10.5061/DRYAD.3N5TB2RCP
Chiu, Wing Tung Ruby
0000-0001-6663-9526
University of Hong Kong
Yasuhara, Moriaki
0000-0003-0990-1764
University of Hong Kong
Cronin, Thomas
United States Geological Survey
Hunt, Gene
0000-0001-6430-5020
Smithsonian Institution
Gemery, Laura
United States Geological Survey
Wei, Chih-Lin
National Taiwan University
Data from: Marine latitudinal diversity gradients, niche conservatism, and
out of the tropics and Arctic: climatic sensitivity of small organisms
Dryad
dataset
2020
Benthos
Ostracoda
Research Grants Council of the Hong Kong Special Administrative Region, China
HKU 17306014
Research Grants Council of the Hong Kong Special Administrative Region, China
HKU 17311316
Seed Funding Programme for Basic Research of the University of Hong Kong
201311159076
Seed Funding Programme for Basic Research of the University of Hong Kong
201611159053
HKU Earth as a Habitable Planet Thesis Development Grant
2020-12-05T00:00:00Z
2020-12-05T00:00:00Z
en
284745 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Aim The latitudinal diversity gradient (LDG) is a consequence of
evolutionary and ecological mechanisms acting over long history, and thus
is best investigated with organisms that have rich fossil records.
However, combined neontological-paleontological investigations are mostly
limited to large, shelled invertebrates, which keeps our mechanistic
understanding of LDGs in its infancy. This paper aims to describe the
modern meiobenthic ostracod LDG and to explore the possible controlling
factors and the evolutionary mechanisms of this large-scale biodiversity
pattern. Location Present-day Western North Atlantic Taxon Ostracoda
Methods We compiled census data from ostracods living in shallow marine
environments of the western North Atlantic Ocean. Using these data, we
documented the marine LDG with multiple metrics of alpha, beta (nestedness
and turnover), and gamma diversity, and we tested whether macroecological
patterns could be governed by different environmental factors, including
temperature, salinity, dissolved oxygen, pH and primary productivity. We
also explored the geologic age distribution of ostracod genera to
investigate the evolutionary mechanisms underpinning the LDG. Results Our
results show that temperature and climatic niche conservatism are
important in setting LDGs of these small, poorly-dispersing organisms. We
also found evidence for some dispersal-driven spatial dynamics in the
ostracod LDG. Compared to patterns observed in marine bivalves, however,
dispersal dynamics were weaker and they were bi-directional, rather than
following the “out-of-the-tropics” model. Main Conclusions Our detailed
analyses revealed that meiobenthic organisms, which comprise two-thirds of
marine diversity, do not always follow the same rules as larger,
better-studied organisms. Our findings suggest that the under-studied
majority of biodiversity may be more sensitive to climate than are
well-studied, large organisms. This implies that the impacts of ongoing
Anthropocene climatic change on marine ecosystems may be much more serious
than presently thought.
1. Present-day shallow marine ostracod data We constructed a
comprehensive, equator-to-pole compilation of ostracod censuses from the
western North Atlantic and the Arctic Oceans. We standardized ostracod
taxonomy and integrated census data from previously published studies,
which involved restudy of previous collections. We obtained complete
ostracod census data from the original faunal slides from the US
Geological Survey’s collections, including those of Hazel (1970),
Valentine (1971), Cronin (1983), Cronin (1990) and Lyon (1990). Taxonomy
was based on Cronin (1990) with additional information for high latitude
species from Yasuhara et al. (2012) and Gemery et al. (2015). In addition
to the census data from the USGS collections, census data from Kontrovitz
(1976), Teeter (1975), and the Arctic Ostracode Database (Gemery et al.,
2015) were added to our dataset after standardizing taxonomy using SEM
pictures and descriptions from the literature. Locality information
(longitude, latitude and water depth) was obtained from the original
cruise reports and literature. 2. Environmental parameters Environmental
parameters were obtained from various databases (Appendix 2 and Table S3).
Mean annual values (1955 – 2012) for temperature (°C), dissolved oxygen
(ml/L) , and salinity were obtained from the World Ocean Atlas (Baranova,
2015). pH data were obtained from the Global Ocean Data Analysis Project
Bottle Data (version 2) (Olsen et al., 2016). Mean sea surface net primary
productivity (NPP, in mgC/m2/day) data (1998-2014) were obtained from
Oregon State University Ocean Productivity Centre
(http://www.science.oregonstate.edu/ocean.productivity/) (Behrenfeld and
Falkowski, 1997). Sea bottom environmental parameters were interpolated
for each standard depth [based on World Ocean Atlas (Baranova, 2015)]
using the Triangulated Irregular Network (TIN) interpolation from the
plugin “interpolation” of QGIS (QGIS Development Team, 2016) with
geographic range: latitude = 0 – 90°N; longitude = 100°W – 30°E.
Interpolated environmental raster layers were overlaid with ostracod sites
in QGIS (QGIS Development Team, 2016) and Point Sampling Tool was used to
extract the values of environmental parameters at each site.