GLOBALBIODIVERSITYGLOBALBIODIVERSITYINFORMATIONFACILITY

Dr Nick KingExecutive DirectorGBIF WWW.GBIF.O

RG

GBIF – Strategic Perspectives on building the Biodiversity

Informatics Commons

Building the Biodiversity Informatics Commons

TDWG Annual Meeting9-13 Nov 2009, Montpellier

Context

ContextThird year of Strategic Plan 07-11, of moving GBIF ”from prototype towards full operation”

- how far are we?

07-11 Strategic Plan, to: 1. Make a whole world of biodiversity data

that are currently exceedingly difficult to access freely and universally available via the Internet;

2. Enable scientific research that has never before been possible; and

3. Facilitate the use of scientific data in biodiversity policy- and decision-making.

Millenium Assessment (2005)

“Balance sheet more red than black”

Nature Vol 461: 24 Sept 2009

Living on credit….

Living on credit….

Fishing Down the Food Web….

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Grow th of the nationally designated protected areas in 39 EEA countries Source – EEA 2009

Growth of the nationally designated protected areas in 39 EEA countries Source – EEA 2009

 

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Common farmland birds

Common forest birds

All common birds

Com m on birds in Europe, population index (1980 = 100)

Common birds in Europe, population index (1980 = 100)

Needs for Biodiv information?

Needs for Biodiv information?

CBD Decision VIII/11: Scientific and technical cooperation and the CHM

“Invites Parties and other Governments to provide free and open access to all past, present and future public-good research results, assessments, maps and databases on biodiversity, in accordance with national and international legislation …”

Open Access: International mandates

The (OECD) governments (Australia, Austria, Belgium, Canada, China, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, the Russian Federation, the Slovak Republic, South Africa, Spain, Sweden, Switzerland, Turkey, the UK, and the US):

DECLARE THEIR COMMITMENT TO work towards the establishment of access regimes for digital research data from public funding in accordance with the following objectives and principles:

Openness: balancing the interests of open access to data to increase the quality and efficiency of research and innovation with the need for restriction of access in some instances to protect social, scientific and economic interests …

OECD/CST Science, Technology and Innovation for the 21st Century, 29-30 Jan 2004

Open Access: International mandates

Establishment of GBIF originally endorsed by Science Ministers to the OECD, 2000

data provider / aggregator

GBIF is a global science/informatics research infrastructure:

What is GBIF?

- promoting global participation, working through and linking up a global network of participants;

- enabling publishing of biodiversity data;- promoting development of data

capture & exchange standards;- building an informatics architecture;

- building capacity;- catalysing development of analytical tools.

GBIF’s Mandate

”To facilitate free and open access to biodiversity data worldwide, via the Internet, to underpin scientific research, conservation and sustainable development.”

The GBIF Secretariat role is to be a facilitator, catalyst and service provider to the globalBI community, particularly in service to govts, as a global ‘public good’ initiative

Growth in GBIF Participation

Growth in GBIF Participation

NB: Drop in Associate Participants in 2007 is attributable to delays in signing the new MOU 2007-2011

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GBIF Country Participants

GBIF Country Participants

Currently 53 countries…

• Argentina• Australia• Belgium• Canada• Costa Rica• Denmark• Equatorial

Guinea• Estonia• Finland• France• Germany

• Iceland• Ireland• Japan• Korea, Rep. Of• Mauritania• Mexico• Netherlands• New Zealand • Norway• Peru

• Portugal• Slovakia• Slovenia• South Africa• Spain• Sweden• Tanzania• United

Kingdom• Uruguay• USA

GBIF Voting Participants 2009: 31

GBIF Voting Participants 2009: 31

• Austria• Benin• Bulgaria• Burkina Faso• Cameroon• Colombia• Cuba

• Ghana• Guinea• India• Kenya• Indonesia• Luxembourg• Madagascar

• Morocco• Nicaragua• Pakistan• Philippines• Poland• Switzerland• Togo• Uganda

GBIF Associate Country Participants 2009: 22

GBIF Associate Country Participants 2009: 22

• ACB• ANDINONET• BioNET-ASEANET• BioNET-EASIANET• BioNET-

INTERNATIONAL• BioNET-SAFRINET• Bioversity

International• BGCI• CABI Bioscience• CBOL• CETAF• Chinese Taipei• CYTED• Discover Life

