9Research Branch

Technical Bulletin 1998-3E

Broad-scale Assessment ofAgricultural Soil Quality

in Canada UsingExisting Land Resource

Databases and GIS

K.B. MacDonald and F. WangSoil Program at Guelph

Greenhouse andProcessingCrop Research Centre

Agriculture and AgriFood Canada

W.R. Fraser and G.W. LelykLand Resource Unit

Brandon Research CentreAgriculture and AgriFood Canada

Canada

Broad-scale Assessment of Agricultural SoilQuality in Canada Using Existing Land

Resource Databases and GIS

_

K.B. MACDONALD AND F. WANGSoil Program at Guelph

Greenhouse and Processing Crop Research Centre, Research BranchAgriculture and Agri-Food Canada

70 Fountain StreetGuelph, ON NIH 3N6

W.R. FRASER AND G.W. LELYKLand Resource Unit

Brandon Research Centre, Research BranchAgriculture and Agri-Food Canada

Ellis Building, University of ManitobaWinnipeg, MB R3T 2N2

Technical Bulletin 1998-3E

Research BranchAgriculture and Agri-Food Canada

Hardcopy of this publication could be obtained from:

Soil Program at Guelph, Greenhouse and Processing Crop Research CentreResearch Branch, Agriculture and Agri-Food Canada70 Fountain Street E .Guelph, ON NIH 3N6

Tel: 519-8262086Fax: 519-8262090Email: macdonaldb@em.agr.ca

The hyper-text version of this document is available at AFFC's intranet:

http : //l42.61 .197.4/olru/sq/

@Minister of Public Works and Government Services Canada 1998Cat . No. A54-8/1998-3EISBN 0-662-26774-5

TABLE OF CONTENTS

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viExecutive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .viiSommaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

1.0 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12.0 Conceptual Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.1 Current Understanding on Soil Quality : An Overview

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.2 A Hierarchical Framework of Soil Quality Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.3 Concepts of Inherent Soil Quality (ISQ) and Soil Quality Susceptibility (SQS)

. . . . . . . . . 62.4 Basic Procedures of Soil Quality Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102.5 Approaches Specific to This Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113.0 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .133.1 GIS System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .133.2 Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .133.3 Spatial Framework

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153.4 ISQ Rating Procedures

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163.5 SQS Indicators and Spatial Identification

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264.0 Results and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294.1 Major Agricultural Regions of Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294.2 Current Status of Inherent Soil Quality

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304.3 ISQ and Potential Land Supply

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474.4 Areas Susceptible to Change in Soil Quality

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 494.5 Implications of Changing Land Use and Management Practices on Soil Quality . . . . . . . 56

5.0 Discussion

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .605 .1 The Sensitivity of ISQ Procedures

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 605.2 Future Applications of ISQ and SQS Procedures

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 676.0 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70

Appendix 1 Key Terms and Acronyms

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Appendix 2 Descriptions of Soil and Landscape Data Attributes (items) from

CanSIS/NSDB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77Appendix 3 A Detail Description of ISQ92 Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82Appendix 4 A Detail Description of ISQ94 Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

List of Figures

Figure 2-1 Multi-dimensional perspective on soil quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3Figure 2-2 Soil health/quality as an indicator of environmental/ecosystem health . . . . . . . . . . . . 4Figure 2-3 A hierarchical framework for soil quality assessment . . . . . . . . . . . . . . . . . . . . . . . . 5

Figure 2-4 Soil Quality change in relation to soil modifying processes andland use and management practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Figure 2-5 Kinds and direction of soil quality changes and research approaches . . . . . . . . . . . . 9Figure 2-6 Basic steps of soil quality assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Figure 3-1 Illustration of the spatial framework for soil quality assessment

and reporting in Canada

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Figure 3-2 The organization of ISQ procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Figure 3-3 Levels of ISQ generalization and mapping/reporting . . . . . . . . . . . . . . . . . . . . . . . . 24Figure 3-4 GIS procedures to identify and map SQS indicators

. . . . . . . . . . . . . . . . . . . . . . . . 28Figure 4-1 The major agricultural regions of Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Figure 4-2 Regional differences of ISQ ratings in the Prairies provinces

. . . . . . . . . . . . . . . . . 33Figure 4-3 Inherent soil quality (ISQ) element map of the Prairies provinces (a,b,c,d,e)

. . . . . 34Figure 4-4 Regional differences of ISQ ratings in the Mixedwood Plains Ecozone . . . . . . . . . . 41Figure 4-5 Inherent soil quality (ISQ) element map of the Mixedwood

Plains Ecozone (a,b,c,d,e)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42Figure 4-6 Soil quality susceptibility (SQS) map of the Prairies Provinces (a,b) . . . . . . . . . . . . 52Figure 4-7 Soil quality susceptibility (SQS) map of the Mixedwood Plains Ecozone (a,b) . . . . 54Figure 4-8 Changes of selected SQS indicators of land use and management

in the Prairies provinces from 1981 to 1991

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58Figure 4-9 Changes of selected SQS indicators of land use and management

in the Mixedwood Plains Ecozone from 1981 to 1991

. . . . . . . . . . . . . . . . . . . . . . 59Figure 5-1 Comparison of the results of ISQ92 and ISQ94 in the Prairies provinces . . . . . . . . . 61Figure 5-2 Location of the scale sensitivity test area in Southern Manitoba

. . . . . . . . . . . . . . . 63Figure 5-3 Comparison of ISQ94 ratings at different scales in Southern Manitoba . . . . . . . . . . 63

List of Tables

Table 2-1 Inherent soil quality elements for crop production . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Table 2-2 Aspects of soil quality susceptibility to change . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Table 3-1 Data sources for broad-scale assessment of soil quality in Canada . . . . . . . . . . . . . 14Table 3-2 . Rating scale of ISQ nutrient retention element . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20Table 3-3 Rating scale of ISQ physical rooting conditions element . . . . . . . . . . . . . . . . . . . . . 20Table 3-4 Rating scale of ISQ chemical rooting conditions element . . . . . . . . . . . . . . . . . . . . . 21Table 3-5 Matrix for determining rating points of ISQ overall chemical

rooting conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22Table 3-6 Typical criteria for indicator selection

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26Table 3-7 Selected SQS indicators and the criteria and threshold values

. . . . . . . . . . . . . . . . . 27Table 4-1 Proportion of area ISQ rated of total land area in the Prairies provinces . . . . . . . . . . 31Table 4-2 Summary of ISQ assessment in the Prairies provinces

. . . . . . . . . . . . . . . . . . . . . . . 32Table 4-3 Proportion of area ISQ rated of total land area in the Mixedwood Plains Ecozone . . 39Table 4-4 Summary of ISQ assessment in the Mixedwood Plains Ecozone

. . . . . . . . . . . . . . . 39Table 4-5 Potential land supply based on ISQ assessment in comparison to

actual land use in the Prairies provinces

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

iv

Table 4-6 Potential land supply based on ISQ assessment in comparison toactual land use in the Mixedwood Plains Ecozone

. . . . . . . . . . . . . . . . .. . . . . . . . . 48

Table 4-7 Proportion of susceptible areas of soil quality change in the Prairies provinces . . . . . 50Table 4-8 Proportion of susceptible areas of soil quality change in the

Mixedwood Plains Ecozone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51Table 4-9 Change in selected SQS indicators in the Prairies provinces from 1981 to 1991 . . . . 56Table 4-10 Change in selected SQS indicators in the Mixedwood Plains

Ecozone from 1981 to 1991

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Table 4-11 Conservation tillage and no-till practices used in the Prairies provinces (1991) . . . . 57Table 4-12 Conservation tillage and no-till practices used in the Mixedwood Plains

Ecozone(1991) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57Table 5-1 Comparison of ISQ94 and ISQ92 ratings in the Prairies provinces . . . . . . . . . . . . . . 62Table 5-2 Comparison of ISQ94 ratings at different scales in Southern Manitoba . . . . . . . . . . . 64Table 5-3 Comparison of detailed and broad scale ISQ ratings for selected

SLC polygons in Southern Manitoba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66Table A2-1 SLC (version 1 .0) DOMinant and SUBdominant file attributes . . . . . . . . . . . . . . . 77Table A2-2 SLC (version 1 .0) Component (CMP) file attributes

. . . . . . . . . . . . . . . . . . . . . . 78Table A2-3 SLC (version 1 .0) Carbon Layer (CLYR) file attributes . . . . . . . . . . . . . . . . . . . . 78Table A2-4 DSM Soil Map Unit File (SMUF) attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Table A2-5 Soil Name File (SNF) attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Table A2-6 Soil Layer File (SLF) attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80Table A3-1 Areas or soils excluded and the thresholds used in ISQ92 procedures . . . . . . . . . . 82Table A3-2 Point system of ISQ92 rating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Table A3-3 The rating criteria of selected ISQ attribute used in ISQ92 procedures

. . . . . . . . . 84Table A4-1 Data attributes used in ISQ94 procedures

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86Table A4-2 Areas or soils excluded and the thresholds used in ISQ94 procedures . . . . . . . . . . 87Table A4-3 Root restrictions and thresholds for layer exclusions

. . . . . . . . . . . . . . . . . . . . . . . 87Table A4-4 ISQ94 program variables for ISQ element rating . . . . . . . . . . . . . . . . . . . . . . . . . . 88Table A4-5 Matrix for determining rating points of ISQ aeration porosity . . . . . . . . . . . . . . . . 90Table A4-6 Relationship between available water holding capacity and surface texture . . . . . . 90Table A4-7 Matrix for determining rating points of ISQ available water holding capacity . . . . . 91Table A4-8 Rating scale of ISQ nutrient retention element . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92Table A4-9 Rating scale of ISQ physical rooting conditions element

. . . . . . . . . . . . . . . . . . . . 92Table A4-10 Rating scale of ISQ chemical rooting conditions element . . . . . . . . . . . . . . . . . . . 93Table A4-11 Matrix for determining rating points of ISQ overall chemical rooting conditions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .94

ACKNOWLEDGEMENTS

This research was mainly funded by the Soil Quality Evaluation Program (SQEP) through theNational Soil Conservation Program (NSCP, http://res .agr.ca/lond/pmrc/nscp/ ) during 1991-1993 . The State of the Environment Directorate, Environment Canada provided funds for SoilQuality Reporting in the Prairies in 1994 . The continuous development and improvement of theprototype system for assessing the inherent soil quality (ISQ) during 1995-96 was partially fundedby the Canada-Ontario Agriculture Green Plan (http://res .agr.ca/lond/) .

The authors also wish to acknowledge people providing comments for development of theconceptual framework, particularly Drs. Don Acton and Wayne Pettapiece and early teammembers Mr. Andy Moore and Ian Jarvis .

EXECUTIVE SUMMARY

Under the National Soil Quality Evaluation Program (SQEP), a series of research projects wereconducted on soil and environmental quality in Canada . The main research findings have beensummarized in a series of technical reports and a 1995 publication, The Health of Our Soils . TheSQEP project to develop and demonstrate a system of soil quality assessment at national andregional scales is documented in this technical bulletin.

The bulletin presents a conceptual framework which defines aspects of soil quality as either staticassessments, termed inherent soil quality (ISQ), as a quasi-dynamic assessments termed soilquality susceptibility to change (SQS), or as actual soil quality change (SQC). It is not feasible tomeasure actual soil quality change at broad regional and national scales and current process-basedmodels are not adapted to broad scale operation . Consequently, this study concentrates on thedevelopment of GIS procedures to assess ISQ and SQS regionally and nationally . Theframework is used to outline the steps needed to conduct soil quality assessments (ISQ and SQS).The capability is demonstrated and results are presented in map and tabular form for the majoragricultural regions of Canada. At a very general level the results are compared to other measuresof agricultural land use and quality . The sensitivity of the assessments to different data sources isevaluated .

Soil quality is a composite expression of properties and processes that interact to determine itsability to perform a number of basic functions, such as supporting crop production, buffering theenvironment from nutrients and other chemicals and partitioning water and gases . The inherentaspects of soil quality function are quite complex and have been simplified into components or,elements for assessment. Within the crop production function, four basic elements of soil qualitywere defined ; (i) available porosity, (ii) nutrient retention, (iii) physical rooting conditions, and(iv) chemical rooting conditions . Attributes were selected from standard land resource data bases,and used in interpretive algorithms developed within the project to estimate each individual soilquality element .

A series of indicators related to conditions of soil, landscape, land use and management practiceswere used to assess SQS. Indicators include attributes such as ; shallow topsoil, low organiccarbon content of topsoil, steep slope, highly erodible surface texture, high intensity land use, andland management practices which expose the soil to degradation, . GIS procedures were used toassist in the spatial identification and mapping SQS indicators .

ISQ and SQS assessment procedures were demonstrated in the major agricultural regions ofCanada - the Prairies and the Boreal Plains ecozones in western Canada and the Mixed WoodPlains ecozone in eastern Canada. These three ecozones include about 91% of the farmland and95% of the cultivated land of Canada. Overall results from ISQ assessments indicate thatapproximately 37% of the land area in the 3 prairie provinces meet the climatic and soilrequirements for spring seeded cereal crop production . In eastern Canada, approximately 83% ofthe land area within the Mixed Wood Plains ecozone in southern Ontario and Quebec meet the

climatic and soil criteria for cereal crop production.

The ISQ assessment indicates that a relatively large proportion of agricultural soils in the threeecozone are in `Good' or `Good to Moderate' rating range . In the Prairies and the Boreal Plainsecozones, about 70-80% of the land area was rated `Good' or `Good to Moderate' for all fourISQ elements . Marginal ("Poor") ISQ ratings varied from 3 to 11% for the different ISQelements . At the overall ISQ rating level, about 46% received `Good' or `Good to Moderate'ratings, about 34% were rated as `Moderate to poor' and about 19% were rated as 'Poor' .

The estimates of potential land supply by ISQ methods in the prairie provinces and the MixedWood Plains were close to the estimates of the first 4 agricultural capability classes of the CanadaLand Inventory (CLI) .

Comparing these figures to the actual land use as reported in the 1991Census of Agriculture shows that nearly 85% of land suitable for agricultural use is currentlybeing farmed .

The SQS assessment indicated that for most provinces, the steep slope indicator identified a smallbut significant proportion of the potential agricultural land (9 - 15%) except for Quebec where theagricultural area was predominantly marine and fluvial sediments . Western Canadian soils wereformed under grassland vegetation, with high organic carbon content in the surface horizon.eastern Canadian soils were formed under forest vegetation and have lower organic carboncontent in the native state . They also have a longer history of intensive crop production. Loworganic carbon content of the topsoil is a more serious problem in eastern Canada than in westernCanada . Soil quality susceptibility to change due to land use and management factors (asrecorded in the 1991 Census of Agriculture) varies widely between and within the differentecozones . A large proportion of the agricultural area in the Mixedwood Plains ecozone,especially in southwestern Ontario, is susceptible to soil quality change as it is predominantly inannual crops, with intensive row cropping . In the Prairies and Boreal Plains ecozones of westernCanada, row cropping is insignificant, but approximately 3-7% of the farmland area has a highpercentage (>30% of farmland) in summerfallow . Most of the summerfallow area occurs in theportion of the Prairies ecozone, where soil moisture is limiting for annual dryland cropproduction, and summerfallow has.traditionally been used as part of the crop rotation . At greatestpotential risk are the areas identified as susceptible to soil quality degradation due to bothbiophysical conditions and land use and management practices ; these represent about 2-3% of thePrairies and Boreal Plains ecozones, and 7- 9% of the Mixedwood Plains ecozone.

The soil quality assessment procedures developed in this project are defined generically so thatthey can be readily adapted to other quality functions or refined with more precise definitions toapply to specific crop types or more detailed map scales with more detailed land resourcedatabases . ISQ procedures can be used in conjunction with process based models to evaluatesequential changes in soil quality as a result of model predictions of altered soil conditions andproperties .

SOMMAIRE

Dans le cadre du Programme national d'évaluation de la qualité des sols, on a mené une série detravaux de recherche sur la qualité des sols et de l'environnement au Canada. Les principalesconclusions des recherches ont été résumées dans une série de rapports techniques et unepublication, parue en 1995, intitulée La santé de nos sols . Le présent bulletin technique a trait auprojet de démonstration d'un système d'évaluation de la qualité des sols à l'échelle régionale etnationale .

Nous présentons un cadre conceptuel qui définit les différents aspects de la qualité des sols sous laforme d'évaluations statiques (qualité intrinsèque des sols), d'évaluations quasi dynamiques(sensibilité de la qualité des sols au changement) ou en fonction du changement réel de la qualitédes sols . E n'est pas possible de mesurer le changement réel de la qualité des sols à l'échellerégionale et nationale, et les modèles actuels, basés sur des processus, ne sont pas adaptés à desopérations à grande échelle . En conséquence, l'étude a consisté principalement à élaborer desméthodes SIG pour l'évaluation de la qualité intrinsèque des sols et de la sensibilité de la qualitédes sols au changement à l'échelle régionale et nationale. Le cadre conceptuel sert à indiquer dansles grandes lignes les étapes nécessaires d'une évaluation de la qualité des sols . Des cartes et destableaux démontrent la capacité du système et présentent les résultats pour les grandes régionsagricoles du Canada. Les résultats sont comparés, à un niveau très général, à d'autres mesures del'utilisation et de la qualité des terres agricoles . II est également question de l'influence dedifférentes sources de données et échelles cartographiques sur les évaluations .

La qualité des sols repose sur un ensemble de propriétés et de processus en interaction quidéterminent la capacité des sols à remplir un certain nombre de fonctions de base, comme laproduction végétale, l'effet tampon sur l'environnement des points de vue chimique et biologiqueet la séparation de l'eau et de gaz . Les paramètres de qualité des sols sont très variés et trèscomplexes ; ils ont été simplifiés sous la forme de composantes ou d'éléments aux fins desévaluations . En ce qui touche la fonction culturale, quatre éléments de base de la qualité des solsont été définis : i) porosité disponible, ii) rétention des substances nutritives, üi) conditionsphysiques d'enracinement et iv) conditions chimiques d'enracinement. Des attributs tirés de basesde données standard sur les ressources en terres ont été utilisés dans des algorithmesd'interprétation élaborés dans le cadre du projet pour évaluer chaque élément de la qualité dessols .

On a utilisé une série d'indicateurs liés aux conditions des sols, aux paysages et aux pratiquesd'aménagement et d'utilisation des terres pour évaluer la sensibilité de la qualité des sols auchangement. Ces indicateurs sont les suivants : faible profondeur de la couche arable, faible teneuren carbone organique, forte inclinaison, textures superficielles très érodables, utilisation trèsintensive des terres et pratiques d'aménagement favorisant la dégradation des sols . L'identification

spatiale et la cartographie des indicateurs de sensibilité de la qualité des sols au changements'appuyaient sur des méthodes SIG .

On a fait la démonstration des méthodes d'évaluation de la qualité intrinsèque des sols et de lasensibilité de la qualité des sols au changement dans les grandes régions agricoles du Canada, soitdans les écozones des Prairies et des Plaines boréales dans l'Ouest et l'écozone des Plaines à forêtsmixtes dans l'Est . Ces trois écozones renferment environ 91 % des terres agricoles et 95 % desterres cultivées du Canada. Selon les résultats généraux des évaluations de la qualité intrinsèquedes sols, environ 37 % des terres des trois provinces des Prairies présentent les conditionsclimatiques et pédologiques nécessaires à la production de céréales semées au printemps . Dansl'est du pays, quelque 83 % des terres de l'écozone des Plaines à forêts mixtes, dans le sud del'Ontario et du Québec, répondent aux conditions climatiques et pédologiques nécessaires à laproduction de céréales .

L'évaluation de la qualité intrinsèque des sols révèle qu'une proportion relativement grande dessols agricoles des trois écozones entrent dans les catégories de qualité « Bonne» ou « Bonne àmoyenne ». Dans les écozones des Prairies et des Plaines boréales, environ 70 à 80 % des terressont classées « Bonne » ou « Bonne à moyenne » pour tous les éléments évalués . De 3 à 11 % desterres entrent dans la catégorie de qualité marginale « Mauvaise » pour ces mêmes éléments . Dansl'ensemble du Canada, environ 46 % des terres appartiennent à la catégorie « Bonne » ou « Bonneà moyenne », environ 34 % à la catégorie « Moyenne à mauvaise » et environ 19 % à la catégorie« Mauvaise » .

Les estimations du bassin de terres à potentiel agricole par les méthodes d'évaluation de la qualitéintrinsèque des sols dans les provinces des Prairies et de l'écozone des Plaines à forêts mixtesétaient proches des estimations propres aux quatre premières catégories possibiltés agricoles dessols de l'Inventaire des terres du Canada . Si l'on compare ces données aux données sur l'utilisationdes terres du Recensement de l'agriculture de 1991, on constate que près de 85 % des terres àpotentiel agricole sont cultivées actuellement .

