nest, egg/nestling, or independent bird) for each mortality
source, including any information on age-composition (for
independent birds killed) and species-group composition of
the kill (see Appendix 2 for details). Additional author
feedback was sought for some sources, especially regarding
estimates of approximate species-group or age composition
of the kill.
Next, unless exact values were available, probability
distributions were assigned to all values for stage-specific kill
totals, age-ratios, and species-group composition (see
Appendix 2, Table A2.1). Kill totals from individual papers
generally included some measure of central tendency (mean,
median, or midpoint) and data spread (confidence interval or
min-max range) that were converted to values required to
model a log-normal distribution (mean µ and standard
deviation σ). We modeled kill estimates as log-normal
distributions because these estimates were all based on some
multiplicative extrapolation. Age-ratios were modeled in
various ways; draws from a binomial distribution were used
when proportions were reasonably well known, beta
distributions were used when estimated variances in
proportions were available, and uniform distributions were
used when only minimum and maximum values were reported.
Similar distributions were used for species-group proportions,
except that multinomial distributions were used when more
than two species-groups were affected. For sport harvest of
migratory birds, detailed data on age-ratios of the kill were
available for ducks, geese, and shorebirds (snipe and
woodcock), and age-ratio data for snipe and woodcock were
applied to other species (doves, pigeons, rails, and cranes).
Age-ratios were not needed for the harvest for upland
nonmigratory game birds (Galliformes), because juvenile and
adult nonbreeding season survivorship probabilities are
comparable for these birds. Age at first breeding was assumed
to be the second year of life for all species groups except
seabirds, which were assumed to breed in their fifth year.
Demographic rates, with associated measures of data spread
where available, were collated for each species group; these
included clutch size, nest success, hatchability (or hatch
success), survival of young to fledging, overwinter
survivorship of juveniles, and adult survivorship. Note that in
some instances only the product of several parameters was
available, e.g., a general productivity value that equaled clutch
size × hatching success × survival of hatchlings to fledgling
(see Appendix 2, Table A2.2). For landbirds, except
nonmigratory game birds, we used the values already collated
in Hobson et al. (2013), with adult survival rates obtained from
Johnston et al. (1997). All other demographic rates were
obtained from literature values for species considered
representative of each species group (Appendix 2, Table
A2.2). For shorebirds, we chose values from two larger bodied
upland nesting species, as these species are more likely to be
affected by the mortality sources considered, i.e., mowing and
collisions, compared to smaller Arctic-breeding migrants.
When a particular value was not available, notably overwinter
survival of hatch-year birds (So), this value was estimated using
the other vital rates available, assuming a stable population
(So = (1- Sa)/F), where Sa is adult survival and F is fecundity
(number of independent young produced). A variety of
distributions was used to model these vital rates. For instance,
beta distributions were used for well-estimated parameters,
draws from uniform distributions were used when uncertainty
was high and only minimum and maximum values were
available, and random draws from a collection of rates were
used for landbirds and shorebirds where a number of estimates
were available. See Appendix 2 for additional details on vital
rates used for each species group.
Finally, these values and distributions were used to estimate
the equivalent number of potential adult breeders that would
be removed from the population, based on the stage-specific
kill estimates. For example, for an activity that kills eggs and
nestlings at the start of the breeding season, draws from the
Avian Conservation and Ecology 8(2): 11
distribution of total kill of eggs for a given species group were
multiplied by draws for estimates of nest success, hatch
success, survival of young to fledging, and overwinter survival
for that species group. Models were run 100,000 times, and
various descriptive statistics of the resulting distributions were
extracted. We present medians with 90% intervals, to allow
direct comparison of the numbers presented for forestry
(Hobson et al. 2013) and terrestrial oil and gas (Van
Wilgenburg et al. 2013). Note that no conversion was
necessary for these two sectors because the authors directly
converted their estimates of nest losses to the equivalent loss
of potential adult breeders.
Extent, scale, and scope of mortality
We tabulated the season when most human-related mortality
occurs (spring, breeding, fall, winter) in Canada for each of
the main groups (landbirds, seabirds, shorebirds, waterbirds,
waterfowl) to better understand the timing and extent of
mortality across Canadian bird populations. We assigned a
qualitative score of ‘no/little known effect,’ ‘some effect,’ or
‘large effect’ to each source/group/season combination, based
on the information in each paper or report and feedback from
their authors. Generally, a ‘large effect’ score was assigned
when a particular species group was clearly identified as being
frequently killed during a given season, whereas ‘some effect’
was assigned to species groups and seasons that were
peripherally affected. Note that factors that kill birds while
they are outside of Canada, including human-caused mortality
to migrants, were not included in this assessment.
To quantify the relative population impact of differing sources
of human-related mortality (hereafter ‘population-level
impacts’), we compared the estimated mortality to the total
abundance of individual populations, species, or families
where data were available at that resolution; in some cases,
mortality data were not available below the level of broad
taxonomic group. For wind power, marine industries, oil and
gas, agriculture, and roadside maintenance, we present
population-level impacts that were directly calculated by the
paper or report authors; for building collisions, we calculated
family-level impacts by combining kill data provided by
authors with current estimates of family-level abundance in
Canada (Blancher 2002; P. Blancher unpublished data). For
all these estimates, total kill of nests/eggs/nestlings was
converted to the equivalent mortality of potential breeding
adults, as described above, to enable comparability among
sources of mortality; see Appendix 3 for full details on
population-level kill and abundance. Note that although
population-level impact estimates provide examples of the
relative importance of particular mortality sources, these
populations do not represent a random sample of all
population-level impacts because they may have been
highlighted by authors for different reasons, e.g., those
considered particularly at risk, those representative of most
birds affected, or those with the best available data on
population size. We considered reference levels of 10%, 1%,
and 0.1% to be informative. Individual sectors near or above
10% could likely translate to detectable negative population
effects. Population proportions of 1% are considered
nationally significant from the perspective of management of
protected areas (e.g., RAMSAR criteria). We are not aware of
documented population effects for rates of mortality below
0.1% from individual sources.