• DIVERSITAS• EOL• ETI

Bioinformatics• EWT• Finding Species• FreshwaterLife• IABIN• ICIMOD• ICIPE• ICZN• ILTER• ISIS• ITIS• MSEF• NSCA

• NatureServe• NORDGEN• OBIS• PBIF• SCAR• SINEPAD• SMEBD• Species 2000• SPNHC

• TDWG• UNEP-WCMC• WDCBE• WFCC• Wildscreen

Int. Organisation Participants 2009: 43

Int. Organisation Participants 2009: 43

GBIF Working PrinciplesGBIF Working Principles

Worldwide network of collaborating institutions that share data (data publishers) — not central compilation;

Ownership of data remains entirely with publishers;

Open, standardised schemas for data sharing — software free to data publishers;

GBIF Participant Nodes promote and coordinate activities of data publishers;

”Towards full operation” = increasing decentralisation and ownership

GBIFS

ReBIF

NBIFImproving outreach, promoting ownership, growing benefits…the next generation of GBIF…

Building Community Ownership

Nodes: from IT gateway to Participant BIF

Nodes: from IT gateway to Participant BIF

Build capacity

Help identify data and information

gapsEngage data holders

Promote best practices in data management

Identify user communities – assess end user needs

Help address data & information needs

Implement informatics

infrastructure

Coordinate data sharing

activities

Helpdesk

Help develop information products and services

Help formulate and adopt data sharing and manahgement policies

Participa

nt BIF

Promote online publication of

scientific data

How formal mandates affect capacity and resourcing

How formal mandates affect capacity and resourcing

Participants leading…France

Participants leading…France

Train the trainers…

Train the trainers…

Spatial Analysis

Spatial Analysis

Spatial Analysis

Spatial Analysis

Partnerships: UNEP-WCMC (WDPA)

Partnerships: UNEP-WCMC (WDPA)

Spatial analysis and integration

Spatial analysis and integration

Forests (using GBIF-enabled data)

Forests (using GBIF-enabled data)

Three major plant families and selected a range of forest-based genera:

FamilySpecies analysed

Genera analysed

Number of Records in GBIF with

Coordinates

Dipterocarpaceae 37 9 705Meliaceae 22 16 701Sterculiaceae 388 49 13582

Using GBIF data in CC models

Using GBIF data in CC models

Sterculiaceae (Meliaceae, Dipterocapaceae)

Summary of CC impacts

Summary of CC impacts

All families and genera suffer >50% habitat loss; Some gain in potential, but this would require

migration and suitable ecological niche (for forests) at destination;

Important implications for REDD and other CC adaptation/mitigation programmes

FamilyAverage habitat

loss

Average habitat

expansion

Percent of species with

more than 50% loss

Percent of species with

more than 90% loss

Dipterocarpaceae 57.1 34.4 56.8 40.5Meliaceae 50.6 29.6 54.5 18.2Sterculiaceae 51.0 32.8 50.3 12.4

Agriculture and climate change

Agriculture and climate change

The geography of crop suitability

The geography of crop suitability

Crop SpeciesArea

Harvested (k Ha)

Alfalfa Medicago sativa L. 15214Apple Malus sylvestris Mill. 4786Banana Musa acuminata Colla 4180Barley Hordeum vulgare L. 55517Common Bean Phaseolus vulgaris L. 26540Common buckwheat Fagopyrum esculentum Moench 2743Cabbage Brassica oleracea L.v capi. 3138Cashew nuts Anacardium occidentale L. 3387Cassava Manihot esculenta Crantz. 18608Chick pea Cicer arietinum L. 10672Clover Trifolium repens L. 2629Cocoa bean Theobroma cacao L. 7567Coconut Cocos nucifera L. 10616Coffee Coffea arabica L. 10203Cotton Gossypium hirsutum L. 34733Cow peas Vigna unguiculata unguic. L 10176Grapes Vitis vinifera L. 7400Groundnut Arachis hypogaea L. 22232Lentil Lens culinaris Medikus 3848Linseed Linum usitatissimum L. 3017Maize Zea mays L. s. mays 144376Mango Mangifera indica L. 4155Millet Panicum miliaceum L. 32846Natural rubber Hevea brasiliensis (Willd.) 8259

