The document discusses how spatial data can be used to inform policy development and review related to biodiversity. It notes that spatial data and maps can help identify conservation priorities, assess trade-offs between development and biodiversity, and monitor progress towards targets. However, barriers include lack of data sharing, expertise, infrastructure, and funding. The document then describes a project in the Lake Victoria Basin that developed land use change scenarios, mapped biodiversity and development data, modeled impacts, and used the results to review relevant policies and recommend revisions.
Using Spatial Data to Guide Policy for Biodiversity
1. The use of spatial data in policy
development and review
A tool for biodiversity mainstreaming
Sarah Darrah, UNEP-WCMC
2. Why include spatial data in policies/action
plans?
• Spatial data and maps provide a
strong communication message
• Help identify hotspots of threat to
determine action and prioritise
limited resources
• Provide a context to decision-making
• Baselines and monitoring to track
progress towards targets
• Multiple layers of data can be used to
compare ‘competing’ demand on land
to assess trade-offs and synergies e.g.
proposed developments vs areas of
high biodiversity importance
3. How spatial data can be used as a tool to
facilitate the mainstreaming process
• Most (spatial) data can be used for
multiple purposes
• Land use planning requires
cooperation as well as the sharing of
(spatial) data
• Changes in land use over time are
relevant for monitoring and planning,
involving many stakeholders
• Solving data availability, costs,
exchange, access problems involves
many stakeholders
• Mainstreaming processes will lead to
more efficient data gathering and use
4. Barriers to use of spatial data
• Lack of access to data (e.g. inter-agency data
sharing is poor) and data collection (e.g. lack of
continuous temporal data/data on certain topics)
• Lack of expertise with spatial data (e.g. GIS analysis
and interpretation)
• Limited infrastructure to conduct spatial data
analysis (e.g. data storage and equipment)
• Lack of financial resources
5. Enabling factors for use of spatial data
• Good institutional exchange
• Existing research and data collection programmes
• Existing network and infrastructure for data
management
6. Engaging stakeholders in using future scenarios
to analyse the potential impacts of agricultural
development in the Lake Victoria Basin
Project steps:
1. Develop future scenarios – four scenarios based on modes
of governance and regionalisation
2. Map biodiversity, ecosystem function and
planned/proposed high impact developments
3. Model biodiversity and ecosystem function under land use
change scenarios
4. Use results to inform scenario guided policy review –
agriculture sector
5. Harmonise policies in the region and look for
transboundary impacts
7. • Key Biodiversity
Areas (KBAs)
• Proposed
freshwater KBAs
• Protected Areas
• Population
density in cities
Areas of biodiversity importance
15. Scenario-guided policy review
• Five policies reviewed against the modelled
scenario results
• Uganda – Draft National Water Policy
• Tanzania – National Livestock Policy
• Burundi – Plan National D’Ivestissement Agricole
• Kenya – Ministry of Agriculture, Livestock and Fisheries
Strategic Plan
• Rwanda – National Food and Nutrition Strategic Plan
• Recommendations produced to input into policy revision
and development
16. 1. Is spatial data relevant to your identified entry
points?
2. Is it already included? And adequately? Does it
include both development and biodiversity data?
3. If not, is it accessible?
4. How can the project help in the provision of
biodiversity data/maps?
Group discussions
Hinweis der Redaktion
A look at how spatial data and future scenarios can be used in the policy development process, using examples from the Lake Victoria Basin region” – presentation follow by country group discussion to review the use of spatial data in their mainstreaming entry points
Examples of mainstreaming biodiversity and agriculture in the Lake Victoria Basin.
From mapping biodiversity priorities
And look at incorporating spatial data
Or just some things to think about…
Based on survey results from 50 countries
Example for mainstreaming biodiversity into the agriculture sector of countries in Lake Victoria Basin – Uganda, Kenya, Tanzania, Rwanda, Burundi.
Proteus partnership – biodiversity data to extractive industry to manage their environmental risk
Protected areas based on national level data submitted to the WDPA.
KBAs dataset maintained by BirdLife International as a partnership between BirdLife and Conservation International. Freely downloadable
A number of freshwater KBAs have been proposed and IUCN’s Freshwater Biodiversity Unit is working on another MacArthur project to prioritise these by undertaking an analysis of the wetland areas within the LVB compiling data on species distribution and abundance to identify threats, prioritise freshwater KBAs and recommend areas that should be proposed for improves PA status.
Protected Area boundaries from: UNEP-WCMC (2015) The World Database on Protected Areas (WDPA) Cambridge, UK: UNEP-WCMC. Available at: http://www.protectedplanet.net/ [Accessed October, 2015].
Key Biodiversity Area boundaries from: BirdLife International and Conservation International (2015) Key Biodiversity Area (KBA) digital boundaries: November 2015 version. Maintained by BirdLife International on behalf of BirdLife International and Conservation International. Downloaded under licence from the Integrated Biodiversity Assessment Tool. Available at: http://www.ibatforbusiness.org.
Population density across the Lake Victoria Basin from: WorldPop (2010) Total number of people per grid square across Africa, with national totals adjusted to match UN population division estimates. Version 1.0 2010, 2012 revision. Available at: http://www.worldpop.org.uk/data/summary/?contselect=Africa&countselect=Whole+Continent&typeselect=Population+2010.
Based on current and planned mining activity, no scale of numbers of mining projects but these are the areas where we know there is activity or think there may be some planned. There is likely to be data missing so it would be good to consider known areas of mining activity in the exercise we have coming up.
SNL (2015) SNL Metals & Mining Database. Available at: http://www.snl.com/Sectors/MetalsMining/Default.aspx [Accessed March, 2015].
Again there are likely to be gaps in this dataset as it is based on global data. Could be validated and improved with local knowledge. maps land deals based on news report, papers, not gathered in a consistent way and not necessarily spatially accurate. Size of bubble represents size of land deal in hectares.
The Land Matrix Global Observatory. Available at: landmatrix.org [Accessed June, 2015].