Kenneth E. Spaeth

National ecosystem assessments supported by scientific and local knowledge

An understanding of the extent of land degradation and recovery is necessary to guide land-use policy and management, yet currently available land-quality assessments are widely known to be inadequate. Here, we present the results of the first statistically based application of a new approach to national assessments that integrates scientific and local knowledge. Qualitative observations completed at over 10 000 plots in the United States showed that while soil degradation remains an issue, loss of biotic integrity is more widespread. Quantitative soil and vegetation data collected at the same locations support the assessments and serve as a baseline for monitoring the effectiveness of policy and management initiatives, including responses to climate change. These results provide the information necessary to support strategic decisions by land managers and policy makers.

A Rangeland Hydrology and Erosion Model

Soil loss rates on rangelands are considered one of the few quantitative indicators for assessing rangeland health and conservation practice effectiveness. An erosion model to predict soil loss specific for rangeland applications is needed because existing erosion models were developed from croplands where the hydrologic and erosion processes are different, largely due to much higher levels of heterogeneity in soil and plant properties at the plot scale and the consolidated nature of the soils. The Rangeland Hydrology and Erosion Model (RHEM) was designed to fill that need. RHEM is an event-based derivation of the WEPP model made by removing relationships developed specifically for croplands and incorporating new equations derived from rangeland data. RHEM represents erosion processes under disturbed and undisturbed rangeland conditions, it adopts a new splash erosion and thin sheet-flow transport equation developed from rangeland data, and it links the model hydrologic and erosion parameters with rangeland plant communities by providing a new system of parameter estimation equations based on 204 plots at 49 rangeland sites distributed across 15 western U.S. states. RHEM estimates runoff, erosion, and sediment delivery rates and volumes at the spatial scale of the hillslope and the temporal scale of a single rainfall event. Experiments were conducted to generate independent data for model evaluation, and the coefficients of determination (r2) for runoff and erosion predictions were 0.87 and 0.50, respectively, which indicates the ability of RHEM to provide reasonable runoff and soil loss prediction capabilities for rangeland management and research needs.

Gradient Analysis of Infiltration and Environmental Variables as Related to Rangeland Vegetation

Rangeland plant communities and the hydrologic cycle associated with them are multivariate in nature and are affected by many interacting biotic and abiotic components. A rotating boom rainfall simulator was used to apply rainfall in three applications (dry run, wet run, and very wet run) to paired 3.05- ¥ 10.7-m runoff plots. Representative plant community types were tall-grass, mixed-grass, short-grass prairie, and sagebrush steppe. Indirect gradient analysis was used to summarize relationships between rangeland plant communities, infiltration, and soil variables. Effective terminal infiltration rate (fe) was consistently higher in sagebrush communities. The best coefficient of determination of fe for the pooled data set (144 runoff plots, 24 sites, 10 states) was R2 = 0.45. Infiltration equations which represented rangeland community types (short-grass, mixed-grass, tall-grass, and sagebrush-grass) were more robust (R2 values > 0.71). The inclusion of endemic plant species in the model building process also improved fe rates. For example, in the tall-grass prairie, the inclusion of above-ground indiangrass (Sorghastrum nutans) biomass, an endemic native grass species, and other plants as independent variables increased regression coefficients of determination from 0.71 to 0.82.

Incorporating Hydrologic Data and Ecohydrologic Relationships into Ecological Site Descriptions

