The broad-scale assessment of natural resource conditions (e.g., rangeland health, restoration needs) requires knowledge of their spatial distribution. We argue that creating a database that links state-and-transition models (STMs) to spatial units is a valuable management tool for structuring ground-based observations, management planning for landscapes, and for housing information on the responses of land areas to management actions. To address this need, we introduce a multifactor classification system based on ecological sites and STMs that is directly linked to recent concepts of vegetation dynamics in rangelands.We describe how this classification was used as a basis for creating a spatial database and maps of ecological states. We provide an example of how the classification and mapping has been applied in over 1.2 million ha of public rangelands in southern NewMexico using aerial photo interpretation supplemented with existing inventory data and rapid field assessments. The resulting state map has been used by the Bureau of Land Management: 1) to design landscape-level shrub control efforts, 2) to structure and report district-wide rangeland health assessments, and 3) to evaluate locations for energy development. We conclude by discussing options for the development of state maps and their current limitations, including the use of satellite imagery and concepts for defining states. We argue that cataloging ecological states in a spatial context has clear benefits for rangeland managers because it connects STM concepts to specific land areas. State mapping provides a means to generate and store spatially explicit data resulting from tests of the propositions in STMs and conservation practices.
A sequence of steps in state mapping within our study area, including (a) use of soil map unit polygons (white) from the Soil Survey Geographic (SSURGO) Database as a base layer, (b) manual delineation of state map unit polygons (green) residing inside soil map unit polygons, and (c) attribution of ecological site and state codes to each state map unit polygon. A state may cross soil polygon boundaries, but the original soil polygon boundaries remain in the same position and retain their original map unit attributes. We used three state codes (numbers following Generalized state classes table below) to denote the presence of multiple states in each state map unit, in order of decreasing estimated areal coverage. The state code 0 for the second and/or third digit indicates that no additional states were recorded.
Generalized state classes (and specific terms applied to ecological site types in italics) used in state mapping within Major Land Resource
Area 42 of southwestern New Mexico (after Bestelmeyer et al. 2009).
|General state||Concept for general state||Classification code||Present in ecological site types|
Grassland, Savanna, Shrubland/woodland/forest
|Site near maximum productivity, populated with full complement historically dominant species.||1||1, 2, 3|
Altered grassland, Altered savanna, Altered shrubland/woodland/forest
|Site often exhibits reduced total annual and/or forage production. If historically dominant species are present, these are fragmented and/or subdominant to less-palatable, grazing-tolerant or ruderal species. Evidence of soil erosion.||2||1, 2, 3|
|Woody plants expanding into perennial grassland become dominant over or codominant with grazing-tolerant grasses. Remnant patches of historically dominant grass species may persist in woody plant interspaces suggesting that competitive exclusion is incomplete and/ or soil degradation infrequent. Soil redistribution to shrub patches apparent. Reduced grass connectivity leads to reduced fire occurrence.||3||1|
Shrub-dominated grassland, Shrub-dominated savanna
|Soil is redistributed to and biological activity is centered beneath expanding woody plants. Scattered perennial grass cover (,10%) exists as relict patches in shrub interspaces. Grazing tolerant or ruderal grass species occur under shrubs. Evidence of interspace erosion/soil degradation, resource retention is low. Facilitation between shrubs and grasses sustains remaining grasses.||4||1, 2|
|Expansion shrubland/ woodland||Near complete loss of perennial grasses in shrub interspaces. Perennial grass species may occur as isolated plants. Woody plants are dominant. Extensive evidence of interspace erosion/soil degradation, resource retention is very low.||5||1, 2|
|Bare/annuals||Woody and perennial grass species are almost entirely absent. Annual vegetation, if present, is dominant. Extensive evidence of interspace erosion/soil degradation, resource retention is very low.||6||1, 2, 3|
Presence of exotic woody, grass, or forb species. Suggests that these invading species may come to dominate the site over time but do not yet govern ecosystem function.
Exotic species (e.g., Eragrostis lehmanniana Nees, Bromus rubens L., Pennisetum setaceum [Forssk.] Chiov, Brassica tournefortii Gouan, Tamarix ramosissima Ledeb.) present or common. Fire and/or livestock grazing preferences may favor growth and reproduction of exotic species relative to natives.
|7||1, 2, 3|
|Exotic dominated||Exotic species are common and dominate ecosystem function of site.||8||1, 2, 3|
Over the last two decades, ecosystem management strategies have increasingly focused on ecological processes and dynamics that support a variety of ecosystem services (Briske et al. 2003). These changes are evident in the increasing use of state-andtransition model (STM) concepts by land managers in the Western United States for field-level assessment of vegetation and soil condition at discrete locations (points or transects). Field-level assessments link small land areas to information in STMs, but they cannot be used for comprehensive management of large landscapes (Fuhlendorf et al. 2006; Briske et al. 2008). The shift to incorporate more information on ecological processes accompanies a growing focus on landscape scale decisionmaking (Karl and Sadowski 2005; Forbis et al. 2007; Ludwig et al. 2007). Thus, there is a need to represent information in STMs at the scale of extensive landscapes.
