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Data from: Abundant-core thinking clarifies exceptions to the abundant-center distribution pattern

Citation

Fristoe, Trevor; Vilela, Bruno; Brown, James H; Botero, Carlos (2022), Data from: Abundant-core thinking clarifies exceptions to the abundant-center distribution pattern, Dryad, Dataset, https://doi.org/10.5061/dryad.dz08kps1b

Abstract

Understanding variation in abundance within species’ ranges is fundamental for ecological and evolutionary theory and applied conservation science. The abundant-center model provides a general hypothesis based on basic ecological principles and macroscale biogeographic patterns: abundance should peak near the center of a species’ range, where environmental conditions are most favorable, and decline towards the periphery. Despite longstanding influence in ecological thinking, consistent support for the ubiquity of abundant-center distributions remains elusive, and recent assessments have questioned the value of this paradigm altogether. We suggest that revisiting the simplifying assumptions that underly the model provides a productive path forward by clarifying predictions and revealing expectations for alternative distribution patterns. Towards this end, we use standardized abundance surveys of North American birds to reassess the prevalence of abundant-center distributions in geographic and climate space, test whether deviations are associated with predictable violations of assumptions, and provide more robust expectations. After accounting for common methodological pitfalls, we find that geographic centrality is generally indicative of centrality in climate space (confirming a key model assumption) and that abundant-center distributions occurred in 71% of passerines. To better understand exceptions, we introduce the concept of abundant-core distributions, of which the abundant-center is a special case. We find that 87% of species fit abundant-core expectations, with abundances peaked and generally declining from a core region within the range. Abundance cores tended to deviate from geographic center where topographic features complicate correspondence between geography and environmental conditions (e.g. the climatically heterogenous West). Such deviations were often associated with truncated climatic availability, with core regions offset towards the continental edge or climate extremes. Overall, our analyses suggest that abundant-center thinking provides a useful generalization for understanding spatial variation in abundance for many species. However, as with any model, its assumptions must be assessed within the context of given applications.

Usage Notes

AbundantCenter R Code.txt:

R code used for processing data and performing analyses.

SppList.csv:

List of species in Breeding Bird Survey data.

‘SppID’ is the identification number assigned for our analysis; we combined infraspecific taxa (e.g. great blue heron and the white morph known as great white heron) and did not include taxa that could not be identified to species (these are given ‘NA’ for SppID).

‘Aou’ are the original BBS species indentification numbers.

'Common.Name’ provide the English common name for species without infraspecific taxa names.

‘Common.Name.1’ includes infraspecific taxa names.

‘scinamemap’ is the file name for the BirdLife range map shapefile.

SppRelationships.zip:

Contains image files (.png) for each species that show geographic and climate abundance maps, and abundance-range position relationships

In maps, cell aggregated abundances are depicted from low values in blue to high values in orange; the geographic or climatic area covered by North America is depicted in black; cells with Breeding Bird Survey data but where the species was not observed are in grey. The estimated center of the range is depicted with a green ‘X’ and the estimated core of abundance with a pink circle; the cells used for estimating the core (10% highest abundances, see methods) are indicated with red points. Spearman’s rank correlation coefficient was used to assess support for abundant-center and abundant-core predictions. Significant positive relationship for distance from edge (ρGeoEdge and ρClimEdge) and negative relationships for distance from center (ρGeoCent and ρClimCent) are consistent with abundant-center distribution patterns; significant negative relationships for distance from the abundance core (ρGeoCore and ρClimCore) are consistent with abundant-core distribution patterns.