A few years ago Stephen Colbert coined a new term that resonated with everyone who has ever waded into the waters of map making and Geographic Information Systems (GIS). Truthiness. Truthiness refers to that feeling you get when you don’t have to prove you’re right about something because you just know you’re right. We could give you an example, but we feel very strongly that you know what we’re talking about – see, that’s truthiness.

   So what does truthiness have to do with GIS, mapping, or spatial scale? Everything. The improvements and increased accessibility of mapping technology along with the rising popularity of GIS have had an enormous impact on our society. Anyone with a navigation system in their car, a smartphone, or Internet access can view spatial data or make a map (e.g., Google Maps, the South Atlantic LCC’s Conservation Planning Atlas, or the USGS National Map Viewer). But just because something is mapped doesn’t make it true, and no map is 100 percent true. This is because geospatial data (information about real world objects, processes, and other elements that depict reality) cannot be represented at actual scale and are 2-D representations of our three dimensional quasi-spherical planet. All maps are models and spatial data imperfect proxies of the real world.

   Sometimes spatial data reflects the real world quite well, and when presented in a map, serves as an excellent tool to support a decision. There’s lots of truth in that truthy map. Other times maps may look truthy, but are made with outdated data sets that no longer reflect the current state of the world. Or sometimes these maps are made with data considered true at one time, which actually were never true. Like when people thought women who could swim were witches (it just felt so truthy at the time!). Yet because maps can present compelling and convincing stories, people consider them highly truthy. Just like witches.

   One place where truthiness and spatial data collide is scale. The finer scale the data, the more detail can be presented in a map and the truthier (and more accurate) it seems. But at a certain level, our minds just can’t handle the truthiness, especially if trying to look at a lot of detail over a large landscape or waterscape. Conservation practitioners and natural resource managers use maps, GIS, and spatial data analysis to make decisions to answer questions like: Which lands should be conserved and why? How should natural areas be managed? What will climate change look like here? How do these protected areas fit into the larger landscape and what contributions do they make?  Maps and spatial models are tools to support these types of questions and, ultimately, the decisions they lead to. But the utility of these tools lies in finding the appropriate match between the scale at which a decision is made and the resolution or scale of data used to provide the answer.

   When we ask questions, we tend to want perfect information so we can make confident decisions. We know this isn’t possible, and yet there’s a seductiveness in maps, a sense of certainty that what we see laid out before us is the way things really are. Our natural reaction to see a fuzzy map at a coarse scale, is to want something more – more information, more details, and more precision. So we ask for some real boss, heavy-weight data that is likely more expensive given the time and effort required to collect and create it. But that boss data may not be more. It may be wrong if the assumptions it is based on are incorrect, if the data is used in a way it was not intended for, or applied to an inappropriate question or decision (what does swimming have to do with witchcraft?).

   So what should we keep in mind when we use spatial data to make decisions? Certainly we should remember uncertainty is an inherent part of the decision making process. Will this floodplain flood? Will this species of concern use the habitat we provide? Maybe yes, if we assume that what we know continues to be true. But if a new variable is introduced such as decreased rainfall, increased urbanization, a speeding comet headed for earth, then the expected result could change. But, that won’t–and shouldn’t–stop decision makers from making decisions. While we won’t ever have a “perfect” map that tells us exactly the way things are now or in the future, we can get “good” maps and spatial data that are useful because they are reasonably accurate (if not precise) and provide information that is relevant to the decision.

   The South Atlantic LCC is hosting a series of workshops across the south starting in February 2015. During these workshops, we will ask participants to help inform our conservation future by suggesting actions given  threats of sea level rise and increasing urbanization. We will show truthy maps, such as the Conservation Blueprint Version 1.0, as tools to help people make decisions about the conservation actions they would like to see applied to the landscape. These maps will not be able to depict with 100 percent accuracy or precision a true reflection of the world. The South Atlantic is requesting the help and participation of its cooperative community in recognition that spatial data is imperfect and cannot replace the intimate and deep knowledge of biologists, ecologists, researchers, planners, and conservation practitioners in our region. Please follow these links to find a workshop near you or register.

Written by Dr. Adam Terando and Louise Vaughn