ABSTRACT The purpose of this paper is to recommend a framework and methodology for incorporating hydrologic data and ecohydrologic relationships in Ecological Site Descriptions (ESDs) and thereby enhance the utility of ESDs for assessing rangelands and guiding resilience-based management strategies. Resilience-based strategies assess and manage ecological state dynamics that affect state vulnerability and, therefore, provide opportunities to adapt management. Many rangelands are spatially heterogeneous or sparsely vegetated where the vegetation structure strongly influences infiltration and soil retention. Infiltration and soil retention further influence soil water recharge, nutrient availability, and overall plant productivity. These key ecohydrologic relationships govern the ecologie resilience of the various states and community phases on many rangeland ecological sites (ESs) and are strongly affected by management practices, land use, and disturbances. However, ecohydrologic data and relationships are often missing in ESDs and state-and-transition models (STMs). To address this void, we used literature to determine the data required for inclusion of key ecohydrologic feedbacks into ESDs, developed a framework and methodology for data integration within the current ESD structure, and applied the framework to a select ES for demonstrative purposes. We also evaluated the utility of the Rangeland Hydrology and Erosion Model (RHEM) for assessment and enhancement of ESDs based in part on hydrologic function. We present the framework as a broadly applicable methodology for integrating ecohydrologic relationships and feedbacks into ESDs and resilience-based management strategies. Our proposed framework increases the utility of ESDs to assess rangelands, target conservation and restoration practices, and predict ecosystem responses to management. The integration of RHEM technology and our suggested framework on ecohydrologic relations expands the ecological foundation of the overall ESD concept for rangeland management and is well aligned with resilience-based, adaptive management of US rangelands. The proposed enhancement of ESDs will improve communication between private land owners and resource managers and researchers across multiple disciplines in the field of rangeland management.

Application of a rangeland soil erosion model using National Resources Inventory data in southeastern Arizona

Rangelands comprise a large portion of the western United States. They are important for providing ecosystem services such as sources of clean water and air, wildlife habitat, ecosystem biodiversity, recreation, and aesthetics. The National Resources Inventory (NRI) is a primary data source for ongoing assessment of nonfederal land in the United States, including rangelands, and the data collected during an NRI assessment is typical of rangeland monitoring conducted by managers. This study outlines a methodology for using that type of monitoring data to run a rangeland hydrology and erosion model in order to estimate the relative soil erosion rates across ecosystems located in the American Southwest. The model was run on 134 NRI rangeland field locations with data collected between 2003 and 2006 in Major Land Resource Area 41, the Southeastern Arizona Basin and Range, which is a diverse ecological area of 40,765 km2 (15, 739 mi2) in the transition zone between the Sonoran and Chihuahuan deserts. Results of the study showed that the data collected was adequate to run the model and effectively assess the influence of foliar cover, ground cover, plant life forms, soils, and topography on current soil erosion rates. Results suggested that the model could be further improved with additional measured experimental data on infiltration, runoff, and soil erosion within key ecological sites in order to better quantify model parameters to reflect ecosystem changes and risk of crossing interdependent biotic and abiotic thresholds.

Extent of Kentucky Bluegrass and Its Effect on Native Plant Species Diversity and Ecosystem Services in the Northern Great Plains of the United States

Abstract Kentucky bluegrass, a nonnative species, has invaded rangelands in the United States and is currently present in most rangelands across the Northern Great Plains. Despite its accelerated expansion, the consequences of Kentucky bluegrass on the diversity of native plant species and on ecosystem services remain largely unknown. We synthesized the available data related to Kentucky bluegrass and how it affects native plant diversity and ecosystem services. We found that invasion may bring negative consequences to ecosystem services, such as pollination, habitat for wildlife species, and alteration of nutrient and hydrologic cycles, among others. To maintain the flow of ecosystem goods and services from these rangeland ecosystems, range science must adapt to the challenge of introduced, cool-season grass dominance in mixed-grass prairie. Based on our findings, we identify research needs that address ecosystem changes brought on by Kentucky bluegrass invasion and the corresponding effects these changes have on ecosystem services. We are dealing with novel ecosystems, and until we have better answers, adaptive management strategies that use the best available information need to be developed to adapt to the invasion of this pervasive invasive species. Nomenclature: Kentucky bluegrass, Poa pratensis L. Management Implications: Maintaining the flow of ecological goods and services instead of unrealistically managing for the past under changing cultural and climatic conditions (i.e., urbanization, climate change, and increased atmospheric nitrogen deposition) has become a reality. This has increased the need to implement adaptive management and new research approaches. Managing these novel ecosystems requires adjustment to timing and application of traditional management tools, such as grazing, fire, deferment, and rest, as well as bringing the collective knowledge and resources of government and educational and private sectors to bear. We need to be open to changing our traditional management practices and working on improving the flow of goods and services provided by natural areas.