Selon l'évaluation de la sensibilité de la qualité des sols au changement, une petite mais néanmoinsimportante partie des terres à potentiel agricole (de 9 à 15 %) dans la plupart des provincesprésentaient une forte inclinaison, alors que cette caractéristique était un facteur moins limitantdans les régions dominées par les sédiments marins et fluviaux de l'écozone des Plaines à forêtsmixtes au Québec. Les terres de l'Ouest canadien étaient constituées de prairies aux sols à forteteneur en carbone organique dans les horizons de surface . Les terres de l'Est étaient couvertes deforêts et les sols avaient une teneur initiale en carbone organique moindre dans les horizons desurface . La sensibilité de la qualité des sols au changement attribuable à l'utilisation et àl'aménagement des terres (selon le Recensement de l'agriculture de 1991) varie grandement danset entre les différentes écozones . Dans une grande proportion des zones agricoles de l'écozone desPlaines à forêts mixtes, surtout dans le sud-ouest de l'Ontario, la qualité des sols est sensible auchangement vu que ceux-ci produisent en majeure partie des cultures annuelles et font l'objetd'une . culture sarclée intensive. Dans les écozones des Prairies et des Plaines boréales, ce type de

culture est quasi inexistant; néanmoins, un grand nombre d'agriculteurs (plus de 30 % des terresagricoles) pratiquent la culture sur jachères dans environ 3 à 7 % des zones agricoles . La plupartdes terres mises en jachère se trouvent dans la partie de l'écozone des Prairies où la teneur en eaudu sol limite les cultures sèches annuelles ; dans cette région, la rotation des cultures intègre lamise en jachère depuis longtemps . Les zones dont les sols sont susceptibles de se dégrader à causedes conditions biophysiques ainsi que de (utilisation et de l'aménagement des terres sont exposéesà un plus grand risque ; elles représentent de 2 à 3 % des terres des écozones des Prairies et desPlaines boréales et de 7 à 9 % de celles de l'écozone des Plaines à forêts mixtes .

Comme les méthodes d'évaluation de la qualité des sols mises au point dans le cadre du projetsont générales, elles peuvent être adaptées à d'autres fonctions de qualité ou raffinées par l'ajoutde définitions plus précises pour être appliquées à des types de culture particuliers ou à deséchelles cartographiques plus fines avec des bases de données plus détaillées sur les ressources enterres . Les méthodes d'évaluation de la qualité intrinsèque des sols et de la sensibilité de la qualitédes sols au changement peuvent être employées de concert avec des modèles basés sur desprocessus pour l'évaluation de changements successifs de la qualité des sols quand ces modèlesprévoient l'altération des conditions et des propriétés de sols .

1.0 Introduction

In the past, experts who carried out broad regional and national assessments of soil/land quality(for example, the Canada Land Inventory) relied on their personal knowledge to compensate forgaps in data and inconsistencies between geographical areas . However, current assessmentsshould be carried out in a documented, reproducible way with a minimum of subjectivity . Thedevelopment of digital soil and land resource databases, such as the Canadian Soil InformationSystem and National Soil DataBase (CanSIS/NSDB, http://res .agr.ca/ecorc/program3/cansis/ ) ,and the wide use of geographical information system (GIS) technology make it possible todevelop procedures for such automated and reproducible assessments .

The characterization of soil quality and degradation is a basic agri-environmental issue in Canadaas it is in many other nations . It has been the focus of much recent attention and research efforts(Conte et al ., 1982 ; Nowland, 1987 ; Nowland and Halstead, 1986 ; Science Council of Canada,1986 ; Mathur and Wang, 1991 ; Acton 1991a) . During 1989-1993, the National Soil QualityEvaluation Program (SQEP) of Canada supported and coordinated a series of research activitieson soil and associated environmental quality. One of these research studies, the development of aGIS-based system to facilitate improved regional and national assessment of agricultural soilquality in the major crop production regions of Canada, is the subject of this report. The mainobjectives of the study are:

to translate the current understanding of soil quality into a conceptual frameworkfor broad-scale assessment,

to develop procedures within GIS environment and to demonstrate the capabilityusing digital land resource databases and other related data, and

to evaluate the sensitivity of the procedures to different data sets and to thevarious scales of mapping .

Components ofthe rationale and major results of this study have been documented and reportedin previous publications (MacDonald et al ., 1991 ; 1992 ; 1993 ; 1994 ; and 1995) . These reportsalso reflect the course of development and improvement of both methodology and databases .There was a need, however, for a comprehensive and detailed document to summarize thecurrent `state of the art' with respect to the major research methods and findings .

This Technical Bulletin describes the soil quality concepts and the GIS-based procedures for soilquality assessment at regional and national scales using existing land resource databases .

2.0 Conceptual Framework

The conceptual framework for assessing and monitoring soil quality in Canada was extensivelydiscussed during the implementation of the Soil Quality Evaluation Program and has beendocumneted by Acton and Padbury (1994). In this report, a brief overview of the historicaldevelopment of the term soil quality is provided (Section 2.1) . This is followed by a summary ofthe soil quality terms specifically used and adapted by this study, including ; a hierarchicalframework for soil quality (Section 2.2), working definitions of several key concepts, such asinherent soil quality (ISQ, soil quality susceptibility (SQS) and soil quality change (SQC)(Section 2.3), and the basic steps of soil quality assessments (Section 2.4) . Finally, theapproaches taken by this study are outlined in Section 2.5 .

2.1 Current Understanding on Soil Quality : An Overview

2.1.1 Shift and expansion of the context of soil quality

Soil quality is a term that has undergone a significant shift and expansion in recent years .Historically, the concept of soil quality was defined mainly in terms of suitability for cropproduction or other agricultural land uses (Bouma 1989a; Bouma 1989b ; van Diepen et al .,1991) . Recent discussions and reviews (Acton, 1991 a, 1991b, 1992 ; Larson and Pierce, 1991 ;Rodale Institute, 1991 ; Acton et al ., 1992;1994 and 1995 ; Doran, et al ., 1994 ; Acton andGregorich, 1995 ; Warkentin, 1995 ; Doran, et al., 1996 ; Bouma, 1997 ; Karlen et al ., 1997 ; Simset al ., 1997 ; Lal, 1998 ) have indicated that there is a significant shift and expansion in thecontext of interpretations to be included as components of soil quality .

The major change in the scope of soil quality is the inclusion of functions which are not directlyrelated to productivity . For example, Karlen et al . ( 1996) has defined soil quality as "the capacityof a specific kind of soil to function, within natural or managed ecosystem boundaries, to sustainplant, animal productivity, maintain or enhance water and air quality, and support human healthand habitation." Lal (1998) suggests an even more expansive definition which includes thefollowing four principal soil functions ;

Sustain biomass production and biodiversity including preservation andenhancement of gene pool,Regulate water and air quality by filtering, buffering, detoxification, andregulating geochemical cycles,Preserve archeological, geological and astronomical records andSupport socioeconomic structure, cultural and aesthetic values and provideengineering foundation .

The expanded definition of soil quality extends its range of influence from a direct impact on thequantity of food and fibre produced to considerations of environmental quality and food quality .

In addition, the environmental filtering function is directly concerned with the cycling of toxicelements, biological entities and heavy metals in the environment and, indirectly, with the effectson human and animal health (Rodale Institute, 1991 ; Hortensius and Nortcliff, 1991) . The waterpartitioning function is directly related to the quantity of surface and groundwater availably. In itsexpanded form soil quality becomes an important component of a holistic assessment ofenvironmental quality and an important environmental indicator to monitor the effects of land andwater management. Soil quality changes occur as a result of environmental processes which varygreatly over space and within and between ecosystem boundaries (Larson and Pierce, 1991) .

Crop production has been emphasized as the primary soil quality function, especially in thecontext of agricultural land uses (Arnold, et al, 1990 ; MacDonald and Moore, 1991 ; Pettapiece,1995). Acton and Gregorich (1995) recently defined soil quality/health in this manner, namelysoil quality for agriculture is the soil'sfitness to support crop growth without resulting in soildegradation or otherwise harming the environment . Consideration of the various soil functions'on an equal basis' has been suggested by the Rodale Institute (1991) . In reality, the majorfunctions are closely interrelated, andoccur concurrently in any farmingsystem at any management level,whether low (natural or undisturbed) or

Viabilityhighly manipulated (or managed). For

e'° ;R .̀~

~i l il,i't , ,example, land area which is used forintensive agricultural production mayalso be required to serve as anenvironmental buffer to retain nutrientsfrom manure in the rooting zone forcrop uptake and also to partitionprecipitation into soil storage ratherthan allowing surface runoff andcontamination of adjacent water withsediment . The combination of nutrient,crops and water creates conditions inthe soil atmosphere which can becontrolled to promote or inhibitprocesses such as denitrification Temporal changes 10

-10

(MacDonald et al ., 1994).

Sod ModificationProcesses

Figure 2-1 illustrates the broad contextof a multi-dimensional perspective on soil quality (Figure 2-1) .

2.1.2 Adoption of `soil health' as a synonymous term of soil quality

Figure 2-1. A multi-dimensional perspective on soil quality

In the past decade, the term `health' has been used extensively in environmental applications as ametaphor drawn from human health, even though there is not always a parallel between medical

health and environmental issues (Ayala, 1987 ; Schaeffer et al ., 1988 ; Rapport 1992, Haskell et al .,1992) . Terms such as `ecosystem health' and `environmental health' are often cited in theliterature . Recently the term `health' is also adopted by some soil scientists (Haberm 1991, Actonet al 1995) as an equivalent term of `quality' .

In general, human health can be defined in a negative manner as the absence of disease or inpositive manner as the resilient and robust characteristics of a healthy human body . The term`health', as used in soil quality assessment, can also be viewed in negative or positive manner .Soil health is a composite picture of the state of the soil's many physical, chemical, and biologicalproperties and of the processes that interact to determine this quality or health (Acton andGregorich 1995) . In the broad, holistic context of ecosystems, soil health is an indicator ofenvironmental or ecosystem health (Figure 2-2) .

2.2 A Hierarchical Framework of Soil Quality Assessment

Figure 2-2. Soil health/quality as an indicator ofenvironmental/ecosystem health

We agree with Acton and Gregorich (1995) that soil quality and soil health can be usedinterchangeably, however ; for consistency, soil quality is the term used in this report .

EnvironmentalSustainability

Soil quality approaches have to be developed to operate at a variety of scales and associatedlevels of data availability (Halvorson et al ., 1997 ; Karlen et al ., 1997) . At the farm level, Romiget al . (1995;1997) have demonstrated a descriptive qualitative assessment using a soil healthscorecard . For assessments at localized scales (e.g . field or farm) it is frequently possible tocollect site-specific information . However, as the area to be assessed increases, constraints of

time and money usually restrict the information available to data which can be extracted fromreadily available standard databases . At broad regional and national scales, generalized soil andland resource databases have been used to characterize the wide range of spatial variation ofsoil/land quality from one area to another (Thomasson and Jones, 19898; van Diepen et al .,1991) .

I"

I

rRIDUCTt"11

: w

t

atm

SOIL QUALITY

FUYCTIINS

DatabasesSoil u"CiMr

London 8 Management

Figure 2-3. A hierarchical framework for soil quality assessment

The relationship between standard land resource databases and soil quality assessments has beenstructured hierarchically for this project as shown in Figure 2-3 . At the highest level, soil quality isshown as a composite of several soil functions . Most soil functions are too complex to beestimated directly but can be defined by a series of somewhat arbitrary elements which contributeto the function . The framework consists of increasingly specific levels ; functions, elements,attributes and databases . The combination of attributes selected depends, to a large extent, on theavailability of data.

In general terms, it is possible to define the elements which contribute to a soil quality function .The same elements are estimated regardless of the level of assessment but the kinds and quality ofdata used for the estimates will vary with the application and the data which are available.

For effective data integration in a GIS environment, attributes from a variety of data sources canbe extracted and combined into elements of the soil function of interest . The integration can be ;1) additive, multiplicative or some other arithmetic combination; 2) flexible enough for inputadditional data and adjustable weighting and 3) implemented by using specific algorithms and GISoperations .

The more precisely the soil quality function is defined, the more specific the elements and attributelimits can also be defined to make a more detailed assessment. For example, soil quality for cropproduction can be defined for a certain crop and management, such as spring seeded wheat underdryland agriculture . This permits the soil quality elements and attribute limits to be specificallytailored to the needs of the particular crop .

2.3 Concepts of Inherent Soil Quality (ISQ) and Soil Quality Susceptibility (SQS)

Soil Quality is actually a series of related concepts ; some deal with current conditions, and otherswith soil quality change over time . For the purposes of this study, it was necessary to define theseterms more explicitly .

2.3.1 Inherent soil quality (ISQ) and ISQ elements

Some soil properties are mainly determined by naturally-controlled factors and processes, such asparent materials and chemical and physical weathering, They are relatively stable in short andmedium time scales . In order to distinguish these properties from the more dynamic aspects of soilquality which are considered within the context of susceptibility and change, the concept ofinherent soil quality was developed.

Inherent soil quality (ISQ) is defined as those properties ofthe soil which contribute to thecapacity ofthe soil to support a specific criticalfunction (such as crop production) and whichare relatively unchanging through time.

Inherent soil quality is defined by in situ soil and landscape properties such as ; slope, soil horizon

thickness, texture, and soil organic matter . The inherent soil quality of any particular site canchange over longer time periods, due to soil formation, or due to soil degradation by wind, water,compaction, or other factors .

Inherent soil quality could be further characterized by elements, which are key componentscontributing to a specific soil function (Figure 2-3) . For the crop production function, four keyelements were defined (Table 2-1) . A severe limitation in any one element would be detrimentalto the overall soil quality function, and would result in a lower ISQ rating .

Table 2-1 . Inherent soil quality elements for crop production

Normally, data about soil or landscape properties and related environmental features arecollected and recorded as attributes (Figure 2-3) and are stored in standard land resource databases .

The major challenge faced with this project was to define inherent soil quality, in terms of ISQelements, using the available soil attributes and databases . Sections 3 and 4 of this report describeattributes selected, and how they were integrated into the rating algorithms, classes, and thresholdvalues for each ISQ element .

The ISQ elements for other functions of soil, such as the environmental buffer and waterpartitioning may be defined in a similar fashion but would have a different set of ISQ elements .For example, the water partitioning function would involve ISQ elements for the capacity ofsurface water recharge for certain soil-landscape types and the water transmission capacity belowthe rooting zone of the soil .

2.3.2 Soil quality change (SQC) and soil quality susceptibility (SQS)

Ideally, the procedure for assessment of soil quality should precise enough to determine soilquality change (SQC). At localized scales it is possible to achieve this objective, however, at

ISQ Element Description

Available Porosity The capacity ofthe soil to retain and supply moisture to the crop, and alsoits ability to provide sufficient aeration for healthy root development.

Nutrient Retention The capacity ofthe soil to retain plant available nutrients and release themas required by the plants

Physical Rooting Conditions The quantity or volume of available soil material that is physically suitablefor root development.

Chemical Rooting Conditions The quantity or volume of available soil that is chemically suitable for rootdevelopment. This is based on the absence ofexcessive or noxiouschemical conditions such as salts, pH extremes, heavy metals, pesticideswhich inhibit the growth of crops or degrade the safety of the produce

broad regional and national scales, the level of resolution (both spatial and temporal) in standarddatabases is not adequate for change assessment .

Soil Quality Change is a dynamic concept . In a broad sense, soil quality change may include bothchange over space, i .e . between different map areas, and changes through time, i .e . temporalchange . In this report, soil quality change is defined in terms of temporal changes, as thealteration of overall soil quality, or certain soil quality properties, between two points in time(t2 - t,) . Temporal changes in soil quality may be regarded as either random, regular-periodical,or trend changes (Varallyay et al ., 1990) . It is difficult, but necessary, to distinguish the naturalrandom or cyclical variability from the trend changes in soil quality, and to define the threshold or

limiting range of change beyond which theresults will be regarded as significant orcause for concern (Lal et al . 1989) . Theprocesses responsible for soil modificationand soil quality change include basicphysical, chemical and biological processes(Lal et al, 1989 ; Varallyay et al, 1990) . Therates of these processes are determined bythe land use and management practices

Compractio~a

>g

(Figure 2-4) . Changes in soil quality may be"

Fa~obioii (w

, wuid and age)

positive (agradation), negative(degradation), or neutral (fluctuation) . Landuse and management practices can affect

Nahnal Agents(Physical, chemicalmid biological)

Htnir&i Agents(Land use and

nuuragenmit piacUces)

" Acidilication

both the direction and rates of change of soil"

ToAficadon (he%tvy iilet:als)

quality (Figure 2-4 and 2-5) .'

ofOrgankMatter Content

Figure 2-4. Soil Quality change in relation to soilmodifying processes and land use and

management practices

Several different approaches can be taken toassess soil quality change . It can bemeasured directly by research at specificmonitoring sites over long time periods .Since most soil quality attribute changes aresubtle and long term, very precise andrepetitive monitoring of specific plots isrequired . While vital for scientificunderstanding of soil quality change, it iscostly, and only feasible for limited numbersof soil and landscape conditions .

Another option to measure soil quality change is to use data from historical sampling sites, suchas ground truth information collected during detailed soil surveys . This option was tested inManitoba, using a network of soil inventory sites that were re-sampled to estimate soil qualitychange . No definitive trends in soil quality change were noted . This was attributed to the lack inprecision in the original recording of soil horizon attributes and site location, and the relatively

short (10 year) time interval . Soil inventory data are only available in limited areas . In general,the location and horizon attribute information have not been recorded with sufficient precision forcomparative re-sampling .For a more general approach, process-based models can be used in conjunction with fieldmeasurements to separate trends in soil quality from random and cyclical changes . These models

Figure 2-5. Kinds and direction of soil quality changes and research approaches

normally require large quantities of site specific information and site calibration. Models can alsobe used to predict future changes in soil quality based on scenarios of climate, land use andmanagement. In future, generalized models may be able to use soil map databases, and to predictchanges in soil attributes in each landscape unit over time and to estimate how these change affectsoil quality. Such models are not yet available for Canadian conditions, although a number ofmodels are under development (Environmental Indicator Working Group, 1994).

As Hamblin (1991) points out, all research methodologies are limited either by constraints ofspace, in that they are too specific to be extrapolated to whole regions, or by constraints of time,being measured over too short a period to be predictive of any long-term trend. Therefore, it isvery difficult to incorporate and extrapolate the limited existing data of measured soil qualitychange into regional or national assessments.

In this study, an alternative approach was developed to address soil quality change at broadscales . It consists of identifying and assessing the relative `susceptibility' of soil quality to change

" Monitoring Site speck measurements Detection of change" Modelling Site specific and general Quantification of trends

measurements and prediction ofchange" Inference/indication General measurements Indication of soil quality

susceptibility to change

using existing databases and GIS tools . Soil Quality Susceptibility (SQS) to change is definedas an estimate ofthe ease or likelihood that a soil modifying process will change some basicland resource attributes and result in a net change in soil quality. There are two major aspectsof SQS: (i) biophysical (intrinsic) characterized by soil and landscape conditions and (ii) landuse and management (extrinsic) characterized by land use and management practices, past,current and proposed (Table 2-2) .

Table 2-2. Aspects of soil quality susceptibility to change .

Although SQS does not provide estimates of actual soil quality change, soil-landscapes withdifferent SQS classes can be mapped to show areas with varying degrees of susceptibility to soilquality change . More detailed assessment of SQS will identify where programs to change landuse and management would be most beneficial .

SQS is normally considered under current climatic and land use and management conditions,however, it can also be estimated under a variety of alternative climatic and land use andmanagement conditions, over particular time periods . This can be used to study the implicationsof such land use and management alternatives on long term soil quality change and agriculturalsustainability .

2.4 Basic Procedures of Soil Quality Assessment

Soil Quality assessment can be consdered as a sequence of steps, as outlined in Figure 2-6 . Thesecan be applied to areas as small as a field site, or very broad areas as large as a country .

Historically, soil quality assessments have been done intuitively by local farmers or agronomists .Soils were considered as suitable or unsuitable for crop production, based on long term yields, orperformance of similar soils elsewhere. Risks of declining soil quality from water erosion, winderosion, and other factors were also considered, and influenced certain land use and cropmanagement options . Past experience and perceptions of soil quality change, or the lack of it,was often a major influence in such decision making. Long term sustainability of lands for cropproduction was largely dependent on the insight and commitment to long term stewardship by

10

Aspects Description

Biophysical Susceptibility Soil and landscape conditions which make the soil more or lesssusceptable to processes which modify the quality of the soil for thecritical function of interest . For the crop production function, this caninclude such factors as slope, silt content, and soil structural stability.

Land Use and Management Past, current and proposed land use and management practices whichSusceptibility make the soil more or less susceptible to processes which modify of the

soil for the critical function of interest . For the crop productionfunction, this can include such factors as crop type, rotation, and tillage .

individual land owners .

Step 1 :

Estimate the inherent soil quality for one

MOO

ortnore specific soil functions, using soiland land resource information.

