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Boreal forest landbirds in relation to forest composition, structure, and landscape: implications for forest management L.A. Venier and J.L. Pearce
Abstract: We examined a landbird community and its relationship to environmental variables within the boreal forest in north–central Ontario to evaluate its potential usefulness as an indicator of sustainable forest management. Our study had two components. First, we compared bird assemblages in mature forest stands inside Pukaskwa National Park (n = 17) with similar forested stands in a logged landscape (n = 18) over 3 years. We found significant separation of sites in the two treatments based on an ANOSIM (analogue of the standard univariate one-way ANOVA test) of the bird communities (R = 0.238, p < 0.001). We identified four significant indicators of the park landscape (bay-breasted warbler (Dendroica castanea (Wilson, 1810)), black-throated green warbler (Dendroica virens (J.F. Gmelin, 1789)), ovenbird (Seiurus aurocapillus (L., 1766)), and red-eyed vireo (Vireo olivaceus (L., 1766))) and five indicators of the logged landscape (blackbacked woodpecker (Picoides arcticus (Swainson, 1832)), brown creeper (Certhia americana Bonaparte, 1838), winter wren (Troglodytes troglodytes (L., 1758)), white-throated sparrow (Zonotrichia albicollis (J.F. Gmelin, 1789)), and yellowbellied sapsucker (Sphyrapicus varius (L., 1776))). Some relationships were attributable to differences in vegetation, whereas other differences were attributable to the landscape context. Second, we used generalized additive models to examine the relationship of individual species with four sets of environmental data (understorey floristics, forest structure, overstorey composition, and landscape context) using the 35 sites noted above and 18 additional mature forest sites in the logged landscape (n = 53). We found that all four types of variables were frequently included in the best model based on Akaike’s information criterion (AIC) (structure in 23 models, landscape in 20 models, overstorey in 19 models, and understorey in 15 models). We discuss our results in terms of their implications to forest management and note that our ability to map habitat for forest birds is substantially compromised by the lack of good spatial estimates of environmental variables that describe bird habitat. Re´sume´ : Nous avons examine´ une communaute´ d’oiseaux terrestres et ses relations avec des variables environnementales dans la foreˆt bore´ale du centre-nord de l’Ontario pour e´valuer son utilite´ potentielle comme indicateur d’ame´nagement forestier durable. Notre e´tude comportait deux volets. Premie`rement, nous avons compare´ pendant trois ans les assemblages d’oiseaux de peuplements de foreˆt mature du parc national Pukaskwa (n = 17) avec ceux de peuplements forestiers semblables dans un paysage qui avait subi des coupes forestie`res (n = 18). Nous avons observe´ une se´gre´gation des stations dans les deux traitements a` partir d’une analyse de variance (ANOSIM) des communaute´s d’oiseaux (R = 0,238, p < 0,001). Nous avons identifie´ quatre indicateurs significatifs du paysage du parc (la paruline a` poitrine baie (Dendroica castanea (Wilson, 1810)), la paruline a` gorge noire (Dendroica virens (J.F. Gmelin, 1789)), la paruline couronne´e (Seiurus aurocapillus (L., 1766)) et le vire´o aux yeux rouges (Vireo olivaceus (L., 1766))) et cinq indicateurs du paysage coupe´ (le pic a` dos noir (Picoides arcticus (Swainson, 1832)), le grimpereau brun (Certhia americana Bonaparte, 1838), le troglodyte mignon (Troglodytes troglodytes (L., 1758)), le bruant a` gorge blanche (Zonotrichia albicollis (J.F. Gmelin, 1789)) et le pic macule´ (Sphyrapicus varius (L., 1776))). Certaines relations e´taient attribuables aux diffe´rences dans la ve´ge´tation tandis que d’autres diffe´rences e´taient attribuables au contexte paysager. Deuxie`mement, nous avons utilise´ des mode`les additifs ge´ne´raux pour examiner la relation entre chaque espe`ce et quatre jeux de donne´es environnementales incluant le corte`ge floristique du sous-bois, la structure de la foreˆt, la composition de la canope´e et le contexte paysager des 35 stations mentionne´es plus haut et de 18 stations additionnelles de foreˆt mature dans le paysage coupe´ (n = 53). Nous avons trouve´ que les quatre types de variables e´taient souvent repre´sente´s dans le meilleur mode`le sur la base du crite`re d’information d’Akaike (AIC) (la structure dans 23 mode`les, le paysage dans 20 mode`les, la canope´e dans 19 mode`les et le sousbois dans 15 mode`les). La discussion fait e´tat des implications de nos re´sultats pour l’ame´nagement forestier et nous notons le fait que notre capacite´ a` cartographier l’habitat des oiseaux forestiers est substantiellement compromise par l’absence de bonnes estimations spatiales des variables environnementales qui de´crivent l’habitat des oiseaux. [Traduit par la Re´daction]
Received 19 June 2006. Accepted 1 December 2006. Published on the NRC Research Press Web site at cjfr.nrc.ca on 8 August 2007. L.A. Venier1 and J. Pearce.2 Great Lakes Forestry Centre, Canadian Forest Service, 1219 Queen St. E, Sault Ste. Marie, ON P6A 2E5, Canada. 1Corresponding 2Present
author (e-mail:
[email protected]). address: Pearce & Associates Ecological Research, 1405 Third Line East, Sault Ste. Marie, ON P6A 6J8, Canada.
