Canadian Journal of Zoology
Evaluating policy-relevant surrogate taxa for biodiversity conservation: a case study from British Columbia
Journal: Canadian Journal of Zoology
Manuscript ID cjz-2019-0178.R1
Manuscript Type: Note
Date Submitted by the 24-Sep-2019 Author:
Complete List of Authors: Falconer, Sarah; University of British Columbia Okanagan, Biology Ford, Adam; University of British Columbia Okanagan, Biology
Is your manuscript invited for consideration in a Special Not applicableDraft (regular submission) Issue?:
WILDLIFE MANAGEMENT < Discipline, conservation, game species, Keyword: HABITAT < Habitat, indicator species
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Evaluating policy-relevant surrogate taxa for biodiversity conservation: a case study from
British Columbia
Sarah Falconer a, Adam T. Ford a,b
a Department of Biology, The University of British Columbia - Okanagan Campus, 1177
Research Road, Kelowna, British Columbia, Canada V1V 1V7
b Corresponding author:
[email protected] Draft
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Abstract
Conservation efforts often lead to a small proportion of species receiving a disproportionate amount of attention. This bias in finding may help or hinder broader goals of biodiversity conservation depending on the surrogacy value of the well-funded species. Surrogate species are selected to represent other taxa in a shared environment when it would be costly or impractical to obtain information on individual taxa. We compared the surrogacy value of common groups of taxa implicated in conservation – game species, carnivores, non-game species, and other species. Using a publicly available dataset of species-habitat associations, we compared the surrogacy value for 1012 species and 64 habitat types in British Columbia. We used a conditional entropy metric to quantify pairwise associations betweenDraft species via their occurrence in different habitat types. Our analysis reveals that game and non-game species surrogacy groups do not significantly differ in either the frequency of captured pairwise associations or their coverage of species. These results suggest that funding game species conservation is likely conferring some benefits to non-game species, but optimal habitat-based conservation outcomes will come from a combination of taxa. This analysis provides an important step in influencing management decisions for the preservation of biodiversity in British Columbia.
Keywords: conservation, game species, habitat, indicator species, wildlife management
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Introduction
There is widespread, human-induced losses of biodiversity and wildlife population
declines driven by overexploitation, climate change, diseases, and invasive species (Dirzo
et al. 2014). Habitat loss however, is considered the most important contemporary driver
of species declines (Tilman et al. 1994; Hanski 2011; Newbold et al. 2015). The human
footprint is spreading (Venter et al. 2016), giving rise to range contractions (Shackelford
et al. 2018), changing animal behavior (Gaynor et al. 2018; Tucker et al. 2018), and
altered evolutionary trajectories for wildlife (Otto 2018). To counter these declines,
global efforts are being made to prioritize both species and habitats for protection (Martin
et al. 2018).
Implementing habitat protectionDraft often involves trade-offs among target species
and other values derived from land (Bottrill et al. 2008). Habitat protections typically
reduce opportunity to use land for urbanization, agriculture, or extractive resources,
which means that social, economic, and political pressures minimize the amount of land
allocated for protection. Moreover, the diverse life-history needs of different taxa means
that protections targeted at one species will not necessarily confer benefits to other
species (Hermoso et al. 2013; Barnes et al. 2018; Heim et al. 2019). In addition,
relationships between habitat and fitness are unknown for most species, making
protection of habitats that enhance population viability elusive for managers (Fahrig
2001). For these reasons, it will be very challenging to implement habitat protection for
all species – prioritization may be needed to maximize the benefits of limited
conservation resources (Martin et al. 2018).
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The use of surrogate species in conservation is a common approach to prioritize species, and therefore maximize conservation outcomes with limited funds. A surrogate species is any species that is selected to represent another, or several others, in a shared environment (Caro 2010). Surrogate species are usually perceived to share characteristics that are unknown in other target species, and it would be costly or impractical to obtain that information (Landres et al. 1988; Caro et al. 1999; Rodrigues and Brooks 2007; Caro
2010; Nekaris et al. 2015). Conceptually, this definition of conservation surrogates includes umbrella species, which are used to indicate the extent or type of habitat to be protected (Nekaris et al. 2015), flagship species, which are selected because they attract public attention (Jepson and Barua 2015; Nekaris et al. 2015), and indicator species, which are species that have characteristicsDraft that can serve as a proxy for another species that might be too difficult to measure directly (Landres et al. 1988). Surrogate species are also used in natural resources and environmental monitoring to estimate or track changes to ecosystems (Muir et al. 2011; Campbell et al. 2019).
Though the use of surrogate species is widespread in conservation and resource management, the manner in which this concept is commonly applied has important limitations. First, it is often not clear how representative a surrogate species is for broader ecological conditions, as relationships or co-occurrence patterns are often assumed
(Andelman and Fagan 2000; Caro 2010; Hermoso et al. 2013; Campbell et al. 2019;
Henry et al. 2019). Second, species identified or presumed to have high surrogacy value may not align with the knowledge and infrastructure of existing conservation funding mechanisms or established ecological knowledge (Schweizer et al. 2014). For example, an obscure species may accurately predict the occurrence of other species (i.e., it is a
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strong indicator), but there may be limited information on the life history of the obscure
species that would help inform management. Conversely, species with established
funding streams may be common, and so underappreciated for their potential role as
conservation surrogates (Neeson et al. 2018). Third, many existing tests of surrogate
species focus on a subset of taxa, such as fishes and mollusks (Stewart et al. 2018), birds
(Morelli et al. 2017), and vertebrates (Meurant et al. 2018), with limited inferences
between plants, animals, and other higher-order taxonomic groups. These taxonomic foci
may not conform to existing conservation infrastructure, such as engagement campaigns
or agency expertise.
Funding and knowledge for wildlife management in North America typically
focuses on game species (i.e., those Draftharvested for recreation and subsistence hunting),
which have a high profile but whose populations are not usually at risk (Jacobson et al.