Because STMs are already used for land management decision-making, it is logical to identify the information within these models that can be used for input into a spatial data set. STMs use diagrams and data-supported narratives to describe the dynamics of plant communities and associated changes in ecosystem services, land uses, and management needs (Westoby et al. 1989; Briske et al. 2003; Bestelmeyer et al. 2004). STMs formally represent plant community dynamics by first characterizing discrete plant community types (community phases) that can occur at the same location, usually based on dominant plant species. Following current concepts employed by federal land management agencies, multiple community phases are classified to the same ecological state when shifts among community phases are reversible without energy-intensive interventions (e.g., via by succession; Stringham et al. 2003). Community phases are classified to distinct ecological states (i.e., alternative states) when succession alone does not result in recovery of the original community and energy-intensive interventions (restoration pathways) are needed to reverse change, or reversal is impossible (Briske et al. 2008). Thus, the classification of a plant community phase to an alternative state asserts the existence of an ecological threshold (Suding and Hobbs 2009) beyond which changes in plant community structure, rates of ecological processes, and ecosystem services are large compared to community phase shifts within states. In contrast to community phase shifts, state changes from the "reference" or historical state are typically persistent and selfreinforcing, and their effects on society are comparatively severe, such as through soil erosion or changes to fire frequency (Briske et al. 2008). Consequently, the identity of the ecological state of a land area contains especially valuable information for use in the design of management actions, assessment, and monitoring (e.g., Karl and Herrick 2010; Rumpff et al. 2011).
In order to establish the identities of ecological states present in a landscape, it is necessary to select a spatial framework upon which to build the new data set. STMs developed by the Natural Resources Conservation Service (NRCS) are explicitly linked to individual ecological sites. Ecological sites are soiland climate-based classes of land that differ in potential plant communities and responses to disturbance and, therefore, use and management (Moseley et al. 2010). Ecological sites are linked directly to soil map unit components (soil series phases) of the National Cooperative Soil Survey, effectively grouping soil components that have similar ecological characteristics. Due to limitations in the scale of soil mapping, soil mapping units represent spatially one or more ecological sites.
The relationship of STMs to soil mapping suggest that creating a spatial database of ecological state land units is achievable, although not without challenges. The first challenge is to identify single or multiple attributes from the STMs that provide the relevant information needed to represent states as spatial entities. Associated with attribute identification is the selection of a classification system with which to categorize those attributes. Second, the data needed and methods by which data are interpreted to compile the map must be determined. Finally, a suitable data delivery format must be agreed upon between the data provider and data user. These tasks require that we understand how the data will be used by natural resource professionals and the technologies available for producing and updating a spatial database and map. We must also recognize when changes in the availability of data, technologies, and concepts to produce such maps warrant novel mapping approaches.
Ecological site types recognized within Major Land Resource Area (MLRA) 42 of southwestern New Mexico.
|Ecological Site Type||Criteria||MLRA 42 Ecological Site|
|1 Historical grasslands||At potential, vegetation is dominated by dense, continuous stands of historically dominant perennial grass species.||Bottomland, Salty Bottomland, Salt meadow, Draw, Sandy, Shallow sandy, Limy, Loamy sand, Loamy, Loamy bottom, Clayey, Gyp Upland, Malpais, Swale, Gyp interdune (dry), Clay loam upland|
|2 Historical savanna||At potential, there is a significant woody component (shrubs or trees) within a continuous perennial grass matrix. Larger sizes of shrubs and trees, coupled with more age distinguish the historical savanna from the shrub invaded type 1 ecological site.||Deep sand (MLRA 42.2), Gravelly, Gravelly Loam, Gravelly sand, Hills, Limestone hills, Gyp hills, Gyp outcrop, Salt flats, Malpais, Shallow|
|3 Historical woodlands||At potential, vegetation is dominated by woody species with perennial grasses as co- or subdominant. These sites may also feature subdominant subshrubs.||Deep sand (MLRA 42.3), Sand Hills, Salt meadow, Vegetated gypsum dunes|
|Applications of the ecological state map with the Bureau of Land Management (BLM) Las Cruces District Office. a, A state map used to delineate areas for brush control applications and to stratify monitoring. Drainages and Draw ecological sites were avoided. Monitoring and assessment points (yellow dots) were distributed randomly to distinct states, and the dominant ecological site-state combination was selected for intensive monitoring (white point). b, A state map used to stratify rangeland health assessments, using lowintensity (yellow) and high intensity (white) protocols in different ecological site-state combinations.|
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