2.5 Approaches Specific to This Study

Assess the biophysical conditions causingsoil quality to be susceptible to change, usingsoil and landscape information

Assess the hcumn-imposed conditions causingsoil quality to be susceptible to change usingland use and management information.

Step 4: Combine the procedures of ISQ and SQSassessment over time to predict change insoil quality : a) by estimation ; b) throughmonitoring and modeling

Step 5: Re-assess soil quality at some time infuture using land-resource data.

Figure 2-6. Basic steps of soil quality assessment

As stated in the introduction, the overall objective of this study is to develop an operational GIS-based system and a set of procedures which allow an improved assessment of agricultural soilquality for the major crop production regions of Canada . To achieve the objective, we havestratified the nature and approaches of this study as follows :

It is mainly a macro- or broad-scale assessment at regional and national level using(approx . 1 :1 million to 1 :5 million scale) . More detailed assessments (approx. 1 :50,000map scale) are included to indicate how methodologies can be extended to more detailedscales, and for validation and sensitivity analysis of the broad scale results .

It is a spatially oriented assessment and analysis . The spatial variation and patterns ofinherent soil quality (ISQ) and Soil Quality Susceptability to potential change (SQS)across or within a region are analysed and mapped for intra- or inter-regionalcomparisons .

The assessment and analysis are implemented with a set of GIS procedures using currentlyavailable digital data bases . The use of an automated GIS-based approach allows for fullyreproducible results, to facilitate comparison of the assessments at different time intervalsand with updated land resource information .

For the purposes of this study, soil quality was assessedfor the crop productionfunction . The logic and algorithms for assessing inherent soil quality (ISQ) weredeveloped for the generic requirements of annual cereal crop production . Cereals are amajor crop type grown in all major agricultural areas of Canada, and are appropriate forbroad level comparisons .

Actual soil quality change (SQQ cannot be estimated and mapped directly for largeland areas, as measured data about soil modification and change is only available for afew, selected monitoring sites . Mapping of predicted soil quality change, under variousclimatic and land management scenarios is possible in the future . This will requireintegration of calibrated, process based soil degradation models with GIS databases, andsoil quality assessment techniques developed in this study . The most appropriatesubstitute, at the present time, are maps indicating soil quality susceptibility to change(SQS) for different regions, under specified land use and management practices .

3.0 Methods

3.1 GIS Systems

The system and GIS procedures were developed using Arc/Info' GIS software from theEnvironmental Systems Research Institute, Redlands, California, USA and PAMAP GIS softwarefrom PCI Pacific GeoSolutions Inc ., Victoria, Canada. The main procedures have been tested onvarious computer platforms, such as VAX mainframe, VAX and DEC Alpha UNIX workstations,and PC Windows environment . Some ISQ rating algorithms were developed and implemented indBASE IV and linked with the PAMAP GIS .

3.2 Data Sources

Based on the soil quality conceptual framework documented in Chapter 2, the minimum data setsrequired for assessing inherent soil quality and soil quality susceptibility were identified. Theyare :

- Soil and land resource data- Topographic data- Climatic data- Land use and management data.

In general, soil and land resource data are regarded as prerequisite or "first order' data sets, asthey describe the fundamental soil properties required to characterize inherent soil quality for cropproduction . The additional data sets are required to estimate the susceptibility to change of soilquality, or to make actual predictions of soil quality change .

In Canada, reasonable amount of soil and related data are available at regional and national levelsin digital format. Table 3 summarizes the main features of some of these data sets and indicateshow they can be used for soil quality assessment. Soil, land resource data and some climate andlandscape (topographic) data were obtained from the Canadian Soil Information System andNational Soil Data Base (CanSIS/NSDB, http://res .agr.ca/ecorc/Program3/cansis/) of Agricultureand Agri-Food Canada; Census of Agriculture data were purchased from Statistics Canada, andthe AVHRR land cover data were purchased from the Manitoba Centre for Remote Sensing andvectorized by GIS Division, Natural Resources Canada . They were all either available orconverted to standard GIS formats .

The reliability assessment in Table 3-1 is subjective based on the documentation attached to eachdata set and our data checking and sensitivity analysis . The quality of the attribute informationwas quite variable, particularly for the land resource layer which was compiled from a variety ofdata sources ranging from expert estimates to summaries from detailed soil surveys .

1The mention of a trademark, proprietary product or vendor does not imply endorsement by Agriculture andAgri-Food Canada to the exclusion ofother products or vendors .

1 3

Table 3-1 . Data sources for broad-scale assessment of soil quality in Canada (used in this study)

* For a complete list of acronyms used in this report, please see appendix 1

14

Category Data Source Scale & Reliability Utility in This StudyAvailability

Soil and land Soil Landscapes of Canada (SLC)* map with 40 CanSIS/NSDB, 1 :1 million low to medium ISQ rating( ISQ92) proceduresresource attributes for dominant (DOM) and subdominant Agriculture and (variable from

(SUB) soils in each SLC polygon (DOM/SUB Agri- Food Canada All land areas of area to area)files are also called SLC extended legend) (AFFC) Southern Canada

Soil Carbon Data Base linked to SLC polygons CanSIS/NSDB, 1 :1 million medium SQS indicators and ISQ94with component (CMP) and layer (LYR) files AFFC. procedures linking SLC mapcontaining more than 20 attributes All of Canada components to soil name and

layer attributes (SNF and SLF) .

Soil Map Unit File (SMUF) in Detail Soil Map CanSIS/NSDB, Approx. 1:20,000 - medium to ISQ94 procedures linking(DSM) database AFFC. 50,000 high detail soil map units to soil

Limited areas name and layer attributes

Soil Name File (SNF) and Soil Layer File (SLF) CanSIS/NSDB, Pedon-scale medium to ISQ94 rating procedureswith more detail soil attributes. Data from these AFFC. variable from highfiles can be related to map polygons . province to province

Topographic Landscape shape and slope attributes from SLC CanSIS/NSDB, 1:1 million low to medium SQS indicatorDOM, SUB and CMP files AFFC. All of Canada

Climate EGDD and P-PE (1951-80 climatic normals), Agronomic Inter- 1 :1 million low to medium Defining area suitable forre-compiled to SLC polygons pretation Working All ofCanada annual crop production and

Group, AFFC adjusting ISQ porosity rating

Land use and Census of Agriculture (CoA) 1981 and 1991 re- Statistics Canada 1 :1 million medium SQS indicator and estimationmanagement compiled to SLC polygons and containing and AFFC (joint re- of past changes in land use and

common land use and management attributes . compilation) Agricultural areas management

Vectorized AVHRR 1989 composite containing Natural Resources 1 :1 million (approx .) low to medium Defining the extent ofagri-broad land cover classification Canada All area of Canada cultural areas and estimating

area of agri-crop land

3.3 Spatial Framework

Along with decisions regarding the attribute data to be used in this study, it was necessary tochoose appropriate spatial units for the assessment, analysis, and map displays . The spatialframework acts as a set of `spatial folders' of data or information . The hierarchy of broad scaleCanadian land resource data used in this report and its organization is briefly summarized in thissection . Figure 3-1 illustrates the hierarchical nestings between SLC and the National EcologicalFramework of Canada .

ECOZONES

Ecodistrict #565 as one of 12 Ecodistrictsin the Lake Erie Lowland Ecoregion

DETAIL SOIL MAP (DSM) DATA( 1 :20,000 - 125,000 scale)

(Map units NOT nested withSLC polygons)

SOIL-LANDSCAPE (SLCI UNITS( 1 :1 million scale)

22 SLC polygons inthe Ecodistrict #565

ECODISTRICTSApprox . 1 :5 million scale)

Lake Erie Lowland as one of 4 Ecoregionsin,the Mixedwood Plain Ecozone

Mixedwood Plain as one of 15Canadian Terrestrial Ecozones

Figure 3-1. Illustration of the spatial framework for soil quality assessment and reporting in Canada

The Soil Landscapes of Canada (SLC) digital maps were selected as the appropriate spatialframework for land-related assessments and environmental reporting at regional and nationalscales . SLC maps are part of the Canadian Soil Information System and National Soil Data Base

1 5

LEVEL FOR:i-,

" Testing ISQ algorithmsJ

" Validation of results of SLClevel ISQ ratings and SQSindication

Primary LEVEL OF :" Data collection and integration" ISQ rating and mapping" Identification and mapping ofISQ indicators

LEVEL OF :" Generalized ISQ analysis &mapping

" Analysis and reporting of soilrelated environmental andpolicy issues.

(CanSIS/NSDB, http://res .agr.ca/ecorc/program3/cansis/) of Agriculture and Agri-Food Canada.SLC polygons are compiled at a scale of 1 :1 million by regional land resource experts, from avariety of more detailed historical data sources . SLC polygons also constitute the basic spatialunits in the National Ecological Framework for Canada (Ecological Stratification Working Group,1996) . Ecological units, such as ecodistricts, ecoregions, and ecozones, are all "nested" to theSoil Landscapes of Canada polygonal coverage . This ecological framework permits furtheraggregation and generalization of soil quality assessments at even broader scales . Ecodistricts,typically consisting of several SLC polygons, were selected as the appropriate units for ISQreporting at national and broad regional scales (approx . 1 :5 million) .

Detailed digital soil maps (DSM) are also available for selected areas of Canada from the NationalSoil Database of AAFC. These maps are linked to a standard set of soil attribute files(MacDonald and Valentine, 1992), permitting the development and testing of soil qualityalgorithms at the scale of detailed soil maps (approximately 1:20,000 to 1 :125, 000 ) . Selecteddetail map data sets were used in this project, for development and testing of inherent soil qualityrating algorithms for application at both detailed and broad scales . They were also used forvalidation and sensitivity analysis of broad level soil quality assessments in selected areas, asdescribed in Section 5.1 .2 .

3.4 ISQ Rating Procedures

3.4.1 Evolution of ISQ Procedures

During the course of this study, two separate sets of inherent soil quality (ISQ) rating procedureswere developed for application at regional and national levels . Both of them were based on theframework illustrated in Figure 2-3, Chapter 2. The same four elements of soil quality (Table 2-1)were defined under the crop production function of soil quality, as well as an overall soil qualityrating for each soil polygon component . A generic cereal crop was selected in both cases, as thisrepresents a major crop type grown in all crop production areas of Canada. The differencesbetween the two ISQ procedures which resulted from different available soil databases were in theattributes, and algorithms used to define the soil quality elements .

The first set of procedures, developed in 1992 (referred to as "ISQ92"), uses attributes containedin the Soil Landscapes of Canada extended legend as described in Table 3-1 and Table A2-1 ofAppendix 2. The extended legend database has generalized soil attributes for dominant andsubdominant soil landscapes in each SLC polygon (SLC DOM and SUBDOM attribute files) .The SLC extended legend properties were defined by local soil experts in each region, in terms ofa few broad classes for each attribute. ISQ92 can be run for all agricultural areas of Canada, asthe SLC extended legend databases are available for all of southern Canada (SLC v1 .0) . The SLCextended legend database has not be updated with further versions of the SLC map (currentlyv2.2) . The ISQ92 rating program (Appendix 3) is relatively simple but, nevertheless, should beappropriate for regional or national level assessments .

1 6

The second, more detailed set of ISQ procedures was developed in 1994 ("ISQ94"), to takeadvantage of improved SLC file structures . The general structure of data describing SLCpolygons had undergone a major revision such that each polygon was described by a series ofcomponents which occupied a specified proportion of the polygon area . Each soil componentcould be linked to two additional files, the Soil Names File (SNF) and Soil Layer File (SLF),which contain modal values of physical and chemical properties for each soil . The SLCComponent file data structure was quite similar in concept to the Soil Map Unit File (SMUF)structure used to delineate soil map components and extents for detailed Canadian soil mappolygons (at scales of 1 :20,000 to 1 :125,000) . ISQ94 procedures can be applied to both SLC anddetailed scale digital maps, linked to the same provincial SNF and SLF soil attribute files .

ISQ94 procedures can also be easily modified to suit additional crops, or be used to performsensitivity analysis of various attribute limits . ISQ94 requires linkage to detailed SNF and SLFdatabases, which are not currently available or fully correlated for all agricultural regions ofCanada . Also, there are some concerns about the representation of broad, SLC level polygons bya limited number of soil types in the current SLC Component file . In many instances, SLFattribute values for individual soils are based on estimates, or only a few samples from detailedsoil sampling sites in various locations .

Refinements of the SLC CMP, and SNF and SLF fileswill increase the applicability of the ISQ94 procedures in the future .

3.4.2 Components of ISQ Procedures

The ISQ procedures can be subdivided into stages (Figure 3-2) consisting of pre-rating(screening) procedures, rating procedures and post-rating or presentation procedures .

3.4.3 Pre-Rating Procedures

The main purpose of the pre-rating procedures is to ensure that all GIS databases and essential

rte_ rso rl ri J~r~r~rliir=~

" Data checking" Selection of filesand attributes

" Exclusion" Preparation ofinterim items andfiles

:1f_fl1

PJfiJ

('JJ ~

-(' J~~~fI 11 l'iJ" f , llf' ~

" Available porosity" Nutrient retention" Physical rootingconditions

" Chemical rootingconditions

" ISQ overall rating

Figure 3-2. The organization of ISQ procedures

1 7

" Generalization formapping at certainscaleGIS query anddisplay

" Reporting

data fields required for the ISQ94 rating procedures are present, and that all of the mandatorydata fields have acceptable attribute values . Once the ISQ crop type is selected, the thresholdvalues for the various soil and climatic attributes can be reviewed or altered. Interim files aregenerated to store the output ratings and statistics . Soil map components with inappropriate datavalues for rating calculations are assigned "data error" codes and are excluded from furtheranalysis . Details of these steps are presented in Appendix 4.

3.4.4 Rating Procedures

Once pre-rating procedures are completed, calculation of ISQ ratings proceeds for each soilpolygon component. An initial set of threshold criteria are used to identify climatic, landform, orsoil conditions that are considered unsuitable for crop production . SLC polygon components thatlack sufficient heat for a minimal growing season (Effective Growing Degree Days less than1050), or are too steep (over 30% slope), or have non mineral soil types (organic soils, frozensoils, bedrock, or other non soils) are rated as "Unsuitable" for cereal crop production, and areexcluded from further analysis .

The soil polygon components for areas that meet minimum threshold criteria for crop productionare then evaluated using the algorithms developed for the four elements of soil quality . The ISQ94rating procedures consist of four basic sub-procedures and one overall rating sub-procedure, eachof the four basic sub-procedures corresponding to one of the four elements of inherent soil quality(Table 2-1) . The general approaches andrating considerations are described in the followingsection. Further details of the ISQ94 rating program and procedures are provided in Appendix 4.

1) Available porosity element

This procedure evaluates the capacity of the soil component to retain and supply moisture to thecrop, and also its ability to provide sufficient aeration for healthy root development. The twocomponents, aeration porosity and moisture holding porositv, are calculated and rated separately.The most limiting of the two conditions determines the overall ISQ available porosity elementrating .

Aeration Porosity is calculated for each soil horizon and the accumulated value is the totalaeration porosity value (in cm of air) . This is calculated for the surface layer (20 cm) and for theentire rooting zone (an accumulated value, "AIR TOT", for all horizons down to the maximumallowable rooting depth) . The formula used is :

nAIR-TOT _ Y, THICKNESS,*[(PDT -BD,) / PD,- 0.01*KP33i]

where,

1 8

2) Nutrient retention element

where,

AIR-TOT = accumulated air-filled porosity (cm) from top to the maximumallowable rooting depth (horizon i = 1, . . ., n) .THICKNESS = the thickness of the soil layer i (cm) .PD = Particle Density, g/cm3 . (2.65 g/m3 for mineral soil layers)BD = Bulk Density, g/cm3 .KP33 = % water, by volume, that is retained by the soil at 1/3 atmospheresuction. This is multiplied by 0.01 to convert from % to a ratio of the soil volume .KP33 approximates field capacity.

The soil aeration value (AIR TOT, expressed in cm of air), is also calculated for the surface 20cm by adding soil layers or portions of layers occurring within this zone . A minimum thresholdvalue of I cm of air within the top 20 cm (5% of the surface layer volume) must be reached; if thisdoes not occur, the soil is rated as unsuitable, and excluded from further ISQ elementcalculations .

Values exceeding the minimum are adjusted for the moisture regime to give an aeration porosityrating value ranging from "Good" (0) to "Poor" (3) . The moisture regime adjustment is based onprecipitation, potential evapotranspiration, soil taxonomy, and drainage (details in Table A4-5 ofAppendix 4).

Moisture Holding_Porosity is determined from an estimate of the available water holding capacity(AWHC). The AWHC is based on soil texture and ranges from 40 to 200 mm/m. It is estimatedfor each soil and summed over the crop rooting depth. The AWHC is modified by the moistureregime to derive a moisture holding porosity rating with a similar range of values to the aerationporosity . Low AWHC values are considered a more serious limitation to crop growth in moreand climatic regimes, such as the Brown Chernozemic soil zone . See Table A4-7 of Appendix 4for details .

The overall Available Porosity element rating is determined as the `most limiting' of the twocomponent ratings .

This procedure evaluates the capacity of the soil to retain plant available nutrients and releasethem as required for crop production . This is assessed from the cumulative cation exchangecapacity (CEC) of all soil horizons within the surface rooting depth (top 20 cm), using theformula:

nNUTR_SUR =

CECi*BD,* BASESi*0.01* ELTHICKNESSi

(3-2)

19

NUTR SUR = Accumulated nutrient retention capacity of surface 20 cm(meq/cm3) of all soil horizons or portions of horizon (i = l, . . ., n)CEC= cation exchange capacity (meq/100g)BD = Bulk Density (g/cm3)BASES = base saturation (%), This is multiplied by 0.01 to convert from % to aratio of total CEC .ELTHICKNESS= the eligible thickness of the soil layer i considered as part oftop 20 cm surface soil . If a soil horizon has a lower depth that exceeds 20 cm,only the portion to a depth of 20 cm is considered eligible .

The average CEC of the top 20 on aunit volume basis is calculated as:

NUTR_RATIO (meglCM3) = NUTR SUR (meglCm2)/20 (cm)

(3-3)

A nutrient retention rating is assigned based on classes of average CEC by volume of the top 20cm (NUTR_RATIO). The generic rating scale, for cereal crops is shown in Table 3-2 .

Table 3-2. Rating scale of ISQ nutrient retention element

0 = good; 1 = good to moderate ; 2 = moderate to poor; 3 _ poor; 9 = not rated

3) Physical rooting conditions element

This ISQ element evaluates the volume of soil material that is physically suitable for rootdevelopment. For each soil component, the successive soil layers are evaluated, starting from thesurface, until a physical root restriction or the maximum crop rooting depth is encountered.Rating classes are assigned based on ranges of the eligible rooting depth (THICK-TOT), asshown in Table 3-3.

Table 3-3. Rating scale of ISQ physical rooting conditions element

4) Chemical rooting conditions element

20

NUTR_RATIOof Top 20 cm < 8 8.0 to 8.9 9.0 to 15 .9 16 to 22 > 22(megtcm3)

ISQNUTR 9 3 2 1 0Ratings

THICK TOT < 20 20 to 29 30 to 54 55 to 79 >= 80(cm)

ISQ_ROOT 9 3 2 1 0Rating

0 = Gond_ 1=('*nnd to Mnrjerate- 7 = MnrleratP to Pnnr-'I = Pnnr- Q -_ not rntarl

The chemical rooting conditions procedure evaluates the volume of available soil that ischemically suitable for root development . For this report two natural chemical conditions, pH andsoil salinity (measured as Electrical Conductivity, or EC) are each evaluated separately. The sameapproach could be used for anthropogenic chemical conditions such as pesticide or petroleumcontamination . For each condition, both surface (0 to 20 cm) and subsurface (20 to 80 cm)depths are averaged and evaluated separately, using threshold tolerance values . Both conditionscan vary considerably with depth, and surface conditions are considered more limiting to cropproduction . The final rating for each chemical rooting condition is determined by combiningsurface and subsurface ratings .

Both pH and salinity are assessed in a similar fashion, and the most restricting of the twoconditions is used in the overall ISQ chemical rooting element rating . In general terms, an average(depth weighted) pH and EC of the top 20 cm of the soil (SURPH and SUREC, respectively), iscalculated for each soil component, based on Soil Layer File data;

where,SURPH = depth weighted average pH of surface 20 cm of all eligible soilhorizons (i = 1, . . ., n)PHCA = soil pH in 0.01M calcium chlorideSUREC = depth weighted average EC of surface 20 cm (mS/cm) of all eligiblesoil horizons (i = 1, .. ., n)EC = electrical conductivity (mS/cm)ELTHICKNESS =the eligible thickness of the soil layer i, considered as part of the top20cm of soil

The surface chemical rooting condition (Table 3-4), ISQ_SURCHEM, is determined based themost restricting value of classes SURPH and SUREC values .

