Data from: Species traits mediate the abundant-center patterns in ground-dwelling mammal and bird species in China

Zhang, Ludan 1 ; Zhang, Baoming1; Zhou, Minghui1; Duan, Haoting1; Xie, Zhipeng1; Huo, Xinglin1; Yu, Jiehua1; He, Jiekun 1

Published Mar 27, 2026 on Dryad. https://doi.org/10.5061/dryad.51c59zwmp

Data files

Mar 27, 2026 version files 177.24 MB

1SupplementaryData.xlsx

183.73 KB
2Data_Code.zip

177.04 MB
README.md

24.28 KB

Abstract

This dataset contains the data supporting the findings of the study titled “Species traits mediate the abundant-centre patterns in ground-dwelling mammals and birds of China.” The abundance centre hypothesis (ACH) posits that species abundance peaks at their distribution centres; however, empirical evidence testing the ACH has yielded mixed results. To assess the generality of the ACH and explore whether species traits mediate distance–abundance relationships, we compiled relative abundance indices (RAI) estimates from 196 camera trap studies conducted across China between 2008-2023. The dataset contains 2,558 RAI estimates of 81 ground-dwelling species (56 mammals and 25 birds). Species traits were also compiled from different datasets to test whether species traits mediate distance–abundance relationships.

Dataset DOI: 10.5061/dryad.51c59zwmp

A. Description

B. Directory structure

This dataset includes an Excel table (.xlsx format) and a folder. The table includes five sheets comprising information on data source, survey sites, species records and traits. The folder contains code and data for analyses.

1SupplementaryData

|-- 00MetaData

|-- 01DataSource

|-- 02MonitoringOverview

|-- 03MonitoringSpecies

|-- 04SpeciesLevel

2Data&Code

|-- 00Rcode.R

|-- 01MainData.csv

|-- 02Fig2Statistic.csv

|-- 03Fig4Statistic.csv

|-- 04Fig4BubblePlot.csv

|-- 05MammalTree.trees

|-- 06BirdTree.trees

|-- 07Mammal_bird_100tree.trees

|-- 08RandomPoints.Rdata

C. Dataset description

1SupplementaryData.xlsx

This table includes five sheets comprising information on references, survey sites, species records and traits.

00MetaData: This table provides detailed metadata on this dataset.

01DataSource: This table provides detailed information on all data source references included in the dataset.

Columns	Description
No	Sequence number
ReferenceCode	Code of the reference
Author	Author name of the publication
PublicationYear	Year of the publication
TitleCN	Chinese title of the publication
TitleEN	English title of the publication
Journal	Journal name
Volume	Volume of the publication
Issue	Issue of the rpublication
Pages	Pages of the publication
DOI	DOI of the publication

02SiteInformation: This table contains detailed information about the camera trap monitoring sites and survey efforts reported in each study.

Columns	Description
No	Sequence number
ReferenceCode	Code of the reference
SiteName	Name of study area
Province	Province where the study area is located
Longitude	Longitude of study area
Latitude	Latitude of study area
StartDate	Start date of survey in this study (YYYY-MM-DD)
EndDate	End date of survey in this study (YYYY-MM-DD)
CaremaNumber	Number of camera traps included in this study
CameraTrapDays	Number of camera trap days included in this study

03CameraTrapData: This table records all ground-dwelling species detected by camera traps, including the taxonomy, relative abundance, and detection details.

Columns	Description
No	Sequence number
ReferenceCode	Code of the reference
Class	Mammal or bird
Binomial	Species taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
RAI	Standardized relative abundance index, defined as the number of independent valid photos captured of a species per 100 trap-days
IndependentValidPhotos	The number of independent valid photos per species. Multiple detections of the same species occurring within the independence interval are grouped into a single record

04SpeciesInfo: This table contains species traits for each species.

Columns	Description
No	Sequence number
Binomial	Species taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
Class	Mammal or bird
Order	Order-level taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
Family	Family-level taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
Genus	Genus-level taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
BodyMass	Body mass (g) per species was obtained from Faurby et al. (2018) for mammal and Tobias et al., (2022)
TrophicLevel	Trophic level per species was obtained from Faurby et al. (2018)
DietDiversity	Diet diversity was quantified by the Shannon Index on the proportions of 7 dietary categories reclassified from EltonTraits (Wilman et al., 2014)
HabitatBreadth	Habitat breadth was measured as the number of suitable habitats using the IUCN Habitat Classification Scheme, and was obtained from Etard et al. (2020)
ClimateNicheBreadth	Climate niche breadth was calculated as the minimum convex polygon within the climatic space using the WorldClim data (version 2.0; Fick & Hijmans, 2017)
CentroidLatitude	The median latitude of breeding range for each species
RangeSize	Range size was measured using the polygon-based geographic range from the IUCN Red List database. Unit: number of 1° × 1° grid cells
HomeRange	Home range size was estimated as a surrogate proxy for the dispersal capacity of mammals following the methods provided by Tucker et al. (2014). Unit: km²
HandWingIndex	Hand-wing index (HWI) data was obtained from Sheard et al. (2020)
HumanFootprintIndex	We obtained the global HFI data (Mu et al. 2022) and calculated the median HFI value for each species within its geographic range polygon

Note:

(1) The symbol “——” indicates that the information is not reported in the original source (i.e., the original publication did not provide this information). This applies to bibliographic fields such as Journal, Volume, Issue, DOI, CameraTrapDays and IndependentValidPhotos.

