Healthy ecosystems provide many benefits – from food and clean water to flood management and climate mitigation – and we’ve seen previously on the blog how both the human-modified and natural elements of landscapes can contribute. Our guest author today from the USGS provides a quick tour of the evolution of mapping to understand the world’s natural resources. He shares some more recent work with emerging tools in this realm, which have particular promise in spatial planning and assessment management options at various scales. What other tools might be useful for making tough decisions in landscape management? We seem to have just hit the tip of the iceberg!
The idea that maps can help us to better understand the world around us is not a new one. The U.S. Geological Survey, the agency I work for, began its efforts to fill in blank spots on the national map 135 years ago. While mapping technology has changed since then, the goal of understanding our world and its natural resources has not. The first geologists, hydrologists, and botanists did the best they could with the scientific knowledge of the day to map geologic formations, water resources, and plant communities. So while we learn to map ecosystem services, we can expect a similar trial-and-error period, as scientists test and learn best practices from each other and strive to incorporate ever-better data from today’s satellites, aerial photographs, and sensor networks.
In the world of ecosystem services, maps let us visualize regions that provide and deliver important ecosystem services to people. They can help us to better plan where we can get the most “bang for the buck” from our scarce conservation and restoration dollars. But how we draw the maps matters. The earliest and simplest ecosystem service maps assigned a single dollar value to each land cover type, drawn from libraries of economic valuation studies. Think US$100 for an acre of forest, US$1,000 for wetlands, or US$10,000 for beaches. We know that the picture that those maps paint is too unrealistically simple for sound decision making. The type of forest matters (Tropical rainforest? Temperate deciduous forest? Boreal forest?), as does the economic status, cultural values, and sheer number of people who rely on the ecosystem services that forest provides.
The next generation of ecosystem service mapping approaches that emerged relied on geographic information system (GIS) data – map layers generated from satellite or aerial photography images – of climate, soils, vegetation, or human population density. GIS data were combined using ecological production functions from scientific field experiments. These are the recipes for making a certain amount of an ecosystem service: a given soil type, slope, and tree canopy cover might yield, for example, a certain quantity of floodwater storage or groundwater recharge. These approaches were developed and applied at sites around the world, but they too had their own drawbacks.
In our work recent with the U.S. Bureau of Land Management – an agency that oversees 245 million acres of land and 700 million acres of subsurface mineral resources for uses ranging from energy and mineral extraction to recreation and wildlife conservation – five basic needs rose to the top when considering how to best measure and map ecosystem services. Ecosystem service mapping methods need to be:
1) quantifiable – able to be measured, so that we can understand the gains and losses associated with different resource management choices
2) replicable – producing the same results each time, a key attribute of any scientific model
3) credible – incorporating the best possible data and ecological production functions to yield realistic results
4) flexible – capable of being adapted to diverse geographic regions of the nation and world
5) affordable – not excessively expensive to apply.
In the last few years, scientists have developed a series of modeling and mapping tools that offer a more systematic approach to ecosystem services assessment than the case-by-case approaches of the past.
Working with the BLM, we reviewed the strengths and weaknesses of 17 ecosystem service mapping, modeling, and valuation tools and applied two tools – Artificial Intelligence for Ecosystem Services (ARIES) and Integrated Valuation of Ecosystem Service Tradeoffs (InVEST) – to a common site, the San Pedro River in southeast Arizona. Tools like these can assess tradeoffs and co-benefits between ecosystem services at landscape and watershed scales, making them useful for resource management and conservation planning. Not surprisingly, each method has its own strengths and weaknesses, and a “one-size-fits-all” approach to ecosystem service mapping is not likely realistic. ARIES and InVEST models measured similar changes in ecosystem services caused by watershed-wide urban growth, but results diverged for a site-scale ecological restoration project. Further testing of multiple ecosystem service tools at common sites around the world will help us to better understand when the choice of a certain tool is most appropriate.
When our project was being completed in Summer 2012, models remained too time-intensive to run for use in day-to-day decision making for a large agency like the BLM. However, work is underway to make these and other models easier and faster to run without sacrificing their scientific accuracy. As we continue our work with other government agencies to map and understand nature’s value, projects like this are helping to pave the way toward more widespread use of ecosystem services in economic decision-making.
Bagstad, K.J., D.J. Semmens, S. Waage, and R. Winthrop. 2013. A Comparative Assessment of Decision Support Tools for Ecosystem Services Quantification and Valuation. Ecosystem Services 5: 27-39.
Bagstad, K.J., D.J. Semmens, and R. Winthrop. 2013. Comparing Approaches to Spatially Explicit Ecosystem Service Modeling: A Case Study from the San Pedro River, Arizona. Ecosystem Services 5: 40-50.