2007; Dalrymple et al. 2012). For example, in the USA, state wildlife agencies dedicate
only about 2 percent of their revenue to non-game species (Scheffer 1973), though
endangered species managed by or in conjunction with game management agencies may
affect this estimate (Restani and Marzluff 2002; Jacobson et al. 2010). Funding for game
species may contribute towards general wildlife management budgets and have spill-over
benefits for non-hunted species (Jacobson et al. 2007). However, in other cases, funding
for conservation of game species diverts funding for direct conservation of non-game
species (Darimont et al. 2018). In spite of the criticisms to this funding model (Artelle et
al. 2018a; 2018b) it is not clear if these funding biases are actually problematic from the
perspective of restoring and conserving biodiversity.
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In addition to funding models associated with consumptive users, non- government conservation organizations often focus on a subset of biodiversity to advance their campaigns. Large mammals in general, and carnivores specifically, feature prominently on the covers of conservation magazines (Clucas et al. 2008), even if their ecological roles are frequently overstated (Allen et al. 2017). Quantifying the surrogacy value among game, non-game, and other species is an important step towards maximizing conservation outcomes from existing wildlife management and conservation infrastructure.
Using a matrix of categorical species-habitat associations, we derived a surrogacy metric by examining the degree to which large game species, large carnivores, and other species overlap in their habitat associationsDraft with terrestrial non-game species. In addition to game and carnivore guilds, we also evaluated the surrogacy value of non-game species, iterating the number of species in the surrogacy group to optimize the strength and coverage of species-habitat associations. We suggest that greater overlap in the habitat associations of species confers a stronger surrogacy value than weaker overlap.
Our goal was to determine which surrogate groups perform best at representing other taxa.
We focused our analysis on British Columbia, Canada’s most species-rich province (Canadian Endangered Species Conservation Council 2001). Currently, British
Columbia is re-examining policy on wildlife habitat management and seeking input on ways to fund wildlife management (Artelle et al. 2018a). As in many areas of North
America, there is a tension in British Columbia to increase opportunity for consumptive uses while also conserving non-game biodiversity (Butler et al. 2003; Artelle et al.
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2018a). As such, there is a need to understand the extent to which current expertise and
funding streams of wildlife management agencies can be leveraged to maximize multiple
conservation outcomes. We shaped our analysis on the spatial planning units used by
wildlife and land managers in British Columbia (i.e., ‘wildlife management units’), each
of which may have local priorities, species representation, and budget constraints.
Methods
We obtained data on species-habitat associations from the Conservation Data Centre
(CDC), an agency of the Provincial Government of British Columbia provincial
government via (Retrieved July 7th 2017
https://www2.gov.bc.ca/gov/content/environment/plants-animals-Draft
ecosystems/conservation-data-centre). These data included 8684 species, of which 7830
were terrestrial and the rest aquatic or marine. Of these terrestrial species, 5856 had no
listed area of occurrence or habitat association, so were excluded from our analysis,
leaving a 1012 species in our data set for analysis (Tables S1, S2, S3 and Fig. S1). There
is an estimated 1140 vertebrate species present in British Columbia, which means that the
vertebrate species included in our analysis represent approximately 21% of those in B.C.
(https://www2.gov.bc.ca/gov/content/environment/plants-animals-
ecosystems/biodiversity). The remaining species in the data set mostly comprised of
vascular and non vascular plants (~40% and ~16% respectively). There were no
invertebrate animals in the dataset. In this case, the area of occurrence was one of nine
designated Wildlife Management Units (WMUs), which are administrative regions over
which hunting regulations, habitat restoration priorities, and funding for wildlife
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8 conservation are allocated (Figure 1). The majority of the 5856 terrestrial species with no
WMU information were plants (n = 2612) or invertebrates (n =1879) (Table S2).
Habitat types were created and assigned to wildlife species by the CDC. Habitat types were categorical, and reflect the classifications used by IUCN species status assessments (IUCN/SSC 2017). To assign species to these habitat types, the CDC integrates information from a variety of sources including museum collections, published literature, unpublished reports, ecosystem mapping, citizen science, and natural history groups (BC Conservation Data Centre 2018). Information about conservation or taxonomy is updated annually (BC Conservation Data Centre 2018). The associations between species and habitat types were binary. We recognize that a more realistic approach would be informed by the Draftstrength of species-habitat association, life history phase, or seasonality. Though our data are limited in this manner, these data are also relatively unique: they contain the associations of diverse taxa from plants, mammals, birds, and insects from a single jurisdiction using a relatively standardized approach across all species.
Data analysis
We used a conditional entropy statistic to measure the strength of pairwise associations in a species occurrence - habitat matrix. We used the netassoc package (Blonder and
Morueta-Holme 2017) in R (Version 1.1.383) to calculate an association score between each pairwise combination of species via their overlapping dependency on habitat categories (code available upon request from the authors).
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We have no a priori information about the link between a given association score
and covariation in fitness or population density between two species. Our approach
assumes that the highest association scores represent a perfect match between habitats for
two species and the lowest scores represent an absence of surrogacy. A field-based
validation of these links were outside the scope of our study, given that this would
involve population performances of multiple taxes (plants, mammals, birds). Thus, we
assessed the percentile association scores to measure habitat-mediated surrogacy.
We created eight types of surrogate species groupings: (1) game species, (2)
ungulates, (3) large carnivores, (4) non-game species, and (5) four groups of aggregated
taxa. A given species may belong to more than one of these groupings (e.g., a species can
be both a game species and an ungulate).Draft Here, game species refer to large mammals and
include: bighorn sheep (Ovis Canadensis Shaw, 1804), cougar (Puma concolor Linnaeus,
1771), grizzly bear (Ursus arctos Linnaeus, 1758), American black bear (Ursus
americanus Pallas, 1780), grey wolf (Canis lupus Linnaeus, 1758), mountain goat
(Oreamnos americanus Blainville, 1816), mule deer (Odocoileus hemionus Rafinesque,
1817), white-tailed deer (Odocoileus virginianus Zimmermann, 1780), elk (Cervus
elaphus Erxleben, 1777), and moose (Alces alces Linnaeus, 1758 ). Ungulates consist of:
bighorn sheep, mountain goat, mule deer, moose, elk, and white-tailed deer. Carnivores
include: cougar, grizzly bear, grey wolf and the American black bear. For each species,
we calculated its mean pairwise association score with all other species. We then selected
the top 11 (i.e., equal in number to the number of game species) non-game species for
each region (see Table S3). The aggregated surrogate groups derived from the mean
pairwise association scores by selecting the top nth percentile species, regardless of their
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game status (see Table S3). We used 80th, 90th, 95th and 99th percentile scores for this
ranking procedure. Lower percentile surrogate groups contain more species, but the
strength of the mean species association value is lower.
