The Automated Reference Toolset: A Soil‐Geomorphic Ecological Potential Matching Algorithm

Ecological inventory and monitoring data need referential context for interpretation. Identification of appropriate reference areas of similar ecological potential for site comparison is demonstrated using a newly developed automated reference toolset (ART). Foundational to identification of reference areas was a soil map of particle size in the control section (PSCS), a theme in US Soil Taxonomy. A 30-m resolution PSCS map of the Colorado Plateau (366,000 km²) was created by interpolating ∼5000 field soil observations using a random forest model and a suite of raster environmental spatial layers representing topography, climate, general ecological community, and satellite imagery ratios. The PSCS map had overall out of bag accuracy of 61.8% (Kappa of 0.54, p < 0.0001), and an independent validation accuracy of 93.2% at a set of 356 field plots along the southern edge of Canyonlands National Park, Utah. The ART process was also tested at these plots, and matched plots with the same ecological sites (ESs) 67% of the time where sites fell within 2-km buffers of each other. These results show that the PSCS and ART have strong application for ecological monitoring and sampling design, as well as assessing impacts of disturbance and land management action using an ecological potential framework. Results also demonstrate that PSCS could be a key mapping layer for the USDA-NRCS provisional ES development initiative.

[1]  H. Jenny,et al.  Derivation of State Factor Equations of Soils and Ecosystems , 1961 .

[2]  R. Huggett,et al.  Soil landscape systems: A model of soil Genesis , 1975 .

[3]  Chris Moran,et al.  A strategy to fill gaps in soil survey over large spatial extents: an example from the Murray-Darling basin of Australia , 2003 .

[4]  G. Nowacki,et al.  Terrestrial Ecological Unit Inventory technical guide , 2005 .

[5]  R. Amundson,et al.  On a state factor model of ecosystems , 1997 .

[6]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[7]  D. Briske,et al.  State-and-Transition Models, Thresholds, and Rangeland Health: A Synthesis of Ecological Concepts and Perspectives , 2005 .

[8]  Brandon T. Bestelmeyer National Assessment and Critiques of State-and-Transition Models: The Baby with the Bathwater , 2015 .

[9]  R. T. Belote,et al.  Assessment of rangeland ecosystem conditions, Salt Creek watershed and Dugout Ranch, southeastern Utah , 2012 .

[10]  Steven R. Archer,et al.  Spatial perspectives in state-and-transition models: a missing link to land management? , 2011 .

[11]  P. Drohan,et al.  Rapid Delineation of Preliminary Ecological Sites Applied to Forested Northern Appalachian Landscapes , 2015 .

[12]  J. McAuliffe Landscape Evolution, Soil Formation, and Ecological Patterns and Processes in Sonoran Desert Bajadas , 1994 .

[13]  G. Heuvelink,et al.  SoilGrids1km — Global Soil Information Based on Automated Mapping , 2014, PloS one.

[14]  Pierre Goovaerts,et al.  Disaggregation of legacy soil data using area to point kriging for mapping soil organic carbon at the regional scale. , 2012, Geoderma.

[15]  Jacob Cohen A Coefficient of Agreement for Nominal Scales , 1960 .

[16]  H. Monger,et al.  Soil classification in arid lands with Thematic Mapper data , 2002 .

[17]  James Thompson,et al.  Semi-Automated Disaggregation of a Conventional Soil Map Using Knowledge Driven Data Mining and Random Forests in the Sonoran Desert, USA , 2014 .

[18]  B. Schröder,et al.  Spatial disaggregation of complex soil map units: A decision-tree based approach in Bavarian forest soils , 2012 .

[19]  Elisabeth N. Bui,et al.  Extracting soil-landscape rules from previous soil surveys , 1999 .

[20]  N. Odgers,et al.  Fuzzy disaggregation of conventional soil maps using database knowledge extraction to produce soil property maps , 2012 .

[21]  James M. Omernik,et al.  Ecoregions of the Conterminous United States: Evolution of a Hierarchical Spatial Framework , 2014, Environmental Management.

[22]  T. Nauman Digital Soil-Landscape Classification for Soil Survey using ASTER Satellite and Digital Elevation Data in Organ Pipe Cactus National Monument, Arizona , 2009 .

[23]  B. Minasny,et al.  On digital soil mapping , 2003 .

[24]  John B. Wright,et al.  Ecological services to and from rangelands of the United States , 2007 .

[25]  A-Xing Zhu,et al.  Automated soil inference under fuzzy logic , 1996 .

[26]  A. Zhu,et al.  Updating Conventional Soil Maps through Digital Soil Mapping , 2011 .

[27]  Mark E. Miller,et al.  Alternative states of a semiarid grassland ecosystem: implications for ecosystem services , 2011 .

[28]  J. Neyman,et al.  Principles of the mathematical theory of correlation , 1939 .

[29]  Philip E. Dennison,et al.  Inductively mapping expert-derived soil-landscape units within dambo wetland catenae using multispectral and topographic data , 2009 .

[30]  L. A. Goodman,et al.  Measures of association for cross classifications , 1979 .

[31]  Bridget A. Emmett,et al.  Natural Capital, Ecosystem Services, and Soil Change: Why Soil Science Must Embrace an Ecosystems Approach , 2012 .

[32]  Curtis J. Talbot,et al.  The Natural Resources Conservation Service Land Resource Hierarchy and Ecological Sites , 2016 .

[33]  Michael J. Oimoen,et al.  The National Elevation Dataset , 2002 .

