Dataset DOI: 10.5061/dryad.pc866t233

Description of the data and file structure

These data incorporate echolocating and non-echolocating mammalian richness, as well as various climate and human activity data. This data can be used to explore the influence factors of echolocating species' global distribution.

Files and variables

File: data_for_analysis_land.csv

Description: Species richness, climate, human activity data of terrestrial domain, including echolocating and non-echolocating species.

Variables

• X: Row number
• long: Longitude
• lat: Latitude
• land_spr_echo: Species richness of echolocators
• land_spr_nonecho: Species richness of non-echolocators
• elevation_median:Median of elevation
• elevation_range: Elevation range
• NDVI_annual: Net primary productivity (Normalized difference vegetation index)
• PET_annual: Potential evapotranspiration
• AI_median: Aridity index
• BIO1_median: Annual mean temperature
• BIO4_median: Temperature seasonality (Coefficient of Variation)
• BIO5_median: Max temperature of warmest month
• BIO6_median: Min temperature of coldest month
• BIO12_median: Annual precipitation
• BIO13_median: Precipitation of wettest month
• BIO14_median: Precipitation of driest month
• BIO15_median: Precipitation seasonality (Coefficient of Variation)
• SHDI_value: Shannon’s land-use diversity index
• SSR_annual: Net short wave radiation flux
• Wind10_annual: Wind speed (at an elevation of 10m)
• HFP_mean: Human footprint
• region_type: Biogeographic realms

Median of elevation and elevation range in meter (m)

Potential evapotranspiration in meter (m)

Annual mean temperature, max temperature of warmest month and min temperature of coldest month in Celsius degree (℃)

Annual precipitation, precipitation of wettest month and precipitation of driest month in millimeter (mm)

Net short wave radiation flux in joules per square metre (J m^-2)

Wind speed (at an elevation of 10m) in meters per second (m s^-1)

File: data_for_analysis_ocean.csv

Description: Species richness, climate, human activity data  of marine domain, including echolocating and non-echolocating species.

Variables

• X: Row number
• long: Longitude
• lat: Latitude
• ocean_spr_echo: Species richness of echolocators
• ocean_spr_nonecho: Species richness of non-echolocators
• ocean_depth: Depth of ocean
• elevation_range: Depth variation of seabed
• chla_value: Net primary productivity (Chlorophyll-a concentration)
• mixedlayer_depth: Depth of mixedlayer
• salinity_surface: Salinity of sea surface
• seasurfaceT: Temperature of sea surface
• surfaceT_seasonal: Temperature seasonality of sea surface (Coefficient of Variation)
• bottomT: Temperature of seabed
• waterspeed: Water velocity of sea surface
• ocean_hfp_mean: Human footprint

Depth of ocean, depth variation of seabed and depth of mixedlayer in meter (m)

Salinity of sea surface in Practical Salinity Units (PSU)

Temperature of sea surface and temperature of seabed in Celsius degree (℃)

Water velocity of sea surface in meters per second (m s^-1)

File: PAM_land_echolocator.csv

Description: Presence-Absence Matrix of terrestrial echolocating species.

1 = Species presence

0 = Species absence

File: PAM_land_non-echolocator.csv

Description: Presence-Absence Matrix of terrestrial non-echolocating species.

1 = Species presence

0 = Species absence

File: PAM_ocean_echolocator.csv

Description: Presence-Absence Matrix of marine echolocating species.

1 = Species presence

0 = Species absence

File: PAM_ocean_non-echolocator.csv

Description: Presence-Absence Matrix of marine non-echolocating species.

1 = Species presence

0 = Species absence

Reference: 

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, 4302–4315. https://doi.org/10.1002/joc.5086

NOAA National Geophysical Data Center (2009). ETOPO1 1 Arc-Minute Global Relief Model. NOAA National Centers for Environmental Information. https://doi.org/ 10.7289/V5C8276M (Accessed on 17-12-2024)

Pinzon, J. E., Pak, E. W., Tucker, C. J., Bhatt, U. S., Frost, G. V., & Macander, M. J. (2023). Global Vegetation Greenness (NDVI) from AVHRR GIMMS-3G+, 1981-2022 (Version 1). ORNL Distributed Active Archive Center. https://doi.org/10.3334/ORNLDAAC/2187

Sathyendranath, S., Brewin, R. J. W., Brockmann, C., et al. (2019). An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI). Sensors, 19, 4285. https://doi.org/10.3390/s19194285

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. https://doi.org/10.1038/s41597-022-01284-8

Halpern, B.S., Frazier, M., Afflerbach, J., Lowndes, J.S., Micheli, F., O’Hara, C., Scarborough, C., Selkoe, K.A., 2019. Recent pace of change in human impact on the world’s ocean. Scientific Reports, 9, 11609. https://doi.org/10.1038/s41598-019-47201-9

Copernicus Climate Change Service, Climate Data Store (2021). ORAS5 global ocean reanalysis monthly data from 1958 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.67e8eeb7. (Accessed on 16-12-2024)

Copernicus Climate Change Service, Climate Data Store (2019). Land cover classification gridded maps from 1992 to present derived from satellite observation. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.006f2c9a (Accessed on 16-12-2024)

Sabater, J. M. (2019). ERA5-Land monthly averaged data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.68d2bb30 (Accessed on 16-12-2024)

Zomer, R. J., Xu, J., & Trabucco, A. (2022). Version 3 of the global aridity index and potential evapotranspiration database. Scientific Data, 9, 409. https://doi.org/10.1038/s41597-022-01493-1

Dinerstein, E., Olson, D., Joshi, A., Vynne, C., Burgess, N. D., Wikramanayake, E., Hahn, N., Palminteri, S., Hedao, P., Noss, R., et al. (2017). An ecoregion-based approach to protecting half the terrestrial realm. BioScience, 67, 534–545. https://doi.org/10.1093/biosci/bix014