For each species within a surrogate group, we calculated its pairwise association
with all other species. We then determined how many pairwise associations exceeded
different thresholds of association. We used percentiles of all pairwise associations to
represent these thresholds: 1st, 50th, 80th, 90th, 95th, and 99th percentiles. If a pairwise
association exceeded the threshold value, the target species was considered ‘captured’ by
the surrogate group (Supplemental Information Figure S1). The lower percentiles are
more comprehensive in the number of species represented by surrogate group than higher
percentiles. The higher percentiles includedDraft fewer species, but the average strength of
association was higher.
We calculated the frequency of pairwise associations captured by each of the
eight surrogate groups (i.e., the 80th, 90th, 95th, and 99th aggregate, game, non-game, carnivores, and ungulates). This analysis measures the frequency of coverage for all unique pairwise associations per se (i.e., 95344 ± 47391 [mean± standard deviation] per region). In other words, we counted how many pairwise associations were captured by a surrogate group, out of all possible pairwise associations. Some of these pairwise associations are redundant, because more than one species in a surrogacy group captures the same non-surrogate species (Supplemental Information Figure S1). We therefore calculated the frequency of species (i.e., 300 ± 81 per region), rather than the frequency of pairwise association, captured by the surrogate groups. In this analysis, a non-
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surrogate species is considered captured when >= 1 species in the surrogate group
exceeded the threshold value for the association score.
We summarized the frequency of pairwise interactions captured by a given
surrogate group and strength of association. For the 95th and 99th thresholds for
association strength, we performed an ANOVA with frequency of included pairwise
associations as the response variable, surrogate group as the predictor, replicated across
WMUs. We then used a Tukey’s Honest Significant Difference test to determine which
surrogate groups were significantly different from one another.
Results
Each species had 5.24 ± 4.83 (meanDraft ± standard deviation) habitat types associated with
them. Mule deer appeared in 33 different habitat types, which represented the widest
habitat breadth in the dataset. Among WMUs, there was a mean of 27-42 species per
habitat type, with ‘meadow’ having the largest number of species (79-167 species per
management unit).
Six of the eleven species identified in the 99th percentile surrogate group are game
species (Table 1), including: American black bear, elk (Rocky Mountain and Roosevelt
subspecies), grey wolf, grizzly bear, and mule deer. Of the species in the 99th percentile
surrogate group, only the American black bear and the rufous hummingbird (Selasphorus
rufus Gmelin, 1788) occurs in every WMU (Table 1). All of the species included in the
top 99th percentile surrogate group appeared in over 20 different habitat types (Table 2).
Grizzly bears appeared in the fewest habitat types of any species included in the top 99th
percentile surrogate group, with occurrences in 25 habitat types. Species included in the
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top 99th percentile surrogate group appeared in 28 different habitat types. In the non-
game surrogate group, 75% of species were birds (Table 2). There were more species that
were found in all WMUs in the non-game species surrogate group, all of which were
birds: American kestrel (Falco spaverius Linnaeus, 1758), barn swallow (Hirundo rustica
Linnaeus, 1758), Barrow’s goldeneye (Bucephala islandica Gmelin, 1789), common
nighthawk (Chordeiles minor J. R. Forster, 1771), killdeer (Charadrius vociferus
Linnaeus, 1758), rufous hummingbird, and the tree swallow (Tachycineta bicolor
Vieillot, 1808).
At weaker thresholds of association (i.e., below the 50th percentile), all surrogate
groups captured all possible pairwise associations in the province (Figure 2). As the
strength of association threshold exceedsDraft 80th percentile, the surrogate groups diversify
in their performance. The top 80th percentile surrogate group captures the lowest
frequency of pairwise associations (> 25%), while the top 99th percentile has the overall best coverage of pairwise associations (~50%) (Figure 2). A post-hoc Tukey test indicated that game and non-game species surrogate groups do not significantly differ in the frequency of captured pairwise associations (P = 0.982). The game and non-game surrogate groups both cover > 25% of potential pairwise associations. The carnivore surrogate group performed significantly better than the ungulate group at high levels of association (P = 0.004), with carnivores covering approximately 25% of pairwise associations (Figure 2). This is consistent with other papers that suggest the importance of carnivores as biological indicators (Ripple et al. 2014; Allen et al. 2017).
Considering the proportion of species covered per se (rather than the proportion of pairwise associations) by surrogate groups, ungulates covered the fewest species
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(~40% of species), while the 95th percentile surrogate group covered the most (~80% of
species) (Figure 3). The game and non-game surrogate groups did not significantly differ
in their coverage of species (P = 0.999), with both groups covering > 75% of species
(Figure 3). However, the carnivore surrogate group did significantly better than the
ungulate group (P = 0.035), covering greater than 50% of species, while the ungulate
group covered ~ 40% (Figure 3).
Discussion
Based on the association scores of 1012 species, mediated by 64 habitat types, the
best surrogate grouping to direct conservation funding are aggregate taxa composed of
both game and non-game species. OurDraft results reveal that the game species surrogate
group did not perform significantly better than the non-game surrogate group (Figure 3).
This finding is consistent with analyses conducted on similar data-sets for the Southern
California Coastal Sage Scrub Ecoregion, the Columbia Plateau Ecoregion, and the
continental United States, which found that large game species did not perform better
than a random selection of species from within those regions (Andelman and Fagan
2000).
