A test of the abundant-center hypothesis for stream fishes
Data files
May 15, 2025 version files 10.27 MB
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ACH_code.R
3.09 KB
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ACHtest_distanceData.csv
10.24 MB
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Ecography_Rproject.Rproj
253 B
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KDEcoreResults_Ecography.csv
16.52 KB
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README.md
2.35 KB
Abstract
The abundant-center hypothesis (ACH) provides a conceptual model for predicting range-wide distributions of species abundance, suggesting that abundance peaks in the center of the geographic range and declines towards range edges. Empirical studies testing the ACH and its subsequent derivations predominantly occurred in terrestrial systems and reported mixed support. Moreover, none of these models consider the possibility of multiple geographic areas of elevated abundance (which we refer to as abundant cores). Naturally, dispersal limited species may exhibit multiple abundant cores, requiring refinement of the ACH. We used fish species abundances from 29,206 community monitoring surveys and weighted geospatial kernel density estimation to identify the number of abundant cores for 64 freshwater fish species. We regressed the number of abundant cores against range size and body size to test if larger geographic distributions and body sizes contain more abundant cores than smaller distributions and body sizes. The two predictors are surrogates for evolutionary age and dispersal ability, respectively, because older species are generally associated with larger ranges, and large-bodied fishes have greater dispersal ability than small-bodied fishes in dendritic networks. For studied species, 43 exhibited multi-core distributions, and 21 exhibited a single-core distribution. Species range size, but not body size, was significantly and positively associated with the number of abundant cores. The ACH was not a good descriptor of the abundance patterns of most stream fishes we studied, suggesting that an abundant center model may not be well-suited for freshwater fishes. Recent geo-climatic events in evolutionary time have isolated populations of the same species by a matrix of unsuitable habitat and/or hard dispersal barriers, providing the basis for multi-core distributions. Biogeographic and ecological mechanisms likely underpin observed multi-core patterns, and our work indicates that the ACH and related concepts still present opportunities for testing and refinement.
Dataset DOI: 10.5061/dryad.r4xgxd2r1
Description of the data and file structure
The following files include data and code for running analyses in the associated study. The study hinges on the KDE (kernal density estimates) that inform the distribution modeling.
Files and variables
File: Ecography_Rproject.Rproj
Description: R Project file for the analysis
File: ACH_code.R
Description: R script for running the abundance center hypothesis analysis
File: KDEcoreResults_Ecography.csv
Description: CSV data for the kernal density data
Variables
- Scientific_Name: Scientific name of stream fishes in study
- Common_Name: Common name of stream fishes in study
- avg.c10: average number of c10 cores estimated
- sd.cores10: standard deviation of c10 core estimates
- c10_SE: standard error of c10 core estimates
- c10_2.5: 2.5% quantile of c10 core estimates
- c10_97.5: 97.5% quantile of c10 core estimates
- avg.cores25: average number of c25 cores estimated
- sd.cores25: standard deviation of c25 core estimates
- c25_SE: standard error of c25 core estimates
- c25_2.5: 2.5% quantile of c25 core estimates
- c25_97.5: 97.5% quantile of c25 core estimates
- totalCoverage: Percent coverage area of species in study (compared to total species range)
- sampleRangeSize: Range size (km^2) included in the study for the species
- MAXTL: maximum total length estimate (cm)
- distribution: species distribution information (MCH = multicore hypothesis; SCH = single core hypothesis)
- Family: Taxonomic family
- Order: Taxonomic order
File: ACHtest_distanceData.csv
Description: CSV data for species distance from center
Variables
- Scientific_Name: Scientific name of stream fishes in study
- Common_Name: Common name of stream fishes in study
- relAbund: Species relative abundance (proportion, 0–1)
- distance_km: Distance (km) from center of distribution
Code/software
R is required to run the code, and R Studio would be preferable or required to use the R project file. CSV files are loaded into R and do not need to be otherwise opened, but can be done so in Excel or even a text editor.
Access information
Other publicly accessible locations of the data:
- None