Spatial assessment of mortality risk
A spatial representation of cumulative human-related
mortality in Canada was created for a subset of sectors.
Applicable or proxy spatial information was available for the
following eight sources of terrestrial-based mortality: cats,
bird-window collisions, bird-vehicle collisions, bird-
communication tower collisions, agriculture (haying and
crops), commercial forestry, oil and gas, and wind turbines.
All data were summarized and displayed on a 50 × 50 km tile
grid covering Canada. This grid-level balanced the goal of
providing interpretable images against the false precision of
mapping data that usually had low spatial resolution or
concordance with specific processes causing mortality, e.g.,
we know precisely where all paved roads are, but not where
bird-vehicle collisions occur on those roads. All data sources
and detailed procedures used to derive the maps are provided
in Appendix 4.
We began by taking the proportion of activity in a 50 × 50 km
tile grid across areas of resolution defined by the original
research paper, e.g., provincially for forestry; by turbine for
wind facilities; and by applicable portions of Bird
Conservation Regions for agriculture. The total mortality
estimate for each tile was then calculated by multiplying the
proportion of activity in each tile by the original mortality
estimate (number of wind turbines, km² of oil and gas activity,
etc.). The completed tiles from the eight sources were overlaid
and summed to compute the total mortality estimate per tile.
The final map was colored using 10 classes calculated by the
Jenks classifier (Jenks 1967) in ArcGIS 10 and output in raster
format. We applied a low-pass filter to the raster output using
a 5 × 5 tile kernel size (Jensen 2005). We caution that the map
represents an index of probable mortality across key sources,
and is only an approximation. Accurately mapping mortality
would require spatially explicit information on bird density,
specific details on how and when each sector interacts with
birds in each tile, and a variety of covariates that are not
available nationally or may not be understood, e.g., why does
mortality at tall buildings apparently differ appreciably among
cities (Machtans et al. 2013)?
Total mortality estimates
Mortality estimates from each human-related source ranged
from a few thousand to tens or hundreds of millions of birds.
Avian Conservation and Ecology 8(2): 11
In Canada, all combined sources of human-related mortality
destroyed an average of ~2 million nests and killed ~269
million birds per year, or the equivalent of ~186 million
potential adult breeders each year (Fig. 1). Cats and collisions
with structures were the largest causes of human-related bird
mortality in Canada: cumulatively, the top five sources of
mortality, i.e., predation by feral and pet cats, and collisions
with road vehicles, houses, and transmission lines, represented
more than 95% of the individuals killed across all human-
related sources. Because each of these top-ranking mortality
sources are widespread, they may represent relatively small
numbers at the local scale, but sum to very high levels of
mortality when extrapolated across Canada. In contrast, some
other mortality sources do not occur uniformly across the
country, e.g., terrestrial oil and gas, fisheries, or are from
industries located at relatively few scattered locations, e.g.
wind power, and thus have relatively modest national-level
kill totals, despite measurable localized effects.
The nine largest sources of anthropogenic mortality all killed
mobile individual birds, including adult, subadult, and juvenile
birds, although over a million nests and eggs are destroyed
annually by forestry and agriculture, respectively (Fig. 1A).
Fig. 1A and Table 1 show the total number killed by each
source, identifying the life stage at which most mortality
occurs, i.e., nest destruction, mortality of eggs or nestlings, or
loss of independent mobile individuals. Mortality occurring
at two stages, i.e., loss of eggs and mobile individuals through
road maintenance, is shown as two points for that source. Note
that although most estimates were made at a national level,
for example, by extrapolating from local-scale estimates
across the country, a few were only made at smaller scales
(indicated as hollow symbols in Fig. 1): the agricultural haying
and road maintenance estimates each represent impacts on just
five and six focal species, respectively, and the hydro reservoir
estimate was made for Quebec only. Total Canada-wide cross-
taxa mortality caused by these activities is therefore likely to
be appreciably higher than the values presented here.
The relative ranking of mortality sources was similar for the
stage-specific and converted values (Figs. 1A, 1B),
particularly for the largest sources of mortality. However, for
human activities that destroy eggs and nests, the equivalent
potential adult breeder total was considerably reduced, and
thus the relative ranking of these sources somewhat altered,
because many of the eggs or young killed by these sources
would have not been expected to survive to adulthood
otherwise (Fig 1B).
Converted estimates pooled across related activities provided
broad estimates for the main sources of human-caused
mortality (Fig 1C). These pooled sectors were cats (feral and
pet), transportation (vehicle-collisions, road maintenance, and
chronic ship-source oil), buildings (collisions with all three
types), electrical power (transmission-line collisions, hydro
reservoirs, electrocutions, transmission-line maintenance, and
wind energy), harvest (migratory and nonmigratory game
birds), agriculture (haying and pesticides), fisheries (all gear
types), oil and gas (all terrestrial and marine sources), and
mining (pits/quarries and metals/minerals); the original
single-source values for forestry and communication towers
are also shown. Nonindustrial activities (cats, transportation,
and buildings) still represented the greatest overall sources of
mortality, while electrical power and agriculture represented
the largest industrial sources of mortality, with an annual kill
of over 18 million and over 2 million potentially breeding
birds, respectively. At the other end of the spectrum, the
fisheries, oil and gas, and mining industries each killed the
equivalent of fewer than 25,000 breeders annually (Fig. 1C).
Note that within sectors, some sources of mortality were
relatively low, e.g., electrocutions in the electrical power
sector, while others dominated the overall sectoral kill, e.g.,
transmission line collisions.
Evaluating potential population effects: seasonal and
taxonomic distribution of mortality
The distribution of anthropogenic mortality among bird
groups and across seasons for each mortality source showed
that landbirds as a group were affected by the widest range of
human activities (Table 2). These impacts occurred primarily
during the breeding seasons, as expected, because many
species overwinter outside of Canada. Shorebirds and
waterfowl also faced many potential threats at their nesting
sites, and birds across all groups confronted a range of human-
caused mortality during spring and fall migration, particularly
from collisions with cars, buildings, power-lines, and
transmission structures.