Although the 11 species that comprised the non-game surrogate group did not
have higher average association scores than the game species surrogate group (Figures 2
and 3), our results suggest that there is not necessarily a need to restructure the existing
funding model to favour non-game species per se, nor to devalue the use of game species
as surrogate taxa. Considering the existing funding bias in British Columbia - large game
species currently receive a disproportionate amount of conservation funding (Dayer et al.
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2016; Habitat Conservation Trust Foundation 2018-19 Approved Project List) - and our analysis suggests that this existing funding bias is likely adequate to conserve the habitats for a significant portion of species in British Columbia.
To maximize conservation outcomes in British Columbia, our analysis reveals that a mix of game and non-game species should be adopted as surrogates. The top 99th percentile surrogate group, which covered the most pairwise associations (Figure 2, bottom) contained both game and non-game species. Similarly, the Top 80th, 90th, 95th, and 99th surrogate groups also contained game and non-game species, and have a large
(>= 75%) proportion of captured species. These results suggest that conservation projects targeting non-game species will create benefits for game species, and vice-versa.
However, acting on these results in aDraft conservation management setting would require shifting conservation budgets and gaining stakeholder support to broaden definitions of
‘wildlife’. This transition may prove to be costly and time consuming, with unclear gains relative to the current emphasis on game species.
Our analysis also supports the use of carnivores as conservation surrogates, as this group captured significantly more pairwise associations and more species compared to the ungulate surrogate group (Figures 1 and 2, respectively). This finding is consistent with other research that has highlighted the use of large carnivores as umbrella species due to their expansive home ranges, and therefore increased species and habitat associations (Noss et al. 1996; Branton and Richardson 2011; Rozylowicz et al. 2011).
However, this approach has been criticized for failure to consider the connectivity of the respective habitat used by the carnivores, and the lack of a multi-taxonomic approach in these studies (Roberge and Angelstam 2004; Cushman and Landguth 2012). Therefore,
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further studies that validate the use of carnivores of surrogates in general, and their
functional roles specifically, are needed to justify these taxa as a broad scale surrogate
group in British Columbia.
Our analysis was framed around the spatial planning or decision-making units
adopted by British Columbia’s resource management agencies (i.e., WMU - wildlife
management units). In British Columbia, each WMU is associated with some degree of
individualized hunting and trapping regulations, budgetary constraints, restoration
priorities, and stakeholder cultures. Our analyses match the scale and boundaries of these
decision-making units, thereby harmonizing these data to existing management
infrastructure. This scale of analyses differs from some common, ‘ecoregional’
approaches used in surrogate speciesDraft analyses, which may well match ecological process
and biogeographic patterns of diversity, but may not align with the decision making unit
of the agencies responsible for implementing conservation actions (Coristine et al. 2018;
2019; Rapacciuolo et al. 2018).
Our analysis addressed ecological and management redundancy through
examining the surrogacy of each species’ pairwise associations, wherein a single species
could be covered by more than one of the surrogate groups we selected. For example, the
long-tailed weasel (Mustela frenata Lichtenstein, 1831) appeared as a top-ranking
surrogate in both the non-game and 99th percentile surrogate groups (Tables 1 and 2).
Redundancy in ecological systems in general has been identified as a key factor in
increasing the stability of ecosystems and maintaining ecosystem functions (Naeem 1998;
Rosenfeld 2002; Goswami et al. 2017). Therefore, using surrogate groups that have
redundant associations with other species may help mitigate imprecision in species-
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16 habitat data and provide a more robust assessment of covariation in fitness between surrogate and non-surrogate species.
Interestingly, the highest ranked surrogate species for each WMU, as well as the province itself, was the rufous hummingbird. The rufous hummingbird breeds farther north than any other hummingbird species, has the largest migration of any bird relative to body size (Moran et al. 2013), and is vulnerable to changes in habitat quality along it’s migratory route (Russell et al. 1994). Birds in general are considered good surrogates due to their broad and variable home ranges, short life spans, and generally accurate and abundant survey data (Järvinen and Väisänen 1979; Canterbury et al. 2000; Browder et al. 2002; Quinn et al. 2011). Our analysis supports these findings, as all of the species in the non-game surrogate group foundDraft to be high-ranking surrogates ubiquitously across each WMU were birds (Table 2). It is possible that the expansive home range of the rufous hummingbird contributed to its success as a surrogate species. Given the performance of birds as surrogate species, further studies linking bird fitness to other biodiversity indicators may be a more cost-effective approach to surveillance than quantifying trends in large mammals.
While these results have interesting implications for conservation and management, we were unable to validate this approach within the confines of this study.
A field-based validation in which species co-occurrences (or population trajectories) were recorded in respective habitat types would be ideal, however due to the large-scale nature of this study, it would be logistically impractical. Part of the challenge of validating a surrogate approach of this kind is the use of multi-taxa surrogate groupings. There is a lack of quality data surrounding spatially-distinct occurrences of multiple taxa, much of
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which reflects taxonomic biases in conservation literature (Troudet et al. 2017). The use
of multiple surrogate species is gaining traction in conservation literature (Meurant et al.
2018) and our study represents a practical way to integrate this knowledge in decision -
making for multiple taxa approach in British Columbia.
There are at least three ways in which our study could be improved for future
analysis. First, there was a clear taxonomic bias in the species removed from our analysis
due to incomplete habitat association information, which could have influenced the
results. The majority of species with incomplete information are plants or invertebrates,
which is consistent with taxonomic biases towards more charismatic species apparent in
both conservation literature (Clark 2002; Ford et al. 2017), as well as general scientific
literature (Troudet et al. 2017). To expandDraft the results of this study and studies like it,
better data needs to be collected for these underrepresented species. Second, this study is
spatially implicit in the sense that associations were based off co-occurrence in habitat
types, not necessarily demographic rates, interactions, or locations. This meant that we
could not prioritize certain interactions, such as mutualistic relationships or trophic
cascades, that may be relevant for ecosystem level conservation (Ritchie and Johnson
2009; Harvey et al. 2017). Third, there is a need to develop surrogacy measures that
address the co-occurrence of species and the contributions of habitat types to species
diversity (Rapacciuolo et al. 2018). A logical next step in this field is to quantify
surrogacy of fitness or population density, rather than occurrence per se.
