Predicted Soil organic carbon (%) at a defined depth range (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm).

The Agri-Environmental Indicator Soil Organic Matter data series provides a measure of soil health and an estimate of how much carbon dioxide (CO2) has been removed from the atmosphere by plants and sequestered as soil organic carbon (SOC) in agricultural soils.

Coastal vegetated ecosystems are recognized for their role in cycling and storing carbon in the world’s oceans (i.e., blue carbon); however, high uncertainty in carbon sequestration rates is partly due to an absence of studies estimating carbon export to the deep sea. We modeled export from nearshore kelp forests and seagrass beds, showing variability by orders of magnitude across spatial scales (3 to hundreds of kilometers), kelp and seagrass species, seasons, and carbon forms, raising caution in using generalized export rates in blue carbon accounting. Our results also show rapid (20 to 30 days) and extensive export of neutrally buoyant dissolved organic carbon particles to the shelf break (up to 44% within 90 days), contrasting sinking particulate organic carbon particles that largely remained within 100-meter water depth in the nearshore. These results improve estimates of carbon sequestration by blue carbon ecosystems and reveal contrasting patterns of export relative to other regions of the globe. Cite this data as: Kira A. Krumhansl et al., Pathways of blue carbon export from kelp and seagrass beds along the Atlantic coast of Nova Scotia.Sci. Adv.11,eadw1952(2025).DOI: 10.1126/sciadv.adw1952

The National Ecological Framework for Canada's "Soil Development by Ecodistrict” dataset contains tables that provide soil development information for components within the ecodistrict framework polygon. It provides soil development codes and their English and French-language descriptions as well as the percentage of the polygon that the component occupies. The soil development descriptions are based on the second edition of the Canadian System of Soil Classification (Agriculture Canada Expert Committee on Soil Survey, 1987).

Soil Survey polygons contain soils spatial and attribute information utilized by the Ministry of Environment online Soil Information Finder Tool ([SIFT](http://www2.gov.bc.ca/gov/content/environment/air-land-water/land/soil-information-finder)). The information pertains to soil survey data in the Province of British Columbia, as well as links to a variety of reports and maps. Polygons related to soil surveys can be made up of a complex of up to 3 components representing 3 different soil types. These components are aspatial and represent the amount in the polygon indicated by the PERCENT_x field for the component x. Each unique soil type has a soil name and generalized attributes such as drainage, texture and coarse fragment percent. The [Soil Name and Layer Files](https://catalogue.data.gov.bc.ca/dataset/a3bc4cd3-0f1b-4a2f-bd88-76f821756d10) can be joined and related to each of the 3 components of the Soil Survey Spatial View polygons using the SoilSymbol field in the name and layer tables and the `SOILSYM_x` fields in the Soil Survey Spatial View.

The “Soil Landscapes of Canada V.2.2/V.3.1 - Soil Order” displays the highest (most general) level of soil classification. Within the Canadian System of Soil Classification there are ten recognized soil orders (Soil Classification Working Group 1998). This system is hierarchical (from general to specific). Soil orders are further subdivided to great groups, subgroups, families, and series.

The National Ecological Framework for Canada's "Soil Development by Ecozone” dataset contains tables that provide soil development information for components within the ecozone framework polygon. It provides soil development codes and their English and French-language descriptions as well as the percentage of the polygon that the component occupies. The soil development descriptions are based on the second edition of the Canadian System of Soil Classification (Agriculture Canada Expert Committee on Soil Survey, 1987).

The National Ecological Framework for Canada's "Soil Development by Ecoprovince” dataset contains tables that provide soil development information for components within the ecoprovince framework polygon. It provides soil development codes and their English and French-language descriptions as well as the percentage of the polygon that the component occupies. The soil development descriptions are based on the second edition of the Canadian System of Soil Classification (Agriculture Canada Expert Committee on Soil Survey, 1987).

The National Ecological Framework for Canada's "Soil Development by Ecoregion” dataset contains tables that provide soil development information for components within the ecoregion framework polygon. It provides soil development codes and their English and French-language descriptions as well as the percentage of the polygon that the component occupies. The soil development descriptions are based on the second edition of the Canadian System of Soil Classification (Agriculture Canada Expert Committee on Soil Survey, 1987).

## Purpose The Ministry of Agriculture, Food and Agribusiness (OMAFA) is responsible for Ontario’s provincial soil maps and maintains and update them as necessary. Digital Soil Mapping (DSM) is a modern methodology using spatially explicit soils and environmental data to predict soil variation throughout a landscape at a high, consistent resolution. Digital soil maps are being rolled out throughout Ontario’s agricultural land base to update provincial soil maps. ## Reach Provincial soil maps are used in many decision-making processes including: * land use planning * land evaluation * farming practices * best management practices * ecological monitoring * land resource mapping Potential users of this data include: * farmers * certified crop advisors * conservation authorities * academic researchers * land use planners ## Potential impacts Digital soil maps provide more accurate and precise soils data and enables improved management of soil resources across multiple stakeholders. This allows for better decision making to maximize land use efficiency, improve economic efficiency of soil resources and promote soil health and soil conservation. ## Technical description Digital soil mapping combines geo-referenced soil observations with geo-referenced environmental layers to mathematically model soil variation as a function of environment variation. These models are based on well established, but often complex relationships, between soil properties and topography, biology, geology and hydrology.