(2) In the “HomeRange”, “NA” represents missing data for bird species.

In the “HandWingIndex”, “NA” represents missing data for mammal species.

HomeRange and HandWingIndex are used as proxies for dispersal ability, with HomeRange applied to mammals and HandWingIndex applied to birds.

2Data_Code.zip

This zipped archive contains 9 files, including R code and all datasets used as input for the analyses in this study, as well as result data for visualization.

00Rcode.R: R script used for data processing and statistical analyses. This script includes:

(1) sensitivity analysis,

(2) factors preprocessing (log₁₀ transformation and standardization),

(3) construction of null models to estimate the mean effect size of the distance-abundance relationship,

(4) subgroup-level meta-analysis,

(5) models incorporating species traits as fixed effects,

(6) calculation of phylogenetic signals,

(7) correlation analysis between geographic distance-abundance(geoCD-abundance) and environmental distance-abundance(envCD-abundance),

(8) visualization of results.

01MainData.csv: The primary dataset used for all analyses.

Columns	Description
Class	Mammal or bird
Order	Order-level taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
Family	Family-level taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
Genus	Genus-level taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
Binomial	Species taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
n	The sample size for each species, i.e., the number of records
Gr_median	The median distance to the geographic center (geoCD) across the 1,000 resampled points for each species
Cr_median	The median distance to the climatic niche center (envCD) across the 1,000 resampled points for each species
G.z	The Fisher’s Z-transformed correlation coefficient (Zr) describing the relationship between geographic distance (geoCD) and abundance for each species
C.z	The Fisher’s Z-transformed correlation coefficient (Zr) describing the relationship between environmental distance (envCD) and abundance for each species
z_vi	The sampling variance of the Fisher’s Z-transformed correlation coefficient (Zr) for each species, calculated as 1/(n − 3)
BM	Body mass (g) per species was obtained from Faurby et al. (2018) for mammal and Tobias et al., (2022)
TL	Trophic level per species was obtained from Faurby et al. (2018)
DI	Diet diversity was quantified by the Shannon Index on the proportions of 7 dietary categories reclassified from EltonTraits (Wilman et al., 2014)
HB	Habitat breadth was measured as the number of suitable habitats using the IUCN Habitat Classification Scheme, and was obtained from Etard et al. (2020)
CN	Climate niche breadth was calculated as the minimum convex polygon within the climatic space using the WorldClim data (version 2.0; Fick & Hijmans, 2017)
ML	The median latitude of breeding range for each species
RS	Range size was measured using the polygon-based geographic range from the IUCN Red List database. Unit: number of 1° × 1° grid cells
HR	Home range size was estimated as a surrogate proxy for the dispersal capacity of mammals following the methods provided by Tucker et al. (2014). Unit: km²
HW	Hand-wing index (HWI) data was obtained from Sheard et al. (2020)
HFI	We obtained the global human footprint index (HFI) data (Mu et al. 2022) and calculated the median HFI value for each species within its geographic range polygon

02Fig2Statistic.csv: Input data used to generate Figure 2.

Columns	Description
species	Species taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
n	The sample size for each species, i.e., the number of records
pearson_r	The Pearson correlation coefficient between distance and abundance for each species
pp_value	The p-value associated with the Pearson correlation coefficient between distance and abundance for each species. P value ≤ 0.05 indicates significance
Significance	P indicates a significant positive correlation, N indicates a significant negative correlation, and A indicates no significant correlation
Class	Mammal or bird
Distance	Geography (geoCD) or Climate (envCD)

03Fig4Statistic.csv: Input data used to generate Figure 4.

Columns	Description
Class	Mammal or bird
space	Geo (geographic space) or env (climatic space)
factor	The predictor variables influencing the distance–abundance relationship
estimate	The effect size of the model
p	The statistical significance. P value ≤ 0.05 indicates significance
ci.lb	The lower bounds of the 95% confidence interval
ci.ub	The upper bounds of the 95% confidence interval

04Fig4BubblePlot.csv: Input data used to generate Figure 4.