Landbirds make up the majority of all Canadian breeding
birds, and they constituted most of the estimated total mortality
among the five species groups when expressed in common
units of potential adult breeders (Table 3). In total, we
estimated that 89% of all birds killed annually by human
activities are landbirds; 6% are waterfowl, and the remaining
5% includes waterbirds, shorebirds, and seabirds. The
majority of mortality occurred through direct kill of mobile
individuals (74%; mostly cats, but see Table 2 for categories
of impact type), with 25% of mortality caused by collisions.
The destruction of nests represented less than 1% of overall
estimated impact when converted to potential adult breeders.
Although overall national-scale mortality estimates illustrated
the magnitude of bird mortality across Canada, some human-
related activities had disproportionately large effects on
particular species or populations, with the potential for
population-level impacts at a regional or national level (Fig.
2; see Appendix 3 for full details). For example, marine
fisheries bycatch had one of the lowest total mortality
estimates nation-wide, but may annually kill a relatively large
Avian Conservation and Ecology 8(2): 11
Fig. 1. Annual mortality of Canadian birds due to human activities (log-scale). Panel A shows stage-specific estimates for
each activity, according to whether entire nests, single eggs/nestlings, or mobile individuals were killed, as in original papers
and reports. Values include both means and medians, and error bars represent both confidence limits (90% or 95%) and
maximum/minimum ranges, as originally presented. Panel B shows converted mortality estimates for each activity (median
with 90% confidence limits), where stage-specific kill totals have been converted to the equivalent number of potential adult
breeders based on a stochastic model incorporating species-composition and demography. Hollow symbols indicate mortality
only estimated for part of Canada or for a limited number of species, and thus where total Canada-wide cross-taxa mortality
is likely much higher than these estimates. Panel C shows these same converted estimates (median with 90% confidence
limits), pooled across related activities (cats: feral and pet; transportation: vehicle-collisions, road maintenance, and chronic
ship-source oil; buildings: collisions with all 3 types; power: transmission-line collisions, hydro reservoirs, electrocutions,
transmission-line maintenance, and wind energy; agriculture: haying and pesticides; harvest: migratory and nonmigratory
birds; fisheries: all gear types; oil and gas: all terrestrial and marine sources; mining: both pits/quarries and metals/minerals),
as well as the original single-source values for forestry and communication towers. Values in all panels are ranked in
descending order according to the converted kill totals. See text and Appendix 2 for citations of papers and reports used as
data sources.
Avian Conservation and Ecology 8(2): 11
Figure 1 continued.
proportion of Canadian populations of a few species, e.g.,
Black-footed Albatross Phoebastria nigripes: 4% of the entire
Canadian population, or Common Eiders Somateria
mollissima: 7% of the Nova Scotia breeding population (Fig.
2). Mortality from building collisions also nonrandomly
impacted landbirds. Overall, tall buildings killed less than
0.01% of total abundance of any landbird family, whereas
between 2-5% of nuthatches, chickadees, and pigeons may
have been killed at houses (see Bayne et al. 2012 for
proportions of house-collision kills by family, which we used
in Appendix 3 and Fig. 2). Although this simple comparison
does not capture the complexity of potential population
effects, it confirms that national mortality totals alone do not
reflect the ecological importance of human-related activities
for most species and that mortality is not simply proportional
to abundance (see also Longcore et al. 2013).
We did not directly assess the impacts of sport harvest on
populations of game birds because ongoing assessments exist
elsewhere (e.g. Williams and Johnson 1995, Nichols et al.
2007), and extensive programs are in place throughout North
America that ensure that any population-level effects of
regulated harvests are sustainable in the long term (e.g., Runge
et al. 2009). These impacts would likely have dominated Fig.
2, because sport-harvest was clearly important as a human-
related source of mortality in Canada for waterfowl and an
important factor for some other bird groups (Table 3).
Spatial distribution of mortality risk and potential
cumulative effects
Human-related mortality from terrestrial sources was not
uniformly distributed across Canada (Fig. 3A) because areas
of higher mortality corresponded with areas of high human
population and high human activity. Peak mortality for all
sources combined was highest in southern Ontario and
Quebec, around the five major prairie cities, and in
southwestern British Columbia. In addition to having high
human populations, and correspondingly large numbers of
cats, buildings, and roads, numerous industries overlap with
these areas. Overall, very little avian mortality from the
sources that we mapped currently occurs in the northern part
of many provinces and in the territories.
The distribution of mortality when excluding the three largest
sources (cats, buildings, roads) was spread more evenly across
southern Canada (Fig. 3B), partly reflecting broad areas of
forest harvesting and the diffuse distribution of
communication towers across this area. Southern Alberta and
southeastern Ontario appeared to be areas for potential
additive effects of multiple industries. The high values in the
Maritimes were partially attributable to forestry, whereas
those in the lower mainland of British Columbia primarily
reflect the high number of hay farms. Individual, unsmoothed
maps for each mortality source are provided in Appendix 4.
In contrast to most impacts of clearing activities (Fig. 3B),
collision-based sources of mortality impacted some species
more than others, and thus potential cumulative effects were
harder to assess spatially. Based on available data, we found
indications that different types of collisions appeared to affect
different groups of landbirds. At the family level, warblers
dominated birds killed in communication tower collisions (15
of the most abundant 20 species recorded, Longcore et al.