Our findings suggest that focusing conservation attention - specifically habitat
restoration - on game species is likely to confer benefits to many other species in British
Columbia. Our results also suggest that a non-game per se surrogate group would not be
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18 significantly better at covering species associations, and therefore the current bias of conservation funding towards game species is likely adequate for providing benefits to broader biodiversity conservation objectives. However, based on our results, conservation efforts are maximized by focusing efforts on a mix of game and non-game species. This outcome could be achieved by facilitating cooperation among groups advocating for the consumptive and non-consumptive values of wildlife.
Acknowledgements
This research was supported by the Canada Foundation for Innovation, the National
Sciences and Engineering Research Council (Canada), and the Canada Research Chairs program. Comments from J. Pither helpedDraft shape the direction of this research. We thank
Drs. J.T. Fisher and R. Schuster for their thoughtful comments on an earlier version of this manuscript.
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References
Allen, B.L., Allen, L.R., Andrén, H., Ballard, G., Boitani, L., Engeman, R.M., et al.
2017. Can we save large carnivores without losing large carnivore science? Food
Webs, 12: 64–75. doi:10.1016/j.fooweb.2017.02.008.
Andelman, S.J., and Fagan, W.F. 2000. Umbrellas and flagships: efficient conservation
surrogates or expensive mistakes? Proc. Natl. Acad. Sci. U.S.A. 97(11): 5954–9.
doi:10.1073/pnas.100126797.
Artelle, K.A., Moola, F.M., Paquet, P.C., and Darimont, C.T. 2018a. British Columbia’s
Wildlife Model Reform. Science, 361(6401): 459–460.
doi:10.1126/science.aau4222.
Artelle, K.A., Reynolds, J.D., Treves,Draft A., Walsh, J.C., Paquet, P.C., and Darimont, C.T.
2018b. Hallmarks of science missing from North American wildlife management.
Sci. Adv. 4(3): eaao0167. doi:10.1126/sciadv.aao0167.
Barnes, M.D., Glew, L., Wyborn, C., and Craigie, I.D. 2018. Prevent perverse outcomes
from global protected area policy. Nat. Ecol. Evol. 2(5): 759-762.
doi:10.1038/s41559-018-0501-y.
BC Conservation Data Centre. 2018. BC Species Ecosystems Explorer. B.C. Ministry of
Environment, Victoria B.C. Available:
https://www2.gov.bc.ca/gov/content/environment/plants-animals-
ecosystems/conservation-data-centre/explore-cdc-data/faq [Accessed 31 January
2018]
Blonder, B., and Morueta-Holme, N. 2017. Inference of Species Associations from Co-
Occurence Data. Available from https://cran.r-
https://mc06.manuscriptcentral.com/cjz-pubs Canadian Journal of Zoology Page 20 of 37
20
project.org/web/packages/netassoc/netassoc.pdf.
Bottrill, M.C., Joseph, L.N., Carwardine, J., Bode, M., Cook, C., Game, E.T., et al. 2008.
Is conservation triage just smart decision making? Trends Ecol. Evol. 23(12): 649-
654. doi:10.1016
Branton, M., and Richardson, J.S. 2011. Assessing the Value of the Umbrella-Species
Concept for Conservation Planning with Meta-Analysis. Conserv. Biol. 25(1): 9–20.
doi:10.1111/j.1523-1739.2010.01606.x.
Browder, S.F., Johnson, D.H., and Ball, I.J. 2002. Assemblages of breeding birds as
indicators of grassland condition. Ecol. Indic. 2(3): 257–270. doi:10.1016/S1470-
160X(02)00060-2.
Butler, J.S., Shanahan, J., and Decker,Draft D.J. 2003. Public attitudes toward wildlife are
changing: a trend analysis of New York residents. Wildl. Soc. Bull. 31(4): 1027–
1036. doi:10.2307/3784448.
Campbell, M.A., Kopach, B., Komers, P.E., and Ford, A.T. 2019. Quantifying the
impacts of oil sands development on wildlife: perspectives from impact assessments.
Environ. Rev.doi:10.1139/er-2018-0118.
Canadian Endangered Species Conservation Council. 2001. Wild Species 2000: The
General Status of Species in Canada. Ottawa.
Canterbury, G.E., Martin, T.E., Petit, D.R., Petit, L.J., and Bradford, D.F. 2000. Bird
Communities and Habitat as Ecological Indicators of Forest Condition in Regional
Monitoring. Conserv. Biol. 14(2): 544–558. doi:10.1046/j.1523-1739.2000.98235.x.
Caro, T.M., O ’Doherty, G., and O ’Dohertyt, G. 1999. On the Use of Surrogate Species
in Conservation Biology. Conserv. Biol. 13(4): 805–814.
https://mc06.manuscriptcentral.com/cjz-pubs Page 21 of 37 Canadian Journal of Zoology
21
Caro, T. 2010. Conservation by proxy: Indicator, Umbrella, Keystone, Flagship and other
surrogate species. Island Press, Washington, DC.
Clark, J.A. 2002. Taxonomic Bias in Conservation Research. Science, 297(5579): 191b –
192. doi:10.1126/science.297.5579.191b.
Clucas, B., McHugh, K., and Caro, T. 2008. Flagship species on covers of US
conservation and nature magazines. Biodivers. Conserv. 17(6): 1517–1528.
doi:10.1007/s10531-008-9361-0.
Coristine, L.E., Jacob, A.L., Schuster, R., Otto, S.P., Baron, N.E., Bennett, et al. 2018.
Informing Canada’s commitment to biodiversity conservation: A science-based
framework to help guide protectedDraft areas designation through Target 1 and beyond.
FACETS, 3(1): 531–562. doi:10.1139/facets-2017-0102.
