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The efficacy of common species as indicators: avian responses to disturbance in British Columbia, Canada

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Abstract

Common species can be major drivers of species richness patterns and make major contributions to biomass and ecosystem function, and thus should be important targets for conservation efforts. However, it is unclear how common species respond to disturbance, because the underlying reasons for their commonness may buffer or amplify their responses to disturbance. To assess how well common species reflect changes in their community (and thus function as indicator species), we studied 58 bird species in 19 mixed conifer patches in northern British Columbia, Canada, between 1998 and 2010. During this time period two disturbance events occurred, stand level timber harvest and a regional-scale bark beetle outbreak. We examined relationships among densities of individual species, total bird density and overall species richness, correlations in abundance among species, and responses to disturbance events. We found three broad patterns. First, densities of common species corresponded more strongly with changes in total bird density and overall species richness than rare species. These patterns were non-linear and species with intermediate-high commonness showed similar or better correspondence than the most common species. Second, common species tended to be more strongly correlated with abundances of all other species in the community than less-common species, although on average correlations among species were weak. Third, ecological traits (foraging guild, migratory status) were better predictors of responses to disturbance than species commonness. These results suggest that common species can collectively be used to reflect changes in the overall community, but that whenever possible monitoring programs should be extended to include species of intermediate-high commonness and representatives from different ecological guilds.

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Acknowledgments

Thanks to A. Norris for discussions on study design, to A. Adams and H. Kenyon for assistance with data entry and interpretation, and all field workers over the years that assisted with data collection. K. Martin received financial support from Sustainable Forest Management Network, Forest Renewal BC, FIA Forest Sciences Program of BC, Environment Canada, and the Natural Sciences and Engineering Research Council of Canada (NSERC) Strategic Special Project. Tolko Industries Limited (Cariboo Woodlands) provided logistical and financial support from 1996 to 2003.

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Authors and Affiliations

  1. Department of Forest Sciences, Centre for Applied Conservation Research, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada

    Amelia J. Koch, Mark C. Drever & Kathy Martin

  2. Forest Practices Authority, 30 Patrick St, Hobart, TAS, 7004, Australia

    Amelia J. Koch

  3. Environment Canada, Pacific Wildlife Research Centre, 5421 Robertson Rd, RR1, Delta, BC, V4K 3N2, Canada

    Mark C. Drever & Kathy Martin

Authors
  1. Amelia J. Koch
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  2. Mark C. Drever
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  3. Kathy Martin
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Correspondence to Amelia J. Koch.

Appendices

Appendix 1

See Table 1.

Table 1 Details on the four-letter code, common name, scientific name and ecological attributes of each species examined
Full size table

Appendix 2

The results of the models examining species responses to harvesting and MPB are outlined in Table 2, which is best explained using some examples. The second row of data is for the western wood-pewee (WWPE). Of the five models for this species the harvest model had the lowest QAICc value, and therefore the best explanatory power, as evidenced by the zero in the harvest column. The + indicates that harvesting had a positive effect on WWPE density. The QAICc value of the WWPE harvest model is at least two units less than the next simplest model, the null model (ΔQAICc = 20.8 − 0 = 20.8), so the text is bolded to indicate the strong support for an effect of harvesting. The pine model is also bolded, indicating that the QAICc value of this model is at least two units less than the next simplest model, the null model (ΔQAICc = 20.8 − 11.4 = 9.4). The + sign for the WWPE pine model is in brackets, indicating that the model-averaged coefficient for pine was positive but that the model that only included pine (i.e. not MPB or harvest) had a negative coefficient. The WWPE MPB model is also bolded, indicating strong support for an effect of MPB (ΔQAICc = 11.4 − 8.7 = 2.7). The MPB-harvest model has a low ΔQAICc value, comparable to the harvest model which is the best model overall. However the MPB-harvest ΔQAICc value is not bolded, indicating only weak support for this model. While the MPB-harvest model is better than the MPB model (ΔQAICc = 8.7 − 0.1 = 8.6), it is not better than the harvest model (ΔQAICc = 0 − 0.1 = − 0.1). This result means that while MPB was found to have an effect when considered on its own, the effect of MPB was relatively weak when harvesting was taken into account.

Table 2 Results of the mixed-effect models between species density and harvesting, basal area of pine, and proportion of pine affected by MPB
Full size table

Our second example is for the Dusky or Hammond’s flycatcher (DUHA). Of the five models for this species the harvest model had the lowest ΔQAICc value, and therefore the best explanatory power, as evidenced by the zero in the harvest column. However, the zero is not bolded indicating there was only weak support for an effect of harvesting (ΔQAICc = 0.5 − 0 = 0.5). Similarly there was no support for an effect of pine or MPB on DUHA as these models have QAICc values greater than the null model.

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Koch, A.J., Drever, M.C. & Martin, K. The efficacy of common species as indicators: avian responses to disturbance in British Columbia, Canada. Biodivers Conserv 20, 3555–3575 (2011). https://doi.org/10.1007/s10531-011-0148-3

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