Spatially Explicit Representation of State-and-Transition Models

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 New Mexico 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.     

Generalized and Specific State-and-Transition Models to Guide Management and Restoration of Caldenal Forests

Management impacts and natural events can produce ecosystem state changes that are difficult to reverse. In such cases, a detailed understanding of drivers, thresholds, and feedback mechanisms are needed to design restoration interventions. The Caldenal ecoregion in central Argentina has undergone widespread state change, and restoration is urgently needed, but as yet there has been no knowledge synthesis to support restoration actions. In this paper, we provide evidence-based guidelines for ecological restoration of the Caldenal forest derived from a general to local conceptual understanding of ecosystem dynamics. We develop a Caldenal forest state transition model based on a generalized fire-mediated savanna-woodland transition model. The generalized model depicts global similarities in fire-grass feedback loops as a primary factor controlling savanna to woodland transition (thicketization) in semiarid savannas around the world. An open forest is considered to be the reference state of the Caldenal that developed under a historical regime of frequent low-intensity fire. The introduction of large livestock herds in the region disrupted the positive fire-grass feedback loop and increased dispersal and recruitment of Prosopis caldenia, creating conditions for thicketization of the forest. Controlled, low-intensity fire can be used to build the resilience of an open forest state. Restoring open forest states from woodland states requires a large-scale selective thinning and pruning operation. Long-term restoration requires breaking the positive livestock-thicketization ? high-intensity fire feedback and reestablishing the positive grass-low intensity fire feedback to ensure the persistence of a restored open forest state.     

Effect of Climoedaphic Heterogeneity on Woody Plant Dominance in the Argentine Caldenal Region

Woody plant encroachment is widespread throughout drylands of the world, but rates and patterns of encroachment at the regional scale can be mediated by soil and climate. Climoedaphic properties may therefore help to explain patterns of woody plant dominance. In the Caldenal region of central Argentina, which is experiencing widespread woody plant encroachment, we used stratified and targeted inventory of vegetation and soils alongside climate data to classify vegetation states and then identify factors indicating resistance to woody plant encroachment. We found that three climoedaphic contexts differed in the degree of woody plant dominance. Sandsheet landforms had the lowest likelihood of a shrub thicket state. Within loamy soils, sites with deep soil carbonates in warmer and wetter climates were less likely to feature a shrub thicket state than sites with shallow carbonates in cooler and drier climates. These contexts serve as a basis for recognizing different ecological sites to assist mapping and prioritization of management interventions in the Caldenal region. Simple inventory-based approaches can be helpful for designing land management recommendations in other ecosystems.     

State-and-Transition Models for Heterogeneous Landscapes: A Strategy for Development and Application

Interpretation of assessment and monitoring data requires information about how reference conditions and ecological resilience vary in space and time. Reference conditions used as benchmarks are often specified via potential-based land classifications (e.g., ecological sites) that describe the plant communities potentially observed in an area based on soil and climate. State-and-transition models (STMs) coupled to ecological sites specify indicators of ecological resilience and thresholds. Although general concepts surrounding STMs and ecological sites have received increasing attention, strategies to apply and quantify these concepts have not. In this paper, we outline concepts and a practical approach to potential-based land classification and STM development. Quantification emphasizes inventory techniques readily available to natural resource professionals that reveal processes interacting across spatial scales. We recommend a sequence of eight steps for the co-development of ecological sites and STMs, including 1) creation of initial concepts based on literature and workshops; 2) extensive, low-intensity traverses to refine initial concepts and to plan inventory; 3) development of a spatial hierarchy for sampling based on climate, geomorphology, and soils; 4) stratified medium-intensity inventory of plant communities and soils across a broad extent and with large sample sizes; 5) storage of plant and soil data in a single database; 6) model-building and analysis of inventory data to test initial concepts; 7) support and/or refinement of concepts; and 8) high-intensity characterization and monitoring of states. We offer a simple example of how data assembled via our sequence are used to refine ecological site classes and STMs. The linkage of inventory to expert knowledge and site-based mechanistic experiments and monitoring provides a powerful means for specifying management hypotheses and, ultimately, promoting resilience in grassland, shrubland, savanna, and forest ecosystems.