2013) whereas a wider variety of species dominated tall
Avian Conservation and Ecology 8(2): 11
Table 1. Life stage-specific (nests, eggs/ nestlings, or independent individuals) mortality estimates of human-related avian
mortality in Canada derived directly from published papers and unpublished reports. These values are illustrated in Fig. 1A, and
served as the basis for the stochastic model conversion to an equivalent number of potential adult breeders; mortality sources
are listed in descending order of converted kill totals. Characteristics of the estimate are indicated in the last column, i.e., whether
central values were mean, median, or midpoint of a range, and whether lower/upper values represent a confidence interval (CI)
or a range. Note that the estimates for forestry and terrestrial oil and gas shown here represent the estimated number of nests
Nests Eggs or Nestlings Individuals Values
Source Lower Central Upper
Central Upper Lower Central Upper Estimated
Cats - Feral
116,000,000 232,000,000
95% CI
Cats - Domestic
95% CI
Power - Transmission line collisions
25,600,000 41,200,000 mean,
95% CI
Buildings - Houses
22,400,000 30,500,000 mean,
Transportation - Road vehicle
13,810,906 18,707,470 mean,
95% CI
Agriculture - Pesticides 960,011 2,695,415 4,430,819 midpoint,
Harvest - Migratory birds 2,279,655 mean
Buildings - Low- and midrise 300,000 2,400,000 11,400,000 mean,
Harvest - Nonmigratory birds
2,389,124 3,701,438 mean,
95% CI
Forestry - Commercial
1,351,340 2,086,720
Transportation - Chronic ship-source
oil 217,800 321,900 458,600 mean,
95% CI
Power - Electrocutions 160,836 481,399 801,962 midpoint,
Agriculture - Haying 2,209,400 mean
Power - Line maintenance
388,274 592,418 midpoint,
Communication - Tower collisions 220,649 mean
Power - Hydro reservoirs 152,162 mean
Buildings - Tall 13,000 64,000 149,000 mean,
Fisheries - Marine gill nets 2185 20,612 41,528 mean,
Power - Wind energy 13,330 16,700 21,600 mean,
95% CI
Oil and Gas - Well sites 7688 13,182 20,249 median,
90% CI
Mining - Pits and quarries
Oil and Gas - Pipelines 503 6314 30,234 median,
90% CI
Mining - Metals and minerals
Oil and Gas - Oil sands 1281 2939 5236 median,
90% CI
Oil and Gas - Seismic exploration 374 2280 16,438 median,
Fisheries - Marine longlines and trawls 494 1,999 4058 mean,
Transportation - Road maintenance
25,149 50,294 84 149 270 median,
Oil and Gas - Marine 188 2244 4494 median,
Avian Conservation and Ecology 8(2): 11
Fig. 2. Proportion of population affected by anthropogenic mortality on Canadian birds, by species group (panel A) and by
mortality source (panel B), for populations where data were available at sufficient resolution. Estimated annual kill for a
given species, population, or family (converted to potential adult breeders) is plotted against the estimated Canadian
abundance for that group, to show the estimated proportion of the total population killed by each activity. The three diagonal
lines represent a mortality rate of 10%, 1%, and 0.1% for visual reference and are explained in more detail in the text. Details
of mortality and abundance totals, as well as the identity of the species/population/family represented by each data point, are
provided in Appendix 3. Game bird harvests are not included in this figure because they would dominate the figure and this
source of mortality is regulated.
Avian Conservation and Ecology 8(2): 11
Fig. 3. Approximated distribution of total bird mortality estimates in Canada from eight terrestrial sources (cats, building
collisions, vehicle collisions, agriculture, forestry, terrestrial oil and gas, communication towers, and wind turbines). Panel A
is the sum of all eight sources, while panel B excludes the first three in the above list. These maps present the probability of
mortality based on the distribution of each source in Canada. The hotspot on Montreal is because a single tile of our grid
overlapped that city perfectly, while, for example, Toronto was centered at the intersection of 4 tiles. Unsmoothed maps for
each mortality source and all mapping methods are provided in Appendix 4.
Avian Conservation and Ecology 8(2): 11
Table 2. Seasonal and species-group breakdown for each source of human-related avian mortality in Canada: o little or no known
effect, + some effect, including effects anticipated but not quantified [highlighted yellow], ++ large effect [highlighted orange],
na not applicable. Within the effect-type categories (collisions, direct kill, or nest destruction), mortality sources are ordered in
descending order of converted kill totals, as presented in Fig. 1B. Comparisons should be made within source rows, rather than
within columns because the level of effect was evaluated qualitatively among seasons and species-groups within each source,
and is not intended to reflect differences in magnitude among sources. Note that ‘winter’ refers only to impacts on birds while
wintering in Canada.
Primary type of
impact Source S-
Collisions Transportation - Road vehicle
collisions + ++ + + o o o o + + + o + + + o + + + o
Buildings – Houses ++ ++ ++ + o o o o o o o o o o o o o o o o
Power - Transmission line collisions + + + + o o o o ++ ++ ++ + + + + + ++ + ++ +
Buildings - Low- and mid-rise ++ ++ ++ o o o o o o o o o o o o o o o o o
Power – Electrocutions + + + + o o o o + o + o + o + o o o o o
Communication - Tower collisions ++ + ++ + o o o o + o + o + o + o + o + o
Buildings – Tall ++ o ++ o o o o o o o o o o o o o o o o o
Power - Wind energy + ++ + o o o o o o o o o o o o o o o o o
Direct kill Cats (feral and domestic) ++ ++ ++ ++ o o o o o + o o o + o o o + o o
Agriculture – Pesticides + ++ + o o o o o + + + o + + + o + + + o
Harvest - Migratory game birds o o o o o o + + o o + + o o + + + o ++ +
Harvest - Non-migratory game birds o o ++ + o o o o o o o o o o o o o o o o
Transportation - Chronic ship-source
oil ooooooo++ooooooooooo o
Fisheries - Marine gillnets o o o o o ++ + o o o o o o o o o o + o o
Fisheries - Marine longlines and
trawls ooooo++oooooooooooo o
Oil and Gas - Marineoooo++++ooooooooooo o
Nest destruction Agriculture – Haying and mowing na ++ na na na o na na na o na na na o na na na ++ na na