Can. J. For. Res. 37: 1214–1226 (2007)
doi:10.1139/X07-025
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Introduction Forest birds are an important component of the boreal forest ecosystem. In the boreal forests of northern Ontario, birds represent approximately 71% of the terrestrial vertebrates (Niemi et al. 1998). In terms of ecosystem function, birds reduce insect densities (Holmes et al. 1979), lengthen time between spruce budworm (Choristoneura fumiferana (Clemens)) outbreaks (Holling 1988), increase forest productivity through predation of leaf-eating insects (Marquis and Whelan 1994), influence tree species composition (Folke et al. 1996), and provide a variety of other ecosystem services, including the dissemination of seeds and nutrient and energy cycling (Niemi et al. 1998). Birds integrate many structural and functional components of the forest ecosystem such that changes in their populations may serve to indicate changes in important ecological conditions (McLaren et al. 1998; Niemi et al. 1998; Venier and Pearce 2004). They are included as important elements of many monitoring programs designed to assess the sustainability of forest management practices (Mulder et al. 1999; Voigt et al. 2000). Forest birds are currently being used to evaluate forest management plans for some components of forest sustainability within Ontario (McLaren et al. 1998) through the use of data and expert-driven habitat suitability matrices (Voigt et al. 2000). To use birds to assess the effectiveness of forest management policy, and as part of the operational forest management planning process, information is required on habitat use of individual species. There is a great deal of life history information available on birds (e.g., The Birds of North America series, Poole and Gill 2002), and much longterm monitoring data available (Sauer and Droege 1990; Baillie 1991); however, within the boreal forests of Canada, relatively little empirical information is available (Kirk and Hobson 2001). In addition, there is geographical variation in habitat use amongst birds and other organisms (Collins 1983; Osborne and Suarez-Seoane 2002) that limits our ability to transfer information from one location to another. As a consequence, regional bird information is required for regional management. A key approach to incorporating biological indicators, such as birds, into the forest management planning process is to use maps of forest inventory to spatially extrapolate these models (Voigt et al. 2000; Venier and Pearce 2004; Wintle et al. 2005). Identifying the types of environmental variables that are best for predicting habitat will help to identify the environmental variables needed for spatial estimates. Another element of forest land management is the establishment of parks to provide representative ecosystems to sustain biodiversity including birds. Parks can also provide a baseline for what is going on in the more managed areas of forest ecosystems. The capacity of parks to maintain representative biodiversity and to act as baselines has rarely been examined at local scales. The objective of this paper is to examine the relative abundance of members of a boreal songbird community and their relation to environmental factors within boreal forests in north–central Ontario. The study consists of two parts. The first is a comparison of forested sites in a contiguously forested area (Pukaskwa Park) versus forested sites within a harvested landscape (White River Forest). We examine the
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influence of landscape context on the bird community and how well the park landscape represents the managed forest immediately outside the park. This examination is necessarily limited in that we have only two landscapes to compare; thus, our sites within landscapes are pseudoreplicates (Hurlbert 1984). We interpret our analyses in this context. The second part is an examination of relative abundance of birds in relation to understorey and overstorey composition and structure and landscape-level context. This analysis is intended to identify those variables that would provide the best predictions of habitat for the boreal songbird community. We discuss the implications of these analyses to some of the approaches currently taken to maintain sustainable forests.
