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soil-organic-carbon-estimation-in-regenerative-cropping-and-managed-grassland-ecosystems.md

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Soil Organic Carbon Estimation in Regenerative Cropping & Managed Grassland Ecosystems

Overview

Developer: ecometric

Sectoral Scope: Carbon Removal

Abstract:

This methodology protocol proposes the use of remotely sensed multispectral imagery and soil sample results to train an Artificial Neural Network (ANN) to monitor changes in Soil Organic Carbon (SOC) stocks, within a project area, through time. The project area will be defined in the credit class document. The SOC change will be reported as CO2 equivalent. SOC is crucial to soil health, fertility and ecosystem services including food production, making its preservation and restoration essential. This methodology will concentrate on the assessment of SOC sequestration as a major soil health characteristic, consisting of:

  1. SOC stocks.
  2. CO2 equivalents (CO2e)

Soil contains approximately 2344 Gt of organic carbon globally and is the largest terrestrial pool of organic carbon (Stockmann et al., 2013). Small changes in the soil organic carbon stock could result in significant impacts on the atmospheric carbon concentration. By monitoring the carbon levels in the soil, farmers and landowners will be able to measure the impact of their stewardship.

Summary of Methodology Update:

Update V1.2.2 of the ecometric Methodology for Soil Organic Carbon Estimation in Regenerative Cropping and Managed Grassland Ecosystems proposes the following changes:

  • The inclusion of Loss on Ignition laboratory test in geographies where there is no regional availability of DUMAS testing.
  • Using a sampling simulation based on the estimated SOC value range within a Project Area to calculate and report sampling uncertainty for a range of Compact Geographic Stratification strata sizes, for each monitoring round. This tool will be used to balance sampling uncertainty with sampling cost on large project areas and to transparently report the uncertainty associated with the selected sampling density for verifiers and auditors.

Updated Version:

{% file src="../.gitbook/assets/Ecometric Methodology Update ID0044 V1.2.2_Final (1).pdf" %}

Document History

{% tabs %} {% tab title="Initial Submission" %}

Initial Submission

Methodology Proposal for Soil Organic Carbon Estimation in Regenerative Cropping and Managed Grasslands Ecosystems

{% file src="../.gitbook/assets/Ecometric Methodology Proposal Doc ID 0038 Pre-Internal Review Original.pdf" %} Submission Date: July 3, 2022 {% endfile %} {% endtab %}

{% tab title="Internal Review Round 1" %}

Regen Registry Internal Review

Reviewers: Gisel Booman, Ned Horning

Date: August 1, 2022

Review Documents

Internal Review Feedback

{% file src="../.gitbook/assets/Ecometric_Methodology Internal Review Feedback_Round 1.pdf" %}

Internal Review Revision Report

{% file src="../.gitbook/assets/Ecometric_Internal Review_R1_Comment Revision Report_PC Copy.pdf" %} Approval Date: August 1, 2022 {% endfile %}

Post Internal Review Markup

{% file src="../.gitbook/assets/Ecometric Methodology Proposal Doc ID 0041 Post Internal Review Round 1 Markup Response.pdf" %} {% endtab %}

{% tab title="Internal Review Round 2" %}

Regen Registry Internal Review

Reviewers: Gisel Booman, Ned Horning

Date: August 29, 2022

Review Documents

Round 2 Version for Review

{% file src="../.gitbook/assets/Ecometric Methodology Proposal Doc ID 0041 Post-Internal Review Round 1_Start of Round 2.pdf" %}

Internal Review Feedback

{% file src="../.gitbook/assets/Ecometric - Methodology Internal Review Feedback - Round 2_PC Copy.pdf" %}

Internal Review Revision Report

{% file src="../.gitbook/assets/Ecometric_Internal Review_R2_Comment Revision Report_PC Copy.pdf" %}

Additional Comments from Internal Review Process

{% file src="../.gitbook/assets/Additional Comments from Ecometric Internal Review.pdf" %}

Round 2 Final Version

{% file src="../.gitbook/assets/Ecometric Methodology Proposal Doc ID 0042 Post-Internal Review Round 2.pdf" %} {% endtab %}

{% tab title=" Expert Peer Review" %}

Expert Peer Review

Reviewers: Stuart Marsh, PhD, Apostolos Papadopoulos, PhD

Review Date: November, 2022

Review Documents:

Final Edits Round 2 Comparison to Expert Review Draft

{% file src="../.gitbook/assets/Comparison V0043 with V0044 Expert Peer Review Comment Markup.pdf" %}

Draft Submitted for Expert Peer Review

{% file src="../.gitbook/assets/Ecometric Methodology Proposal Doc ID 0043 Final_Pre-External Expert Peer Review.pdf" %} Submission Date: November 1, 2022 {% endfile %}

Dr Stuart Marsh - Expert Peer Review Feedback Form

{% file src="../.gitbook/assets/Ecometric Methodology Expert Peer Review Comments & Revisions_Marsh_1.0.docx.pdf" %}

Dr Apostolos Papadopoulos - Expert Peer Review Feedback Form

{% file src="../.gitbook/assets/Ecometric Methodology Expert Peer Review Comments & Revisions_Dr Papadopoulos_1.0.docx.pdf" %} Submission Date: November 22, 2022 {% endfile %}

Final Version

{% file src="../.gitbook/assets/Ecometric Methodology Proposal Doc ID 0044_Final_Post-External Peer Review.pdf" %} {% endtab %}

{% tab title="Version Update" %} Updated Version 2024 -Tracked Changes :

{% file src="../.gitbook/assets/Ecometric Methodology Update_ID0044 V1.2.2_Tracked.pdf" %}

Internal Review:

{% file src="../.gitbook/assets/Ecometric - Methodology Update Internal Review May 10 - June11.docx.pdf" %} {% endtab %} {% endtabs %}