Table 3-4. Rating scale ofISQ chemical rooting conditions element

0 = Good ; 1 = Moderate; 2 = Moderate to Poor; 3 = Poor; 9 = not rated

2 1

< 4.0 4.0 to 5 .0 5.0 to 5.5 5 .5 to 6.0SURPH or SURPH or or or or 6.0 to 7.3

> 9.5 8 .1 to 9.5 7.7 to 8.1 7 .3 to 7.7

SUREC or SUREC(ms/cm) > 12.0 8 .1 to 12.0 4.1 to 8.0 2.1 to 4.0 <= 2.0

ISQ-SURCHEM orISQ_SUBCHEM Rating 9 3 2 1 Ô

nSURPH=,E PHCA,* ELTHICKNESSil20) (3-4)

i=i

nSUREC=1:ECi * ELTHICKNESSiI20) (3-5)

i=i

The sub-surface chemical condition is determined from the average (depth weighted ) pH andEC of the sub-surface soil layers between 20 cm and 80 cm depth . An 80 cm lower depth waschosen, as it is the minimum rooting depth considered as no restriction for cereal crops . SUBPHand SUBEC are calculated as follows :

where,SUBPH = depth weighted average pH of sub-surface of all eligible soil horizons (i = 1,. . . .n)PHCA = pH in calcium chlorideSUBEC = depth weighted average EC of sub-surface 20 - 80 cm (mS/cm) of all eligible soilhorizons (i = 1, . . ., n)EC = electrical conductivityELTHICKNESS = the eligible thickness of soil layer i considered as part of subsurfacesoil.

Sub-surface chemical rooting conditions, ISQ_SUBCHEM, is determined based the mostrestricting value of classes of SUBPH and SUBEC values .

Overall chemical rooting condition represents a combination of the surface chemical conditionsand the subsurface conditions, as shown in Table 3-5 .

Table 3-5 . Matrix for determining rating points ofISQ overallchemical rooting conditions

0 = Good; 1= Good to Moderate ; 2 = Moderate to Poor; 3 = Poor; 9 = not rated

22

Overall Rating Surface Rating (ISQ-SURCHEM)(ISQ_CHEM)

0 1 2 3

0&1 0 1 2 3

ao

â 2 1 1 2 3

°' 3 2 2 2 3

nSUBPH=I, PHCAj * ELTHICKNESS,160) (3-6)

i=1

nSUBEC=EECj * ELTHICKNESS,l60) (3-7)

5) Overall ISQ ratings

During the course of development of ISQ procedures, several approaches were explored andtested for aggregating ISQ element rating to overall ISQ rating, such as additive and weightedadditive forms, multiplicative forms, maximum and minimum operators (Ott, 1978) . The fourISQ elements for the crop production function (Table 2-1) are considered of equal importance,and crop production is constrained by the element with the most unfavorable conditions .Considering these factors, the ISQ94 procedure uses the `most limiting' ISQ element rating as theoverall rating for each soil map component. The rule can be expressed as :

ISQ_ OVER = min{ISQ_ PORO, ISQ_ NUTR, ISQ_ ROOT, ISQ_ CHEIVI}

(3-8)

where,ISQ_OVER = the overall ISQ rating .ISQ_PORO = the ISQ available porosity element ratingISQ_NUTR = the ISQ nutrient retention element ratingISQ_ROOT = the ISQ physical rooting conditions element ratingISQ_CHEM= the ISQ chemical rooting conditions element rating

3.4.5 ISQ post-rating procedures

As illustrated by Figure 2-3, the evaluation of soil quality can be considered as a successiveprocess of integration from database `attributes' to `elements' to 'function' . The precedingsection outlined the inherent soil quality rating procedures developed for each of the four soilquality elements of the crop production function, based on available data elements . Additional,post rating procedures are required to integrate the individual element ratings into an overallrating for a soil map component. Procedures were also developed to further generalize or portrayinherent soil quality ratings at broad regional and national map scales .

ISQ map generalization procedures

A SLC map polygon can have several components, with separate ISQ elements and an overallISQ rating for each component. For regional scale maps, it is useful to portray generalized ratingsfor each SLC polygon as a single, simplified ISQ class or color. For broad regional or nationalassessments, at scales between 1 :2 million and 1 :20 million, "higher level" map polygons, such asEcodistricts, Ecoregions, or Ecozones are preferred (Figure 3-3) .

SLC components

Where,

Level of initial

Level of mappingISQ rating

and reporting

Generalization skipping interim levels

010-

Generalization across every levels

Figure 3-3 Levels of ISQ generalization and mapping/reporting(for the hierarchy of the spatial units, see Figure 3-1)

Individual SLC polygon ratings may be aggregated to produce more generalized "higher level"ratings for broad regional and national level assessments . Two methods were used to generalizeISQ rating from a lower level of spatial entities/units to a higher level of spatial entities/units :

1) Area weighted aggregation of rating points

ISQ rating points of each spatial unit (component or polygon) at a lower level were weighted bytheir areal proportion within the higher level spatial unit/polygon, and then accumulated into therating points of a polygon at the higher level. This procedure results in an average ISQ rating forthe spatial unit which is based on data from the entire rated area . The aggregation can beexpressed as :

24

Main forms of mappingand reporting

ISQj ,k�

=rating points of ISQ element m of polygonj at k level . (m = 1, 2, 3, 4 andrepresents 4 ISQ elements respectively ;j = 1,2, . ..,n and can be any polygon inthe study area ; k = 1, 2, 3, 4 and represents SLC, ecodistrict,

ecoregion, andecozone levels respectively) .

ISQ k -f

= rating points of ISQ element m of component or polygon i at k-f level (i =ijm

1,2, . ..,n, components or polygons within polygon j at k level, when aggregatedwithout skipping interim levels,f=1 ; when aggregated skipping interim levels,f>= 2) .

W;

= weighting coefficient based on area proportion of component orpolygon i at k-flevel within polygonj at k level .

S

= numerical constant used to scale up the magnitude of rating points .

2) Aggregation of areas of different rating classes

Instead of aggregating the actual rating points, this method aggregates the area of different ratingclasses, i.e. `Poor', `Poor to Moderate', `Moderate to Good' and `Good" . The area of each ratingclass is summed up respectively as expressed by the following formula:

nISQ)m(AP,Apm,Amg,A,)=~ ISQjmf(AP,Apn,Amg,Ag)

Where,kISQj n(AP,Apm,Amg,Ag)

= Areal proportion ofeach ISQ rating class (`poor', `poor tomoderate', `moderate to good' and `good') ofISQ element

mofpolygonj at k level . (m = 1, 2, 3, 4 and representsthe 4 ISQ elements respectively; j = 1,2, . . .,n and can be anypolygon in the study area; k = 1, 2, 3, 4 and represents SLC,ecodistrict, ecoregion, and ecozone polygonal levels) .

SQ; . (A,,Apm,A,ng,Ag

= Areal proportion of each ISQ rating class of ISQ element m ofcomponent or polygon i at k-flevel (i = 1,2, . . .,n, components orpolygons within polygonj at k level receiving same rating class,when aggregation without skipping interim levels, f=1 ; whenaggregation skipping interim levels, f>= 2).

The rating class for ISQ element m of polygonj at k level is determined by the class which hasthe largest area proportion . This can be expressed as:

ISQjm =max(ISQjm(AP,Apm,Amg,Ag))

(3-11)

For example, if the area proportion (%) of ISQ rating classes of a polygon, ISQ (AP,Apm,Amg,Adis equal to ISQ ( 10, 20, 15, 55), the rating class ofthe polygon is "Good" (Ad .

An alternative to this is to use a pie chart map to represent the areal proportion ofthe four ISQclasses within the polygon, as illustrated in Figure 3-3 . This is most effective where the totalnumber of map polygons is limited, and each polygon covers a relatively large portion ofthemap. It is useful to report ISQ assessment results at higher level spatial units, such as ecoregionsor ecozones.

Ecodistricts were selected as the most appropriate spatial units for the broad regional mapping ofinherent soil quality in this report. The first method, the area weighted aggregation of ratingpoints from SLC components to ecodistrict units, was used to provide generalized ISQ ratings for

25

(3-10)

ecodistrict polygons .

3.5 SQS Indicators and Spatial Identification

Soil quality susceptibility (SQS) to change could be assessed qualitatively, by use of selectedindicators, or quantitatively, with specific procedures similar to those used for rating the inherentsoil quality elements . Development of quantitative, or semi-quantitative procedures wouldinvolve investigation of a range of parameters and specific models for various types of potentialsoil degradation . Research on the development, calibration, and verification of variousdegradation models is a major area of ongoing research.

Table 3-6. Typical criteria forindicator selection

The mandate of the current project was to investigate soilquality, and soil quality change, for broad geographic areas ofCanada, using existing digital GIS data sources . At this level,it is more appropriate to portray soil quality susceptibility tochange in a qualitative manner, using currently availableindicators that are applicable at broad regional and nationalscales . Various potential data sources were investigated forthis purpose . In order to be considered as indicators of soilquality susceptibility (SQS) for change, data had to meet thebasic criteria outlined in Table 3-6 .

(After the Council ofGreat Lakes

The specific SQS indicators were selected based in part on

Research Managers, 1991)

the soil modifying processes and in part on the availableinformation sources (Table 3-1) . Two distinct aspects of SQS were recognized, those due tobiophysical conditions, and those due to land use and management conditions (Table 3-7) .

26

Criteria ofIndicator Selection

SensitiveDiagnosticIntegrativeInterpretableNot redundantAppropriate scaleBroadly applicable

Biophysical aspects are inherent properties of the soil and landscape that increase thesusceptibility or likelihood of soil quality change . The most susceptible soils are those with ashallow topsoil, low levels of organic carbon, steep slopes, highly erodible surface textures, orshallow effective rooting depths. The assumption is that soils with one or more of thesecharacteristics are more likely to lose topsoil due to wind or water erosion, and that these losseswill result in a more significant decline in soil quality than for deeper soils with larger reserves ofsoil organic matter.

Land use and management SQS indicators are primarily related to intensive cultivation practices,that leave the soil exposed with limited protective cover for significant periods of time . Intensivecultivation and exposure of the soil were considered likely to result in a more rapid decline inorganic carbon and overall lower soil quality .

The extent of particular susceptible land management practices and farming systems variesbetween different ecoregions. In the Prairies ecoregion of western Canada, high percentages ofsummer fallow result in a higher susceptibility of degradation . In eastern Canada, a high

percentage of row crops, and low levels of conservation tillage practices are more commonsusceptibility indicators .

Each of these indicators identified in Table 3-7 was considered to be relatively independent . Thecollective effects of different SQS indicators can be spatially identified by using a GIS overlapoperation . The level of susceptibility of soil quality change from water or wind erosion isestimated to be highest where biophysical and land use and management SQS indicators wereboth identified on the same parcels of land . Maps of these conditions can be used to identifystudy areas where soil quality change is most likely.

Table 3-7. Selected SQS indicators and the criteria and threshold values

* applicable to the Prairies and Boreal Plains Ecozones** applicable to the Mixedwood Plains Ecozone

The GIS procedures to identify the selected SQS indicators using existing data bases wereimplemented with the basic query and mapping functions of Arc/Info GIS. The procedures are

27,

SQS Aspects SQS Indicator Threshold Values . Modifying ProcessesAffected

A) Biophysical " Shallow topsoil A horizon thickness <= 15 cm Water erosion andorganic matter decline

" Low organic carbon Organic carbon of A horizon < 1% Organic matter declinecontent oftopsoil

" Steep surface slope Slope steepness > 9% Water erosion

" High erodible surface Surface texture = silt or silt loam Wind and water erosiontexture

" Shallow effective Depth to impenetrable layer Water erosion anddepth <= 60 cm organic matter decline

B) Land Use and " High intensity of Area under crop > 70% offarmland Organic matter declineManagement agricultural land use and **row crops > 60% of cropped

land

" High level of *summer fallow > 30% Water erosion and`unfriendly' practices organic matter decline(e.g. summer fallow)

" Increase of intensity of **Increase of cropped land and row Organic matter declineland use crop > 10% within a 10 year period

shown schematically in Figure 3-4 .

Soil and landscape, land use& management practices

Conceptual Framework(Indications of soil quality change by assessing

the susceptibility to change)

Major soil modifying processes and current land use ``& management conditions

Underlying factors & driving forces

Selection of Indicators

GIS data assembly,spatial & statistical

analysis and mapping

Results(reports, maps)

Figure 3-4 GIS procedures to identify and map SQS indicators

Basic criteria ofindicators

4.0 Results and Analysis

As stated in Chapter 1, One of the objectives of this study is to demonstrate the methodology andprocedures at national and regional level with existing digital databases . In this chapter, wemainly use maps and the results of statistic analysis to shown the spatial patterns, areaproportion and regional distribution of the current status of soil quality and susceptibility tochange for the major agricultural regions of Canada.

4.1 The Major Agricultural Regions of Canada

Two major agricultural regions were selected : the Prairie and Boreal Plains Ecozones in Alberta,Saskatchewan and Manitoba, and the Mixedwood Plains Ecozone in southern Ontario andsouthwest Quebec (Figure 4-1) . Based on Census of Agriculture data (1991), about 91% of thefarmland and 95% of the cultivated land in Canada are in these two regions .

Major Farming Areas of Canada

Study Areas in Western Canatlit- The Pidlrle and llored Plains I'iozones

Detail study area inSouthern Ntanitoba

Study Area in Eastern Canada- The Mixedmod Plain Ecozone

Detail study area inEastern Ontario

Figure 4-1 Major agricultural regions of Canada

Most agriculture in western Canada takes place in the Prairie Ecozone, but significant farmingareas also occur in the southern part of Boreal Plains Ecozone, such as the Peace River region .The predominantly Chernozemic soils, relatively low relief landforms, and favorable climaticconditions make the prairies the most productive region for cereal crop production in Canada(Acton, 1995) . Unsuitable soil and climatic conditions limit agricultural suitability in the

29

portions of Manitoba, Saskatchewan, and Alberta. In the southern prairies, many agriculturalsoils are subject to the stress of a dry climate and are susceptible to certain degradation processes,such as wind and water erosion, salinization and decline of organic matter (Gregorich and Acton,1995). Summerfallow is a major land management practice to maintain soil moisture reserves inthe prairies, however it also increases the susceptibility of the soil to wind and water erosion.

The Mixedwood Plains Ecozone in eastern Canada covers the lower Great Lakes-St . LawrenceRiver valley . Most agricultural production in Ontario and Quebec takes place in this ecozone.The combination of gentle surface landforms, fertile soil, warm growing season and abundantrainfall makes this region the most productive area of high-value crops, including corn, beans andavariety of specialty crops. Major soil degradation processes are watererosion, compaction anddecline of organic mater. Intensive row crop production is one of the major land managementpractices contributing to soil degradation in this ecozone.

In addition to the broad-scale assessment and analysis, detail study areas were selected inSouthern Manitoba and Eastern Ontario (Figure 4-1) to evaluate the sensitivity of ISQ ratingprocedures to map scale in each region .

4.2 Current Status of Inherent Soil Quality

For both regions, the initial ISQ ratings were made for SLC polygon components, and thenfurther generalized to the Ecodistrict level of the National Ecological Framework for Canada(Ecological Stratification Working Group, 1996). A description of the ISQ map generalizationtechniques developed for this project is provided in Section 3.4.5 .

Results from the ISQ assessment of the major agricultural areas of Canada are reported separatelyfor the prairie region of western Canada (Prairies and Boreal Plains Ecozones), and theMixedwood Plains Ecozone of eastern Canada. For each region, generalized maps and statisticswere compiled to illustrate the distribution of the four elements of theISQ crop productionfunction ; available porosity, nutrient retention, physical rooting conditions, and chemical rootingconditions and overall ISQ rating (Figures 4-3a,b,c,d,e and4-5a,b,c,d,e) .

4.2.1 The Prairies Provinces - Prairies and Boreal Plains Ecozones

In the Prairie provinces, over one-third (37%) of the total land area meets the minimum soil andclimatic requirements for agriculture. This 37% land was included for the assessment of ISQ(Table 4-1) . The details of inclusion and exclusion criteria are listed in Table A4-2 and A4-3 inAppendix 4.

Results of the ISQ assessment using ISQ94 procedures in the included area were summarized byprovinces for each of the 4 elements and the overall rating of soil quality in Table 4-2. The spatialdistribution and patterns of ISQ status are shown in the generalized maps at Ecodistrict level(Figure 4-3a,b,c,d,e)

30

At ISQ element level (Table 2-1), of the 37% of rated land, about 70-80% received `Good' or`Good to moderate' ratings for all four ISQ elements (Table 4-1) . Marginal ("Poor") ISQ ratingsvaried from 3 to 11% for the different ISQ elements . At the overall ISQ rating level, about 46%received `Good' or `Good to moderate' ratings, about 34% was rated as `Moderate to poor' andabout 19% was rated as `Poor' .

Summary statistics for each element of soil quality in Table 4-2 can also be compared to thegeneralized maps for the Prairies provinces (Figures 4-3a,b,c,d,e) to indicate areas with particularsoil quality conditions. The ISQ94 classification results can also be examined in more detail toprovide a particular understanding of the limitations in each area .

Table 4-1. Proportion of area ISQ rated of total land area in the Prairies provinces

'~ As % of total land area (water area not included)z~ Land area (not including water) calculated based on 1 :1 million SLC data in Arc/Info formatArea meets minimum ISQ requirements

For example, Moderate to Poor ratings for the ISQ Porosity element occur in two main areas; thePalliser Triangle area of southeastern Alberta and southwestern Saskatchewan, and the Red RiverValley of southern Manitoba (Figure 4-3a). A closer examination of the ISQ94 subelementratings in Alberta and Saskatchewan indicates this is due to the lack of water holding capacity,primarily due to dry climatic conditions associated with the Brown and Dark Brown Chernozemicsoil zones . In southern Manitoba, the main porosity limitation is due to lack of aeration, due tothe heavy clay soils and poor internal soil drainage .

Physical rooting conditions are Good throughout most of the Prairies provinces (Figure 4-3c),with some Poor (marginal) areas in the Interlake area of central Manitoba, and the Peace Riverarea of northwestern Alberta . A further analysis of the data reveals this is due to high bulkdensities that restrict root penetration in the extremely calcareous glacial till parent materials inManitoba, and in the Luvisolic Bt horizons in the Peace River area of Alberta .

Since ISQ is a digital map rating procedure, results can also be summarized by province,ecological region, or other geographical units identified in the GIS . This can be expressed in mapform or graphically , as illustrated in Table 4-2 and Figure 4-2 .