A process-based hydrology submodel dynamically linked to the plant component of the simulation of production and utilization on rangelands SPUR model

Due to the great diversity and complex interactions of vegetation, soils, and climate on rangelands, process-based models designed to evaluate rangeland hydrology must include sophisticated plant and animal components that simulate changes in vegetation over space and through time. An infiltration-based submodel similar to that used in WEPP (Stone et al. (1995) USDA-Agri. Res. Service, NSERL Report No. 10, Chap. 4) was dynamically linked to the SPUR2.4 rangeland ecosystem model (Foy et al., Ecol. Model. 118 (1999) 149) to provide the framework for future model enhancement and investigation of the impacts of management on the rangeland ecosystem. Model description and documentation of model modifications are presented for SPUR 2000. A sensitivity analysis and initial test of SPUR 2000 were performed using rainfall simulation plot and micro-watershed data from Idaho sagebrush rangeland. The sensitivity analysis showed improved sensitivity of runoff and erosion to various vegetation parameters. The long-term simulations demonstrated good representation of soil water content, peak standing crop, and evapotranspiration. SPUR 2000 did a better job of predicting individual thunderstorm runoff events, and estimated 15-year runoff within 12% compared to SPUR2.4, which grossly overestimated runoff. Neither model accurately predicted sediment loss, but predicted values did demonstrate the relatively small amount of erosion that occurs from these rangelands. Neither model could reasonably estimate the snow-driven runoff that dominates these types of western rangelands. Additional research needs to explore the degree of influence that vegetation has on infiltration and runoff and how it varies for different plant communities. Development of specific Ke estimation equations based on this information will strengthen the vegetation–hydrology linkage within the model.

An ecologically based landscape classification system for monitoring and assessment of pastures

The pastures and haylands of the United States have substantial potential to contribute to national goals for sustainably increasing food production (Nelson 2012). Realizing this potential will require technologies and management strategies that are tailored to the agroecosystems of the region, are economically viable, enhance the environment, and are sufficiently flexible to adapt to climate change. Forage production is the foundation for pasture-based dairy and livestock production, including low input and organic systems, and contributes to confined animal feeding operations through hay production. Pastures often include a diverse mixture of numerous forage species, the identities of which depend on complex interactions between soil, climate, landscape, and management (Goslee and Sanderson 2010). Plant species composition affects not only plant productivity and length of grazing season, but also animal intake, production, and greenhouse gas emissions. An applied understanding of these complex relationships is lacking in current pasture classifications, even though an ecologically based framework is needed to support management practices that sustain biological integrity and enhance plant and animal productivity while minimizing adverse environmental impacts (Sanderson et al. 2011). Effective ecosystem management requires that we simplify the complex natural world enough that we can understand how to manage it while at the…

The Rangeland Hydrology and Erosion Model: A Dynamic Approach for Predicting Soil Loss on Rangelands

In this study, we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed against data collected from 23 runoff and sediment events in a shrub-dominated semiarid watershed in Arizona, USA. To evaluate the model, two sets of primary model parameters were determined using the RHEM V2.3 and RHEM V1.0 parameter estimation equations. Testing of the parameters indicated that RHEM V2.3 parameter estimation equations provided a 76% improvement over RHEM V1.0 parameter estimation equations. Second, the RHEM V2.3 model was calibrated to measurements from the watershed. The parameters estimated by the new equations were within the lowest and highest values of the calibrated parameter set. These results suggest that the new parameter estimation equations can be applied for this environment to predict sediment yield at the hillslope scale. Furthermore, we also applied the RHEM V2.3 to demonstrate the response of the model as a function of foliar cover and ground cover for 124 data points across Arizona and New Mexico. The dependence of average sediment yield on surface ground cover was moderately stronger than that on foliar cover. These results demonstrate that RHEM V2.3 predicts runoff volume, peak runoff, and sediment yield with sufficient accuracy for broad application to assess and manage rangeland systems.

Application of Ecological Site Information to Transformative Changes on Great Basin Sagebrush Rangelands

On The Ground The utility of ecological site descriptions (ESD) in the management of rangelands hinges on their ability to characterize and predict plant community change, the associated ecological consequences, and ecosystem responsiveness to management. We demonstrate how enhancement of ESDs with key ecohydrologic information can aid predictions of ecosystem response and targeting of conservation practices for sagebrush rangelands that are strongly regulated by ecohydrologic or ecogeomorphic feedbacks. The primary point of this work is that ESD concepts are flexible and can be creatively augmented for improved assessment and management of rangelands.