Materials and methods Study area The research area (187 800 ha) is located at White River in north–central Ontario, in the Central Plateau and Superior sections of the Boreal Forest Region (Rowe 1972) (Fig. 1). The approximate centre of the area is 48.51488N, 85.50988W. The study area contains a large portion of the White River management area (23%) and the northeast corner of Pukaskwa National Park and includes both protected forest and forest actively managed for timber production. Mixedwood forests with a large jack pine (Pinus banksiana Lamb.) component dominate the study area. Common coassociates are black spruce (Picea mariana (P. Mill.) B.S.P.), trembling aspen (Populus tremuloides Michx.), balsam fir (Abies balsamea (L.) P. Mill.), and white birch (Betula papyrifera Marsh.), with lesser amounts of white spruce (Picea glauca (Moench) Voss), eastern white cedar (Thuja occidentalis L.), and eastern larch (Larix laricina (Du Roi) K. Koch). Different disturbance regimes in the park and the logged landscape have resulted in different distributions of seral stages in the two landscapes. The park portion of the study area is mostly 50- to 80-year-old fire-origin stands with very little forest under 40 years or over 100 years. The logged portion of the study area has approximately 36% forest under the age of 40 (logging origin) and approximately 30% forest over the age of 80 (fire origin). The 53 mature forest stands were sampled for birds and habitat variables. All sampling locations were at least 500 m apart and were located within single stands identified by the Forest Resource Inventory of Ontario (Fig. 1). Bird sampling Forest birds were sampled using the point count method (Howe et al. 1997). Each stand was visited twice, and all birds heard or seen during a 10 min period within a 100 m radius were recorded. Birds were sampled at a single point on the plot (Fig. 2). The first visit occurred in early to midJune and the second visit in mid-June to early July. Counts were performed between dawn and 0930 Eastern Daylight Savings Time. Point counts were not conducted during windy conditions or precipitation. An observer sampled stands in each of 3 years: 2001–2003. However, in 2003, 30 of the 106 point count surveys were conducted using CVX microphone recording (Rempel et al. 2005). This micro#
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Fig. 1. Sampling locations in the study area: White River Forest and Pukaskwa National Park in northern Ontario, Canada (48.51488N, 85.50988W).
Fig. 2. Plot design for bird and habitat sampling. The coarse woody debris (CWD) transect is indicated in bold. Birds were sampled at a single point count in the centre of the plot.
phone system has proved effective for collecting abundance and community data for forest songbirds (Hobson et al. 2002). Recordings were then interpreted by the same observer who conducted the other point counts. All stands were surveyed at least once by an observer and no more than once by the CVX microphone. Annual abundance was calculated as the maximum count for the species in two visits. Total bird abundance for the sample was calculated as the sum of the annual abundances over 3 years and was used as the response variable in all of the analyses. Habitat sampling Broad vegetation information is available for the study area in the form of forest resource inventory (FRI) maps. These maps are derived from interpretation of aerial photographs (1 : 20 000) flown in the White River management area in 1998 and Pukaskwa Park in 1996–1997. The forest vegetation data for areas harvested prior to 1998 was obtained from FRI inventory undertaken in approximately 1972. FRI maps delineate homogenous forest stands and provide a brief description of the relative dominant tree species composition, age, height, and site class. The FRI data was used to calculate six landscape-level variables, including area of mature conifer, deciduous, and mixed forest and area of immature conifer, deciduous, and mixed forest within 500 m of each point count. To estimate stem density of tree species, we counted the number of stems within 5 m of the bird census point (Bird #
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Point in Fig. 2) and at 50 m in each cardinal compass direction from this point (Sampling location 1 in Fig. 2). A tree was defined as having a diameter at breast height of 10 cm or greater. To assess tree species composition, we identified the species of the five closest trees to the five sampling points described above (25 trees per site), which we converted into a percent composition for each species. We recorded the three most dominant understorey plant species at each of the 5 m radius areas described above (five samples per plot). To estimate tree height and age for the stand, we selected three representative individuals of each tree species (if available) at a plot. Mature tree heights were measured with a clinometer. Age of mature trees was measured with a tree core that was taken at breast height and the number of rings counted. Each ring was assumed to represent 1 year of growth. Stand age was determined as the age of the oldest tree, and stand height as the average of all tree height measurements. Vertical vegetation structure was measured at sampling locations 1 and 2 (nine locations per site; Fig. 2). The amount of cover in a 1 m radius plot at each of seven height strata was visually estimated on a scale of 0–5 (0 = 0%, 1 = >0%–15%, 2 = 16%–40%, 3 = 41%–65%, 4 = 66%– 90%, 5 = >90%). The seven strata are 0–0.1 m, 0.1–0.5 m, 0.5–2.5 m, 2.5–5 m, 5–10 m, 10–20 m, >20 m. The vegetation structure at each stratum was calculated as the sum of the nine cover scores. The total structure for the stand was calculated as the sum of the structure from all strata. Coarse woody debris was measured in each stand using three 50 m transects that formed the sides of an equilateral triangle. The diameter and decay stage of all downed logs or snags that intersected each transect (of at least 10 cm diameter) was recorded. Decay stage was measured on a three-point scale: 1, >75% wood still hard and most bark intact; 2, 25%–75% of wood soft, shape still intact; 3, >75% of wood soft, shape lost. The volume of downed wood per hectare was calculated using Van Wagner (1968).