Coristine, L.E., Colla, S., Bennett, N., Carrlsson, A., Davy, C., Davies, et al. 2019.
National contributions to global ecosystem values. Conserv. Biol. 33: 1219-
1223.doi:10.1111/cobi.13284.
Cushman, S.A., and Landguth, E.L. 2012. Multi-taxa population connectivity in the
Northern Rocky Mountains. Ecol. Modell. 231: 101–112. Elsevier.
doi:10.1016/J.ECOLMODEL.2012.02.011.
Dalrymple, C.J., Peterson, M.N., Cobb, D.T., Sills, E.O., Bondell, H.D., and Dalrymple,
D.J. 2012. Estimating public willingness to fund nongame conservation through
state tax initiatives. Wildl. Soc. Bull. 36(3): 483–491. doi:10.1002/wsb.164.
Darimont, C.T., Paquet, P.C., Treves, A., Artelle, K.A., and Chapron, G. 2018. Political
populations of large carnivores. Conserv. Biol. 32: 747-749.
https://mc06.manuscriptcentral.com/cjz-pubs Canadian Journal of Zoology Page 22 of 37
22
doi:10.1111/cobi.13065.
Dayer, A.A., Bright, A.D., Teel, T.L., and Manfredo, M.J. 2016. Application of a Stated
Choice Approach to Assessing Public Preferences for Wildlife Conservation
Funding. Hum. Dimens. Wildl. 21(5): 379–390.
doi:10.1080/10871209.2016.1169565.
Dirzo, R., Young, H.S., Galetti, M., Ceballos, G., Isaac, N.J.B., and Collen, B. 2014.
Defaunation in the Anthropocene. Science, 345(6195): 401–406.
doi:10.1126/science.1251817.
Fahrig, L. 2001. How much habitat is enough? Biol. Conserv. 100(1): 65–74.
doi:10.1016/S0006-3207(00)00208-1.
Ford, A.T., Cooke, S.J., Goheen, J.R.,Draft and Young, T.P. 2017. Conserving megafauna or
sacrificing biodiversity? Bioscience, 67(3): 193-196. doi:10.1093/biosci/biw163.
Gaynor, K.M., Hojnowski, C.E., Carter, N.H., and Brashares, J.S. 2018. The influence of
human disturbance on wildlife nocturnality. Science, 360(6394): 1232–1235.
doi:10.1126/science.aar7121.
Goswami, M., Bhattacharyya, P., Mukherjee, I., and Tribedi, P. 2017. Functional
Diversity: An Important Measure of Ecosystem Functioning. Adv. Microbiol. 7(01):
82–93. doi:10.4236/aim.2017.71007.
Habitat Conservation Trust Foundation 2017-18 Approved Project List. Victoria B.C.
Available: https://hctf.ca/wp-content/uploads/2019/04/HCTF-Project-List-2017-
18.pdf [Accessed April 19 2018]
Hanski, I. 2011. Habitat Loss, the Dynamics of Biodiversity, and a Perspective on
Conservation. Ambio, 40(3): 248–255. doi:10.1007/s13280-011-0147-3.
https://mc06.manuscriptcentral.com/cjz-pubs Page 23 of 37 Canadian Journal of Zoology
23
Harvey, E., Gounand, I., Ward, C.L., and Altermatt, F. 2017. Bridging ecology and
conservation: from ecological networks to ecosystem function. J. Appl. Ecol. 54(2):
371–379. doi:10.1111/1365-2664.12769.
Heim, N., Fisher, J.T., Volpe, J., Clevenger, A.P., and Paczkowski, J. 2019. Carnivore
community response to anthropogenic landscape change: species-specificity foils
generalizations. Landsc. Ecol. 34 (11): 2493–2507. doi:10.1007/s10980-019-00882-
z.
Henry, E., Brammer-Robbins, E., Aschehoug, E., and Haddad, N. 2019. Do substitute
species help or hinder endangered species management? Biol. Conserv. 232: 127–
130. Elsevier. doi:10.1016/J.BIOCON.2019.01.031.
Hermoso, V., Januchowski-Hartley,Draft S.R., and Pressey, R.L. 2013. When the suit does not
fit biodiversity: Loose surrogates compromise the achievement of conservation
goals. Biol. Conserv. 159: 197–205. doi:10.1016/j.biocon.2012.11.026.
IUCN/SSC. 2017. The IUCN Red List of Threatened Species.Version 2017-3. Available
from https://www.iucnredlist.org/resources/summary-statistics#Summary%20Tables
[Accessed 31 January 2018]
Jacobson, C.A., Decker, D.J., and Carpenter, L. 2007. Securing Alternative Funding for
Wildlife Management: Insights from Agency Leaders. J. Wildl. Manage. 71(6):
2106–2113.. doi:10.2193/2006-442.
Jacobson, C.A., Organ, J.F., Decker, D.J., Batcheller, G.R., and Carpenter, L. 2010. A
Conservation Institution for the 21st Century: Implications for State Wildlife
Agencies. J. Wildl. Manage. 74(2): 203–209. Wiley-Blackwell. doi:10.2193/2008-
485.
https://mc06.manuscriptcentral.com/cjz-pubs Canadian Journal of Zoology Page 24 of 37
24
Järvinen, O., and Väisänen, R.A. 1979. Changes in bird populations as criteria of
environmental changes. Ecography, 2(2): 75–80. doi:10.1111/j.1600-
0587.1979.tb00684.x.
Jepson, P., and Barua, M. 2015. A Theory of Flagship Species Action. Conserv. Soc.
13(1): 95. doi:10.4103/0972-4923.161228.
Landres, P.B., Verner, J., Thomas, J.W. 1988. Society for Conservation Biology
Ecological Uses of Vertebrate Indicator Species : A Critique. Conserv. Biol. 2(4):
316–328. doi:10.1111/j.1523- 1739.1988.tb00195.x
Martin, T.G., Kehoe, L., Mantyka-Pringle, C., Chades, I., Wilson, S., Bloom, R.G., et al.
