Philip Heilman

Remote Sensing for Grassland Management in the Arid Southwest

Abstract We surveyed a group of rangeland managers in the Southwest about vegetation monitoring needs on grassland. Based on their responses, the objective of the RANGES (Rangeland Analysis Utilizing Geospatial Information Science) project was defined to be the accurate conversion of remotely sensed data (satellite imagery) to quantitative estimates of total (green and senescent) standing cover and biomass on grasslands and semidesert grasslands. Although remote sensing has been used to estimate green vegetation cover, in arid grasslands herbaceous vegetation is senescent much of the year and is not detected by current remote sensing techniques. We developed a ground truth protocol compatible with both range management requirements and Landsats 30 m resolution imagery. The resulting ground-truth data were then used to develop image processing algorithms that quantified total herbaceous vegetation cover, height, and biomass. Cover was calculated based on a newly developed Soil Adjusted Total Vegetation Index (SATVI), and height and biomass were estimated based on reflectance in the near infrared (NIR) band. Comparison of the remotely sensed estimates with independent ground measurements produced r2 values of 0.80, 0.85, and 0.77 and Nash Sutcliffe values of 0.78, 0.70, and 0.77 for the cover, plant height, and biomass, respectively. The approach for estimating plant height and biomass did not work for sites where forbs comprised more than 30% of total vegetative cover. The ground reconnaissance protocol and image processing techniques together offer land managers accurate and timely methods for monitoring extensive grasslands. The time-consuming requirement to collect concurrent data in the field for each image implies a need to share the high fixed costs of processing an image across multiple users to reduce the costs for individual rangeland managers.

RANGES improves satellite-based information and land cover assessments in southwest United States

Because of its influence on hydrology climate, and global biogeochemical cycles, land cover change may be the most significant agent of global environmental change. Land degradation results not only from land cover conversion, but also land cover function. For example, human activities in the southwest U.S., such as grazing regimes and fire frequency, are accelerating functional changes to fragile rangeland ecosystems, causing increased proportions of shrubs in grasslands, decreases in overall vegetation density and the introduction and spread of non-native invasive species.

Targeting farms to improve water quality

Voluntary programs to improve the quality of surface and subsurface water affected by agriculture should target the farms that have an economic incentive to adopt management systems with water quality benefits. We propose a method that can identify such opportunities within a region by linking a field scale simulation model, a multiobjective decision model, and a pair of farm-scale constrained optimization models. The simulation model estimates the effect of alternative management systems on the quantities of pollutants leaving individual fields and on economic returns. The multiobjective decision model uses site specific economic and technical information to score and rank the alternative management systems. An optimization model is solved to select the set of management systems which are most economically advantageous to the farmer. A second, similar optimization model is solved to select the set of management systems of interest to society considering offsite water quality issues. Farms which have economic incentives to adopt management systems with water quality benefits can be identified and targeted by extension agents or policy makers.

Modeling climate change effects on runoff and soil erosion in southeastern Arizona rangelands and implications for mitigation with conservation practices

Climate change is expected to impact runoff and soil erosion on rangelands in the western United States. This study evaluated the potential impacts of precipitation changes on soil erosion and surface runoff in southeastern Arizona using seven General Circulation Model (GCM) models with three emission scenarios for the 2050s and 2090s. A spatial-temporal downscaling process was used to generate daily precipitation series from GCM outputs for runoff and erosion modeling with the Rangeland Hydrology and Erosion Model (RHEM). Results were compared to 1970 through 1999 conditions. Our results suggested no significant changes in annual precipitation across the region under the three emission scenarios, while projected mean annual runoff and soil loss increased significantly, ranging from 79% to 92% and from 127% to 157%, respectively, relative to 1970 to 1999. At the seasonal scale, though an increase of summer precipitation and a reduction of winter precipitation were projected, both runoff and soil loss increased significantly for both periods. The dramatic increases in runoff and soil loss were attributed to the increase in the frequency and intensity of extreme events in the study area. Predicted soil loss from shrub communities increased more than that predicted for other plant communities under the three emission scenarios. Future increases in runoff and soil erosion may accelerate the transitions of grassland to shrublands or to more eroded states due to the positive vegetation-erosion feedback. Rangeland management policies and practices should consider these changes and adapt to the increased risk of runoff and soil erosion.

Mapping Total Vegetation Cover Across Western Rangelands With Moderate-Resolution Imaging Spectroradiometer Data