Columns	Description
species	Species taxonomy according to Wei et al. (2022) for mammal and Zheng et al. (2023) for bird
Class	Mammal or bird
n	The sample size for each species, i.e., the number of records
BM	Body mass (g) per species was obtained from Faurby et al. (2018) for mammal and Tobias et al., (2022)
DI	Diet diversity was quantified by the Shannon Index on the proportions of 7 dietary categories reclassified from EltonTraits (Wilman et al., 2014)
HB	Habitat breadth was measured as the number of suitable habitats using the IUCN Habitat Classification Scheme, and was obtained from Etard et al. (2020)
CN	Climate niche breadth was calculated as the minimum convex polygon within the climatic space using the WorldClim data (version 2.0; Fick & Hijmans, 2017)
ML	The median latitude of breeding range for each species
RS	Range size was measured using the polygon-based geographic range from the IUCN Red List database. Unit: number of 1° × 1° grid cells
HR	Home range size was estimated as a surrogate proxy for the dispersal capacity of mammals following the methods provided by Tucker et al. (2014). Unit: km²
z_log_BM	Standardized values of body mass after log-transformation
z_DI	Standardized diet diversity index
z_HB	Standardized habitat breadth
z_CN	Standardized climatic niche breadth
z_ML	Standardized median latitude of the species distribution
z_log_RS	Standardized values of range size after log-transformation
z_log_HR	Standardized values of home range size after log-transformation
G.pearson_r	The Pearson correlation coefficient between geoCD and abundance for each species
G.pp_value	The p-value associated with the Pearson correlation coefficient between geoCD and abundance for each species. P value ≤ 0.05 indicates significance
C.pearson_r	The Pearson correlation coefficient between envCD and abundance for each species
C.pp_value	The p-value associated with the Pearson correlation coefficient between envCD and abundance for each species. P value ≤ 0.05 indicates significance
G.z	The Fisher’s Z-transformed correlation coefficient (Zr) describing the relationship between geographic distance (geoCD) and abundance for each species
C.z	The Fisher’s Z-transformed correlation coefficient (Zr) describing the relationship between environmental distance (envCD) and abundance for each species
z_vi	The sampling variance of the Fisher’s Z-transformed correlation coefficient (Zr) for each species, calculated as 1/(n − 3)

05MammalTree.trees: Phylogenetic trees for mammals used in the analyses.

06BirdTree.trees: Phylogenetic trees for birds used in the analyses.

07Mammal_bird_100tree.trees: Combined phylogenetic trees for mammals and birds, primarily used for the visualization of the phylogenetic tree in Figure3.

08RandomPoints.Rdata: Input data used for sensitivity analyses.

D. Reference:

Etard, A., Morrill, S., & Newbold, T. (2020). Global gaps in trait data for terrestrial vertebrates. Global Ecology and Biogeography, 29(12), 2143-2158.

Faurby, S., Davis, M., Pedersen, R. Ø., Schowanek, S. D., Antonelli, A., & Svenning, J. C. (2018). PHYLACINE 1.2: the phylogenetic atlas of mammal macroecology. Ecology, 99(11), 2626.

Fick, S. E. & Hijmans, R. J. (2017). WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302–4315.

Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K., & Mooers, A. O. (2012). The global diversity of birds in space and time. Nature, 491(7424), 444-448.

Mu, H., Li, X., Wen, Y., Huang, J., Du, P., Su, W., Miao, S. & Geng, M. (2022). A global record of annual terrestrial Human Footprint dataset from 2000 to 2018. Scientific Data, 9, 176.

Sheard, C., Neate-Clegg, M. H., Alioravainen, N., Jones, S. E., Vincent, C., MacGregor, H. E., ... & Tobias, J. A. (2020). Ecological drivers of global gradients in avian dispersal inferred from wing morphology. Nature Communications, 11(1), 2463.

Tobias, J. A., Sheard, C., Pigot, A. L., Devenish, A. J., Yang, J., Sayol, F., ... & Schleuning, M. (2022). AVONET: morphological, ecological and geographical data for all birds. Ecology Letters, 25(3), 581-597.

Tucker, M. A., Ord, T. J., & Rogers, T. L. (2014). Evolutionary predictors of mammalian home range size: Body mass, diet and the environment. Global Ecology and Biogeography, 23(10), 1105– 1114.

Upham, N. S., Esselstyn, J. A., & Jetz, W. (2019). Inferring the mammal tree: Species- level sets of phylogenies for questions in ecology, evolution, and conservation. PLoS Biology, 17(12), e3000494.

Wei, F., Yang, Q., Wu, Y., Jiang, X., & Liu, S. (2022). Taxonomy and distribution of mammals in China. Beijing: Science Press.

Wilman, H., Belmaker, J., Simpson, J., de la Rosa, C., Rivadeneira, M. M., & Jetz, W. (2014). EltonTraits 1.0: Species‐level foraging attributes of the world's birds and mammals: Ecological Archives E095‐178. Ecology, 95(7), 2027-2027.

Zheng, G. (2023). A checklist on the classification and distribution of the birds of China (Fourth ed.). Beijing: Science Press.