Forestry – Commercial na ++ na na na o na na na + na na na o na na na + na na
Power - Line maintenance na ++ na na na o na na na ++ na na na ++ na na na ++ na na
Power - Hydro reservoirs na ++ na na na o na na na ++ na na na ++ na na na ++ na na
Oil and Gas - Terrestrial (all) na ++ na na na o na na na + na na na o na na na + na na
Mining (all) na ++ na na na o na na na + na na na o na na na + na na
Transportation - Road maintenancena ++ na na na o na na na + na na na o na na na ++ na na
mortality from both direct kill and collisions;
mortality from both nest destruction and direct kill
building collisions (only 6 of the top 20 were warblers,
Machtans et al. 2013). At the species level, the top five species
killed in tall building collisions in southern Ontario (based on
the Toronto Fatal Light Awareness Program,
were Golden-crowned Kinglet (Regulus satrapa), White-
throated Sparrow (Zonotrichia albicollis), Ruby-crowned
Kinglet (Regulus calendula), Dark-eyed Junco (Junco
hyemalis), and Ovenbird (Seiurus aurocapilla), together
comprising 42% of mortalities. In contrast, the top five species
killed in communication tower collisions in the Bird
Conservation Region, which includes Toronto (Longcore et
al. 2013), were Ovenbird, Ruby-crowned Kinglet, Blackpoll
Warbler (Setophaga striata), Red-eyed Vireo (Vireo
olivaceus), and Common Yellowthroat (Geothlypis trichas),
together comprising 44% of mortalities. Species reported
killed most often at wind-turbines only showed some overlap
with these other collision-sources, with the top five being
Horned Lark (Eremophila alpestris), Golden-crowned
Kinglet, Red-eyed Vireo, European Starling (Sturnus
vulgaris), and Tree Swallow (Tachycineta bicolor;
Zimmerling et al. 2013). Only 80% of birds killed at wind
turbines were passerines, proportionately much lower than at
communication towers (97% passerines, Longcore et al. 2013)
or in collisions with windows of tall buildings (90%
passerines, Machtans et al. 2013). Much better species-level
data are required concerning cat kills and window collisions
at homes, as well as from the range of other human activities
for which population-level data are not yet available, to better
understand the most significant population impacts and to
identify additive or cumulative impacts. Even the species
comparisons above should be taken with caution because the
spatial scale of the data sources differ across each study.
Avian Conservation and Ecology 8(2): 11
Table 3. Median annual estimates of human-related mortality in Canada across the five major species groups, based on a stochastic
model that converted stage-specific mortality to potential adult breeders, ranked in descending order according to total estimated
mortality across all bird groups. Note that species-group totals do not sum exactly to the ‘all birds’ value because uncertainty
in species composition was explicitly modeled and the “all birds” value was modeled independently of each species group’s
total. See text and Appendix 2 for details of the stochastic model conversions. In cases where mortality was not fully extrapolated
to all regions and taxa, e.g., where it was only estimated for a given region or set of focal species, the taxonomic or regional
scope of the estimate is indicated; impacts estimated Canada-wide and across taxa are indicated as ‘all’ in the Scope column.
Cats - Feral All 78,600,000 293,400 380,500 79,600,000
Cats - Domestic All 54,150,000 199,300 258,300 54,880,000
Power - Transmission line collisions All 574,700 2,548,000 5,170,000 8,459,000 16,810,000
Buildings - Houses All 16,390,000 16,390,000
Transportation - Road vehicle collisions All 8,743,000 197,000 187,200 218,500 9,814,000
Agriculture - Pesticides All 1,898,000 19,230 19,430 19,130 1,998,000
Harvest - Migratory game birds All 235 55,520 24,770 8773 1,691,000 1,786,000
Buildings - Low- and mid-rise All 1,132,000 26,310 23,870 32,190 1,283,000
Harvest - Non-migratory game birds All 1,031,000 1,031,000
Forestry - Commercial Landbirds 887,835 887,835
Transportation - Chronic ship-source oil All 282,700 282,700
Power - Electrocutions All 178,200 1715 1854 2275 184,300
Agriculture – Haying and mowing 5 species 135,400 135,400
Power - Line maintenance All 70,140 4474 33,030 116,000
Communication - Tower collisions All 101,500 965 1050 1278 101,500
Power - Hydro reservoirs Québec 31,260 490 1571 158 35,770
Buildings - Tall All 32,000 388 339 501 34,130
Fisheries - Marine gill nets All 19,790 19,790
Power - Wind energy All 13,060 13,060
Oil and Gas - Well sites Landbirds 9815 9815
Mining - Pits and quarries All 5169 39 168 5637
Oil and Gas - Pipelines Landbirds 4687 4687
Mining - Metals and minerals All 2798 2798
Oil and Gas - Oil sands Landbirds 2193 2193
Oil and Gas - Seismic exploration Landbirds 1966 1966
Fisheries - Marine longlines and trawls All 1843 1843
Transportation - Road maintenance 6 species 1103 71 324 1545
Oil and Gas - Marine All 584 584
TOTAL 163,980,226 360,437 2,848,252 5,931,455 11,124,386 186,429,553
Interpreting mortality estimates
Human-related activities inadvertently kill hundreds of
millions of birds and destroy millions of nests in Canada every
year, with landbirds most affected. Birds are primarily affected
during the breeding season, although collisions occur year
round. Landbirds were subject to the largest diversity of
impacts, suggesting that they may be most vulnerable to
additive effects across sources and seasons. Many of these
human-related activities also pose a threat to migrants when
outside of Canada, mortality that has not been quantified here,
and thus the cumulative year-round population-level effects
will be higher for species that migrate outside Canada. For
instance, in the United States a median estimate of 2.4 billion
birds are killed annually by cats (Loss et al. 2013), and a
substantial proportion of these birds will have been produced
in Canada. In the context of severe population declines already
observed for many groups (e.g. long-distance migrants:
BirdLife International 2008; grassland breeders, shorebirds,
aerial insectivores: NABCI-Canada 2012), human-related
activities create additional population pressures for many of
Canada’s birds.
