1) The document evaluates ecosystem services models and their map outputs to determine how well they support decisions. It surveys 74 tools and focuses on 6 interactive webmaps.
2) The webmaps allowed prioritizing conservation and assessing scenarios but few showed uncertainties or enabled comparing scenarios visually.
3) The author concludes maps are important for decision-making but current tools have limitations and comparing scenarios and changes over time in maps could better support decisions.
Evaluating map design of ecosystem services models - NACIS 2017
1. Evaluating map design
and funding of ecosystem
services models
Eric Nost
University of Wisconsin-Madison
nost@wisc.edu | @ericnost
2. Goals
•Survey ecosystem services models for the
kinds of cartographic representations they
produce
•Ask:
• Do models live up to their expectation as “decision
support”?
• Even if so, what kinds of decisions do they support?
3. What are ecosystem services? (ES)
•“The benefits nature provides to society”
•Example: storm surge
•Why would decision-makers want to measure ES?
• To restore or conserve them
•Why model ES?
• To determine location, value, tradeoffs
4. How do decision-makers learn with
ES models?
• Maps!
• What kinds of maps?
• Time, expertise, tools, and
(mis)communication shape
decision-makers’ use and
interpretations
• Differences maps!
• But absolute or relative
differences? Animation,
interaction, or static?
8. What do we already know about
decision-support tools for ES?
•All ES researchers acknowledge communication
is key
•Yet, emphasis is on spatial analysis (e.g. 2013
special issue of Ecosystem Services)
•Less on representation and considerations like
how to display absolute vs. relative differences
• Even though representation choices shape policy (e.g.
McKendry and Machlis 2009; Neset et al. 2016)
9. Research questions
•What kinds of maps do ecosystem services
models produce?
• What can decision-makers learn from them?
•How is their development funded?
10. Survey
• Find as many ES DSTs as possible. Start very broadly -
frameworks for helping decision-makers act on ES
• Note that this excludes many research models (e.g.
GUMBO)
• But it still includes many kinds of DSTs: conceptual,
databases, desktop/standalone, ArcGIS plug-ins, and
interactive webmaps
• Aimed widely – explicitly ES but also coastal planning
tools that may deal with ES
11. Sources
• Ecosystem-Based Management Tools Network
• “Tools for Coastal Climate Adaptation Planning”
• “Tools for Landscape-Level Assessment and Planning”
• BSR “Analytical Tools for Assessing Business Impacts &
Dependencies Upon Ecosystem Services” report for 2013,
2014, 2015
• “Payments for Ecosystem Services: Catalog of Online Tools
and Resources” (Oregon State)
• esp-mapping.net/home (Drakou et al. 2015)
• Previous surveys (e.g. Bagstad et al. 2013)
12. Sources
• 74 “tools” in the coastal planning, adaptation, and
ecosystem services space, ranging from conceptual to
databases to engineering-level computer models to
webmaps
• 39 explicitly (29) or implicitly (10) calculated ES
• 7 of the 29 were conceptual decision-making frameworks
• 19 of the remaining 22 involved mapping, usually through
an ArcGIS plug-in
• Excluded: 1 is proprietary, 2 are still in development
• 7 out of 16 were webmaps or had a webmapping
component (!)
13. Webmaps sample
• Focused on 6 out of the 7 as one requires use of an iPad
• 1 of the 6 is explicitly coastal, 2 were forest-oriented
1. InForest
2. LandServer
3. iTree
4. Co$ting Nature (unlicensed version)
5. TNC Coastal Resilience (Gulf of Mexico)
6. InVEST Coastal Vulnerability and Habitat Risk Assessment
dashboards
14.
15.
16.
17. What kinds of things would we want
to know about these maps?
Based on interviews with decision-makers, experience in
using these tools, and the cartographic literature, I
proposed 4 factors:
1. Scale
2. Uncertainties
3. Color
4. Change
18. Results - summary
• All 6 webmaps were tools designed to inform planning decisions
• Spatial focus ranged from site-based assessment to regional/global
assessment
• Applicability varied from specific states (e.g. Virginia) to countries (US) to
anywhere on the globe
• 5/6 enabled prioritization-type decisions (where is the best place to
protect this ES?)
• 4/6 allowed scenarios (what if sea level rise was 2m?)
• 5/6 were developed by or with the involvement of nonprofits
• 4/6 ... by government entities
• 2 focused on > 5 ES, the rest < 5
• Only 1 operated on a fee model
19. Results - cartography
• Scale
• 1 webmap enabled changing the unit of analysis (e.g. from Census block
group to county)
• 1 (re)aggregated data at different zoom levels (more shortly)
• Uncertainty
• Only 2 visualized uncertainty, either by providing access to different (climate)
scenarios or displaying pre-modeled uncertainties (e.g. for sea-level rise)
• Color
• 1 allowed users to change color ramps
• 2 allowed changing transparency (to see basemap/other overlays)
• Change
• Only 2 enabled any kind of differences map (change in ES value between
now and some future)
20. Case – InVEST dashboards
• InVEST: 18 different ES models, all of which can
produce maps as outputs, at local, regional, or global
scale.
• Was an ArcGIS plug-in; now open source standalone
programs.
• Users can upload model outputs into interactive map-
based dashboards (for coastal vulnerability and habitat
risk models only)
• Both only visualize one scenario/output at a time
22. An experiment
I built a webmap that takes two or more scenarios and
allows for comparison – side by side or valued
23.
24.
25.
26. Conclusions
• Even with the models that don’t enable map
representations, the data could be mapped with some
other tool. But there are real challenges to that: time,
expertise, miscommunications.
• Interactive maps offer a solution.
• But you can’t do everything in a webmap. Tradeoffs.
• Decision-makers would be better served with tools for
comparing scenarios and change in different ways.
