Getting Biodiversity Data

Transcription

1 Getting Biodiversity Data NatureServe Canada Douglas Hyde Executive Director

2 Value of biodiversity data to business? Reasons vary depending on the business Reduce development uncertainty Integrated views of data help communicate priorities; Businesses can avoid or minimize planning risks Increase operational efficiency Ties to permitting, EA, monitoring, performance audits Enhance mitigation, adaptation Enhance/protect market access Avoid pest import/export, product life cycle assessment Ensure consumer acceptance Communicate performance, support effective CSR, environmental reporting CBBC Completing Business Data Needs Assessment (why, what, how)

3 Responsibility for biodiversity Primary mandate: Provincial and territorial governments (lead); Indigenous peoples (land claims) Fisheries and Oceans Canada (marine, fish habitat); Environment Canada (migratory birds, MBS, NWA); Parks Canada; Federal (North - AAND (DIAND)) Role: Other federal agencies (e.g., Agriculture and Agri-food Canada; NRCan, CFIA, PHAC), municipalities, non-profit organizations (e.g., NCC, DU, CBI, land trusts), business (e.g., mining, oil and gas, electricity, forestry, etc.) NatureServe Canada supports international vegetation classification standards.

4 About NatureServe Canada

5 Data overview About 50,000 species elements and 1,500 community elements in our system nationally; 80 experts Of these, 12,000 elements are actively tracked (spatially) Approximately 125,000 EOs nationally Each EO can represent one to thousands of specimen/observation records Data for most elements is incomplete

6 NatureServe Canada Network Nine conservation data centres (CDCs) Atlantic Canada CDC (PEI, NS, NB and Newfoundland and Labrador) Centre de données sur le patrimoine naturel du Québec Ontario Natural Heritage Information Centre Manitoba CDC Saskatchewan CDC Alberta CIMS British Columbia CDC Yukon CDC NWT CDC Standards and consistent methods Data aggregated on a national basis Membership expanding

7 CDCs as aggregators: Data sharing fundamental

8 NatureServe s Business Process and Tools

9 NatureServe s Business Process and Tools

10 Consistent, Quality Data Product: Network-based Spatial Methodology

11 Understanding an Element Occurrence An EO is a locational record representing one or more populations of a species Developed through a process which defines/ refines the meaning of an observation or observations Assess locational uncertainty (what exactly was the observation - telemetry, passive survey, active survey) Explore separation distance (what does the observation mean - a distinct population?) Requires documented source for the observation (as a source feature - only need information about the survey, nothing else)

12 EO Refinement 1. Historical record 2. EO - locational uncertainty high, no consideration of separation distance (single record) 3. New observations - locational uncertainty lower, no consideration of separation distance 4. New observations, locational uncertainty lower, consideration of separation distance (based on EO specifications) 5. Documentation of source features 6. Biodiversity in flux - Ongoing refinement

13 EO Refinement 1. Historical record 2. EO - locational uncertainty high, no consideration of separation distance (single record) 3. New observations - locational uncertainty lower, no consideration of separation distance 4. New observations, locational uncertainty lower, consideration of separation distance (based on EO specifications) 5. Documentation of source features 6. Biodiversity in flux - Ongoing refinement

14 EO Refinement 1. Historical record 2. EO - locational uncertainty high, no consideration of separation distance (single record) 3. New observations - locational uncertainty lower, no consideration of separation distance 4. New observations, locational uncertainty lower, consideration of separation distance (based on EO specifications) 5. Documentation of source features 6. Biodiversity in flux - Ongoing refinement

15 EO Refinement 1. Historical record 2. EO - locational uncertainty high, no consideration of separation distance (single record) 3. New observations - locational uncertainty lower, no consideration of separation distance 4. New observations, locational uncertainty lower, consideration of separation distance (based on EO specifications) 5. Documentation of source features 6. Biodiversity in flux - Ongoing refinement

16 EO Refinement 1. Historical record 2. EO - locational uncertainty high, no consideration of separation distance (single record) 3. New observations - locational uncertainty lower, no consideration of separation distance 4. New observations, locational uncertainty lower, consideration of separation distance (based on EO specifications) 5. Documentation of source features 6. Biodiversity in flux - Ongoing refinement

17 EO Refinement 1. Historical record 2. EO - locational uncertainty high, no consideration of separation distance (single record) 3. New observations - locational uncertainty lower, no consideration of separation distance 4. New observations, locational uncertainty lower, consideration of separation distance (based on EO specifications) 5. Documentation of source features 6. Biodiversity in flux - Ongoing refinement

