Biodiversity and Climate Change Scenario Development for the GEOSS Interoperability Pilot Process Hannu Saarenmaa 1,5, Jeremy Kerr 2, Stefano Nativi 3,4, Éamonn O Tuama 1 & Motomi Ito 6 1 GBIF Secretariat, 2 University of Ottawa, 3 Italian National Research Council – IMAA, 4 University of Florence, 5 University of Helsinki, 6 University of Tokyo GEOSS Architecture and Data Committee Meeting, Tokyo, May 2007

Outline Background Interoperability scenarios between biodiversity and other Societal Benefit Areas. Some ideas for demonstration

The 2010 Biodiversity Target Convention on Biological Diversity's (CBD) sixth Conference of the Parties adopted the Strategic Plan for the Convention in Decision VI/26. The Decision says "Parties commit themselves to a more effective and coherent implementation of the three objectives of the Convention, to achieve by 2010 a significant reduction of the current rate of biodiversity loss at the global, regional and national level as a contribution to poverty alleviation and to the benefit of all life on earth."Convention on Biological Diversity The World Summit on Sustainable Development held in Johannesburg in 2002 confirmed the 2010 biodiversity target and called for "the achievement by 2010 of a significant reduction in the current rate of loss of biological diversity".

Global Biodiversity Information Facility (GBIF) International organisation launced under the OECD Megascience Forum in 2001 –40 countries, 33 int’l organisations members Network of primary data –200 providers in 30 countries, connecting over 1000 databases, 124 million records of in-situ observations Infrastructure –UDDI Registry, Data Portal, Cache of all data, Web Services Building on Biodiversity Informatics Standards ( –Darwin Core, ABCD, DiGIR, BioCASE, TAPIR,... –MoU with OGC

Portal Data provider Provider Services Request Marshaller Query Engine Registry Institutions Providers Services ( UDDI ) Resource Metadata Resource Metadata GBIF Component Architecture Index Name provider Provider Services Resource Metadata Resource Metadata Cache Metadata Accounting SOAP DiGIR HTTP other Data Portal Data providers Provider Services Provider query Request Marshaller Query Engine Available providers Registry Institutions Providers Services ( UDDI ) User Resource Metadata Resource Metadata Index Name providers Provider Services Resource Metadata Resource Metadata and name query Cached partial data response Full data query Full data response Metadata and statistics Synonyms Publish availability Data Cache Metadata Accounting SOAP DiGIR HTTP other e.g., BioMoby web service National and Thematic Portals

Makes available through the GBIF mechanism 900,768 in-situ records from 55 databases. Will provide (in this year): Fully customized new portal Available GBIF data using Japanese language Japanese vernacular names Scientific name dictionary DNA barcoding database for Native species of Japan Start of project in Etc. GBIF-Japan National Node GBIF-Japan Data portal:

Scenarios for interoperability between biodiversity and other SBAs such as climate change

Pilot Phase 2 – Cross-System Interoperability Scenarios Develop scenarios that require the exchange of data and information between GBIF and other disparate systems –Address needs identified in one or more of the Societal Benefit Areas. –Ensure relevancy Create interoperability arrangements between GBIF and another system –Analyze the entries in the GEOSS Service Register for the systems to be made interoperable. Where the registered standards are insufficient to support interoperability, work with technical experts to identify solutions –When a solution is identified it will be circulated for approval and, upon acceptance, this arrangement will be entered into the Interoperability Register

The process of developing scenarios A scenario is a description of a person's interaction with a system. Scenarios is user language help focusing the work on user's requirements. Scenarios should not be technical, and therefore their development should fit for participatory design activities. They should confine complexity to the technical level (where it belongs). Develop through interviews with users and experts. Scenarios can be formalised into use cases. A scenario is an instance of a use case. A use case specifies all possible scenarios for a given piece of functionality (incl. actors, requirements, constraints, all scenarios)

There are several interesting biodiversity cross-SBA scenarios Climate change threatens to commit 15-37% of species to extinction by –Accelerating the mass extinction already precipitated by widespread land use changes. Biodiversity has cross-linkages with many other Societal Benefit Areas (SBA): –Climate change: Impacts to and adaptation of species –Ecosystems: Reforestation, desertification, and loss of species –Agriculture: Impacts of invasive species on crops –Health: Spread of infectous diseases –Industry: Search of new drugs –Land Use and Poverty: Loss of natural habitat

Ortalis poliocephala in Mexico before (green) vs. after (red) Biodiversity & Climate Change & Land Use scenario Town Peterson & al The species will be pushed to marginal areas