The estimated number of potential breeders killed annually by
specific sectors or sources differs by several orders of
magnitude, ranging from fewer than one thousand for routine
marine oil and gas activities, to tens of millions for collisions
with vehicles, transmission lines, and houses, and over 140
million for cat kills. Most of these activities are known to effect
birds at a local scale, although extrapolation to the national
level has highlighted the magnitude and potential significance
of several widespread impacts, such as cats and building
collisions. For other activities, a national scale perspective
may lead to important local-scale mortality being overlooked,
e.g., regionally concentrated fisheries bycatch. Our
geographical assessment revealed the highest cumulative risk
to birds in regions of high human population density and
related road networks. Southern Alberta and Ontario also
Avian Conservation and Ecology 8(2): 11
stood out as areas with potentially high cumulative effects
because of a convergence of several human activities in
addition to the top three sources, whereas other high risk
locations were generally attributable to single mortality
Although these estimates provide new insight into the relative
significance of different industrial and other human-related
activities to wild birds in Canada, the precision of our review
is limited by the availability of relevant information from
Canada. The wide confidence ranges around the converted
estimates explicitly indicate the considerable uncertainty in
our present knowledge of the magnitude of source-specific
mortality, so these should be viewed as preliminary estimates
pending further refinement, additional research, and increased
monitoring and assessment.
Uncertainties and caveats
Accurate estimation of the magnitude of bird mortality from
industrial and other human-related activities is compromised
by the need to estimate large-scale national impacts by
extrapolating from small studies, often with limited data.
Wherever possible, authors directly accounted for known
sources of bias, such as variability in detection and scavenging
of bird carcasses (e.g., road vehicles: Bishop and Brogan 2013;
building collisions: Machtans et al. 2013; wind power:
Zimmerman et al. 2013; transmission line collisions: Rioux et
al. 2013). Some explicitly assessed the sensitivity of mortality
estimates to key parameters such as the number of unowned
cats in Canada (Blancher 2013), or the timing of agricultural
or oil and gas activities in relation to breeding seasons (Tews
et al. 2013, Van Wilgenburg et al. 2013). Overall, we consider
that the estimates presented in this issue are likely to be precise
to within an order of magnitude, particularly because actual
levels of mortality from each source will likely vary
significantly from one year to the next.
Some important sources of estimation bias still remain. For
instance, the scale of available data may sometimes be
mismatched to the scale of human-related activities. The
harvest volume from commercial forestry activities is
typically reported provincially and not by area cut, while the
density of nesting birds is inferred from extrapolating local-
scale point-counts to Bird Conservation Regions, which do
not align with provincial boundaries (Hobson et al. 2013).
Additionally, specific Canadian data for predation rates by
cats, pesticide use, and mortality from power generation were
also lacking (Blancher 2013; Appendix 1), so the estimates
presented here are derived in part using data from other
countries or continents. Extrapolations for marine oil and gas
were based on untested assumptions, with few data available
to inform these estimates (Ellis et al. 2013).
Estimates of effects from most sources could be improved by
a better understanding of the seasonal distribution of mortality.
For instance, the proportion of industrial activities that occur
within the breeding season had to be approximated for several
sources (e.g., forestry: Hobson et al. 2013; oil and gas: Van
Wilgenburg et al. 2013). Species-composition of the kill is
also poorly known for many human activities (e.g., vehicle
collisions: Bishop and Brogan 2013; transmission line
collisions: Rioux et al. 2013), limiting our ability to evaluate
potential population-level impacts. Finally, most analyses
presented here were designed to estimate direct annual kill of
individual birds or destruction of nests. Estimates for most
mortality sources that also involve significant clearing or
alteration of habitat do not reflect the total long-term impact
of the activity on bird populations because most analyses did
not account for additional long-term impacts, e.g., via habitat
change (Wells et al. 2008) or related one-time mortality events,
e.g., destruction of nests during initial construction of
transmission lines (Rioux et al. 2013).
The stochastic simulation model addressed some of these
biases, so that the distributions of potential adult breeder
mortality are more likely to reflect the actual impacts of
estimated mortality. The confidence limits around median
estimates reflect the remaining uncertainty in the input values;
for instance, the magnitude of mortality caused by fisheries
bycatch or wind power is known with greater precision than
that caused by mining activities or terrestrial oil and gas. These
estimates all assume that most mortality estimated here is
additive to natural mortality, so density-dependence was not
incorporated into these conversions. The stochastic simulation
model did make some simplifying assumptions, such as
assigning age of first breeding to the second year of life for
all but the seabirds, which would overestimate the number of
potential breeders when breeding begins later, and by using
nest success estimates that assume that nests were destroyed
at the beginning of nesting, which would underestimate the
number of potential breeders if nest destruction occurred later
in the season. An important potential bias of the modeling
process was the use of representative vital rates from only a
few species, except the landbirds. In the future, more detailed
estimates of species-specific kills could be incorporated with
models using their species-specific vital rates to properly
assess the effects of any particular mortality source. Finally,
there are some considerations that the conversion to potential
adult breeders could not incorporate. Long-lived, low-
fecundity species take longer to recover from population
perturbations, and mortality for these species is more likely to
be additive than for shorter lived high-fecundity species.
Additionally, long-lived, low-fecundity species tend to have
much smaller population sizes, so a greater portion of the
population is removed with each potential adult killed.
The risk mapping also relied on some important assumptions,
specifically that mortality from each source was spread across
the landscape in proportion to its existing spatial intensity.
This is certainly not the case; forestry companies do not harvest
equally across their tenure area and not every communication
Avian Conservation and Ecology 8(2): 11
tower or wind turbine kills the average number of birds.
However, adopting this assumption was necessary to create a
first order spatial representation of the distribution of avian
mortality risk across Canada.
The values considered here represent the current best estimates
of source-specific annual bird mortality for Canada across all
species groups and age classes, although a few sectoral
mortality estimates must be considered to be quite preliminary,
and there is some inherent uncertainty in all estimates.
Moreover, because the magnitude of the estimates is likely to
be fairly accurate, with true mortality levels contained within
the estimation range, the relative ranking of mortality sources
is unlikely to change substantially with improved precision.
From a conservation perspective, it is now important to
develop a more complete understanding of the population level
effects of human-related avian mortality within and across
sectors, at relevant spatial scales. Sources such as window
strikes at houses cause high levels of mortality nation-wide,
but this mortality is not spread equally across different species
or families. Longcore et al. (2013) found similarly variable
population impacts of communication tower collisions.