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mensions to use. We conducted an ANOSIM, which is an analogue of the standard univariate one-way ANOVA test, to test the null hypothesis that there is no difference in the bird species assemblages between forested park sites and forested sites in the logged landscape. The ANOSIM test statistic (R) indicates the observed differences between groups, contrasted with the differences among replicate stands within groups. The average distance between every pair of stands within groups was compared with the average distance between each pair of stands from different groups using the rank similarity matrix. R lies within the range of –1 to 1 but usually falls between 0 and 1, indicating some degree of discrimination between groups of sites. The statistic was compared against a distribution of the statistic generated by permuting the samples and recomputing the statistic (n = 999). PRIMER (Plymouth routines in multivariate ecological research; Clarke and Warwick 1994) was used to conduct the analysis. Individual bird species We used Dufreˆne and Legendre’s (1997) method of indicator species analysis to examine the specificity of use of the different landscapes by individual species. This method combines the faithfulness of occurrence of the species in a group with the abundance in that group and the occurrence and abundance of the species in other groups. As such, it provides a measure of importance of the group to the species. Values range from 0 to 100, where perfect indication (100) means that the species indicates a particular group without error. Randomization tests were used to evaluate the statistical significance of the indicator value, using 1000 randomizations. The probability of type I error is the proportion of times that the indicator value calculated from the randomized data set is equal to or greater than the indicator value from the observed data set. We conducted this analysis using PC-ORD (McCune and Mefford 1999). We included in the analysis only those species that were observed 10 or more times in either the park or logged landscape sites for a total of 32 species.
Analysis Park versus logged landscape Bird communities We conducted nonmetric multidimensional scaling (NMDS) to compare the pattern of bird species composition in park and logged landscapes. NMDS was chosen because fewer assumptions need to be made about the nature and quality of the data than for other ordination methods because it relies only on the rank order of similarities rather than their actual values (Clarke and Warwick 1994). Of the 53 survey sites, 35 sites with similar overstorey composition were selected to contrast the bird community of the contiguous landscape and harvested landscapes, resulting in 17 sites within the park’s contiguous forest landscape and 18 sites within the harvested landscape. We used a square root transformation of the bird abundance data to increase the relative contribution of the less common species. We then summarized the data using the Bray–Curtis dissimilarity measure, as recommended by Clarke and Warwick (1994). We calculated NMDS ordinations in two and three dimensions and examined stress values to determine the best number of di-
Habitat We conducted Kruskal–Wallis tests to compare the values of each of 41 variables between landscapes. These variables represented the overstorey, understorey, structure, and landscape. Because of the rarity of some individual species in the understorey, we only conducted Kruskal–Wallis tests on understorey species that were represented by at least 10 observations. Habitat associations Bird communities To examine the structure of the bird communities in relation to environmental variables, we conducted an NMDS ordination of the 53 sites using a square root transformation of the bird abundance data to increase the relative contribution of the less common species. We then summarized the data using the Bray–Curtis dissimilarity measure, as recommended by Clarke and Warwick (1994). We calculated NMDS ordinations in two and three dimensions and examined stress values to determine the best number of dimensions to use. We examined the relationship between bird #
