Technology News: Digital Soil Mapping and Ecological State Change
Submitted by mrlevi21 on Mon, 04/21/2014 - 13:54
The path toward environmental sustainability and ecological resilience starts with maps.
Different land areas present different risks and opportunities, so we need to be able to classify those land areas and know where the classes occur. One new approach to this task fuses soil science and vegetation ecology by linking digital soil mapping (DSM) to state-and-transition models (STMs). DSM generally refers to any approach linking environmental data, such as Landsat reflectance or topographic variables from digital elevation models, to soil types or soil properties. New sensor technologies and statistical approaches continue to improve predictive power and resolution. Perhaps the biggest charge to the DSM community is the GlobalSoilMap project which aims to produce a uniform dataset of gridded soil properties at multiple depths for the entire globe. The objectives of the project are to provide a dataset that can be used in planning for global food production, climate change adaptation, and restoration.
Because the goal of DSM has been to map soil, many approaches attempt to minimize vegetation signals in reflectance indices in order to isolate the influence of soil properties. While this can be helpful for detecting soil properties, it overlooks a considerable amount of information provided by vegetation about soil and by the soil about vegetation. Plant-soil relationships are especially obvious in water-limited ecosystems, which cover more than 40 % of the global land area, because plants respond to subtle variation in soil properties affecting water availability.
Ecological sites exploit these relationships to describe soils and vegetation simultaneously. Ecological sites are landscape units with similar soil, topography, and climate that can support a specific suite of plant communities or land uses. STMs linked to ecological sites describe the possible ecological ‘states’ of vegetation and ‘transitions’ between states that are most likely to occur as a result of disturbance regimes (fire, climate, grazing, etc.)1 and land uses; for example, a grassland vs. an eroding shrubland. The ecological states can be mapped using the ever-increasing availability of remotely-sensed imagery2. By mapping the spatial extent of ecological states in addition to soils, we can use an understanding of vegetation change processes and ecological thresholds in management planning.
Ecological state maps provide a framework for applying specific management practices to parts of the landscape where they will be most effective: the restoration analog of “precision agriculture”. A good example is the selection of shrub-invaded grassland units for shrub removal. A simple query for ecological states that are currently shrub-invaded with minimal erosion and sufficient water holding capacity to support perennial grass could quickly identify areas that are the best candidates.
Current methods of producing ecological state maps in the Chihuahuan Desert area are time-intensive and costly because they require hand digitizing of ecological states followed by field visits. This approach is largely dependent on existing soil survey data; thus, any discrepancies in soil survey data can emerge in ecological state maps. Many soil maps in rangeland consist of individual map units that mix soil components (distinct soil types). In some cases these soil components are similar with regard to their effects on plants so they are grouped within the same ecological site; however, soil components often represent different ecological sites resulting in different management considerations; hence, uncertainty in soil maps complicates conventional state mapping efforts.
DSM can be a useful approach to state mapping because it can differentiate unique soil components independently from existing coarse-grained soil maps (Fig. 1). Combining environmental data and spatial modeling can enhance ecological state mapping with optimal field sample designs, powerful prediction models, and estimates of model uncertainty. Advanced classification algorithms can greatly reduce the time needed to produce ecological state maps because they provide a means of grouping pixels of landscape information into similar units; thereby reducing the burden of hand digitizing. DSM approaches can also be scaled up or down to meet desired management objectives which is currently difficult to do with soil survey maps. Another benefit of coupling DSM and state mapping is the identification of vegetation response thresholds related to soil properties that may inform management decisions and improve STMs.
Linking spatial patterns with landscape processes is essential to advance our understanding of ecosystem function and to interpret land conditions. DSM and ecological state mapping provide a quantitative approach to this linkage. The concept of ‘the critical zone’, or the zone between the tops of the trees to the bottom of the water table, provides us with a new way to view the interactions of soil, geology, vegetation, fauna, and the atmosphere. In spite of increasing attention to critical zone processes, there has been little effort toward mapping land to reflect these processes. Although soil maps describe the consequences of environmental interactions for soil formation3, they are limited in their ability to provide information on those interactions directly. Therefore, a system of evaluating landscapes in an integrated fashion is needed to ensure that multiple management objectives can be met to improve land stewardship. Coupled DSM and ecological state mapping is emerging as a robust approach for evaluating pattern and process feedbacks of landscapes that may reshape the way we view and manage land.
--- Matt Levi, Postdoctoral Research Scientist, Jornada Experimental Range
1 Westoby, M., Walker, B., Noy-Meir, I., 1989. Opportunistic management for rangelands not at equilibrium. Journal of Range Management 42(4), 266-274.
2 Steele, C.M., Bestelmeyer, B.T., Burkett, L.M., Smith, P.L., Yanoff, S., 2012. Spatially explicit representation of state-and-transition models. Rangeland Ecology & Management 65(3), 213-222.
3 Jenny, H. 1941. Factors of soil formation. McGraw-Hill Book Company, Inc., New York.
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DSM has great potential, not only for STM development, but also for refining Ecological Site concepts. As an ESD developer, I see the way the "sausage" is made, and I'm currently working on a few projects that use DSM principles to better tease apart the important soil differences that define ecological classifications. In fact, I see that as the first application of DSM, with state-mapping and STM development as a second step in what is ultimately an iterative process of concept development that DSM should increasingly become a part of. Unfortunately, there are not a lot of DSM folks out there, much less with an ecological bent.
I think there are more DSM folks 'out there' than we think. It seems like more and more focus is directed toward spatial modeling approaches like those employed in DSM to explain ecologically-relevant processes. While the most obvious goal of DSM is to map soil properties, there are many efforts to produce interpretive maps from those predicted soil properties. As the DSM community grows, I suspect that some folks will branch out toward more of the ecological site concepts. We recognize the utility of merging these approaches. Now comes the era of ecological state mapping and reaping the benefits of new technologies.
This is great! One thing that has always concerned me regarding the use of such tools for restoration and managment though is how soils are classified and mapped.
Ecological sites are based on the potential of an area based on a series of topo-edaphic and ecological factors. Soils are very important in determining this potential so it makes sense to use soil and soil maps as a basis. However, many areas have undergone changes that affect this potential but would still be mapped as the same soil. For example, you can have two different adjacent areas mapped as the same soils and with the same historic potential but in one of them you have lost most of the A horizon. They are mapped as the same soil, but the lack or reduction of that A horizon really affects the potential of that area. Are they still the same soil/ecological site even though the ecological processes and potential of that area have completely changed?
If someone is doing range health or paying attention to a range health evaluation matrix for a specific ESD they would notice this. If not, they would probably treat it and manage it for an unattainable potential.
Is there a way of making these distinctions explicit in ESDs and soil maps?
Alternative states or new soils?
I agree that the soil classification can be a problem, but nowadays the two soils you describe should be mapped as separate components (phases). The trick is deciding when to recognize a new ecological potential (ecological site) vs. a permanent change in state within the same ecological site. Functionally these may be the same (i.e., how you treat it going forward) but an accurate recounting of the history is the main reason to regard the eroded phase as a state of the original ecological site. Even if these cautionary tales don't matter any more locally, they may matter alot to folks in other parts of the world.
This has alot of parallels with the idea of "novel ecosystems". I think a large part of the issue involves the psychological baggage of forever regarding a place as "degraded" and hoping one day for a restoration miracle vs moving on with managing what you've got as best you can. I can see how the former must be exhausting for land managers.
I could see developing a new ecological site document that recounts the history of change from a former reference state, so that the degraded state is at once a state of one site (to recount the history) and is also a new site (to manage it for what it is).