Marine fisheries bycatch was not among the highest-ranking
sources of mortality nation-wide, yet it kills disproportionately
high numbers of birds from particular regional populations.
Our assessment did not consider the fact that certain
populations or species may still manifest a population-level
consequence through additive effects of several mortality
sources, even though each source individually would not be
expected to show such an effect. Understanding these
cumulative effects will not be possible until species-specific
kill rates are available for all sectors. In the interim, those
habitats or areas of the country where many sectors operate
together are places where these multiple stressors have the
potential to combine and create such a cumulative impact.
This synthesis and accompanying papers focus primarily on
direct mortality of birds and destruction of nests resulting from
human activities, but do not consider the potential longer term
effects on birds from habitat changes. Wind turbines, for
example, cause mortality by nest-destruction during
construction as well as through collision mortality during
operation. Indeed, recent evidence suggests that initial
construction may sometimes pose a greater overall threat to
birds (Pearce-Higgins et al. 2012). Commercial forestry,
terrestrial oil and gas, and mining are further examples of
activities where there may be significant longer term or
broader scale effects of habitat modification that are not
addressed here. Furthermore, mortality rates may change in
the future for industries undergoing rapid rates of
development, such as wind facilities, which are predicted to
expand ten-fold in Canada over the next 10-15 years
(CanWEA 2013). Human activities currently contributing
relatively little to total mortality may therefore present a
greater risk in years to come.
The complex relationships among all ecological factors
regulating avian populations, and particularly migratory birds,
require consideration of factors operating at points throughout
the entire life cycle (Faaborg et al. 2010). For example, if
wintering habitat conditions are not limiting, human-related
mortality may be additive. However, if wintering habitat
becomes limiting, human-related mortality may shift to being
compensatory and its influence on population regulation may
change. Improved understanding of species composition of
mortality events, the magnitude of mortality of migrants south
of Canada, and survival estimates at each life stage will be
required to effectively model the demography of affected
populations, particularly if bird conservation objectives
include maintaining source-specific mortality from human-
related causes below certain levels (e.g., McGowan and Ryan
2009, Runge et al. 2009, Dillingham and Fletcher 2011).
Insight into the relative magnitude of different human-related
sources of mortality provides a valuable tool for guiding
management, and affords additional perspectives for
prioritizing conservation and research initiatives for Canada’s
birds. We propose four key areas for future research or
management. First, to enable more precise analyses and impact
modeling, we recommend additional Canadian research into
the magnitude of bird effects for data-poor sectors, e.g.,
pesticides, and the species likely affected, and into particular
aspects of mortality, e.g., species composition and seasonal
timing of the kill. Second, our results highlight the value of
increased efforts to minimize impacts of widespread and
generalized low-intensity human-related activities that create
nationally high levels of mortality but could be mitigated at
local scales, e.g., cats and buildings. Such investments could
include local approaches using outreach and other available
conservation tools. Third, we recommend specifically
targeting those mortality sources identified as having
population-level effects at regional or national levels for
priority conservation action. Finally, we encourage further
assessments that integrate the effects on populations across
multiple sectors to truly understand the impacts of all mortality
sources on priority species. Such mitigation efforts can reduce
human-related impacts on birds if appropriately directed (as
shown by e.g., Nocera et al. 2005, 2007: changing the timing
of agricultural activities to reduce impacts on grassland
breeders; Gehring et al. 2009: changing lights on
communication towers to reduce collision mortality; and
Løkkeborg 2011: modifying fishing gear to reduce bycatch of
Given that the relative ranking of mortality sources considered
here is unlikely to change substantially even with increased
precision, an immediate focus should consider mitigation of
those mortality sources with the highest magnitudes at the
Avian Conservation and Ecology 8(2): 11
national level, e.g., cats and collisions. At the same time,
scientists should try to identify and better understand potential
population-level impacts on populations or species, at
appropriate geographical scales. Effective application of these
findings to the conservation of Canadian birds will require
constructive collaboration among the public and various levels
of government, nongovernmental organizations, and
industries within Canada. This assessment should help target
these initiatives appropriately to improve the population and
conservation status of birds within Canada, as well as the
continental conservation status for migratory species.
Responses to this article can be read online at:
This research was instigated and funded by Environment
Canada. Thank you to Amos Chow for assistance in compiling
some of the mapping data, to Beau MacDonald for providing
quality-controlled communication tower data, to Alyssa
Serena for compiling provincial game-bird harvest numbers,
to Steve Van Wilgenburg and Keith Hobson for providing their
landbird demographic rates, and to Peter Blancher for
unpublished family-level abundance estimates. Finally, we
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Appendix 1: Unpublished reports on sources of mortality cited in the text.
The following reports are not peer reviewed and should not be cited as such. The authors of the
main paper for which these materials form a supplementary appendix make no expression on the
validity of individual portions of or computations in the papers aside from what was extracted for
use with noted caveats in the main paper.
Avian Incidental Take due to Roadside
Maintenance Operations in Canada
Prepared by
ESSA Technologies Ltd.
Arbor Vitae Environmental Services Ltd.
