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Biodiversity trend indicators from OBIS
1. Trendylyzer: a Long-Term Trend
Analysis on Biogeographic Data
from OBIS
Ward Appeltans, Peter Pissierssens - IOC-UNESCO
Gianpaolo Coro, Angela Italiano, Pasquale Pagano - ISTI-
CNR
Anton Ellenbroek - FAO
Thomas Webb - University of Sheffield
IMDIS 2013
International Conference on Marine Data and Information Systems
Lucca (Italia), September 23-25, 2013
2. One Ocean – One Planet
The Ocean represents 71% of the
Earth’s surface and
99% of the living space on the
planet by volume
Marine Plankton provides 50% of
the O2 we breathe
The ocean regulates climate by
storing heat and absorbing 30% of
the CO2 we produce
Over 3 billion people depend on
marine and coastal biodiversity
resources for their livelihoods.
3. Climate change (rising temperature, acidification,
melting sea ice..)
Overfishing (30% of fish stocks overexploited)
Pollution (micro plastics, 500 dead zones)
Invasive species (Pests, Fouling, toxic algae)
Habitat destruction (mangrove deforestation,
bottom-trawling)
60% of the world's major marine ecosystems have
been degraded or are being used unsustainably.
Ocean is under threat
5. Polar species are disappearing and warmer water species are
moving towards the Poles
Kaschner K, Tittensor DP, Ready J, Gerrodette T, et al. (2011) Current and Future Patterns of
Global Marine Mammal Biodiversity. PLoS ONE 6(5): e19653. doi:10.1371/journal.pone.0019653
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019653
Average of 72 km
(marine) <-> 6 km
(terrestrial) per
decade
(Poloczanska, E.S. et al (2013).
Global imprint of climate change
on marine life. Nature Clim.
Change.
http://dx.doi.org/10.1038/nclimat
e1958)
Projected effects of climate change on marine mammal species richness.
6. Corals are bleaching
van Hooidonk et al. 2013. Temporary refugia for coral reefs in a warming world. Nature Clim. Change
http://dx.doi.org/10.1038/nclimate1829
50% 100%
7. Cold-water corals are dissolving
Ocean acidification
will affect cold
water corals most in
the North Atlantic
present
2099
Tittensor, D. P. et al. (2010), Seamounts as
refugia from ocean acidification for cold-water
stony corals. Marine Ecology, 31: 212–225. doi:
10.1111/j.1439-0485.2010.00393.x
8. Shells are dissolving
Work in progress as part of the GEOWOW project. Unpublished figures. Copyright Steeve Comeau and James Orr
Pteropod data from OBIS, Aragonite saturation data from James Orr, Model from Steeve Comeau
By the end of the century pteropod
shells will be degraded by 50 to 80%.
10. 90% of large predator fish stocks are gone
Myer & Worm (2003). Rapid worldwide depletion of predatory fish communities. Nature. 423
11. Based on the IUCN Red List:
Only 2% of known global extinctions are marine
Only 3% of known endangered (and critical
endangered) species are marine
Few global marine extinctions are documented, but
many local extirpations, and decreasing populations
Are we losing species?
12. High biodiversity => more stable ecosystem functioning
(biological insurance)
Species composition is one of the most basic metrics of
biodiversity
Most documented trends are on few taxonomic groups
(large commercial species, plankton)
Species diversity and Ecosystem
Functioning
13. Ocean Biogeographic
Information System
OBIS is the world’s largest open access, online data
system on the diversity, distribution and abundance of
marine species
120,000 marine species
35 million distribution records
1,130 datasets
>450 data providers (56 countries)
Data legacy of 10-year Census of Marine Life
Adopted by UNESCO-IOC, project of IODE, hosted by IOC project
office for IODE in Oostende (Belgium)
www.iobis.org
14. Marine Species Diversity
The knowns and unknowns?