Alberta Saskatchewan Manitoba Prairies

10 3 ha %1) 103 ha %1 ) 103 ha %1) 10' ha %1)

Total land area') 63,023 100 58,971 100 55,378 100 177,373 100

Area ISQ rated) 24,064 38.2 31,038 52.6 10,495 19.0 65,593 37.0

Table 4-2 . Summary ofISQ assessment in the Prairies provinces

') As % of total area rated

32

Rating classAlberta Saskatchewan Manitoba Prairies

103 ha 103 ha %D 1()3 ha %1) 10 , ha %I)

Available porosity

Good 13,233 55.0 12,403 40.0 7,536 71 .8 33,172 50.6

Good to moderate 4,582 19.0 9,902 31 .9 881 8.4 15,365 23 .4

Moderate to poor 4,799 20.0 8,144 26 .2 1,501 14.3 14,444 22.0

Poor 1,446 6.0 588 1 .9 576 5 .5 2,610

Nutrient retention

Good 12,881 53.5 19,702 63 .5 7,909 75 .4 40,492 61 .7

Good to moderate 6,358 26.5 7,351 23.7 1,379 13 .1 15,088 23.1

Moderate to poor 3,733 15.5 3,201 20.3 817 7.8 7,751 11 .8

Poor 1,088 4.5 784 2.5 389 3 .7 2,261 3.4

Physical rooting conditions

Good 17,533 72.9 31,017 99.9 5,793 55.2 54,343 82.8

Good to moderate 227 0.9 21 0.1 1,335 12.7 1,583 2.4

Moderate to poor 756 3.1 0 0.0 1,555 14.8 2,311 3.5

Poor 5,544 23 .1 0 0.0 1,821 17.3 7,355 11.2

'Chemical rooting conditions

Good 8,828 36.7 15,526 50.0 3,213 30.6 27,567 42.0

Good to moderate 5,221 21 .7 11,126 35.8 5,419 51 .6 21,766 33.2

Moderate to poor 5,758 23.9 3,196 10.3 1,329 12.7 10,284 15.7

Poor 4,253 17.7 1,190 3 .9 533 5.1 5,975 9.1

Overall rating

Good 3,640 15.1 5,676 18.3 762 7 .3 10,078 15.4

Good to moderate 5,154 21.4 12,333 39.7 2,837 27.0 20,324 31 .0

Moderate to poor 7,647 31.8 10,912 35.2 3,680 35 .1 22;239 33.9

Poor 7,619 31 .7 2,117 6.8 3,216 30.6 12,951 19.7

Available porosity

Physical rooting conditions

Chemical rooting conditions

G - Good; G"M - Oood.dod ro m .darw; M-P - Madsalo m poor-P ~ Pesr

G-Good;0.M - aoed m m.d.mte: M"P - M.d .nn b poor ; P - Po .r

Overall ISQ rating

Nutrient retention

Figure 4-2. Regional differences of ISQ ratings in the Prairies provinces

KM

n

Results are presented at Ecodistrict level

Figure 4-3 Inherent soil quality (ISQ) element map of the Prairies provinces: a) available porosity34

KMResults are presented at Ecodistrict level

Figure 4-3 Inherent soil quality (ISQ) element map of the Prairies provinces: b) nutrient retention35

KM

D GoodGood to Moderate

Moderate to Poor

Poorwater

Area excludedA/ Ecozone boundaries

D

n

!SQ Rating

Results arepresented at Ecodistdct level

Figure 4-3 Inherent soil quality (ISQ) element map of the Prairies provinces: c) physical rooting conditions

36

KMResults are presented at Ecodistrict level

Figure 4-3 Inherent soil quality (ISQ) element map of the Prairies provinces: d) chemical rooting conditions37

r-_

f

_

r

_

r._

r._

,r-r ---r -----

KM

GoodGood to Moderatemoderate to PoorPoorwaterArea excluded

ISQ Rating

Results are presented at Ecodistrict level

Figure 4-3 Inherent soil quality (ISQ) map of the Prairies provinces : e) overall rating38

4.2.2 The Mixedwood Plains Ecozone

In the Mixedwood Plains Ecozone, about 83% of the total land area meets the minimum soil andclimatic requirements for agriculture. This 83% land was included for the assessment of ISQ(Table 4-3) . Results of the ISQ assessment using ISQ92 procedures in the included area weresummarized by provinces for each of the 4 elements and the overall rating of soil quality in Table4-4. The spatial distribution and patterns of ISQ status are shown in the generalized maps atEcodistrict level (Figure 4-5a,b,c,d,e)

At ISQ element level (Table 2-1), of the 83% of rated land, about 85-95% received `Good' or`Good to moderate' ratings for all four ISQ elements (Table 4-4) . Marginal ("Poor") ISQ ratingsvaried from 0% to 4% for the different ISQ elements . At the overall ISQ rating level, about 74%received `Good' or `Good to moderate' ratings, about 19% was rated as `Moderate to poor' andabout 7% was rated as `Poor'(Table 4-4)

Table 4-3 . Proportion ofarea ISQ rated oftotal land area in the Mixedwood Plains Ecozone

'~ As % oftotal land area (water area not included)z> Land area (notincluding water) calculated based on 1:1 million SLC data in Arc/Info format3) Area meets minimum ISQ requirements

Table 4-4. Summary ofISQ assessment in the Mixedwood Plains Ecozone

39

Ontario Portion(S . ON.)

Quebec Portion(SW. QU.)

The MixedwoodPlains Ecozone

103 ha %D 10' ha %1) 103 ha %')

Total land area) 8,340 100 2,764 100 11,104 100

Area ISQ rated3) 6,968 83.5 2,251 81.4 9,219 83.0

Rating classOntario Portion

(S . ON.)Quebec Portion(SW. QU.)

The MixedwoodPlains Ecozone

10' ha T %d) 103 ha %1) 10 3 ha %1)

Available porosity

Good 1,504 21 .6 872 38.7 2,376 25 .8

Good to moderate 5,158 74.0 702 31.2 5,860 63.6

Moderate to poor 292 4.2 295 13.1 587 6.3

Poor 14 0.2 382 17.0 396 4.3

Nutrient retention

Good 3,246 46.6 1,581 70.2 4,827 52.4

Good to moderate 2,919 41 .9 550 24.4 3,469 37.6

') As % of total area rated

Summary statistics for each element of soil quality in Table 4-4 can also be compared to thegeneralized maps for the Mixedwood Plains Ecozone (Figures 4-5a,b,c,d,e) to indicate areas withparticular soil quality conditions.

Moderate to poor 612 8.8 86 3.8 698 7.6

Poor 191 2.7 34 1.5 225 2 .4

Physical rooting conditions

Good 4,566 65.6 157 7.0 4,723 51 .2

Good to moderate 2,078 29.8 1,032 45.9 3,111 33 .7

Moderate to poor 324 4.6 1,057 46.9 1,380 15 .0

Poor 0 0.0 5 0.2 5 0.1

Chemical rooting conditions

Good 5,349 76.8 1,183 52.6 6,532 70.9

Good to moderate 1,619 23.2 933 41.4 2,552 27.7

Moderate to poor 0 0.0 135 6.0 135 1 .4

Poor 0 0.0 0 0.0 0 0.0

Overall rating

Good 612 8.9 47 2.1 659 7.2

Good to moderate 5,291 75 .9 866 38.5 6,157 66.7

Moderate to poor 860 12.3 919 40.8 1,779 19.3

Poor 205 2.9 419 18.6 624 6.8

Available porosity

Nutrient retention

Physical rooting conditions

Chemical rooting conditions

au aao-a..e: axa.a.oero moe..w:Ma- nr,a-mr.oc r-roor

o-o.oao-M- o.ero moa..w; n+ .r-aaea-mr. . .; r-roor

Overall ISQ rating

Figure 4-4. Regional differences of ISQ ratings in the Mixedwood Plains Ecozone

Figure 4-5 Inherent soil quality (ISQ) element map of the Mixedwood Plains Ecozone: a) available porosity42

FIgure 4-5 Inherent soil quality (ISQ) element map of the Mixedwood Plains Ecozone: b) nutrient retention43

London

Good to ModerateModerate to PoorPoorwaterEcozone boundaries

htoj1p

0 75 150 225

KM

Results are presented at Ecodistrict level

Montreal

Figure 4-5 Inherent soil quality (ISQ) element map of the Mixedwood Plains Ecozone: c) physical rooting conditions44

FIgure 4-5 Inherent soil quality (ISQ) element map of the Mixedwood Plains Ecozone : d) chemical rooting conditions45

Good0 Good to Moderate

Moderate to PoorPoorwater

A/ Ecozone boundaries

ISQ Rating

Results are presented at Ecodistrict level

FIgure 4-5 Inherent soil quality (ISQ) map of the Mixedwood Plains Ecozone: e) overall rating46

4.3 ISQ and Potential Land Supply

At broad national and regional levels, ISQ rating procedures provide a general overview of soilquality in each region and indicate the spatial variation of inherent soil quality from one area toanother . They also provide an estimation of the potential land supply for agricultural cropproduction, as well as the quantity of land with each ISQ class .

Only a limited area in Canada has climatic and soil conditions suitable for production of annualcrops . The potential land supply for crop production in Prairies and the Mixedwood PlainsEcozone, based on a broad regional ISQ assessment, is shown in Table 4-5 and 4-6 respectively .Mineral soil areas that met this climatic criteria were then evaluated in terms of inherent soilquality, using ISQ92 and ISQ94 procedures, as described in Appendix 3 and 4.

Table 4-5 . Potential land supply based on ISQ assessment in comparison to actual land use in the Prairiesprovinces.

')As % of total land area (water area not included)2) Based on climate and minimum ISQ requirementsWith ISQ rating better than poor

4) Based on 1991 Census ofAgriculture data') Based on 1989 AVHRR land cover data

In the Prairie provinces, over one-third (37%) of the total land area meets the minimum soil andclimatic requirements for agriculture, and about one quarter has potential for annual cropping (anISQ rating better than `Poor' class) . Comparing these figures to the actual land use based on the1991 Census of Agriculture, it indicates that nearly 85% of land suitable for agricultural use iscurrently farmed . Because a significant amount of land suitable for agricultural use (potentialfarmland) has been used by other alternative land uses, such as national and provincial parks,forest reserves, urban areas, and military reserves, most of the good agricultural land (in the top 3

47

Alberta Saskatchewan Manitoba Prairies

103 ha %') 103 ha %D 103 ha %') 10 3 ha %')

Total land area 63,023 100 58,971 [ 100 55,378 100 177,373 100

Estimates ofpotential agricultural land supply

Land suitable for agriculturalcrop production2) 24,064 38 .2 31,038 52.6 10,495 19.0 65,593 37.0

Land suitable for annual cropproduction' 16,442 26.1 28,921 49 .0 7,280 13.1 52,642 29.7

Estimates of actual agricultural land use

Total farmland4) 20,811 33.0 26,865 45.6 7,724 13.9 55,401 31 .2

Area with crop cover) 12,570 19.9 20,845 35.3 5,910 10.7 39,325 22.2

Cultivated land4) 11,063 17.6 19,172 32.5 5,058 9.1 35,293 19.9

ISQ ratings classes) and much marginal land (in the fourth or "Poor" ISQ ratings class) is alreadyin production.

Table 46. Potential land supply based on ISQ assessment in comparison to actual land use in the MixedwoodPlains Ecozone.

')As % of total land area (water area not included)')Based on climate and minimum ISQ requirements

- 3) With ISQ rating better than poor4~ Based on 1991 Census of Agriculture datas~ Based on 1989 AVHRR land cover data

In the Mixedwood Plains Ecozone, climatic and soil conditions are more favorable for agriculturalproduction. About 83% of the total land area meets the minimum climatic and soil requirementsfor agriculture, and about 77% of the total land area has potential for annual cropping (an ISQrating better than `Poor' class) . Comparing with actual agricultural land use, nearly 68% of landsuitable for agricultural use is currently farmed. . Considering the amount used by other competingnon-agricultural land uses (for example, about 25% and 2% of total land area in the MixedwoodPlains Ecozone are under forest and urban uses respectively based on 1989 AVHRR satelliteimagery), the potential land supply for agricultural production is limited.

The estimates of potential land supply by ISQ methods in both Prairie provinces and theMixedwood Plains Ecozone are close to the estimates of the first 5 classes of agriculturalcapability assessment of soil by the Canada Land Inventory (CLI) conducted in 1970s (Shieldsand Nowland, 1975) .

48

Ontario Portion(S . ON.)

Quebec Portion(SW. QU.)

The MixedwoodPlains Ecozone

103 ha V 103 ha %D 103 ha %D

Total land area 8,340 100 2,764 100 11,104 100

Estimates of potential agricultural land supply

Land suitable for agricultural cropproduction') 6,968 83.5 2,251 81 .4 9,219 83.0

Land suitable for annual cropproduction') 6,763 81.0 1,832 66.3 8,595 77.4

Estimates ofactual agricultural land use

Total farmland) 4,843 58.1 1,550 56.1 6,393 57.6

Area with crop cover') 5,727 68.6 1,837 66.5 7,564 68 .1

Cultivated land4) 3,280 35.1 989 32.5 4,269 38 .4

4.4 Areas Susceptible to Change in Soil Quality

Agricultural areas of Canada with a high Soil Quality Susceptibility to change (SQS) wereidentified and mapped with the GIS procedures documented in the Chapter 3. Two major typesof SQS indicators were recognized : biophysical indicators and land use and managementindicators . The SQS, indicators and threshold values derived from available regional data basesare shown in Table 4-7 . All SQS indicators were compiled at the component level of SoilLandscapes of Canada polygons .

Areas susceptible to change in soil quality due to biophysical factors for westem Canada andeastern Canada are shown in Figures 4-6a and 4-7a respectively . Areas with relatively highsusceptibility are those where more than one indicator are found, especially where the backgroundshows the overall ISQ rating is Poor (the most limiting of the four ISQ elements) .

Areas susceptible to change in soil quality due to land use and management factors for westernCanada (Prairies and Boreal Plains Ecozones) and eastem Canada (Mixedwood Plains Ecozone)are shown in map form in Figures 4-6b and 4-7b respectively . The proportion of land susceptibleto soil quality changes identified by the selected SQS indicators is summarized in Table 4-7 and4-8 .

Depth of topsoil is a most significant biophysical indicator . Canadian soils have been formedsince last glacial period (10,000 B .P.) and are shallow . Between 8.4 and 56.3% of the potentialagricultural land in individual provinces was less or equal to the chosen depth threshold of 15 cm.For most provinces, the steep slope indicator identified a small but significant proportion of thepotential agricultural land (9 - 15 .5%) except for Quebec where the agricultural area assessed waspredominantly marine and fluvial sediments . Western Canadian soil were formed under grasslandvegetation, with high organic carbon content in the surface horizon . Eastern Canadian soils wereformed under forest vegetation with lower organic carbon content, and also have a longer historyof intensive crop production. Low organic carbon content of the topsoil is a more seriousproblem in eastern Canada than in western Canada.

Soil quality susceptibility to change due to land use and management factors varies markedlybetween different ecozones in Canada. A large proportion of the agricultural area in theMixedwood Plains Ecozone, especially in southwestern Ontario, is susceptible to soil qualitychange as it is predominantly crop land, with intensive row cropping . In the Prairies and BorealPlains Ecozones of western Canada, row cropping is insignificant, but approximately 3-7% of thefarmland area has a high percentage (>30% of farmland) of summerfallow practices . Most of thesurnmerfallow area occurs in the portion of the Prairies Ecozone, where soil moisture is limitingfor annual dryland crop production, and summerfallow has traditionally been used as part of thecrop rotation .

Areas with the greatest susceptibility to soil quality change are those with a combination of

49

biophysical and land use and management factors . For example, areas with steep slopes and ahigh percentage of summerfallow or row cropping have a greater susceptibility to soil qualitychange than areas with only a single SQS factor . About 2-3% of the potential agricultural area ofthe Prairies and Boreal Plains Ecozones, and 7- 9% of the Mixedwood Plains Ecozone issusceptible due to both biophysical conditions and land use and management practices .

Table 47. Proportion of susceptible areas of soil quality change in the Prairies provinces

') Based on SLC dataz) As % of total land area assessed for ISQ (see Table 4-1 and 4-3)3)Based on 1991 Census of Agriculture data4) As %of total farmlands) Area where at least one of the bio-physical indicators overlaps with at least one of land use and managementindicators

SQS Indicators Alberta Saskatchewan Manitoba Prairies

A) SQS indicated by soil and landscape conditions') (%Z))

Shallow topsoil (A horizon thickness < 15cm) 16.7 63 .5 37.0 42.1

Low organic carbon content of topsoil (Ahorizon OC < 1%) 0.1 0.6 1 .5 0.6

Steep surface slope (slope steepness > 9%)13 .5 15 .5 9.0 13 .7

High erodible surface texture (surfacetexture = silt or silt loam) 18 .2 8.8 0.8 11.0

B) SQS indicated by land use andmanagement practices') (%1))

High cropping intensity ( area under crop>70% of farmland) 3.0 3.4 32.1 7.2

High level of `unfriendly' practices(summerfallow > 30% of farmland) 2.8 7.3 0.0 4.6

C) SQS indicated by both soil-landscape conditions and land use and management practices (% 2))

Indicators of co-occurance s> 1.9 3.0 1 .8 2.4

Table 48. Proportion ofsusceptible areas ofsoil quality change in the Mixedwood Plains Ecozone

') Based on SLC dataz> As % of total land area assessed for ISQ (see Table 4-1 and 4-3)')Based on 1991 Census of Agriculture dataa) As % of total farmlands) Area where at least one ofthe bio-physical indicators overlaps with at least one ofland use and managementindicators

Broad scale areas with particular combinations of ISQ ratings and SQS conditions can be readilyidentified using GIS mapping techniques and the tools developed in this project. These areas canbe targeted for more detailed analysis and monitoring or delivery of programs to promotealternative land use and management practices to enhance long term agricultural sustainability .

SQS indicators Ontario Portion(S . ON.)

Quebec Portion(SW. QU.)

The MixedwoodPlains Ecozone

A) SQS indicated by soil and landscape conditions'? (%'))

Shallow topsoil (A horizon thickness < 15cm) 51 .5 32.5 46.9

Low organic carbon content of topsoil (Ahorizon OC < 1%) 11 .4 16.5 13.2

Steep surface slope (slope steepness > 9%)12.0 1 .5 10.0

High erodible surface texture (surfacetexture = silt or silt loam) 15.0 2 .9 12.6

B) SQS indicated by land use and management practices') (0/04) )

High cropping intensity 1( area under crop >70% of farmland) 42.1 30.0 39.1

High cropping intensity 2 ( row crops > 60%of cropped land) 40.3 26.8 37 .1

C) SQS indicated by both soil-landscape conditions and land use and management practices (%Z))

Indicators of co-occurance 7.3 8 .7 8.0

0 100 200 300

KM

SQS INDICATORS

Shallow topsoil (< 15 cm)Low organic carboncontent oftopsoil (< 190)Steep slope (> 9%)High erodible surfacetexture (silt or siltloam)waterArea excluded

N Ecozone boundaries

SOS indicators are presented at SLC polygon level

Figure 4-6 Soil quality susceptibility (SQS) map of the Prairies provinces: a) biophysical52

KM

0

High intensiveland use (cropland> 7096 offarmland)High level of'unfriendly' landmanagementpractice(summerfallow > 3096offarmland)SQS not indicatedwaterArea excluded

n/ Ecozone boundaries

SOS indicators are presented at SLC polygon level

Figure 4fi Soil quality susceptibility (SQS) map of the Prairies provinces : b) land use and management53

t'

~ ia 7RJ7-AMA 6..lfl~~r.~

i~~~_

pr,~wrcspW1 aI ~z~~~r r~is W~~

~~w"wymawi

Shallow topsoil (< 15 cm)Low organic carboncontent oftopsoil (< 196)Steep slope (> 996)High erodible surfacetexture (silt or silt loam)SQS not indicatedwaterN Ecozone boundaries

0

SQS INDICATORS

75KM

150 225

SOS indicators are presented at SLCpolygon level

Figure 4-7 Soil quality susceptibility (SQS) map of the Mixedwood Plains Ecozone: a) biophysical54

Figure 4-7 Soil quality susceptibility (SQS) map of the Mixedwood Plains Ecozone : b) land use and management55

4.5 Implications of Changing Land Use and Management Practices on Soil Quality

Land use and management practices, such as high intensity cultivation or summerfallow, areindicators of the potential decline in soil quality . While actual soil quality change (SQC) can notbe directly measured at broad national and regional scales, changes in these land use andmanagement indicators, can be used as an indication of the trends in soil quality change. It isuseful to conduct this kind of analysis in conjunction with inherent soil quality (ISQ assessmentsto locate areas where changes in soil quality are most likely and where more detailed assessment isappropriate . In this study, data of the two census years (1981 and 1991) were used . The areaswhere changes occurred are shown in Figure 8 for the Prairies and Boreal Plains Ecozones andFigure 9 for the Mixedwood Plains Ecozone. Numbers showing the direction and magnitude ofchange over the 10 year period are presented in Table 4-9 and 4-10 .

Some conservation practices, such as conservation tillage and no-till, can halt or reverse soildegradation, or at least reduce the risks . Conservation tillage and no-till management have beenadopted in the major cropping areas of Canada since 1981 . The location and extent of thesespractices could be mapped (only for 1991 as data were not collected prior to this date) toindicated areas where soil quality may be improving and becoming less susceptible to change

Table 4-9 and 4-10 lists the estimates of the changes of selected indicators of land use andmanagement practices between 1981 and 1991, the last two Census of Canada periods . Theseareas of change in management practices are also shown in map form for the Prairies provinces(Figure 4-8) and the Mixedwood Plains Ecozone (Figure 4-9) .

Table 4-9. Change in selected SQS indicators in the Prairies provinces from 1981 to 199')

'~ Based on 1981 and 1991 Census ofAgriculture dataz> As % of total farmland

SQS indicators Year Alberta Saskatchewan Manitoba Prairies(%2))

High cropping intensity 1981 1 .2 1 .4 21 .3 4.2(area under crop > 70% offarmland) 1991 3.0 3.4 32.1 7.2

High level of unfriendly' 1981 0.8 13.5 0.0 6.9practices (summerfallow >30%) 1991 2.8 7.3 0.0 4.6

Table 4-10. Change in selected SQS indicators in the Mixedwood Plains Ecozone from 1981 to 1991')

') Based on 1981 and 1991 Census ofAgriculture dataz) As %of total farmland

There has been about 3% and 5% increase in areas of high cropping intensity (>= 70% offarmland) in the Prairies provinces and the Mixedwood Plains Ecozone respectively over the 10year period . The area of extensive use of summerfallow (>= 30% of farmland) decreased slightlyin some areas in the Prairies provinces (Table 4-5 and Map 4-10) . Also conservation tillage andno-till practices have been adopted and used by many farmers in the past decade (Table 4-11 and4-12) . This might indicate that the soil quality in some areas are improving and becoming lesssusceptible to major degradation processes such as decline in organic matter and erosion by windand water.

Table 4-11 . Conservation tillage and no-till practices used in the Prairies provinces (1991)')

') Based on 1991 Census ofAgriculture dataz) As % of total land prepared for seeding.

Table 4-12 . Conservation tillage and no-till practices used in the Mixedwood Plains Ecozone (1991)')

') Based on 1991 Census of Agriculture datas) As %of total land prepared for seeding.

