Defining specialism and functional species groups in birds: First steps toward a farmland bird indicator

Abstract

Although farmland birds are used extensively in Europe as an indicator group to assess agricultural impacts on ecosystems, no such group has been formally identified in North America. Here we present a hierarchical framework to identify a suite of farmland bird species in Ontario, Canada by consolidating and validating classifications derived from literature review and empirical modelling. First, we reviewed literature to compile candidate farmland bird species in Ontario and assigned species to four guilds (row crop specialists, pasture specialists, farmstead specialists, and farmland edge generalists). Second, we used regression trees (RTs) to test whether these species could be classified into the same literature-based guilds or different guilds, based on modelled relationships between breeding bird atlas abundance data and Census of Agriculture statistics. We consolidated both classifications using a decision tree into a final list of 45 farmland bird species, comprising 11 farmstead specialists, 13 pasture specialists, 5 row crop specialists, 12 farmland edge generalists, and 4 farmland generalists flagged for classification uncertainty. To validate the distinctness of the assigned farmland bird guilds, we used pairwise permANOVA to test for differences in species composition among guilds, based on 34 species with sufficient occurrence data. We found significant compositional differences between almost all guilds, except for the farmstead specialist and row crop specialist guilds which could not be differentiated. We also validated species’ guild assignments using canonical analysis of principal coordinates (CAP) to group 35 species according to ecological resemblance which were then compared to our proposed guild classifications. CAP validated guild assignments for 78.2% of the evaluated farmland specialists, particularly for farmstead specialists and pasture specialists, while 50% of evaluated farmland edge generalists were grouped differently than our final classification. Each final classification was associated with low, moderate, or high uncertainty according to concordance between classification methods and support from CAP groupings to highlight species with uncertainly assigned guilds. For some such species, mismatches between their literature-based and empirically-derived classifications might be due to the predictor variables being measured at too large a scale to reflect associations between their abundance distributions and agricultural landscape characteristics. We recommend that these farmland bird species be further verified using statistical models of bird count data, satellite imagery, and climate variables, and a trait-based approach to bolster confidence in the proposed list. When confirmed and expanded, this list can be used to inform a farmland bird indicator to monitor agroecosystem health in Ontario, and perhaps elsewhere in eastern North America.