2018. Prioritizing recovery funding to maximize conservation of endangered
species. Conserv. Lett. 11(6): e12604.Draft doi:10.1111/conl.12604.
Meurant, M., Gonzalez, A., Doxa, A., and Albert, C.H. 2018. Selecting surrogate species
for connectivity conservation. Biol. Conserv.227: 326 -334
Moran, J.A., Wassenaar, L.I., Finlay, J.C., Hutcheson, C., Isaac, L.A., and Wethington,
S.M. 2013. An exploration of migratory connectivity of the Rufous Hummingbird
(Selasphorus rufus), using feather deuterium. J. Ornithol. 154(2): 423–430.
doi:10.1007/s10336-012-0906-3.
Morelli, F., Møller, A.P., Nelson, E., Benedetti, Y., Liang, W., Šímová, P., Moretti, M.,
and Tryjanowski, P. 2017. The common cuckoo is an effective indicator of high bird
species richness in Asia and Europe. Sci. Rep. 7: Article 4376 doi:10.1038/s41598-
017-04794-3.
Muir, J., Hawkes, V.C., Tuttle, K.N., and Mochizuk, T. 2011. Synthesis of Habitat
Models used in the Oil Sands Region. Report prepared for the Cumulative
https://mc06.manuscriptcentral.com/cjz-pubs Page 25 of 37 Canadian Journal of Zoology
25
Environmental Management Association (CEMA), Fort McMurray, Alberta by
LGL Limited Environmental Research Associates, Sidney, British Columbia.
LGL Report EA3259. 76 pp.
Naeem, S. 1998. Species Redundancy and Ecosystem Reliability. Conserv. Biol. 12(1):
39–45.
Neeson, T.M., Doran, P.J., Ferris, M.C., Fitzpatrick, K.B., Herbert, M., Khoury, M., et al.
2018. Conserving rare species can have high opportunity costs for common species.
Global Change Biol. 24(8): 3862–3872. doi:10.1111/gcb.14162.
Nekaris, K., Arnell, A.P., and Svensson, M.S. 2015. Selecting a conservation surrogate
species for small fragmented habitats using ecological niche modelling. Animals,
5(1): 27–40. doi:10.3390/ani5010027.Draft
Newbold, T., Hudson, L.N., Hill, S.L.L., Contu, S., Lysenko, I., Senior, R.A., et al. 2015.
Habitat Loss and Extinction in the Hotspots of Biodiversity. Brazilian J. Biol.
104(4): 909–923. doi:10.1046/j.1523-1739.2002.00530.x.
Noss, R.F., Quigley, H.B., Hornocker, M.G., Merrill, T., and Paquet, P.C. 1996.
Conservation Biology and Carnivore Conservation in the Rocky Mountains.
Conserv. Biol. 10(4): 949–963.
Otto, S.P. 2018. Adaptation, speciation and extinction in the Anthropocene. Proc. R. Soc.
B. 285(1891): 20182047. doi:10.1098/rspb.2018.2047.
Quinn, J.E., Brandle, J.R., Johnson, R.J., and Tyre, A.J. 2011. Application of detectability
in the use of indicator species: A case study with birds. Ecol. Indic. 11: 1413–1418.
doi:10.1016/j.ecolind.2011.03.003.
Rapacciuolo, G., Graham, C.H., Marin, J., Behm, J.E., Costa, G.C., Hedges, S.B., et al.
https://mc06.manuscriptcentral.com/cjz-pubs Canadian Journal of Zoology Page 26 of 37
26
2018. Species diversity as a surrogate for conservation of phylogenetic and
functional diversity in terrestrial vertebrates across the Americas. Nat. Ecol. Evol. 3:
53-61. 1.doi:10.1038/s41559-018-0744-7.
Restani, M., and Marzluff, J.M. 2002. Funding Extinction? Biological Needs and
Political Realities in the Allocation of Resources to Endangered Species Recovery.
Bioscience, 52(2): 169-177. doi:10.1641/0006-
3568(2002)052[0169:FEBNAP]2.0.CO;2.
Ripple, W.J., Estes, J.A., Beschta, R.L., Wilmers, C.C., Ritchie, E.G., Hebblewhite, M.,
et al. 2014. Status and ecological effects of the world’s largest carnivores. Science,
343(6167): 151-163. doi:10.1126/science.1241484.
Ritchie, E.G., and Johnson, C.N. 2009.Draft Predator interactions, mesopredator release and
biodiversity conservation. Ecol. Lett. 12(9): 982–998. doi:10.1111/j.1461-
0248.2009.01347.x.
Roberge, J.-M., and Angelstam, P. 2004. Usefulness of the umbrella species concept as a
conservation tool. Conserv. Biol. 18(1): 76-85. doi:10.1111/j.1523-
1739.2004.00450.x.
Rodrigues, A.S.L., and Brooks, T.M. 2007. Shortcuts for Biodiversity Conservation
Planning: The Effectiveness of Surrogates. Annu. Rev. Ecol. Evol. Syst. 38(1): 713–
737. doi:10.1146/annurev.ecolsys.38.091206.095737.
Rosenfeld, J.S. 2002. Functional Redundancy in Ecology and Conservation. Oikos, 98(1):
156–162.
Rozylowicz, L., Popescu, V.D., Pǎtroescu, M., and Chişamera, G. 2011. The potential of
large carnivores as conservation surrogates in the Romanian Carpathians. Biodivers.
https://mc06.manuscriptcentral.com/cjz-pubs Page 27 of 37 Canadian Journal of Zoology
27
Conserv. 20(3): 561–579. doi:10.1007/s10531-010-9967-x.
Russell, R.W., Carpenter, F.L., Hixon, M.A., and Paton, D.C. 1994. The impact of
variation in stopover habitat quality on migrant rufous hummingbirds. Conserv.
Biol. 8(2): 483–490. doi:10.1046/j.1523-1739.1994.08020483.x.
Scheffer, V.B. 1973. The Future of Wildlife Management. Wildl. Soc. Bull. 4(2): 51–54.