Abstract Remotely sensed observations of rangelands provide a synoptic view of vegetation condition unavailable from other means. Multiple satellite platforms in operation today (e.g. Landsat, moderate-resolution imaging spectroradiometer [MODIS]) offer opportunities for regional monitoring of rangelands. However, the spatial and temporal variability of rangelands pose challenges to consistent and accurate mapping of vegetation condition. For instance, soil properties can have a large impact on the reflectance registered at the satellite sensor. Additionally, senescent vegetation, which is often abundant on rangeland, is dynamic and its physical and photochemical properties can change rapidly along with moisture availability. Remote sensing has been successfully used to map local rangeland conditions. However, regional and frequently updated maps of vegetation cover in rangelands are not currently available. In this research, we compare ground measurements of total vegetation cover, including both green and senescent cover, to reflectance observed by the satellite and develop a robust method for estimating total vegetation canopy cover over diverse regions of the western United States. We test the effects of scaling from ground observations up to the Landsat 30-m scale, then to the MODIS 500-m scale, and quantify sources of noise. The soil-adjusted total vegetation index (SATVI) captures 55% of the variability in ground measured total vegetation cover from diverse sites in New Mexico, Arizona, Wyoming, and Nevada. Scaling from the Landsat to MODIS scale introduces noise and loss of spatial detail, but offers inexpensive and frequent observations and the ability to track trends in cover over large regions. Resumen Observaciones de pastizales con sensores remotos proporcionan una vista sinóptica de la condición de la vegetación que no está disponible usando otros medios. Múltiples plataformas satelitales en operación hoy en día (e.g. Landsat, MODIS) proporcionan oportunidades para un monitoreo regional de los pastizales. Sin embargo, la variabilidad espacial y temporal de los pastizales posee retos relacionados con el mapeo de la condición de la vegetación. Por ejemplo, las propiedades del suelo pueden tener gran impacto en la reflectancia registrada por el sensor del satélite. Adicionalmente, la vegetación senescente, la cual es a menudo abundante en los pastizales, es dinámica y sus propiedades físicas y fotoquímicas pueden cambiar rápidamente debido al contenido de humedad disponible. Los sensores remotos han sido utilizados con éxito para mapear las condiciones locales de los pastizales. Sin embargo, mapas regionales y frecuentemente actualizados de la cobertura de la vegetación en pastizales no están disponibles en la actualidad. En esta investigación, se compararon medidas del suelo del total de la cobertura, incluyendo ambas coberturas la verde y la senescente, contra la observada por el satélite para desarrollar un método robusto con la finalidad de estimar el total de la cobertura de la copa de la vegetación sobre la diversa región del Oeste de estado Unidos. Se evaluaron los efectos de escala desde observaciones al ras de suelo hasta aquellas usando Landsat a una escala de 30 m, entonces a la escala de 500 m en MODIS y se cuantificaron las fuentes de variación. El índice ajustado total de vegetación (SATV) captura 55% de la variabilidad en la estimación del total de la cobertura vegetal de diversos sitios en Nuevo México, Arizona, Wyoming, y Nevada. La conversión de escala de Landsat a MODIS introduce cierto margen de error y pérdida de detalle espacial, pero ofrece observaciones baratas y frecuentes así como la capacidad de rastrear las tendencias en cobertura sobre extensas regiones.

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.

AGWA: The Automated Geospatial Watershed Assessment Tool to Inform Rangeland Management

AGWA: The Automated Geospatial Watershed Assessment Tool to Inform Rangeland Management DOI:10.2458/azu_rangelands_v33i4_goodrich

Assessing phenological change in China from 1982 to 2006 using AVHRR imagery

Long-term trends in vegetation phenology indicate ecosystem change due to the combined impacts of human activities and climate. In this study we used 1982 to 2006 Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (AVHRR NDVI) imagery across China and the TIMESAT program to quantify annual vegetation production and its changing trend. Results showed great spatial variability in vegetation growth and its temporal trend across the country during the 25-year study period. Significant decreases in vegetation production were detected in the grasslands of Inner Mongolia, and in industrializing regions in southern China, including the Pearl River Delta, the Yangtze River Delta, and areas along the Yangtze River. Significant increases in vegetation production were found in Xinjiang, Central China, and North-east China. Validation of the NDVI trends and vegetated area changes were conducted using Landsat imagery and the results were consistent with the analysis from AVHRR data. We also found that although the causes of the vegetation change vary locally, the spatial pattern of the vegetation change and the areas of greatest impact from national policies launched in the 1970s, such as the opening of economic zones and the ‘Three-North Shelter Forest Programme’, are similar, which indicates an impact of national policies on ecosystem change and that such impacts can be detected using the method described in this paper.

The Nashua agronomic, water quality, and economic dataset

This paper describes a dataset relating management to nitrogen (N) loading and crop yields from 1990 to 2003 on 36, 0.4 ha (1 ac) individually tile-drained plots on the Northeast Research and Demonstration Farm near Nashua, Iowa, United States. The field-measured data were used to calibrate the Root Zone Water Quality Model (RZWQM), and the results were summarized in a special issue of Geoderma (Ahuja and Hatfield 2007). With a comprehensive, long-term measured dataset and a model that simulates many of the components of the agricultural system, one can begin to understand the effects of management practices on N loading, crop yields, and net income to the farmers. Other researchers can use this dataset to assess the effects of management on similar tile-drained systems occurring some distance from Nashua, under alternative climates and soils, with other management systems, or with simulation models using different process representations. By integrating the understanding developed at Nashua with datasets from other highly monitored sites and other sources, progress can be made in addressing problems related to excessive N fluxes in the Mississippi Basin. An example 30-year RZWQM simulation of 18 management systems implies that significant management changes are needed to meet the goal of reducing N loads to the Gulf of Mexico by 45%. This paper and the associated datasets are intended to be used in conjunction with the analyses and process descriptions presented in the Geoderma special issue. The datasets and additional explanatory materials are available for download at http://apps.tucson.ars.ag.gov/nashua.

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.