[34]  J. Herrick,et al.  Making soil health a part of rangeland management , 2016, Journal of Soil and Water Conservation.

[35]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[36]  Brady W. Allred,et al.  National-scale assessment of ecological content in the world's largest land management framework , 2013 .

[37]  Jochen Schmidt,et al.  Fuzzy land element classification from DTMs based on geometry and terrain position , 2004 .

[38]  Suming Jin,et al.  Completion of the 2011 National Land Cover Database for the Conterminous United States – Representing a Decade of Land Cover Change Information , 2015 .

[39]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[40]  B. Bestelmeyer,et al.  Soil Processes and Properties That Distinguish Ecological Sites and States , 2010 .

[41]  D. Tarboton A new method for the determination of flow directions and upslope areas in grid digital elevation models , 1997 .

[42]  R. D. Ramsey,et al.  Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework : A case study of the Southwest Regional Gap Analysis Project (SWReGAP) , 2007 .

[43]  Z. Libohova,et al.  Harmonization of legacy soil maps in North America: Status, trends and implications for digital soil mapping efforts , 2012 .

[44]  M. K. Gillespie,et al.  A Cross-Taxonomic Comparison of Insect Responses to Grassland Management and Land-Use Legacies , 2011 .

[45]  Budiman Minasny,et al.  Methodologies for Global Soil Mapping , 2010 .

[46]  Simon E. Cook,et al.  Use of airborne gamma radiometric data for soil mapping , 1996 .

[47]  Chris Moran,et al.  Disaggregation of polygons of surficial geology and soil maps using spatial modelling and legacy data , 2001 .

[48]  Jonathan D. Phillips,et al.  Divergent evolution and the spatial structure of soil landscape variability , 2001 .

[49]  Jeffrey E. Herrick,et al.  Experiences in monitoring and assessment of sustainable land management , 2011 .

[50]  Albert Rango,et al.  Hierarchical analysis of vegetation dynamics over 71 years: soil-rainfall interactions in a Chihuahuan Desert ecosystem. , 2012, Ecological applications : a publication of the Ecological Society of America.

[51]  Jeffrey E. Herrick,et al.  Consistent Indicators and Methods and a Scalable Sample Design to Meet Assessment, Inventory, and Monitoring Information Needs Across Scales , 2011 .

[52]  James Thompson,et al.  Pedoecological Modeling to Guide Forest Restoration using Ecological Site Descriptions , 2015 .

[53]  James Thompson,et al.  Ghosts of the forest: Mapping pedomemory to guide forest restoration , 2015 .

[54]  T. W. Nauman,et al.  Fuzzy disaggregation of conventional soil maps using database knowledge extraction to produce soil property maps : T.W. Nauman , 2012 .

[55]  J. H. Schuenemeyer,et al.  Statistical Methods For Geographers , 1986 .

[56]  Jeffrey E. Herrick,et al.  State-and-Transition Models for Heterogeneous Landscapes: A Strategy for Development and Application , 2009 .

[57]  B. Bestelmeyer,et al.  Grand Challenges for Resilience-Based Management of Rangelands , 2012 .

[58]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[59]  Wei Sun,et al.  Disaggregating and harmonising soil map units through resampled classification trees , 2014 .

[60]  C. Perry,et al.  Regional Approach to Soil Property Mapping using Legacy Data and Spatial Disaggregation Techniques , 2010 .

[61]  R. D. Ramsey,et al.  Digitally Mapping Gypsic and Natric Soil Areas Using Landsat ETM Data , 2007 .

[62]  Eric F. Wood,et al.  POLARIS: A 30-meter probabilistic soil series map of the contiguous United States , 2016 .

[63]  Sabine Grunwald,et al.  Multi-criteria characterization of recent digital soil mapping and modeling approaches , 2009 .

[64]  W. Getz,et al.  Monitoring the Impact of Grazing on Rangeland Conservation Easements Using MODIS Vegetation Indices ☆ , 2015 .

[65]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[66]  Travis W. Nauman,et al.  Semi-automated disaggregation of conventional soil maps using knowledge driven data mining and classification trees , 2014 .

[67]  Paulo Pereira,et al.  Soil mapping, classification, and pedologic modeling: History and future directions , 2016 .

[68]  B. T. Bestelmeyera,et al.  An integrated framework for science-based arid land management , 2006 .

[69]  Ilyes Jenhani,et al.  Disaggregation of component soil series on an Ohio County soil survey map using possibilistic decision trees , 2014 .

[70]  Sabine Grunwald,et al.  Digital Soil Mapping and Modeling at Continental Scales: Finding Solutions for Global Issues , 2011 .

[71]  H. Jenny,et al.  The soil resource. Origin and behavior , 1983, Vegetatio.

[72]  S. Nusser,et al.  The National Resources Inventory: a long-term multi-resource monitoring programme , 1997, Environmental and Ecological Statistics.

[73]  Anònim Anònim Keys to Soil Taxonomy , 2010 .

[74]  P. A. Burrough,et al.  Multiscale sources of spatial variation in soil. I: The application of fractal concepts to nested levels of soil variation , 1983 .

[75]  M. Duniway,et al.  Rangeland Monitoring Reveals Long-Term Plant Responses to Precipitation and Grazing at the Landscape Scale☆ , 2016 .

[76]  D. Browning,et al.  Digital Soil Mapping in the Absence of Field Training Data: A Case Study Using Terrain Attributes and Semiautomated Soil Signature Derivation to Distinguish Ecological Potential , 2011 .