METHODS



AIM program collects field data to characterize key ecosystem processes following standard soil, vegetation, 

and geomorphological protocols. The dataset presented here is structured in the following tables: (i) Plot 

Characteristics and (ii) Soil Horizon (Tables 1 and 2). The plot characteristics table contains information 

on GPS coordinates, ecological site ID, and geomorphological settings, such as slope, aspect, and landscape type. 

The soil horizon table has information on soil color, texture class, effervescence, and soil structure. The soil 

horizon table is structured by soil horizons examined in excavated pits at AIM monitoring plots. The link between 

plot characteristics and soil horizon tables is made by the “Primary Key” of the plots. 



AIM data are collected at random and targeted geographical locations. For soil morphology description, the AIM 

protocol follows the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems (Herrick et al. 2018) as 

well as the Field Book for Describing and Sampling Soils, which was developed by the National Soil Survey Center, 

Natural Resources Conservation Service (NRCS) (Schoeneberger et al. 2012). Data gatherers record slope percent, 

aspect, shape, landform, and plot location at each monitoring site. A 70 cm soil pit is typically dug near the plot 

center and soil texture, rock fragment by volume, clay percentage, and effervescence are recorded for each soil 

horizon of the pit. Soil structure is an optional observation. Where possible, recorders use the landscape position 

information along with the soil pit to identify the ecological site following the NRCS ecological site classification 

system in Ecosystem Dynamics Interpretive Tool (EDIT, i.e. an online information system for the development and 

sharing of ecological site descriptions, ecosystem state and transition models, and land management knowledge).



AIM data gatherers are required to attend training at least every three years to ensure accurate adhesion to the 

protocol. At these regional AIM trainings, data collectors learn the vegetation core methods (Kachergis et al. 2022, 

Toevs et al. 2011), along with soils and ecological sites, and data quality assurance and quality control procedures 

(McCord et al. 2022). During the soil portion of AIM trainings, data gatherers learn about ecological site concepts, 

landform identification, compass and clinometer use, how to dig a soil pit, and methods for identifying soil 

morphological characteristics. Data gatherers calibrate soil texture class identification by hand with known soil 

samples and have opportunities to practice soil identification techniques under the supervision of experienced soil 

scientists. Calibration for soil texture observation requires AIM data collectors to practice the determination of the 

texture of several soils with contrasting and known textures. Although most AIM data collectors do not have extensive 

experience in determining soil texture by hand test, the accuracy of the exact soil texture class or adjacent has been 

demonstrated to be 78% in AIM data collectors and similar populations (Salley et al. 2018). After field training, AIM 

data collectors receive additional soil support from a network of regional and national soil scientists as questions 

arise. Some states, such as Nevada and New Mexico have additional known soil texture samples for additional 

within-season practice and calibration.



The AIM program actively seeks to improve quality assurance and quality control to ensure data quality (McCord et al. 

2021, McCord et al. 2022). In addition to field training where data collectors have an opportunity to practice soil and 

geomorphology observations under supervision from experienced personnel, collectors may receive feedback from local 

soils experts throughout the season. Where possible, AIM data collectors use electronic data capture, which enables 

real-time data checks to reduce errors made in the field (Kachergis et al. 2022, McCord et al. 2022). For example, 

possible clay values are limited to boundaries of soil texture classes. AIM data are also reviewed during the field 

season and at the end of the field season by project leads and expert soil scientists who identify and correct errors 

where possible. Although the extent of this review varies by state, efforts are ongoing to produce dashboards and other 

tools to support more consistent data review and correction.