Global patterns and predic-tors

of marine biodiversity across taxaDerek P. Tittensor1, Camilo Mora1, Walter Jetz2, Heike K.

Lotze1, Daniel Ricard1, Edward Vanden Berghe3 & Boris Worm1

1: Department of Biology, Dalhousie University, 1355 Oxford Street, Halifax B3H 4J1, Canada.

2: Department of Ecology and Evolutionary Biology, Yale University, 165 Prospect Street,

New Haven, Connecticut 06520-8106, USA. 3Institute of Marine and Coastal Sciences, Rutgers University, New Brunswick, New Jersey 08901-8521, USA.

2010.09.14정다금

Global patterns of species richness and their structuring forces

Ecology, evolution, conservation

Examine:-Global patterns(2-D) and predictors of species richness across 13 major species groups (zooplankton to marine mammals)

* Coastal species: Western pacific

* Oceanic groups: mid-latitudinal in all oceans

* Spatial regression analyses: - Sea surface temperature - habitat availability and historical factors

Important: Temperature or kinetic energy, human impacts

Patterns

Predictors

DP Tittensor et al. Nature 000, 1-4 (2010) doi:10.1038/nature09329

Patterns of species richness for Coastal taxa.

PRIMARILY

COASTAL

DP Tittensor et al. Nature 000, 1-4 (2010) doi:10.1038/nature09329

Patterns of species richness for individual taxa.

DP Tittensor et al. Nature 000, 1-4 (2010) doi:10.1038/nature09329

Patterns of species richness for individual taxa.

PRIMARILY

OCEANIC

DP Tittensor et al. Nature 000, 1-4 (2010) doi:10.1038/nature09329

Global species richness and hotspots across taxa.

0~1 normalizedB-hotspots: Philippins, Japan, China, Indonesia, Australia, India and SriLanka, South Africa, and the Caribbean and southeast USAC-coastal species: Southeast AsiaD-oceanic diversity: ~30’ North or South

SLM ResultsNumber: z-values*: significance levels

13 taxa

6 Hypothesis

Multivariate spatial linear models (SLMs) 6 hypothesis

1)The kinetic energy or temperature hypothe-sis:

Higher temperature

-> increased metabolic rates

-> promote higher rates of speciation

2)‘Productivity-richness’ hypothesis:

Extinction or Niche specialist

- Better discrimination than on land

3) The stress hypothesis:

Negative relationship of richness with environ-mental stress

( Quantifying the extent of oxygen depletion)

4)The Climate stability hypothesis

Higher diversity in more environmentally stable regions

Test: using a measure of temporal variance in sea surface temperature (SST)

5) The availability of important habitat feature:

Influence positively both abundance and richness• coastline length for coastal species • Frontal systems for oceanic species (SST slopes)

6) Evolutionary history among ocean basins

‘Oceans~’

SST: * only predictor of species richness identified as sta-

tistically significant across all species groups in the SLMs

* support to kinetic energy or temperature hypothe-sis

(higher metabolic rates or relaxed thermal con-straints promote diversity)

* supported by minimal-adequate generalized-linear models (GLMs)

SST is the BEST

(3)Historical Geo-

graphicfactors

Not sup-ported(2)Habitat

Temperature or kinetic energy has consistent and dominant role in structuring broad-scale marine diversity patterns, particularly for ectothermic species, with habitat(2) area and historical factors(3) important for coastal taxa, and support for other factors varying by taxon

1) Endothermic groups ( cetaceans and pinnipeds) showed stronger positive relationships with primary productivity than SST ( 5.5***, 12.1*** vs. -10.0***, 6.6***)

1)

DP Tittensor et al. Nature 000, 1-4 (2010) doi:10.1038/nature09329

Diversity, SST and human impact overlap.

SST and species richness was generally positive (a-c)(except pinnipeds , selective advantage in cold waters)

Coastal groups; increase monotonically with temperature

Oceanic groups: asymptotic with SST

Total Div. Coastal Div.

Oceanic Div.Large human impacts (statistically significant): coastal areas of East Asia, Europe, North America and Caribbean

Total s.r ( r = 0.19 , P<0.01)Normalized richnessAll: r = 0.35Cs: r = 0.15Os: r = 0.43 p <0.01 all cases

Limitation

-Limited taxa-Large gap: deep-sea diversity-Microbes or viruses-Limited marine invertebrate data- Analyze only a subset of mechanisms that may shape biodiversity

Founding!: 2 distinct patterns of global marine biodiversity

*** Coastal habitat taxa vs. Open ocean taxa

* Temperature => kinetic energy=> Diversity (species richness) over evo & eco

* Habitat

Limiting the extent of ocean warmingMitigating multiple human impacts

Methods

Data collecting: - www.iobis.org and expert

Analysis: GLMs and SLMs, Dep-indep. Variables -> log-transformed to linearize and normalize dataExcluding: zero diversity, <10% ocean areaMaximum likelihood spatial autoregressive (SAR) model Akaike Information Criterion

Thank you