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community structure and the environmental variables by conducting linear regressions of the NMDS ordination scores of the sites on the environmental variables individually. Individual bird species We conducted generalized additive modelling (GAM) using S-Plus (Insightful Corporation 2001), assuming a Poisson data distribution to examine the relationship of the 32 most common bird species in our sample (species that occurred at least 20 times over 3 years; Table 1) with the four sets of environmental data including understorey floristics, forest structure, overstorey composition, and landscape context. Understorey floristics were first summarized by conducting an NMDS ordination with a Bray–Curtis dissimilarity measure to reduce the total number of environmental variables and because of the relative rarity of many of the understorey species. Understorey species counts, as measured here, ranged from zero to five, which made transformation for down-weighting of common species unnecessary. We examined the bird species count in relation to the three axes of the understorey NMDS ordination. Overstorey species and structure variables were examined with the original measures and were included in stepwise models including three degrees of freedom for each variable. We examined six landscape variables measured in a 500 m radius circle around the plot center; area of mature conifer, deciduous, and mixedwood and area of immature conifer (20 m{ Coarse wood decay class 1{ Coarse wood decay class 2{ Coarse wood decay class 3 Coarse wood volume{ Jack pine{ Trembling aspen Black spruce{ White birch Balsam fir Cornus canadensis Picea mariana{ Abies balsamea Vaccinium spp.{ Alnus spp. Diervilla lonicera Aralia nudicalis Pteridium aquilium Ptilium crista-castrensis Eurybia macrophylla{ Maianthemum canadense Clintonia borealis Lycopodium spp.{ Gaultheria hispidula{ Acer spicatum Corylus cornuta Ledum groenlandicum Mature forest, 500 m{ Mature deciduous, 500 m{ Mature conifer, 500 m{ Mature mixedwood, 500 m Immature deciduous, 500 m Immature conifer, 500 m{ Immature mixedwood, 500 m{
Code TS Hgt Age TSTR S1 S2 S3 S4 S5 S6 S7 CWD1 CWD2 CWD3 CWV Pj Pot Sb Bw Bf CC SbU BfU Vac AL DL AN PA PC AM MC CB LY GH ACS CCN LG Land MD MC MM ID IC IM
Variable type* S S S S S S S S S S S S S S S O O O O O U U U U U U U U U U U U U U U U U L L L L L L L
Logged 52.7 22.1 113.2 159.8 22.3 16.4 14.4 8 8.5 8.4 3.2 45.8 29 25.62 100.38 7 1.89 8.56 3.67 2.72 2.56 1.056 1.94 0.556 0.889 1.11 0.278 0.722 1.056 0.167 0.278 0.222 0.556 0.556 NA NA NA 55.96 12.72 29.28 13.96 1.12 26.61 4.58
Park 42.5 18.1 59.1 148.1 13.4 17.1 13.6 8.29 11.4 14.1 2.2 13.17 5.7 35.49 54.40 12.88 3.65 2.88 2.35 2.65 2.18 2.47 1.29 2.06 1.17 0.882 1.00 0.529 0.176 1.00 0.529 0.353 0.00 0.00 NA NA NA 73.30 2.27 49.03 22.00 0.00 0.57 3.14
w2 0.001 7.15 21.95 0.65 4.64 0.003 0.033 0.37 2.85 5.6 53.8 14.41 9.64 0.012 3.66 5.23 3.25 9.82 0.92 0.14 0.626 6.862 0.577 6.402 0.445 0.135 2.15 0.668 2.612 8.095 1.424 0.296 6.611 6.579 NA NA NA 9.83 7.83 4.89 1.35 3.00 26.24 6.94
p 0.974 0.008 0.001 0.419 0.031 0.960 0.856 0.540 0.091 0.018 0.020 0.001 0.002 0.729 0.056 0.022 0.071 0.002 0.337 0.710 0.429 0.009 0.448 0.011 0.505 0.713 0.142 0.414 0.106 0.004 0.233 0.586 0.010 0.010 NA NA NA 0.002 0.005 0.027 0.246 0.083 0.001 0.008
Variance in environmental variables explained by each NMDS axis (R2) Axis 1 0.159 0.241 0.007 0.26 0.211 0.005 0.474 0.393 0.065 0.084 0.143 0.070 0.051 0.178 0.183 0.160 0.282 0.345 0.466 0.064 0.081 0.125 0.026 0.229 0.018 0.144 0.189 0.015 0.113 0.025 0.004 0.264 0.167 0.056 0.317 0.258 0.323 NA 0.157 0.106 0.170 0.002 0.049 0.005
Axis 2 0.016 0.001 0.275 0.035 0.104 0.000 0.063 0.021 0.081 0.169 0.019 0.099 0.182 0.001 0.119 0.338 0.068 0.256 0.030 0.027 0.000 0.107 0.025 0.055 0.031 0.038 0.058 0.081 0.012 0.056 0.060 0.015 0.137 0.029 0.038 0.017 0.109 NA 0.114 0.195 0.007 0.007 0.156 0.009
Axis 3 0.018 0.079 0.108 0.005 0.000 0.060 0.001 0.000 0.015 0.015 0.034 0.064 0.058 0.010 0.032 0.010 0.002 0.001 0.016 0.002 0.005 0.036 0.001 0.038 0.029 0.012 0.008 0.001 0.062 0.023 0.010 0.000 0.007 0.014 0.050 0.079 0.006 NA 0.017 0.042 0.000 0.040 0.081 0.018
Total 0.193 0.321 0.390 0.300 0.315 0.065 0.538 0.414 0.161 0.268 0.196 0.233 0.291 0.179 0.334 0.508 0.352 0.602 0.512 0.093 0.086 0.268 0.052 0.322 0.078 0.194 0.255 0.097 0.187 0.014 0.074 0.279 0.311 0.099 0.405 0.354 0.438 NA 0.288 0.343 0.177 0.049 0.286 0.032