700K – 1 million marine species
230K described
120K in OBIS
12K OBIS/year
5,4K IUCN assessment
Appeltans et al (2012). The Magnitude of Global Species
Diversity, Current Biology 22
15. Only 1/3 to 1/4 of marine species are known
2/3 of known marine species have < 3 observations
Only 5% of known species diversity is observed per year
Most data from large vertebrates (fish, birds, mammals)
Most data from Northern Hemisphere (least biodiversity rich)
Most data from coastal areas (mid waters almost unexplored)
Very little historical data - only 100 marine species have a yearly
record between 1955 and 2005
Knowledge gaps
21. Data e-infrastructure Initiative for
Fisheries Management and
Conservation of Marine Living
Resources (i-Marine)
Trendylyzer is a tool developed within iMarine
iMarine is an initiative aimed at establishing and operating an
e-infrastructure supporting the principles of the Ecosystem
Approach to Fisheries Management and Conservation of
Marine Living Resources.
Research Infrastructures CP & CSA funded by the European Commission
under the FP7 Capacities Programme - eInfrastructure Unit DG CONNECT
(1 Nov 2011 - 30 April 2014)
25. Discovering trends in pelagic
North Sea species
Plankton regime shift
Herring recovered
after the fish ban
25
26. Major problems:
Data gaps: temporal, geographic and
taxonomic scope
Sampling bias
Few long-term time series data
Discovering trends in biodiversity
27. Major problems:
Most species are rare, or difficult to observe
Still many new species discoveries
creates noise in trends
Which species are most common, and do have
enough data?
+ common species may also have a bigger impact on
ecosystem functioning compared to uncommon species
Discovering trends in biodiversity
28. Questions:
Are e.g. the 20 most common species for each
taxonomic group always common?
What is the natural variation in common
species?
Do we observe higher variation in species
poor regions?
Are there common species endangered (on
the IUCN Red List of threatened species)?
Biodiversity indicator based on
Common Species?
29. For each species:
1. Nr of observations
2. Nr of individuals per observation
3. Nr of observations per dataset
4. Nr of datasets
5. Nr of geographical cells
6. Temporal frequency of the observations
Normalizing => relative commonness.
Create score or rank by taxonomic group
Defining Common Species
30. High variation
among
terms, so each
term
separately will
yield different
ranks
Pisces, by different ranks, 2000s
n records s ranks n records2 s ranks2 n datasets n 1 deg n MEOW
5000
1000
500
200
100
20
10
9
8
7
6
5
4
3
2
1 Lim lim
Lim lim
Lim lim Lim lim
Lim lim
Lim lim Lim lim
Gad mor
Gad mor
Gad mor Gad mor Gad mor Gad mor Gad mor
Clu har
Clu har
Clu har
Clu har Clu har
Clu har Clu har
Mer mer
Mer mer
Mer mer
Mer mer
Mer mer
Mer mer Mer mer
Mel aeg Mel aeg Mel aeg
Mel aeg
Mel aeg Mel aeg Mel aeg
Ple pla
Ple pla
Ple pla
Ple pla
Ple pla
Ple pla Ple pla
Eut gur
Eut gur
Eut gur
Eut gur
Eut gur
Eut gur Eut gur
Pla fle
Pla fle
Pla fle
Pla fle
Pla fle
Pla fle Pla fle
Hip pla
Hip pla
Hip pla
Hip pla
Hip pla
Hip pla Hip pla
Thy atu
Thy atu
Thy atu
Thy atu
Thy atu
Thy atu Thy atu
Xip gla
Xip gla
Xip gla
Xip gla
Xip gla
Xip gla
Xip glaSpr spr
Spr spr
Spr spr
Spr spr
Spr spr
Spr spr
Spr spr
Thu alb
Thu alb
Thu alb
Thu alb
Thu alb
Thu alb Thu alb
Scy can
Scy can Scy can
Scy can
Scy can
Scy can Scy can
Mic kit
Mic kit
Mic kit
Mic kit
Mic kit
Mic kit Mic kitOph elo
Oph elo
Oph elo Oph elo
Oph elo
Oph elo Oph elo
Mer mer
Mer mer
Mer mer Mer mer
Mer mer
Mer mer Mer merTri min Tri min
Tri min
Tri min
Tri min
Tri min Tri minCal lyr
Cal lyr
Cal lyr Cal lyr
Cal lyr
Cal lyr Cal lyr
Aci tra
Aci tra
Aci tra
Aci tra Aci traTri esm
Tri esm
Tri esm
Tri esm
Tri esm
Tri esm Tri esmThu ala
Thu ala
Thu ala
Thu ala
Thu ala
Thu ala Thu ala
Tra tra
Tra tra
Tra tra
Tra tra
Tra tra
Tra tra Tra traSco sco
Sco sco
Sco sco
Sco sco
Sco sco