Environment Canada
June 2010
Suggested Citation: Abraham, D., D. Pickard and C. Wedeles. 2010. Avian Incidental Take due to Roadside Maintenance
Operations in Canada. Report Prepared by ESSA Technologies Ltd. and Arbor Vitae Environmental
Services Ltd. for Environment Canada. 31 pp. + appendices
Estimating the Incidental Take of Birds – Roads Tally
1 EXECUTIVE SUMMARY ....................................................................................................... 1
2 INTRODUCTION ................................................................................................................... 2
3 METHODS ............................................................................................................................. 4
3.1 Deriving a List of Roadside nesting Birds .......................................................................... 4
3.2 Gathering Breeding and Nest Density Information ............................................................. 5
3.3 Obtaining Information about Area Disturbed ...................................................................... 9
3.4 Calculating Incidental Take .............................................................................................. 12
4 RESULTS ............................................................................................................................ 14
5 DISCUSSION ...................................................................................................................... 24
6 REFERENCES .................................................................................................................... 28
APPENDIX A: CONTACTS ......................................................................................................... 32
APPENDIX B: MODELLING APPROACH .................................................................................. 37
APPENDIX C: MODEL INPUTS ................................................................................................. 46
Estimating the Incidental Take of Birds – Roads Tally
Table 1: List of roadside nesting bird species. .............................................................................. 4
Table 2: Model parameter input information for birds. .................................................................. 5
Table 3. Combinations of habitat type and quality for each focal species. . ................................ 8
Table 4. Road classes included in the GIS analysis ................................................................... 10
Table 5. General habitat types used in the analysis. .................................................................. 10
Table 6. The extent of roads in Canada, by province and territory. ............................................ 11
Table 7. Number of kilometers of road within the breeding range for 6 focal species. ............... 12
Table 8. Incidental take for 6 focal species by province/territory. . ............................................ 14
Table 9. Incident take for 6 focal species for all of Canada. . .................................................... 16
Table 10. Incidental take for 12 non-focal species by province/territory. .................................... 17
Table 11. Total annual estimated incidental take for 18 bird species affected by roadside
maintenance operations across Canada. ................................................................................... 23
Table 12. Total annual estimated take for 6 focal species and 12 non-focal species. ............... 23
Table 13: Example of interim results of the Discount.fcn() for killdeer in Ontario. .................... 42
Table 14: Example of model output for killdeer.. ....................................................................... 44
Estimating the Incidental Take of Birds – Roads Tally
ArborVitae Environmental Services Ltd. and ESSA Technologies Ltd. generated preliminary
estimates of the magnitude of avian incidental take due to roadside maintenance operations
across Canada. Eighteen roadside nesting species, all protected under the Migratory Birds
Convention Act, were identified through the literature and expert advice. To model the impacts
on these species, this study took a focal-species approach, in which estimates of incidental take
were modeled for 6 focal species and then extrapolated to 12 other species which had similar
ecologies. The estimates of take for the focal species were based on:
their nesting ecology (i.e. nesting dates, number of eggs laid, incubation periods) and
range in Canada;
preferred nesting habitats relative to the availability of the habitats along roadsides; and
the amount of road and maintenance activities conducted in each province.
We used a modeling approach which integrated the information above with assumed and
calculated distributions of nesting period, road maintenance schedules, egg laying, etc.
Estimates of take were made for these species using a combination of modeling and
extrapolation. Incidental take ranged from 7 (Lark Sparrow) to 820,000 (American Robin)
individuals per year across Canada. We estimate that approximately 861,000 nestlings, eggs,
and adults (only waterfowl adults are susceptible to incidental take) are killed by incidental take
per year. However, this analysis, although very detailed, is subject to a number of caveats
which suggest that the results should be interpreted with considerable caution.
There are no published criteria for what constitutes biologically significant levels of incidental
take for bird populations. However, a widely accepted criterion for identifying key habitat sites
for population conservation may serve as a suitable surrogate. Sites believed to support at
least 1% of a Canadian population are considered to be key habitat sites, and their loss would
potentially have a significant detrimental impact on the total population. By extension, losses to
incidental take of 1% or more of a species Canadian population could be considered biologically
significant (C. Machtans, pers. com.).
As a proportion of total Canadian populations, take was estimated to be less than 1% for all
species, ranging from 0.0057% (Clay-colored Sparrow) to 0.5880% (American Robin).
According to the 1% criterion, incidental take due to roadside maintenance operations is not a
biologically significant mortality factor in Canada.
Estimating the Incidental Take of Birds – Roads Tally
The inadvertent destruction of birds and/or their nests and young occurs in Canada during
otherwise legitimate operations in a variety of sectors, including forestry, mining, agriculture,
electrical generation and transmission, fishing, structures, roadside maintenance and road
construction. Such "incidental take" is an important factor in bird conservation and
management, and Environment Canada has identified a need to better understand the
magnitude and significance of the issue.
The objective of this project was to generate defensible species specific estimates of the
number of birds killed annually due to roadside maintenance activities in Canada, by
province/territory, e.g., for every hectare of roadside affected by mowing and/or brushing, an
average of X number of individuals of species Y are killed each year. Only bird species that
breed in Canada and are covered under the Migratory Birds Convention Act (MBCA) were
included; species not protected by the MBCA include raptors, corvids, blackbirds, gallinaceous
birds, and some others not explicitly mentioned in the Act. The temporal scope of the project
was the breeding season, so winter maintenance activities such as snow management were
excluded. Roadside maintenance activities in Canada include mowing, brushing (shrub cutting),
and tree trimming. Some jurisdictions also use herbicides (e.g., Newfoundland/Labrador) to
control vegetation, but this type of impact falls under the category of substances harmful to birds
(as regulated by S5.1 of the MBCA), and was beyond the scope of the project. All roads for
which roadside vegetation is managed by mechanical means were included in the analysis.
Long-term resource roads that provide access to the back country were included, but short-term
resource roads were out of scope.
This report documents a research and modeling effort to estimate the magnitude of avian
mortality due to roadside maintenance activities, such as mowing and shrub brushing, across
Canada. Roadside vegetation is managed for a variety of reasons, including safety (Forman et
al. 2003; Jacobson 2005), aesthetics (Jacobson 2005), the control of invasive plant species,
and in preparation for snow removal. Mowing-related avian mortality in roadside habitats is
understood by many researchers to occur (e.g., Forman et al. 2003; Maguire 2007), but few
studies have attempted to quantify it, and none have attempted to quantify it on a national scale.
Even comprehensive reviews on the short- and long-term ecological effects of roads do not
cover mortality from mowing equipment (Spellerberg 1998; Trombulak and Frissell 2000;
Forman et al. 2003). In agricultural areas, bird use of strip-cover habitats such as road rights-of-
way, fencerows, farmstead shelterbelts and grassed waterways can be high (Best et al. 1995).
Such habitats provide nest sites, particularly shrubs and trees that are usually not available in