Natural rubber Hevea brasiliensis (Willd.) 8259Oats Avena sativa L. 11284Oil palm Elaeis guineensis Jacq. 13277Olive Olea europaea L. 8894Onion Allium cepa L. v cepa 3341Oranges Citrus sinensis (L.) Osbeck 3618Pea Pisum sativum L. 6730Pigeon pea Cajanus cajan (L.) Mill ssp 4683Plantain bananas Musa balbisiana Colla 5439Potato Solanum tuberosum L. 18830Rapeseed Brassica napus L. 27796Rice Oryza sativa L. s. japonica 154324Rye Secale cereale L. 5994Perennial reygrass Lolium perenne L. 5516Sesame seed Sesamum indicum L. 7539Sorghum Sorghum bicolor (L.) Moench 41500Perennial soybean Glycine wightii Arn. 92989Sugar beet Beta vulgaris L. v vulgaris 5447Sugarcane Saccharum robustum Brandes 20399Sunflower Helianthus annuus L v macro 23700Sweet potato Ipomoea batatas (L.) Lam. 8996Tea Camellia sinensis (L) O.K. 2717Tobacco Nicotiana tabacum L. 3897Tomato Lycopersicon esculentum M. 4597Watermelon Citrullus lanatus (T) Mansf 3785Wheat Triticum aestivum L. 216100Yams Dioscorea rotundata Poir. 4591

Current suitability for agriculture

Current suitability for agriculture

No. of crops

Future suitability -2050

Future suitability -2050

18 GCM models, A2a scenario

Number of crops that lose out

Number of crops that lose out

Number of crops that gain

Number of crops that gain

IAS – 100 Worst Invaders list

IAS – 100 Worst Invaders list

GBIF-enabled data mean of 14,800 records per species. Need >~20 unique occurrence points for robust model development (83 of 100 Worst Invaders list).

Asian longhorn beetle

TEEB study

TEEB study

The `Stern report´ equivalent for biodiversity loss, 2009

Biodiversity, Ecosystem s, and their Services (TEEB study, 2009)

Biodiversity, Ecosystems, and their Services (TEEB study, 2009)

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Pollution,Water use

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Quelle: Dr Carsten Neßhöver, Heidi Wittmer & Christoph Schröter-Schlaack, UFZ

Management, conservation and sustainable use of biodiversity

Policy development and decision

making (at local, national, regional, and global levels)

Scientific monitoring of status and trends of

biodiversity

GBIF-published data and analyses

The Science-Policy Interface

Influencing Policy - Japan

Influencing Policy - Japan Large- and small-mouth bass

introduced from N. America; predatory, huge impact on indigenous spp.

Japanese policymakers needed to know which areas of the country are most at risk from invasion

Used N. American locality data (from GBIF) to establish EN, applied ENM to Japan and tested with (GBIF) locality records – very high correlation.

Instrumental in convincing authorities to develop IAS Act

Iguchi, K., et al. 2004. Transactions of the American Fisheries Society, 133:845-854.

The Japanese Diet passed its IAS Act in June 2004; first list of IAS, based on Act, passed in June 2005.

‘towards full operation’…

‘towards full operation’…

07-11 Strategic Plan, to: Make a whole world of biodiversity data that are

currently exceedingly difficult to access freely and universally available via the Internet;

Enable scientific research that has never before been possible; and

Facilitate the use of scientific data in biodiversity policy- and decision-making.

“Achieving the ambitions laid out in these plans will require a great deal of involvement and funding from GBIF’s Participants and other partners and stakeholders.”

The Challenge now?

The problems are rising

exponentially;

Linear responses will not help solve

them!

Access to GLOBAL BIODIVERSITY INFORMATION can only be achieved by all in the BI community

working together – that’s what GBIF was established for!

We can make a difference;

We must make a difference – not only is it needed, only then can policy-makers justify investing in biodversity informatics!

The Global Biodiversity Information Facility