Biodiversity & Climate Change & Health scenario Where are malaria vectors likely to find appropriate climate and environmental conditions in the future? Here, we present the average of two scenarios created by the Hadley Climate Change Center … for the year quadriannulatus merus melasgambiae Anopheles arabiensis Red areas will be more appropriate to the mosquitoes in the future, blue areas less Town Peterson with Mark Benedict and Bex Levine

Biodiversity & Agriculture (Forestry) scenario Places where the Asian Long-horned Beetle has been recorded in the USA (Chicago and NY) Red: Highest Probability of invasion Source: Town Peterson Distribution model of the invasive Asian Long-horned Beetle applied to North American-based on climatic conditions

BD-CC Scenario Step 1/8: Decide on selected species An analyst needs to report on the impact of climate change to biodiversity. As the entire biodiversity is too broad an area, the question will have to be limited to some “selected species” (CBD decision VIII/15.12). There are no guidelines on how the selection should be made. For practical reasons, the following criteria can be used: 1) availability of data, 2) biological and ecological representativeness, 3) expected susceptibility, 4) importance. This usually leaves only well known groups such as mammals, amphibians, birds, butterflies, trees, vascular plants, etc. as possible target species.

BD-CC Scenario Step 2/8: Set criteria for data The data usually needs to span at least 30 years to catch significant trends. The data would ideally be georeferenced in order to be able to analyse shifts of distribution. It could cover only selected species, or larger groups of species, depending on criteria used.

BD-CC Scenario Step 3/8: Investigate data availability Traditionally, it is assumed that data is off- line, so this involves contacting the relevant administrations and research groups to find out whether and on which groups of species they have sufficient data. Online data exchanges, like GBIF will be queried on the availability of the data for interesting groups in interesting areas.

BD-CC Scenario Step 4/8: Improve quality and access to data If data is not available, relevant research groups may be notified of the need to make data available. If data is available, it will be downloaded for analyses. Serious effort on data cleaning is usually needed.

BD-CC Scenario Step 5/8: Choose approach for modelling Depending on the species group, density of data, and the known environmental requirements of the species, an approach for modelling is selected. Typically this is based on Ecological Niche Modelling (ENM). This technique analyses change of distribution based on knowing from historical data the environmental conditions where the species has lived in the past, and where such conditions are projected for future.

Example: ENM using the OpenModeller Framework A flexible, user friendly, cross platform environment where the entire process of conducting a fundamental niche modeling experiment can be carried out. Client-server architecture enabling the existence of different client interfaces (desktop, command line and web-based). Tasks can be performed in a distributed way, including the possibility of running separately the algorithms in remote cluster machines. Source code is available at sourceforge.

BD-CC Scenario Step 6/8: Acquire and transform climate change and environment data Typically for ENM, it is determined that data layers (rasters) of temperature, rainfall, vegetation, land use cover, etc. are needed. The resolution of data is determined, and different resolutions may be tried, but 1*1 degree cells are often the starting point. The layers include historical data, and projected future scenarios, and cover the area of interest. The layers are acquired from online and offline sources (make use of GEO Clearinghouse!)

BD-CC Scenario Step 7/8: Execute models One or more modelling algorithms for ENM are selected and their parameters set. The models are executed for each selected species. The resulting maps are stored for analysis of shifts of distribution and trends of abundance. Summary statistics are calculated showing how many species expand, contract and move.

BD-CC Scenario Step 8/8: Present the results The statistics are presented in a draft report. (Also make available via GEO Portal!) The data providers will be informed that their data has been used, and they will be asked for comments and eventual more contributions to improve the data and validate the results.

Summary: Open Modeler Activity Diagram Apply GARP, BioClim and other models Ecological Niches Distributional Shifts Categorical Climate Maps Region Shift Distributional Shifts in Ecological Niches

Towards a Demonstration

Demo steps: Work in progress 1.Write a formal and expanded use scenario –Candidate species group: Modeling the impact of climate change on the distribution of the butterflies of Canada and Alaska. 2.Use GBIF web services to access and retrieve the biodiversity data –using GBIF Data Portal centrally –getting the data from the individual data providers 3.Access and retrieve via Web Services climatological data: Interoperability with GBIF registry and GEOSS registries using GI-go/GI-cat ISO19115 metadata as gateway –Average temperature layers, rainfall layers, land cover layers 4.Run the Open Modeller Web services using the SOAP interface –Upload of both Climatological and Biodiversity layers –Create and run models, get outputs 5.Put together a demonstrator user interface, –Include link in GEO Portal and output results in WMS to it.

Demo AJAX Interface to Open Modeller Compute Servers

GBIF & Other GEOSS Components Interoperability Approach Presentation on GBIF and GEO Portals GEOSS Registry Climatological and Environmental Data Processing on Distributed OpenModeller Compute Servers In-situ Biodiversity Records GBIF Registry

Thank you!