57

SQS indicators Year Ontario Portion(S . ON.) (%2))

Quebec Portion(SW. QU.)(%2))

The Mixedwood PlainsEcozone (%2))

High cropping intensity 1 ( 1981 37.3 23.2 33.9area under crop > 70% offarmland) 1991 42.1 30.0 39.1

High cropping intensity 2 ( 1981 43.4 18.8 37 .6row crops > 60% of croppedland) 1991 40.3 26.8 37.1

Tillage Practices Alberta(%)2)

Saskatchewan(%)z)

Manitoba -(%)z)

Prairies(%)z)

Conservation tillage 24.3 25.7 28.7 25.8

No-till 2.7 10 .2 4.6 6.9

Conservation tillage and no-till 27.0 35 .9 33.3 32.7

SQS indicators Ontario Portion(S . ON.) (%)Z)

Quebec Portion(SW. QU.) (%)Z )

TheMixedwoodPlains Ecozone (%)z)

Conservation tillage 17 .7 12.2 16.5

No-till 3 .3 1.3 2.9

Conservation tillage and no-till 21 .0 13 .5 19.4

r r _

r

,

F-

r

r

r- -

r---

KM

CHANGE OFSUSCEPTIBLE AREAS

Areas indicatedfrom1981 dataAreas indicatedfrom1991 dataAreas indicatedfromboth 1981 and 1991 data

0

SOSindicators arepresented at SLCpolygon level

Figure 4-8 Changes of selected SQS indicators of land use and management in the Prairies provinces from 1981 to 1991

58

LDndon

Areas indicatedfrom1981 dataAreas indicatedfrom1991 dataAreas indicatedfromboth 1981 and 1991 dataSQS not indicatedwaterEcozone boundaries

00

CHANGE OFSUSCEPTIBLEAREAS

rrr

onto

0 75 150 225

KM

SOSindicators are presented at SLCpolygon level

Figure 49 Changes of selected SQS indicators of land use and management in the Mixedwood Plains Ecozone from 1981 to 199159

5.0 Discussion

5.1 The Sensitivity of the ISQ Procedures

Land resource data sets are essential for the spatial analysis of Inherent Soil Quality . Broad scaleregional and national data sets provide comprehensive coverages, but have coarse spatialresolution, and a limited set of attributes . More detailed scale data sets provide finer spatialresolution, and a larger number of attributes to enable more precise interpretive ratings, however,the coverage areas may be limited. Different ISQ rating algorithms have been developed to usethe most commonly available Canadian data sources . An comparison of these methods and datasources is provided in this section.

Two separate investigations were conducted to evaluate the sensitivity of ISQ procedures . Thefirst study (Section 5.1 .1) is an evaluation of ISQ sensitivity at broad regional scales, using twodifferent data sets and ISQ algorithms . The second study (Section 5.1 .2) is an evaluation of ISQsensitivity to changes in map scale . A single ISQ rating procedure (ISQ94) was used for acomparative analysis of the same test area, using both detailed and broad scale data sets .

5.1.1 Sensitivity to Different Data Sets and Algorithms

Two separate ISQ procedures were developed for ISQ assessments at broad regional scales .Both use 1 :1 million scale Soil Landscapes of Canada digital maps. The first method ("ISQ92")uses the generalized SLC attributes in the Dominant ("DOM") and Subdominant ("SUBDOM")extended legend files . These data sets are available for all of Canada . Details of the ISQ92 ratingalgorithms are in Appendix 3.

The second ISQ method ("ISQ94") uses the more extensive set of modal soil attribute informationavailable in standardized Soil Names and Soil Layer Files ("SNF' and "SLF' files). While initiallydeveloped for use with detailed soil maps, the more generalized Soil Landscapes of Canada mappolygons are described in terms of soil series components (SLC CMP file records), and can belinked to SNF and SLF soil attribute files . ISQ94 procedures can therefore be used to evaluateboth detailed soil maps and SLC maps (Appendix 4). This capability is currently limited to certainregions of Canada, such as the prairie provinces, where the SNF and SLF files have beencompleted for all SLC soil components. National or regional ISQ assessments may therefore usea combination of ISQ92 or ISQ94 data sets and algorithms for particular regions .

The relative sensitivity and reliability of the ISQ92 and ISQ94 procedures was evaluated, usingthe Prairies provinces, where data sets for both methods are available. A summary of the overallISQ classification results for the prairies, for each element of soil quality, are indicated in the barcharts in Figure 5-1 . Alternatively, this can also be expressed in terms of classification agreementor disagreement, on an areal extent basis, as summarized in Table 5-1 .

60

The ISQ92 and ISQ94 methods show a reasonable level of agreement. On an overall, areaweighted basis, nearly 50% of the agricultural land area was rated in the same ISQ class by bothmethods, while a further 35% of the total land area was rated within one class of each other. Thelevel of agreement varied between the different ISQ elements . Areas with either completeagreement, or agreement within one ISQ class, varied from a high of 92.5% for the NutrientRetention element to a low of 75.2% for the Available Porosity element (Table 5-1) . ThePorosity Element is also the element that has the greatest difference between the ISQ92 andISQ94 ratings algorithms . The ISQ92 algorithm rates porosity in terms of moisture supplylimitation, while ISQ94 has separate subelements to evaluate both moisture and air supplylimitations . Other differences between ISQ92 and ISQ94 ratings results may be attributed todifferences in the dominant soils and soil properties in the different data sources, and to morestrict exclusion procedures used in the ISQ94 algorithms .

Both ISQ92 and ISQ92 are based on the same theoretical framework of soil quality assumptions,and use a similar set of four ISQ elements for the cereal crop production function . AlthoughISQ94 is a more rigorous rating procedure than ISQ92, there is a relatively high level ofagreement between the two systems within the prairie region. This indicates that ISQ ratings, atbroad scales, are relatively compatible, and not particularly sensitive to differences in data sourcesor ratings algorithms . ISQ92 procedures can therefore be used as a substitute for ISQ94procedures, in areas where ISQ94 procedures cannot currently be used due to data limitations .

.

Available porosity

Nutrient Retention

physical rooting conditions Chemical rooting conditions

Figure 5-1 Comparison ofthe results of ISQ92 and ISQ 94 in the Prairies provinces

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Table 5-1 . Comparison of ISQ94 and ISQ92 ratings in the Prairies provinces

') included and rated in ISQ92 but not in ISQ94, as ISQ94 has more strict excluding procedures .

Agreement DisagreementTotal

ISQ Elements 0 class off 1 class off 2 classes off 3 classes off Other"

Area Area Area Area Area Area10 2 ha % 102 ha % 102 ha % 102 ha % 102 ha % 102ha %

Available Porosity 403,439 100.0 143,576 35.6 159,449 39.6 89,411 22.2 1,501 0.3 9,467 2.4

Nutrient 403,439 100.0 204,064 50.6 168,889 41.9 30,299 7.5 185 - - -Retention

Physical Root 403,439 100.0 259,077 64.2 84,689 21.0 50,804 12.6 3,497 0.9 5,331 1.3Conditions

Chemical Root 403,439 100.0 181,223 44.9 163,714 40.6 35,897 8.9 13,559 3.4 9,043 2.2Conditions

5.1.2 Sensitivity to Map Scales

Inherent Soil Quality ratings can also vary with the scale or precision of the spatial databases . Inthis study, the same ISQ94 rating procedure was evaluated using both detailed and broad scaledigital soil data bases, for the same map area. This comparison indicates how well ISQinterpretations at broad regional scales can portray or represent the more detailed informationavailable for detailed soil maps. It is important to understand how much of the detailed variationis masked at broader scales (coarser resolution), and whether this introduces any systematic biaswithin the classification results .

A single study area was selected in south central Manitoba between Brandon and Winnipeg(Figure 5-2) . This area covers 12 Rural Municipalities (over 1 million hectares), and represents awide range of different soil landscape conditions within the Prairie ecozone . Soil landscapesinclude extensive areas of lacustrine sands, loams and clays, glaciofluvial and eohan sands, alluvial

soils, marshes, and portions of three separate tillplains .

The broad scale analysis was conducted using the1 :1 million scale Manitoba SLC digital map andSoil Component file . 25 SLC polygons,representing 97.44% of the total area, met theselection criteria (i.e . occupied over 4000 ha andhad between 20% and 100% of their total areawithin the study area) . The detailed soil database coverage for the test area consisted of 12separate Rural Municipality maps (approximately

Figure 5-2 . Location of the scale sensitivity test

17,400 soil polygons), at, a nominal map scale ofarea in Southern Manitoba.

1 :100,000 . The "broad scale" and "detailedscale" data sets were both evaluated using ISQ94rating procedures, with soil polygon components

linked via common soil codes to the same global Soil Names and Soil Layer modal soil propertyfiles . Since the technical procedures were the same, differences in ratings results can be attributedto differences in map scale and spatial resolution .

A comparison of the overall broad scale and detailed scale ISQ classification results for theManitoba test area, for each element of soil quality, are indicated in Figure 5-3 . The results showa good general level of agreement between the detailed and generalized assessments . For all fourISQ elements, both detailed and broad scale methods are in agreement as to the relative rankingof the ISQ classes . The detailed and broad scale data bases are also in close agreement as to thepercentages of the overall test area that does not meet the criteria of cereal crop production ;approximately 28% and 29% respectively .

An alternative comparison was made of the detailed and broad scale ISQ classification results for

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the 25 significant SLC polygons within the test area (Table 5-2) .

Table 5-2 . Comparison ofthe ISQ 94 ratings at different scales in Southern Manitoba .

1) number of SLC polygons

Available porosity

Physical rooting conditions

Nutrient Retention

Chemical rooting conditions

Figure 5-3. Comparison of the ISQ94 ratings at different scales in Southern Manitoba

64

Agreement DisagreementTotal SLC

ISQ Elements polygons" 0 class off 1 class off 2 classes off 3 or moreclasses off

Number % Number % Number % Number % Number %

Available 25 100 12 48 5 20 7 28 1 4Porosity

Nutrient 25 100 18 72 3 12 3 12 1 4Retention

Physical Rooting 25 100 21 84 1 4 0 0 3 12Conditions

Chemical Rooting 25 100 12 48 8 32 1 4 4 16Conditions

Overall Rating 25 100 11 44 9 36 4 16 1 4(most limiting)

Exact agreement as to the dominant (modal) overall ISQ class rating occurred in 44% (11 out of25) of the SLC polygons, while a further 36% (9 of 25) were within one class . Overall ISQ

ratings were therefore in either exact agreement, or within one class, for 80% (20 out of 25) ofthe SLC polygons within the test area. For the individual ISQ elements, the percentage of SLCpolygons in agreement, or in approximate agreement (within one rating class) varied between68% for Porosity, 84% for Nutrient Retention, 88% for Physical Rooting, and 80% for ChemicalRooting conditions . This indicates a good general correspondence between the detailed andbroad scale ratings, for most SLC polygons . However, approximately 20% of the SLC polygonsshow a significant difference in classification results between the two map scales .

A more detailed analysis of the ISQ ratings within selected SLC polygons in the test area isprovided in Table 5-3 . The ISQ ratings classes with the highest areal coverage in each SLCpolygon, for both detailed and broad scale methods, are shown in bold . This illustrates moreclearly the divergence of the ISQ rating results between detailed and broad scales .

At detailed scales, several hundred soil polygon components are evaluated within each SLC area.ISQ ratings are typically distributed over a wide range of rating classes (from "Good" to "NotRated"), reflecting the variety of different soil landscape conditions in the detailed soil maps.

At broad scales, SLC polygons are represented in the Soil Component file by a comparativelysmall number of soil components, typically only 2 or 3 soils per polygon. Much of the variabilityin the detailed ratings is therefore masked. For many SLC polygons, such as SLC 44 and 59(Table 5-3), the dominant ISQ interpretive ratings at both scales remain closely matched.

For other SLC polygons, broad scale results may be unrealistically high or low, in comparison todetailed data bases . For example, SLC 58 is represented by only a single soil component (100%),and the soil, an eolian Regosol, received an unsuitable ISQ rating . Only 27.1% of the SLC wasconsidered unsuitable for cereal crop production using the detailed soil data bases for the samearea . Conversely, SLC 52 is represented by two soils components at broad scales, with the firstcomponent (70%) rated "Good to Moderate" and the second (30%) rated "Moderate to Poor".Both soils, representing 100% of the polygon, met the criteria for ISQ ratings . However, 44.7%of the polygon area was considered unsuitable when rated using the detailed soil data bases .

Broad scale ISQ ratings for individual SLC polygons are therefore critically dependent on thesoils selected in the SLC CMP files . For approximately 20% of the SLC polygons within theManitoba test area, the soil components currently in the SLC CMP were not adequate torepresent the modal ISQ conditions, as rated by the detailed map coverage . At the present time,somewhat more reliable results can be obtained using detailed soil data bases, re-aggregated to anSLC level . This option is only available in areas where detailed digital soil database coverage hasbeen completed to national soil data base standards .

Table 5-3. Comparison of detailed and broad scale ISQ ratings for selected SLCpolygons in Southern Manitoba.

') G =Good; G-M = Good to moderate ; M-P=Moderate to poor ; P=Poor; N =Not rated2) a) = rating at detail scale; b) = rating at broad scaleDominant rating class for each SLC polygon at each scale is shown in bold .

SLC Available Porosity %) Nutrient Retention (%) Physical Root Conditions (%) Chemical Root Conditions (%)GO G-M M-P P N GO G-M M-P P N GO G-M M-P P N G') G-M M-P P N

22 a) 2) 42.4 14.2 9 .2 7 .8 26.6 60.9 2 .9 9 .7 0.0 26.6 73.4 0.0 0.0 0.0 26.6 17.8 53.2 2.4 0.0 26.6

b) 0.0 0.0 55.0 10.0 35.0 65.0 0 .0 0 .0 0 .0 35.0 65.0 0.0 0.0 0.0 35.0 55.0 10.0 0.0 0.0 35.031 a) 40.6 1 .8 49.2 0 .0 8 .3 91.0 0 .0 0 .6 0 .0 8 .3 83.6 0.0 8 .0 0.0 8 .3 16.8 45.1 29.8 0 .0 8 .3

b) 70.0 0.0 30.0 0 .0 0 .0 100.0 0 .0 0 .0 0 .0 0 .0 100.0 0.0 0.0 0.0 0.0 30.0 0.0 70.0 0.0 0.032 a) 52.8 13.9 21 .6 3.1 8 .7 69.7 3 .3 18.3 0 .0 8 .7 86.8 0 .0 4 .4 0.1 8 .7 10.8 45.5 35.0 0.0 8.7

b) 100.0 0.0 0 .0 0.0 0.0 100.0 0 .0 0 .0 0 .0 0 .0 100.0 0 .0 0.0 0.0 0.0 0 .0 100.0 0.0 0.0 0.033 a) 77.9 3 .2 19.0 0.0 0.0 100.0 0 .0 0 .0 0.0 0 .0 100.0 0.0 0.0 0.0 0.0 0 .0 69.5 30.5 0.0 0.0

b) 0.0 70.0 30.0 0.0 0.0 30.0 0.0 70.0 0.0 0.0 100.0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 100.0 0.0 0.0a) 75.8 0 .5 19.7 0.0 4.1 95.4 0.0 0.5 0.0 4 .1 94.9 0 .0 1 .0 0 .0 4 .1 1 .2 76.3 18.4 0.0 4.1

44 b) 70.0 0 .0 0 .0 10.0 20.0 80.0 0.0 0 .0 0 .0 20.0 80.0 0 .0 0 .0 0 .0 20.0 0 .0 80.0 0.0 0.0 20.049 a) 14.4 56.8 12.8 0.0 16.0 25.1 2.1 56.8 0.0 16.0 84.0 0.0 0 .0 0 .0 16.0 60.7 18.5 4 .8 0.0 16.0

b) 70.0 30.0 0.0 0.0 0.0 70.0 0.0 30.0 0.0 0.0 100.0 0.0 0 .0 0 .0 0 .0 100.0 0.0 0 .0 0.0 0.052 a) 28.4 1 .9 24.1 0.9 44.7 47.1 0.0 8 .1 0.0 44.7 50.0 4.8 0 .0 0 .4 44 .7 2 .8 31 .8 19.7 1 .0 44.7

b) 70.0 0.0 30.0 0.0 0.0 100.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 0 .0 0 .0 0.0 100.0 0 .0 0.0 0.0-55 a) 4 .5 16 .5 5 .1 0.7 73.2 5 .7 0.0 21 .1 0.0 73.2 26.8 0.0 0 .0 0 .0 73.2 8 .3 16.2 2 .3 0.0 73.2

b) 0.0 0.0 10.0 0 .0 90.0 10.0 0.0 0.0 0.0 90.0 10.0 0.0 0 .0 0 .0 90.0 0.0 0.0 10.0 0.0 90.056 a) 9 .8 13 .4 3 .7 5 .2 67.9 10.2 1 .6 20.1 0.3 67.9 32 .1 0.0 0 .0 0 .0 67.9 13.6 13.4 5 .1 0.0 67.9

b) 0.0 30.0 0 .0 0 .0 70.0 0.0 0.0 30.0 0.0 70.0 30.0 0.0 0.0 0.0 70.0 0.0 30.0 0 .0 0 .0 70.057 a) 3.9 32.4 19.6 0 .0 44 .1 30.2 13.3 12.4 0.0 44.1 55.9 0.0 0.0 0 .0 44.1 0.0 49.6 6.3 0 .0 44 .1

b) 0.0 0.0 10.0 0 .0 90.0 10.0 0.0 0.0 0.0 90.0 10.0 0.0 0.0 0 .0 90.0 0.0 0.0 10.0 0.0 90.058 a) 3 .3 11 .4 54.7 3.5 27 .1 58.8 2 .3 11 .9 0 .0 27 .1 72.9 0.0 0.0 0.0 27.1 57.5 15 .1 0 .3 0 .0 27 .1

b) 0.0 0 .0 0 .0 0.0 100.0 0 .0 0.0 0 .0 0 .0 100.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 0 .0 0 .0 100.059 a) 60.2 17 .0 5 .4 1 .9 15.4 51.2 3 .1 29.8 0 .5 15.4 84.5 0.1 0.0 0.0 15.4 7 .2 59.7 17.2 0 .4 15.4

b) 80.0 20.0 0.0 0.0 0.0 80.0 0.0 20.0 0 .0 0 .0 100.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 0 .061 a) 56.1 14.4 4.0 1 .8 23 .8 54.0 9 .2 13 .1 0 .0 23.8 76.2 0.0 0.0 0.0 23.8 60.1 13 .9 2.3 0.0 23.8

b) 100.0 0.0 0.0 0.0 0.0 100.0 0 .0 0 .0 0 .0 0 .0 100.0 0.0 0.0 0.0 0.0 100.0 0.0 0 .0 0 .0 0 .0a) 44.9 6.2 24 .0 4.4 20 .5 73.2 5 .4 0 .9 0 .0 20.5 78.3 0.4 0.9 0.0 20.5 43.5 24.4 10.8 0 .7 20.5

62 b 90.0 0.0 0.0 10.0 0.0 40.0 60.0 0 .0 0 .0 0 .0 100.0 0 .0 0.0 0.0 0.0 90.0 10.0 0.0 0.0 0 .0

At broad regional scales, from 1 :500, 000 to 1 :2 million, SLC polygons are the appropriate unitsfor ISQ spatial analysis . Analysis using ISQ94 algorithms and SLC CMP data bases offer the bestcombination of precision and comprehensive coverage . This should be the method of choice, forareas where the SLC CMP files contain representative soil components, and Soil Names and SoilLayer data bases are successfully linked. GIS techniques can be used to assist in the upgrade ofexisting SLC CMP files, in areas where both detailed and SLC coverages coexist.

When ISQ classification results were further generalized for the entire test area, it was observedthat there was a high degree of similarity between the detailed and broad scale (SLC) methods(Figure 5-3) . Differences between the detailed and broad scale interpretations, perhapsfortuitously, appeared to cancel each other out when averaged over all 25 SLC polygons withinthe test area. This indicates that, although the broad scale analysis masks some of the detailedmap variations within each SLC polygon, it does not seem to introduce any systematic bias in themore generalized ratings for any of the ISQ elements .

For very broad regional or national scale analysis, at scales from 1 :2 million to 1 :20 million,individual SLC polygon ratings are typically reaggregated and summarized within broader landunits. These may be administrative units, such as crop reporting districts or provinces, orecological units, such as ecodistricts, ecoregions, or ecozones . At these very broad scales, thefiner resolution offered by detailed soil maps is not warranted, even in the limited areas of thecountry where such coverage is available . The coarser resolution SLC databases, analyzed byeither ISQ92 or ISQ94 procedures and reaggregated to larger units, should provide adequateprecision for such analysis .