Sco sco Sco scoMic pou Mic pou
Mic pou
Mic pou
Mic pou
Mic pou Mic pou
Pol vir
Pol vir
Pol vir
Pol vir
Pol vir
Pol vir Pol vir
Squ aca
Squ aca
Squ aca
Squ aca
Squ aca
Squ aca Squ aca
Enc cim Enc cim
Enc cim
Enc cim
Enc cim
Enc cim Enc cimGly cyn
Gly cyn
Gly cyn
Gly cyn
Gly cyn
Gly cyn Gly cyn
Myo sco Myo sco
Myo sco
Myo sco
Myo sco
Myo sco Myo sco
Lop pis
Lop pis
Lop pis
Lop pis
Lop pis
Lop pis Lop pis
Thu ori
Thu ori
Thu ori
Thu ori
Thu ori
Rhi typ
Rhi typ
Rhi typ
Rhi typ Rhi typZeu fab Zeu fab
Zeu fab
Zeu fab
Zeu fab
Zeu fab Zeu fab
Mul sur
Mul sur
Mul sur
Mul sur
Mul sur
Mul sur Mul surGym cer
Gym cer
Gym cer
Gym cer Gym cerMol mol
Mol mol
Mol mol
Mol mol
Mol mol
Mol mol Mol molCyc lum Cyc lum
Cyc lum Cyc lum
Cyc lum
Cyc lum Cyc lum
Pte vol
Pte vol
Pte vol
Pte vol
Pte vol
Pte vol Pte vol
38. Conclusion
Work in progress!!
We detected changes in common species composition:
Changing order
Species dropping in and out
These trends will indicate shifting geographic/taxonomic focus
of surveys, together with real changes in the abundance of
some common species.
=> need to involve experts to validate the trends
Biodiversity trends
39. Future
The next step is now to relax the terms of the
Commonness Score Function by giving a weight to each
term using pattern recognition models such as artificial
neural networks.
40. A preliminary test was done using a Bayesian Neural Network
40 fish species (20 rare and 20 common) for training
40 fish species (20 rare and 20 common) for testing
The classification was obtained from FishBase (expert based)
=>80% agreement between Function and Expert
classification
Future
41. For Policy Making,
biodiversity trend
indicators only
make sense when
combined with
environmental and
socio-economic
data.
Future
Global map (A) of cumulative human impact across 20
ocean ecosystem types.
B S Halpern et al. Science
2008;319:948-952
42. Indicators can serve national, regional
and global assessments of the Ocean
• 2014: CBD 4th Global Biodiversity Outlook
• 2014: GEF Transboundary Water Assessment
• 2015: 1st UN World Ocean Assessment
• 2018: 1st IPBES assessment
42
43. One Planet – One Ocean
THANK YOU
This works is part of iMarine (283644) with funding from the European
Commission under Framework Programme 7
Notas do Editor
we only have one planet - We only have one ocean
We observed that Marine Species are moving much faster to the Poles than terrestrial species. With a loss in native species and a gain in new species.
Ocean acidification will affect cold water corals most in the North Atlantic
By the end of the century pteropod shells will be degraded by 50 to 80%.
Species are important for ecosystem functioning.
What is also interesting is that many taxonomic groups reached their maximum Nr of observations many years ago.
When looking at each term separately, there is a high variation in ranks, with the same fish species listed in the top 10 down below to rank 5000.
So when you look at Nr of records, the fulmar had high peaks in the 1990s.
But when you combine all the terms, the Fulmar is losing its common species status among the other seabirds.
We digged further plotting the 20 most common mammal species per decade, and gave rainbow colors to the 1990s list. Grey are those that are not common in 1990. The nice outcome is that there is still a rainbow in the other decades.
We validated our approach by taking 1000 random samples of 20 mammal species and compared it with 20 common species in that decade. => the set of common species in common between decades are in excess compared to the random set of species.
We repeated this for ten different taxonomic groups
We started this modeling approach by asking FishBase to provide us a list of common and rare fish species, which we then used for training and testing the Neural Network. The good news is that 80% of the classification was in agreement between the Function and the Expert classification.