18 EO Refinement 1. Historical record 2. EO - locational uncertainty high, no consideration of separation distance (single record) 3. New observations - locational uncertainty lower, no consideration of separation distance 4. New observations, locational uncertainty lower, consideration of separation distance (based on EO specifications) 5. Documentation of source features 6. Biodiversity in flux - Ongoing refinement

19 Prairie White-fringed Orchid

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21 Ecological Community Mapping Apply international vegetation classification standards in Canada Completed mapping and ranking of ecological communities at fine scales in Alberta (est. ~$10 million nation-wide) Assist in management, modelling applications (fire, pest, range, habitat, ecosystem service evaluation) and in priority setting

22 How is biodiversity data used?

23 Types&of&data&requests*& Site%Management% Conserva0on%Program%Planning% Land%Use%Planning% Environmental%Assessment% Status%assessments% Other% * Estimated, based on 2009 request data

24 Fine Scale: Property Management and Project EA Screening: Simple questions can focus effort What federal or provincially listed species at the site? What other species? Where are they? What threatens them? Beyond screening Engage proper experts Trigger for additional study

25 Coarse Level Decision Making: Species at Risk by EcoDistrict

26 Demand for data? NatureServe Data can be accessed through NatureServe Explorer, Web Services, or through custom data requests Individual CDC s have their own tools tailored to provincial legislation or planning requirements Ontario Explorer CDC Internet Mapping Service BC Species and Ecosystems Explorer Others Currently estimate more than 500 thousands queries per month Custom requests for some data: Must respect data sensitivity

27 Who is asking for data? Total Data Requests Consultants Government Academic ENGO Public Industry Press USA CAN Int Unknown Requests: Consultant Breakdown Consultant - Industry Consultant - Gov't Consultant - ENGO Consultant - unknown Consultant - Gov't Federal Consultant - First Nations Consultant - Gov't Local Consultant - Gov't Provincial Requests: Government Breakdown Gov't Local Gov't Provincial Gov't Federal First Nations BC CDC tracks client requests ~ 900 per year (2009) Response time from 6.5 to 2.7 days since 2004 Time to process requests from 0.5 hours in 2004 to 0.25 hours in 2008

28 What is the status of biodiversity data?

29 Data Highly Fragmented; Data Incomplete Welcome/Bienvenue

30 Spatial Limitations: Element Occurrences in eastern Canada Network data coverage for some species in some areas is high; artifact of where species of conservation risk occur Need more survey work for priority species to enhance coverage Data quality affected by age of supporting observational data - need ongoing investments in surveys and inventories

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32 Taxonomic Gaps

33 Data is highly fragmented Several primary focal points for accessing data (each with limitations) NatureServe Canada (provinces, territories with focus on rare species) Canadensys (primarily from universities; plants, insects) Canadian Biodiversity Information Facility (primarily from federal sources)

34 Other data sources Bird Studies Canada (bird species) Canadian Museum of Nature (north?) Agriculture and Agri-food Canada (CNC) GBIF (not quality reviewed)

35 Implications The costs of obtaining data generally outweigh the benefits to decision making. Business adaptation? Sufficing Aggregate the data you can in the time available - hit known focal points Do it yourself data Solves short term problem, introduces new issues Reinforces fragmentation Get help (following standards? competent observer? Sharing results? CDC, other)

36 Can we improve access to biodiversity data?

37 Work together Overcome barriers to data sharing Develop technology tools to facilitate defragmentation, digitization and sharing Mine and apply standards to existing data Be proactive about ties to decision making, insist on relevance Reduce cost of developing and accessing data, ensure tied to priorities Adopt new technologies, approaches that increase data (bar coding, directed citizen science) Enhance coordination Create a national repository for data Business has an important voice

38 A Vision A Canadian Institute for Biodiversity Information - outside government, joins fragmented communities, a network - funded by federal, provincial agencies; cost recovery mandate; supports business decision making - promotes a Canadian observational data standard (based on DwC), creates spatial data products - sets priorities every 3 years for a national biological survey, based on (1) an understanding of demand, (2) a synthesis of existing data (identification of gaps); offers funding - ensures data is gathered and made available to researchers, CDCs - gathers data and produces reports based on expert input to address issues of the day (policy relevance)

39 Bar Coding Cost of processing and gathering data diminishing Target at lesser studied taxonomic groups? Tie to citizen science - enable accurate identification Build strong corporate sector support - tie to monitoring requirements

40 Naturally Connected: Expanding Canadian Biodiversity Citizen Science

41 Thank you! Questions? What data does business need?