5:2 Future Applications of ISQ and SQS Procedures

ISQ and SQS procedures were developed as tools for broad level land resource analysis, usingsoil quality definitions and currently available Canadian GIS data bases . While intended for broadscale planning and policy applications, they may be used to indicate areas where more detailedinvestigations are warranted.

Land resource data base coverages are expected to increase in both areal extent and precision inthe future . Completion of global Soil Names and Soil Layer data bases in eastern Canada willpermit use of more precise broad scale ISQ94 rating procedures . ISQ94 rating procedures canalso be employed at more detailed levels in additional areas, as detailed NSDB data bases arecompleted. Additional Census of Agriculture questionnaire data bases will extend the time frame,and permit more accurate forecasting of Soil Quality Susceptibility to change (SQS) .

Many refinements of the current ISQ rating procedures are also feasible, particularly regarding theintegration of climatic information . Currently, ISQ procedures only consider two climatic factors,Effective Growing Degree Days (EGDD), and soil moisture availability, as a function of soiltaxonomy. Both of these factors reflect only average long term conditions, and do not reflectprobabilities . Additional national climatic data bases are now available, with a wider range of

67

climatic attributes calculated on an ecodistrict basis . In several regions, climatic data bases arebeing enhanced with additional stations, refinement of climatic contours to account forphysiography, and more advanced probability calculations . These could all be utilized byenhanced versions of the current ISQ rating procedures .

ISQ rating procedures can also be modified to match the soil and climatic criteria of other croptypes . The distribution of the ISQ element ratings, and the total area that meets the minimum ISQrating criteria, may be significantly different than soil quality ratings for cereal production.

An interesting application of these ISQ techniques is the estimation of areas suitable for futureagricultural production, under global climatic change scenarios . Soil conditions for Canada arerelatively static, and are documented in the Soil Landscapes of Canada data base . Variousclimatic models predict global warming in northern areas of Canada, and possible increases inaridity in other areas, such as the southern prairies . If climatic model predictions (such as revisedeffective growing degree days contours) are available, ISQ procedures can be used to identify thefuture areas with favorable soil and climatic conditions for future types of crop production . Someregions may have a more favorable climate, but may have adverse soil conditions that limit anincrease in the potential agricultural land base.

Another application is the integration of ISQ GIS techniques with soil degradation models .Spatial analysis of ISQ can be done at different time periods, under a range of soil climatic,management, and degradation model scenarios . ISQ analysis can show the direction andmagnitude of predicted soil quality changes over space and time, for any particular area . This canbe a powerful tool for forecasting the effects of different management recommendations, anddetermining which alternatives are compatible with principles of sustainable development.

6.0 Conclusions

The current systems for assessment of inherent soil quality and soil quality susceptibility to changewere designed to use available databases and capabilities of existing GIS systems . The systemswere designed to be applied to broad regional and national level (1 :1 - 1 :5 million) . In addition,some procedures such as ISQ94, can be applied to detail-scale (1 :25000 - 1:50000) assessments .The results of the assessments may be combined with other environmental information : i) toassess sustainability of current soil and land management systems; ii) to target current andpotential 'problem areas' of soil quality change and land degradation for monitoring and detailedstudies ; iii) for State of Environment (SOE) reporting .

Technically, the systems and procedures were designed to be flexible enough to

incorporate additional data layers,adjust the rating criteria and algorithm for specific crops or other land userequirements,be used at more detailed levels, e.g . watershed and farm levels,combine with other analytical tools or models, e.g . USLE or RUSLE to assess thepotential effects of soil water erosion to soil quality at regional and national level .Results and models developed in other projects within SQEP may providecapabilities to enhance the ISQ and SQS assessment procedures .

This system cannot be directly compared with previous evaluation systems for Canada (forexample, Wang et al 1991, MacDonald and Brklacich, 1992 ; Brklacich and MacDonald, 1992,Pettapiece 1995), as the approach, objectives, databases and technical environments are not thesame. The evaluation of the sensitivity of the system to different data sets and scales indicates thatrunning ISQ rating program using alternative data sets or at different scales can achieve ratingwithin reasonable range .

Assessments of soil quality change requires repetitive monitoring and resampling of soil landscapeattributes, at specific sites or small plots, over a long time period. `Procedures to measure actualsoil quality change at broad scales were not developed, as the existing land resource data sourcesare not appropriate for this type of assessment. In the future it may be possible to provideassessments of predicted soil quality change, using process-based models in combination with landresource, climatic, and land use and management data sets . At the current time, Soil QualitySusceptibility to change (SQS) is offered as a means of indicating likelihood of changes in soilquality at broad regional scales .

More precise estimates require detailed, large scale data as well as modeling procedures tocharacterize soil modifying processes . However, the sequential assessment (for years with Censusof Agriculture Data) of soil quality and its spatial representation is operational at broad regionaland national scales using existing databases .

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APPENDIX 1. KEY TERMS AND ACRONYMS

AFFC

- Agriculture and Agri-Food CanadaAML

- Arc Macro Language (Arc/Info)Arc/Info - A commercial GIS produced by Environmental Systems Research Institute, CA, USAAVHRR - Advanced Very High Resolution RadiometerCanSIS - Canadian Soil Information SystemCoA

- Census of Agriculture (from Statistics Canada)CLI

- Canada Land InventoryCMP

- SLC Component File (CanSIS/NSDB)DBMS

- Database Management SystemDSM

- Detailed Soil Survey Map (CanSIS/NSDB)EGDD

- Effective Growing Degree DaysGIS

- Geographic Information SystemGPCRC - Greenhouse and Processing Crop Research CentreINFO

- DBMS component of Arc/Info .ISQ

- Inherent Soil QualityLSRS

- Land Suitability Rating System (Pettapiece et al, 1995)NSCP

- The National Soil Conservation Program (Canada)NSDB

- National Soil Data Base (Canada)Pamap

-Acommercial GIS produced by PCI Pacific GeoSolutions Inc., Victoria, CanadaP-PE

- Moisture Index (Precipitation-Potential Evapotranspiration)SC

- Soil Carbon (database, CanSIS/NSDB)SLC

- Soil Landscape of Canada (map, CanSIS/NSDB)SLF

- Soil Layer File (CanSIS/NSDB)SMUF

- Soil Map Unit File (CanSIS/NSDB)SNF

- Soil Names File (CanSIS/NSDB)SQC

- Soil Quality ChangeSQEP

- The Soil Quality Evaluation Program (under NSCP)SQS

- Soil Quality Susceptibility to change

Appendix 2. CanSIS NSDB Data Structures and Definitions

This appendix lists the data structures and data field names for the Canadian Soil InformationSystem National Soil Database files referenced in this report . Data field types are C (Character),D (Date), I (Integer), or N (Numeric) . Data fields used to link to other relational files areindicated (key) . Updated information is available from the CanSIS/NSDB web site athttp://res .agr.ca/ecorc/program3/cansis/ .

Table A2-1. SLC (version 1 .0) DONDnant and SUBdominant files attributes

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DOM Name SUB Name Type Width Attribute DefinitionPROVINCE PROVINCE C 3 provincial code and ma sheet number (key)POLYNUMB POLYNUMB C 4 polygon number (key)DOMKDMAT SUBKDMAT C 2 kind ofrock outcrop or other material at the surfaceDOMDISTR SUBDISTR C 3 percentage distribution ofrock or other surface materialGRIDLOCN GRIDLOCN C 3 'd code for locating polygonsDOMREGFM SUBREGFM C 1 regional landformDOMLOCSF SUBLOCSF C 3 local surface formDOMSLOPE SUBSLOPE C 1 sloe gradient classDOMPMDEP SUBPMDEP C 2 parent material mode ofdepositionDOMPMTEX SUBPMTEX C 4 parent material textureDOMDEVEL SUBDEVEL C 1 soil developmentDOMSRFTX SUBSRFTX C 4 surface texture of mineral soil to 15 cmDOMCFRAG SUBCFRAG C 1 coarse fragment content in control sectionDOMROOT SUBROOT C 3 rooting depthDOMCMPLR SUBCMPLR C 1 compacted, consolidated or contrasting layerDOMCMPDP SUBCMPDP C 1 depth to compacted, consolidated or contrasting layerDOMDRAIN SUBDRAIN C 1 drainage classDOMAVWAT SUBAVWAT C 1 available water capacity in upper 120 cm.DOMWATAB SUBWATAB C 1 depth to water tableDOMICETYSUBICETY C I ice typeDOMICECT SUBICECT C 1 ice contentDOMPERMA SUBPERMA C 1 permafrost occurrenceDOMACTLR SÜBACTLR C 3 active layer depth in permafrost soilsDOMPATGD SUBPATGD C 2 patterned and kindDOMPHCAL SUBPHCAL C 2 H of upper 15 cm of soil - CaCl2DOMPHWAT SUBPHWAT C 2 H of upper 15 cm of soil - waterDOMORGAN SUBORGAN C 2 organic carbon ofupper 15cmDOMNITRO SUBNITRO C 1 nitrogen content of upper 15 cm, % b weightDONII-IUMLR SUBHLJMLR C 1 thickness ofhumus layerDOMCALCA SUBCALCA C 1 calcareous class ofparent materialDINCLUS 1 SINCLUS1 C 2 soil inclusion 1DINCLUS2 SINCLUS2 C 2 soil inclusion 2DOMVEGET SUBVEGET C 2 vegetative cover and/or land use

Table A2-2 . SLC (version 1 .0) Component (CMP) file attributes

Table A2-3. SLC (version 1.0) Carbon Layer (CLYR) file attributes

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DOMLAKE SUBLAKE C 1 lake sizeDOMWATBD SUBWATBD C 1 water bodies, percentage coverage of polygonDOMRELIA SUBRELIA C 1 reliability classDOMCOMPL SUBCOMPL C 1 complexity classDOMNAMEI SUBNAME1 C 6 soil name 1DOMNAME2 SÜBNAME2 C 6 soil name 2DOMTEXGP SÜBTEXGP C 2 parent material texture groupAREAKHA AREAKHA N 7 area ofpolygon (kilohectares)

Number Name Type Width Attribute Definition1 POLYNUMB I 4 polygon number (key)2 COMPNT C 1 component (key)3 NUMB C 1 inclusion number (key)4 PERCENT 1 3 percent occurrence5 KINDMAT C 2 kind ofmaterial6 VEGET C 2 vegetation/land use7 PMDEP C 2 mode of deposition8 CFRAG C 1 coarse fragment content9 ROOTDP C 3 rooting depth10 DRAIN C 1 drainage11 DEVEL C 1 soil development12 CALO C 1 calcareous class13 LOCSF C 3 local surface form14 SLOPE C 1 slope gradient15 SOILCODE C 3 soil name code (key)16 MODIFIER C 3 soil name modifier (key)

Number Name Type Width Attribute Definition1 PROV C 2 province (key)2 SHEETNO 1 2 ma sheet number (key)3 POLYNUMB 1 4 polygon number (key)4 COMPNT 1 2 component (key)5 NUMB I 2 inclusion number (key)6 LAYERNO I 1 layer number (key)7 LAYER C 3 lay zon designator8 THICK 1 3 thickness9 THICK-ME C 1 thickness - reliability10 TEXTR C 4 texture11 TEXTR-ME C 1 texture - reliability

r 12 BDENS N 4.2 bulk density

Table A2-4. DSM Soil Map Unit File (SMUF) attributes

Table A2-5 . Soil Name File (SNF) attributes

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Number Name Type Width Attribute DefinitionI PROVINCE C 2 province (key)2 MAPUNITNOM C 60 ma unit name (key)3 SOIL_CODE1 C 3 soil name code of soil 1 (key)4 MODIFIERI C 3 soil name modifier of soil 1 (key)5 EXTENT1 N 3 extent of soil I6 SOILCODE2 C 3 soil name code ofsoil 2 (key)7 MODIFIER2 C 3 soil name modifier of soil 2 (key)8 EXTENT2 N 2 extent of soil 29 SOILCODE3 C 3 soil name code of soil 3 (key)10 MODIFIIER3 C 3 soil name modifier of soil 3 (key)11 EXTENT3 N 2 extent of soil 312 SLOPEPI N 5.1 sloe stee ness of soil 1 (percent)13 SLOPEP2 N 5 .1 sloe stee ness of soil 2 (percent)14 SLOPEP3 N 5 .1 sloe stee ness of soil 3 (percent)15 STONE1 C 1 stoniness of soil 116 STONE2 C 1 stoniness of soil 217 STONE3 C 1 stoniness of soil 318 DATE D 8 date ofrevision

Number Name Type Width Attribute Definition1 PROVINCE C 2 province (key)2 SOILNAME C 24 soil name3 SOIL CODE C 3 soil name code (key)4 MODIFIER C 3 soil name modifier (key)5 LU C 1 land use type (key)6 KIND C 1 kind of material7 WATERTBL C 2 water table presence8 ROOTRESTRI C 1 root restricting layer number9 RESTR TYPE C 2 root restricting10 DRAINAGE C 2 drainage class11 MDEP1 C 4 parent material mode of deposition12 MDEP2 C 4 parent material mode of deposition13 MDEP3 C 4 parent material mode of deposition14 ORDER C 2 soil classification - Order15 SGROUP C 4 soil classification - Sub-group

13 BDENS-ME C 1 bulk density - reliability14 OCARB N 4.1 organic carbon15 OCARB-ME Î C T 1 organic carbon - reliability

Table A2-6 . Soil Layer File (SLF) attributes

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Number Name Type Width Attribute Definition1 PROVINCE C 2 province (key)2 SOILCODE C 3 soil code (key)3 MODIFIER C 3 modifier (key)4 LU C 1 land use (key)5 LAYER-NO C 1 horizon number6 HZN_LIT C 1 horizon litholo 'cal discontinuity7 HZN MAS C 3 master horizon8 HZN_SUF C 5 horizon suffix9 HZN_MOD C 1 horizon modifier10 UDEVTH N 3 upper depth11 LDEPTH N 3 lower depth12 COFRAG N 3 coarse fragments13 COFRAG# 1 314 DOMSAND C 2 dominant sand fraction15 VFSAND N 3 very fine sand16 VFSAND# 1 317 TSAND N 3 total sand18 TSAND# 1 319 TSILT N 3 total silt20 TSILT# I 321 TCLAY N 3 total clay22 TCLAY# 1 323 ORGCARB N 5 .1 organic carbon24 ORGCARB# 1 325 PHCA N 4.1 H in calcium chloride26 PHCA# I 327 PH2 N 4.1 PH as per project report28 PH2# 1 329 BASES N 3 base saturation30 BASES# I 331 CEC N 3 cation exchange capacity32 CEC# 1 333 KSAT N 7.3 saturated hydraulic conductivity34 KSAT# I 335 KPO N 3 water retention @ 0 kP

16 GGROUP C 3 soil classification - Great Group17 PROFILE C 14 Detail II file header (key)

18 DATE D 8 date ofrevision

Note : A field name with a trailing # indicates the number ofobservations used in determining the value. These fields areoptional and may not always be present. A code of zero (0) indicates an estimated value .

36 KPO# 1 337 KP10 N 3 water retention @ 10 kP38 KP10# 1 339 KP33 N 3 water retention @ 33 kP40 KP33# 1 341 KP1500 N 3 water retention @ 1500 kP42 KP1500# 1 343 BD N 5 .2 bulk density44 BD# 1 345 EC N 3 electrical conductivity46 EC# 1 347 CAC03 N 2 calcium carbonate equivalent48 CAC03# 1 349- VONPOST N 2 Von Post estimate ofdecomposition50 VONPOST# 1 351 WOOD N 2 wood material (percent b volume)52 WOOD# 1 353 DATE D 8 date ofrevision

Appendix 3. A Detailed Description ofISQ92 Rating Procedures

The ISQ92 procedures were developed using Arc/Info GIS and SLC dominant (DOM) andsubdominant (SUB) attribute files (Table 3-1 and Table A2-1). ISQ92 has four basiccomponents; 1) Exclusion procedures (modified in 1996), 2) Rating system and criteria, 3)Algorithms and programs, and 4) a Arc Macro Language Graphic user interface (added in 1996) .

Exclusion procedures:

As the current focus is on the inherent soil quality for crop production, polygon areas withunsuitable climatic and soil conditions for annual cereal crops are excluded (Table A3-1) . Thiswas done using the Arc/Info `RESELECTION' functions, prior to running the ISQ92 ratingprograms .

Table A3-1. Areas or soils excluded and the thresholds used in ISQ92 procedures

* except EGDD, all attributes are from the SLC extended legend DOM and SUB files

Rating system and criteria

Given the generalized nature of the SLC extended legend database, and the broad general natureof the SLC polygons, a four class system for inherent soil quality was considered appropriate .Accordingly, a inductive rating structure was adopted, involving a 3 class rating for each database attribute . These were combined to calculate a 4 class 'element rating' .

Areas or soils excluded SLC attributes and thresholds*

Inadequate climate for annual crops EGDD (effective growing degree days) < 1050

Slopes too steep for crop production DOM/SUBSLOPE (slope) > 30% (Class D, E and F)

Non mineral soil types DOM/SUBKDMAT (kind of surface materials, such as rock,organic, mineral, water, etc .) = `OR' (organic)

Very poor surface drainage DOM/SUBDRAIN (drainage class) = `V' (very poor)

Urban areas DOM/SUBKDMAT = 'UR' (urban area)

Rock DOM/SUBKDMAT= `Rl' or `R2' or `R3' (rock)

Water bodies DOM/SUBKDMAT ='WA' (water)

Each class is assigned numeric points for

Table A3-2. Point system of ISQ92 ratingquantification (Table A3-2). The integrationfrom 'attribute rating' to 'element rating' is anadditive one :

nISQE=E ISQA~j

(A3-1)11=1

Where;ISQEj is the total rating points of ISQelementj (j = 1,2,3, 4 for the 4defined ISQ elements for cropproduction) .

ISQA;; is the rating points of the ISQattribute i selected for ISQ elementj(i = 1, 2,3, . . ., n, normally 3 to 4attributes selected for rating each ISQelement)

Algorithms and programs

Graphic user interface

83

The criteria for rating selected inherent soil quality attributes by the ISQ92 procedure aredescribed in Table A3-3 . The SLC DOM and SUBDOM extended legend data fields consideredfor each of the four ISQ element are indicated, along with the data values in each of the 3 ratingclasses . The database fields and critical attribute values were selected based on their estimatedcontribution to the defined ISQ element. ISQ element definitions and ratings were limited by theavailable data fields, and the generalized nature of the individual data field values .

The ISQ92 point system (Table A3-2) and rating criteria (Table A3-3) are implemented with a setof INFO programs which can be run on any Arc/Info system (version 5 .0 or later) with slightmodification to specify the path of input data .

The early version of ISQ92 does not have a graphic user interface, and the output ratings of ISQelements were directly used by Arc/Info's Arcplot module for spatial query, display and mapping .While adequate for experienced Arc/Info users, a more intuitive graphic user interface wasdesirable for routine operation and demonstration of the rating system. Therefore, a menu basedinterface was added, using Arc Macro Language (AML).

ISQ attribute rating

Class Point

Poor 2

Moderate 1

Good 0

ISQ element rating

Class Point

Poor >= 3

Moderate to poor 2

Good to moderate 1

Good 0

Table A3-3. The rating criteria of selected ISQ attribute used in ISQ92 procedures

* All uppercase abbreviation with DOM- and SUB- prefix are SLC extended legend (DOM and SUB) attribute files .For details, see appendix 2 or check CanSIS/NSDB web site at http://res.agr.ca/

84

Rating criteria and pointsISQ Element ISQ attribute

Poor (2) Moderate (1) Good (0)

Root depth < 20 cm 20 to 75 cm > 75 cm(DOMROOT/SUBROOT*)

Depth to compact layer nla <= 50 cm > 50 cmAvailable Porosity (DOMCMPDP/SUBCMPDP)

Water availability in upper 120 cm <= 50 mm 100 to 150 mm > 150 mm(DOMAVWAT/SUBAVWAT) or saline

soil

Surface texture group and texture, If the texture group is loam and no coarse fragmentsorganic carbon content exist in the surface layer and there is more than 2%(DOMTEXGPISUBTEXGP, organic carbon, deduct 1 point from the summedDOMSRFTX/SÜBSRFTX and points ofthe ratings of above three attributesDOMORGAN/SUBORGAN)

Nutrient Retention Surface texture cobbly or ifloam or clay are anything else .(DOMSRFTX/SUBSRFTX) gravelly or found in significant

with high amounts yet highsilt content silt or coarse

fragments exist.

Surface organic carbon content <2% >= 2% but < 3% >= 3%(DOMORGAN/SUBORGAN)

Physical Rooting Root depth < 20 cm 20 to 75 cm > 75 cmConditions (DOMROOT/SUBROOT)

Depth to compact layer n/a <= 50 cm > 50 cm(DOMCMPDP/SUBCMPDP)

Surface texture cobbly or if loam or clay are anything else .(DOMSRFTX/SUBSRFTX) gravelly found in significant

with high amounts yet highsilt content silt or coarse

fragments are exist.