Schweizer, M., Ayé, R., Kashkarov, R., and Roth, T. 2014. Conservation action based on
threatened species capture taxonomic and phylogenetic richness in breeding and
wintering populations of Central Asian birds. PLoS One, 9(10): e110511.
doi:10.1371/journal.pone.0110511.
Shackelford, N., Standish, R.J., Ripple, W., and Starzomski, B.M. 2018. Threats to
biodiversity from cumulative humanDraft impacts in one of North America’s last wildlife
frontiers. Conserv. Biol. 32(3): 672–684. doi:10.1111/cobi.13036.
Stewart, D.R., Underwood, Z.E., Rahel, F.J., and Walters, A.W. 2018. The effectiveness
of surrogate taxa to conserve freshwater biodiversity. Conserv. Biol. 32: 183-
194.doi:10.1111/cobi.12967.
Tilman, D., May, R.M., Lehman, C.L., and Nowak, M.A. 1994. Habitat destruction and
the extinction debt. Nature, 371(6492): 65–66. doi:10.1038/371065a0.
Troudet, J., Grandcolas, P., Blin, A., Vignes-Lebbe, R., and Legendre, F. 2017.
Taxonomic bias in biodiversity data and societal preferences. Sci. Rep. 7(1): 9132.
Nature Publishing Group. doi:10.1038/s41598-017-09084-6.
Tucker, M.A., Böhning-Gaese, K., Fagan, W.F., Fryxell, J.M., Van Moorter, B., Alberts,
S.C., et al. 2018. Moving in the Anthropocene: Global reductions in terrestrial
mammalian movements. Science, 359(6374): 466-469.
https://mc06.manuscriptcentral.com/cjz-pubs Canadian Journal of Zoology Page 28 of 37
28
doi:10.1126/science.aam9712.
Venter, O., Sanderson, E.W., Magrach, A., Allan, J.R., Beher, J., Jones, K.R., et al. 2016.
Sixteen years of change in the global terrestrial human footprint and implications for
biodiversity conservation. Nat. Commun. 7(1): 12558. doi:10.1038/ncomms12558.
Draft
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Tables
Table 1. Species selected (shown by the “•”) for the top 99th percentile surrogate group
for each wildlife management unit. Association score shown for the Province-wide
assessment only.
Wildlife management unit Association Province- score Species 1 2 3 4 5 6 7A 7B 8 wide (mean ±SD) American black bear • • • • • • • • • • 0.65 ± 0.04 (Ursus amricanus)
Barn swallow • 0.63 ± 0.07 (Hirundo rustica) Draft Coyote • • 0.64 ± 0.06 (Canis latrans) Rocky Mountain Elk • 0.64 ± 0.05 (Cervus elaphus) Grey Wolf • • • • • • • • 0.65 ± 0.05 (Canis lupus) Grizzly bear • 0.63 ± 0.04 (Ursus arctos) Long-tailed weasel • 0.64 ± 0.06 (Mustela frenata)
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Mule deer • • • • • • 0.64 ± 0.06 (Odocoileus hemionus) Rufous hummingbird • • • • • • • • • • 0.66 ± 0.04 (Selasphorus rufus) Tree swallow • • 0.64 ± 0.05 (Tachycineta bicolor)
Draft
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Table 2. Species selected (shown by the “•”) non-game game surrogate group for each
wildlife management unit.
Wildlife management unit
Species 1 2 3 4 5 6 7A 7B 8 Province-wide
American goldfinch
(Spinus tristis) • • • • • • •
American kestrel
(Falco spaverius) • • • • • • • • • •
Bald eagle Draft (Haliaeetus • • • leucocoephalus)
Barn swallow
(Hirundo rustica) • • • • • • • • • •
Barrow's goldeneye
(Bucephala islandica) • • • • • • • • •
Common nighthawk
(Chordeiles minor) • • • • • • • • • •
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Common ringlet
(Coenonymoha tullia) • • • •
Coyote • • • • • • • • (Canis latrans)
Gyrfalcon
(Falco rusticolus) • • •
Killdeer (Charadrius • • • • • • • • • • vociferous) Draft
Long-tailed weasel
(Mustela frenata) • •
Peregrine falcon
(Falco peregrinus) • • • • • • • •
Rufous hummingbird
(Selasphorus rufus) • • • • • • • • • •
Tree swallow • • • • • • • • • • (Tachycineta bicolor)
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Wolverine • • • • • • (Gulo gulo)
Figures: Draft
Figure 1. Province of British Columbia showing the 9 wildlife management units
(WMUs) that are used to guide wildlife management planning. Figure was created using
ArcGIS version 10.5 and assembled using data from British Columbia Wildlife
Management Units Data Catalogue (accessible online at
catalogue.data.gov.bc.ca/dataset/wildlife-management-units). Catalogue published by the
British Columbia Ministry of Forests, Lands, Natural Resource Operations and Rural
Development - Wildlife and Habitat and Licensed under "Open Government Licence -
British Columbia" (https://www2.gov.bc.ca/gov/content/data/open-data/open-
government-licence-bc) Base map from Esri "Light Gray Canvas Map" Scale Not Given.
"Canvas Base"
(https://services.arcgisonline.com/ArcGIS/rest/services/Canvas/World_Light_Gray_Base/
MapServer) Last Accessed: Dec. 6, 2019. Created: Sep. 26, 2011; Updated: Jan. 9, 2020.
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Figure 2. Proportion of pairwise associations capture by the 8 surrogate groups we tested for (top) all levels of association strength and (bottom) for the 99th percentile strength of association. Error bars represent the standard error, observed over the 9 wildlife management units of British Columbia. Letters above the bars indicate significantly different groups (P < 0.05) from a Tukey’s Post-Hoc comparison.
Figure 3. Proportion of species captured by the 8 surrogate groups we tested for (top) all levels of association strength and (bottom) for the 99th percentile strength of association.
Error bars represent the standard error, observed over the 9 wildlife management units of
British Columbia. Letters above the Draftbars indicate significantly different groups (P < 0.05) from a Tukey’s Post-Hoc comparison.
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