*S, structure; O, overstorey; U, understorey; L, landscape. { Significant at = 0.05.
relationships with both total structure and mature forest within 500 m. Total structure did not differ between parks sites and logged landscape sites; however, amount of mature forest was greater in the park. There is also some evidence in the literature that black-throated green warblers have disappeared from some small forest patches (20 and 10–20 m strata. Of these, only age and height are available in a mapped form through the forest resource inventory. None of the understorey structure variables are readily available in a mapped form over large scales. All of the structure models included variables for which good spatial estimates do not exist, and in the majority of cases, the best combined models included understorey floristics, understorey structure, or other variables for which good quality spatial estimates also do not exist. Being able to map habitat is essential to incorporating species indi-
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cators into the forest management planning process (Mulder et al. 1999; Venier and Pearce 2004), because it allows a manager to predict potential impacts of alternative management scenarios on the indicator species. One challenge, then, is to develop methods for mapping or predicting the distribution of the understorey structure. Some efforts have been made to model the dynamics of snags (Morrison and Raphael 1993) and coarse woody debris (Densmore et al. 2004). These models predict future availability of snags and coarse woody debris as a function of current stand structure and time. Understorey structure such as shrub density is likely related to forest type and underlying drivers such as richness and moisture gradients, but we have no spatial predictions for these underlying gradients either. Other solutions may involve innovations in remote sensing technologies and methodological improvements including leaf-off measurements, but the additional cost of these types of inventory techniques makes it unlikely that they will be adopted on a large scale anytime soon. Conclusions The comparison between logged and park landscapes indicates that for some species, landscape context does appear to influence the likelihood of a species being present. Several species were clearly more closely associated with the park, whereas others were more closely associated with the logged landscape, even though all birds were sampled in forests and differences in habitat were taken into consideration. There is some suggestion in our analysis that the park may not act as a representative reserve in that it does not appear to contain a vegetation or bird community that is representative of the surrounding area, although this conclusion is based on a small number of samples. A more thorough analysis of the representivity of the park is warranted to evaluate how well it can provide representative forest habitat. The individual species models suggest that all environmental variable types are important in predicting species occupancy but that understorey floristics are least important and structure is most important. The general lack of good spatial estimates of understorey structure is a major challenge to our ability to generate robust, spatially-explicit models of species occurrence across the landscape for forest management applications.
Acknowledgements Funding for this study was provided by the Living Legacy Trust as part of a collaborative study by the Canadian Forest Service, Parks Canada, the Ontario Ministry of Nautral Resources, Domtar, and the Upper Lakes Environmental Research Network. We thank Dan Schuurman, Andrew Davis, Keith Wade, Cheryl Widdifield, Jamie Broad, Verne Bastable, Scott Rocks, Tanya Hunter, and Darlena Tousignant for assistance with data collection. Additional logistic support was provided by Gillian Eccles, Teri Bonnell, and Kerrie Wainio-Keizer. CVX microphones were kindly provided by Rob Rempel at the Ontario Ministry of Natural Resources. Two anonymous reviewers provided useful comments on the manuscript.
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