Soil development Gray n/a All others(DOMDEVEUSÜBDEVEL) Luvisol

Water availability in upper 120 cm a saline soil n/a All othersChemical Rooting (DOMAVWAT/SUBAVWAT)Conditions - -

pH ofsurface layer measured in < 4.5 or >= 4.5 but <= 5.5 > 5.5 andwater (DOMPHWAT/SUBPHWAT) > 8.0 or <= 7.5

>= 8.0 but <= 7.5

Appendix 4. A Detail Description of ISQ94 Rating Procedures

The ISQ94 procedures for assessing inherent soil quality were developed to take advantage of therevised/ improved structure of attribute data associated with the SLC CMP files . ISQ94procedures are developed in dBASEIV, and utilize databases that are also in dBASE format. Theprocedures described here use the SLC Component (CMP) file for national and broad regionalassessments, and the Soil Map Unit File (SMUF) for detailed regional assessments . In both files,digital map polygons are described in terms of soil components and areal extent . These are linkedin each case to the same set of modal soil attributes stored in Soil Names and Soil Layer files . Forfurther information concerning the ISQ94 rating program, contact Mr. W. Fraser, Land ResourceUnit, Brandon Research Centre.

ISQ94 pre-rating procedures :

The pre-rating procedures include data checking, selection of files and attributes to be used,exclusion and inclusion of areas/soils, and preparation of interim files to store the output ratingsand statistics . The program performs an initial check to verify the location and structure of theCMP/SMUF, SNF, and SLF databases . All data fields used by the ISQ94 ratings program mustbe present before the main ISQ94 procedures can be run (see Table A4-1) .

It is also important that the data fields contain actual data values for all soil components in thedigital maps. National Soil Databases may have data deficiencies, indicated by "-9" values fornumeric fields . The ISQ94 routines are programmed to skip over such records . It is highlyrecommended that NSDB data checking programs, such as INFOCHEKEXE, be run on all soildatabases before they are used by ratings programs such as ISQ94 .

The ISQ94 program employs a "CROP.LOG" file to store standard exclusion and ratingsthreshold values . These are used by the program as input variables for various ratingscalculations . All "CROP.LOG" threshold values may be reviewed, altered and stored asalternative sets of program values prior to running the actual ratings program . This is useful forsensitivity analysis testing, and development of different crop parameters for additional croptypes. Final output ratings from the ISQ94 program are stored in a dBASE file("RATINGS.dbf'), including a copy of the original input data file (the SLC CMP file or SMUFfile) . A matching ASCII "History" file ("RATINGS .his") provides a summary of the ISQ ratingsstatistics for the map area, as well as all "CROP.LOG" settings and databases used by the ISQ94program .

Table A4-1 . Data attributes used in ISQ94 procedures*

* See appendix 2 for details of definition of each attribute or check CanSIS/NSDB web site at http://res .agr.ca/* *Not official NSDB file .

86

ISQ Procedure where the attribute is usedDatabase andattribute fields data link exclusion Available Nutrient Physical Chemical

porosity retention rooting rootingconditions conditions

1 . SLC Carbon Component file (CMP) - broad scale

POLYNUMBPOLY AREACOMPNTNUMBPERCNTSOIL-CODEMODIFIER

2. SLC Climatic file (.CLM)** - broad scale

POLYNUMBEGDDP-PE

3 . DSM Soil Map Unit File (SMUF) - detail scale

POLY AREASOIL_CODE1,2,3MODIFIER1,2,3EXTENT1,2,3SLOPEP1,2,3STONE1,2,3

4. Soil Names File (SNF) - both broad and detail scale

SOIL CODE -MODIFIERLUKINDROOTRESTRIRESTRI TYPEDRAINAGEORDERS_GROUPGLGROUP

5. Soil Layer File (SLF) - both broad and detail scale

SOIL_CODEMODIFERLULAYER NOUDEPTHLDEPTHCOFRAGVFSANDTSANDTSILTTCLAYORGCARBPHCABASESCECKP33BDEC 0

Table A4-2. Areas or soils excluded and the thresholds used in ISQ94 procedures

* except for EGDD and SLOPE, all attributes are from the SNF .

The exclusion procedures in ISQ94 includetwo parts ; general and layer exclusions .The criteria of general exclusion (TableA4-2) are generally similar to ISQ92 .Note that ISQ94 uses Soil Names File datafields for most exclusion criteria, whileISQ92 uses the Soil Carbon ComponentFile data fields .

The ISQ94 layer exclusions are defined asa set of root restrictions for annual cropproduction, such as extremely high bulkdensity, salinity and extreme pH (TableA4-3). The thresholds for excluding layerswith root restrictions are crop specific andcan be modified in the CROPIOG file .

Table A4-3. Root restrictions and thresholds for layer exclusions

Areas or soils excludedBroad-scale Detail-scale

SLC CMP, SNF attributes andthresholds

SMUF, SNF attributes andthresholds*

Areas with inadequate heatfor annual crops

EGDD (effective growing degree days) <1050

EGDD (effective growing degree days) <1050

Slopes too steep SLOPE > 30% SLOPEP1,2,3 > 30%

Soil surface too stony n/a (no data) STONE1,2,3 (stoniness) >= 3

Organic soil ORDER ='OR' ORDER = `OR'

Very poor surface drainage DRAINAGE (drainage class) ='VP' DRAINAGE (drainage class) ='VP'

Urban areas KIND = `U' (Unclassified) KIND = `U' (Unclassified)

Rock KIND = `N' (Non soil) KIND = `N' (Non soil)

Water bodies KIND = `N' (Non soil) andcorresponding SOII._CODE

KIND = `N' (Non soil) andcorresponding SOIL_CODE

Rooting conditions Thresholds for exclusion

Rooting depth Max. 80 cmMin . 40 cm

<= 20 cm (excluded)

Maximum bulk density(clay < 40%)

>=1.75 g/cm3

Maximum bulk density(Clay >= 40%)

>=1.50 g/cm'

Maximum salinity (EC) >= 16 mS/cm

Minimum pH <= 3 .5

Maximum pH >=10

Root restricting layers Duric, Ortstein, Placic andFragipan

Table A4-4. ISQ94 program variables for ISQ element rating

ISQ element Variable Definition dimension

Available porosity AIR TOT Accumulated air-filled porosity from surface to the cmmaximum allowable rooting depth

AWHC TOT Accumulated available water holding capacity from cmsurface to the maximum allowable rooting depth .

ISQ_AIR Rating ofISQ aeration porosity sub-element by arbitrarylooking up the matrix ofAIR_TOT and moisture pointsindex

ISQ_AWHC Rating of ISQ-AWHC sub-element by looking up arbitrarythe matrix ofAWHC_TOT and moisture index . points

ISQ_PORO Final rating ofAvailable Porosity element by arbitrarytaking the more restricting rating ofISQ AIR sub- pointselement and ISQ AHWC sub-element

Nutrient retention NUTR_SUR Accumulated nutrient retention capacity oftop 20 meq/cm2cm (for algorithm, see Formula 3)

NUTR_RATIO The ratio of NUTR-SUR to thickness, i.e. meq/cm3NUTR RATIO = NUTR SUR / 20

ISQ NUTR Final rating of Nutrient Retention element based arbitraryon NUTR_RATIO points

Physical rooting THICK TOT Accumulated thickness from top to the maximum cmconditions allowable rooting depth.

ISQ ROOT Final rating of Physical Rooting Conditions arbitraryelement based on THICK TOT points

Chemical rooting SURPH Depth weighed average pH oftop 20 cm pH scaleconditions

SUBPH Depth weighed average pH from 20 to 80 cm pH scale

SUREC Depth weighed average EC of top 20 cm mS/cm

SUBEC Depth weighed average EC of 20 to 80 cm ms/cm

ISQ_SURCHEM Rating of surface chemical rooting conditions arbitraryby taking the `worse' rating of SURPH and pointsSUREC

ISQ-SUBCHEM Rating ofsub surface chemical rooting conditions arbitraryby taking the `worse' rating of SUBPH and pointsSUBEC

ISQ_CHEM Final rating of Chemical Rooting Conditions arbitraryelement based on the matrix ofISQ SURCHEM pointsand ISQSUBCHEM

ISQ94 Rating Procedures

The rating procedures consist offour sub-procedures, each corresponding to one ofthe fourelements of inherent soil quality (Table 2-1) . The specific criteria, algorithms, and calculationprocedures for each element are given in the following sections .

Program variables were used to store intermediate values calculated from particular proceduresand algorithms (Table A4-4). Threshold values are used to classify the calculated programvariables, and produce ratings for each ISQ element . An examination ofprogram variables isalso useful for error checking and program debugging.

1) Available porosity procedure

Step 1 : Calculate the air-filled porosity for each soil horizon in the Soil Layer file, andaccumulate this as a total aeration porosity value (in cm ofair) . This is calculated in twostages ; the surface layer (20 cm) and the subsurface (an accumulated value, "AIR TOT",for all horizons down to the maximum allowable rooting depth). The formula used is :

nAIR- TOT = E THICKNESS,*[(PDi - BDi) / PDi - 0.01* KP33i]

(A4-1)i=1

where,AIR_TOT= accumulated air-filled porosity (cm) from top to the maximum allowable rootingdepth (horizon i = 1, . . ., n) .THICKNESS = the thickness ofthe soil layer (cm) i. This is the absolute value ofthe upperdepth minus the lower depth, [ABS(UDEPTH-LDEPTH)], as recorded in the Soil Layer file.PD = Particle Density, g/cm~ . A particle density (PD) of 2.65 g/cm' is used where the organiccarbon ofthe mineral soil material is less than 2.0% (ORGCARB field in the SLF). Where theorganic carbon values are between 2% and 17%, a particle density of2.54 g/cm' is used . Fororganic layers (organic carbon values of>17% ), a particle density of 1 .00 g/cm' is used .BD = Bulk Density, g/cm' .KP33 = % water, by volume, that is retained by the soil at 1/3 atmosphere suction . This ismultiplied by 0.01 to convert from % to a ratio of the soil volume . KP33 approximates fieldcapacity.

The total soil aeration value (AIR TOT, expressed in cm of air), is then added for allvalid soil layers within the SURFACE LAYER. The default setting for SURFACELAYER THICKNESS is 20 cm. A minimum threshold value of 1 cm of air within thesurface layer (5% of the surface layer volume) must be reached; if this does not occur, thesoil is considered as NOT RATED for 0 ISQ elements .

Table A45. Matrix for determining rating points of ISQ aeration porosity

0 = good ; 1 = good to moderate ; 2 = moderate to poor; 3 = poor; 9 = not rated

Step2 : Assign rating points to ISQ aeration porosity sub-element (ISQ AIR) by looking up the matrix ofAIR TOT and moisture index class, based on SoilTaxonomy and Drainage in the Soil Names File(Table A4-5).

Step 3: Estimate the available water holdingcapacity (AWHC). The AWHC is calculated foreach soil, from the total silt, clay and very finesand values for each soil layer in the SNF file .This is multiplied by the horizon thickness(absolute value of UDEPTH-LDEPTH), and atotal value (AWHC_TOT, in mm of totalavailable water) is accumulated to either themaximum rooting depth, or some restricting layerabove the maximum rooting depth. Values forAWHC are calculated as shown in Table A4-6.

Step 4: Assign rating points to ISQ availablewater holding capacity sub-element(ISQ-AWHC) by looking up the matrix ofAWHCTOT and moisture index (Table A4-7).

90

Table A4-6. Relationship between availablewater holding capacity and texture

'USDA soil texture classes indicated here areonly approximate . Several classes may overlapdue to varying percentages of silt and clay.'For soils with coarse fragments, AWHCestimates are reduced by the volume percentageofcoarse material, a Soil Layer File attribute .' Organic soils are recognized by tsand + tsilt +tclay = 0 in the Soil Layer File data.

Moisture Conditions (by drainage, soil-climatic zones and approx. P-PE range)

Well drained Well drained Well drained All other well All poorlyOverall Rating Brown Dark Brown Black, D. Gray drained and drained soils(ISQ_AWHC) Chemozems, Chemozems, Chem., Luvisols, imperfectly

Solonetz Solonetz Brunisols drained soils(<-350) (-350 to -300) (-300 to 200) (>-200)

> = 15.0 0 0 0 0 1

E 10.0 to 15.0 0 0 0 0 2

O 5.0 to 9.9 0 0 0 3 3i99 1.0to4.9 0 1 2 3 3

< 1.0 (within 9 9 9 9 9top 20 cm)

Texture' 0.5*VFSAND +TSILT +TCLAY2

AWHC(mmIM)

Organic 0 500

S 1-10 40

LS 11-20 60

SL 21-40 100

L, VFSL 41-60 150

SI, SIL 61-70 170

SICL, CL 71-75 180

SIL 76-80 190

SICL 81-85 200

Step 5: Assign overall rating points to ISQ available porosity (ISQ-PORO). The `most limiting'principle is used, namely taking the worse rating of ISQ_AIR and ISQ_AWHC as the finalrating point of ISQ^PORO.

Table A4-7. Matrix for determining rating points ofISQ available water holding capacity .

0 = good ; 1= good to moderate ; 2 = moderate to poor; 3 = poor ; 9 = not rated

2) Nutrient retention procedure

Step 1: Calculate the cumulative cation exchange capacity (CEC) of all eligible soil horizonswithin the surface rooting depth (top 20 cm). The formula used is as follows :where,

n

NUTR_ SUR =

CEC*BDi* BASESi*0.01* ELTHICKNESS,

(A4-2) . .t=1

NUTRSUR = Accumulated nutrient retention capacity of surface 20 cm (meq/cm3 ) of all eligiblesoil horizons (i = 1, . . ., n)CEC = cation exchange capacity (meq/100g)BD = Bulk Density (g(cm3)BASES = base saturation (%), This is multiplied by 0.01 to convert from % to a ratio oftotal CEC .ELTHICIKNESS = the eligible thickness of the soil layer i considered as part oftop 20 cm surfacesoil. If a soil horizon has a lower depth that exceeds 20cm, only the portion to a depth of 20cm isconsidered eligible . Ifthe total horizon thickness is less than 20cm, the next horizon is also evaluated .

91

Moisture Conditions (drainage, soil-climatic zones and approx. P-PE range)

Well drained Well drained Well drained All other well All poorlyOverall Rating Brown Dark Brown Black, D. Gray drained and drained soils(ISQ_AWHC) Chernozems, Chernozems, Chem., Luvisols, imperfectly

Solonetz Solonetz Brunisols drained soils(< -350) (-350 to -300) (-300 to -200) (> -200)

<= 5.0 9 9 9 3 0

5 .1to6.0 9 9 3 2 0

Ô 6.1 to 7 .0 9 3 2 1 0F.0

iU 7.1 to 12.0 3 2 1 0 0

12.1to15 .0 2 1 0 0 0

> 15 .0 2 1 0 0 0

Step 2: Calculate the ratio of accumulated CEC of the top 20 cm:

NUTR RATIO (meglcm3) = NUTR SUR (meq/cm2) / 20 (cm)

(A4-3)

Step 3: Assign rating points to ISQ Nutrient retention element based on the ratio of accumulatedCEC of top 20 cm (NUTR_RATIO) . The generic rating scale, for cereal crops is shownin Table A4-8. The rating scale can be modified in the CRORLOG for other crops .

Table A4-8. Rating scale of ISQ nutrient retention element

0 = good; 1 = good to moderate ; 2 = moderate to poor ; 3 = poor; 9 = not rated

3) Physical rooting conditions procedure

Step 1: Calculate the total depth of soil available to the crop roots (THICK-TOT) .successive soil layer is examined, starting with the surface, until a physical rootrestricting condition is encountered .

Each

A number of standard checks are made by the ISQ program to determine if eachsuccessive soil layer in a given soil is root restricting or not. These include checks forrecognized root restricting layer types . Further checks are made on each successive soilhorizon for bulk density, salinity and pH threshold conditions . If any such conditions areencountered, processing stops at the upper depth of this horizon, and the total thickness(THICK TOT) of the rooting zone is calculated accordingly .

Step 2: Assign rating points to ISQ physical rooting condition element based on THICK TOTcalculated from step l, as shown in Table A4-9.

Table A4-9. Rating scale ofISQ physical rooting conditions element

p , -p ,

92

NUTR_RATIOof Top 20 cm < 8 8.0 to 8.9 9.0 to 15 .9 16 to 22 > 22(megtcm')

ISQ-NUTR 9 3 2 1 0Ratings

THICK-TOT < 20 20 to 29 30 to 54 55 to 79 >= 80(cm)

ISQ_ROOT 9 3 2 1 0Rating

at'0& 1 = gnmi tn mndPmtP' 7 =TnMPrAtP tn oor. 3 = oor& 0 - nnt rntari

4) Chemical rooting conditions procedure

Chemical conditions are defined in ISQ94 in terms of an adequate depth of soil with pH (PHCAfield in the SLF) and salinity (Electrical Conductivity, EC field in the SLF) within tolerable limits .Surface (top 20 cm) and subsurface (20 to 80 cm) conditions for both pH or salinity can varyconsiderably for each soil, and are therefore assessed separately . Where the rooting zone isrestricted to less than 80cm by adverse soil conditions, the chemical conditions are evaluatedwithin the restricted rooting zone . Chemical conditions are considered more limiting within thesurface zone for annual crop production . The final rating of pH and salinity is determined bycombining both surface and subsurface ratings . Both pH and salinity ratings are assessed in asimilar fashion, and the most restricting of the two conditions is used in the overall ISQ chemicalrooting element rating .

Step 1 : Calculate average (depth weighted) pH and EC of surface layer (top 20 cm), i.e . SURPHand SUREC respectively :

where,SURPH = depth weighted average pH of surface 20 cm of all eligible soil horizons (i = 1, . . ., n)PHCA = pH in Calcium chloride as recorded in SLFSUREC = depth weighted average EC of surface 20 cm (mS/cm) of all eligible soil horizons (i =1, . . ., n)EC = electrical conductivity as recorded in the SLF (mS/cm)ELTHICKNESS = the eligible thickness of the soil layer i (See explanation of formula (3)

Step 2: Assign rating points to ISQ SURCHEM based on SURPH and SUREC respectively andthen take the most restricting rating as the final rating of surface chemical rootingconditions (Table A4-10) .

Table A4-10 . Rating scale of ISQ chemical rooting conditions element

0 = good; 1 = moderate ; 2 = poor ; 3 = very poor; 9 = not rated

93

<4.0 4.0to5 .0 5.0to5.5 5 .5to6.0SURPH or SURPH or or or or 6.0 to 7.3

> 9.5 8.1 to 9.5 7.7 to 8.1 7.3 to 7.7

SUREC or SUBEC(MS/CM) > 12.0 8.1 to 12.0 4.1 to 8.0 2.1 to 4.0 <= 2.0

ISQ-SURCHEM orISQ_SUBCHEM Rating 9 3 2 1 . 0

nSURPH=E PHCAi * ELTHICKNESSil20) (A4-4)

i=1

nSUREC=I, ECi * ELTHICKNESS i 20) (A4-5)

Step 3: Calculate average (depth weighted ) pH and EC of sub-surface layer (20 - 80 cm),i.e . SUBPH and SUBEC respectively :

where,SURPH = depth weighted average pH of sub-surface of all eligible soil horizons (i =1, . . .,n)PHCA = pH in calcium chloride as recorded in SLFSUREC = depth weighted average EC of sub-surface 20 - 80 cm (mS/cm) ofall eligible soil horizons(i = 1, . . ., n)EC = electrical conductivity as recorded in SLFELTHICKNESS = the eligible thickness of the soil layer i considered as part of sub-surface soil .

Step 4: Assign rating points to ISQ SUBCHEM based on SUBPH and SUBEC respectively andthen take the most restricting rating as the final rating of sub-surface chemical rootingconditions (Table A4-10) .

Step 5 : Assign rating points to overall chemical rooting conditions. In recognition that thesurface chemical conditions are more limiting, the weighting for the top 20 cm isdoubled . The combination of surface and sub-surface rating in determining the finalrating is shown in Table A4-11 :

Table A4-11. Matrix for determining rating points of ISQ overallchemical rooting conditions

0 = good; 1 = good to moderate; 2 = moderate to poor; 3 = poor; 9 = not rated

Overall Rating Surface Rating (ISQ_SURCHEM)(ISQ_CHEM)

0 1 2 3

0&1 0 1 2 3d w

W â2 1 1 2 3

~ad 3 2 2 2 3

nSUBPH=E PHCAi * ELTHICKNESS i160) (A4-6)

i=1

nSUBEC=J: ECj * ELTHICKNESS1160) (A4-7)

H

ISQ94 post-rating procedures

Several post rating procedures have been developed to further process the ISQ ratings for GISanalysis and display . Some utility programs translate ISQ output ratings into colour code values,for GIS colour map displays . Ratings programs have also been developed to summarize ISQrating results from individual elements to overall polygonal ratings, and to further summarizeratings to higher level polygons . Section 3.4.5 in the main document provides an explanation ofthese alternative post rating procedures .