ISSN 0137-0944
eISSN 2949-6144
En Ru
ISSN 0137-0944
eISSN 2949-6144
Application of basic and modifi ed method for assessing the land degradation neutrality in the context of studying the relationship between degradation and agricultural production

Application of basic and modifi ed method for assessing the land degradation neutrality in the context of studying the relationship between degradation and agricultural production

Abstract

The article is devoted to the theory and practice of applying the concept of land degradation neutrality (LDN) for
the conditions of the Belgorod region of the Russian Federation. Its basic version is considered, based on the analysis
of three sub–indicators, where the assessment of land degradation trends in the study area is based on the analysis of changes in the main indicator — the percentage of degraded land from the total area of the territory, and three
sub-indicators of SDG 15.3.1: changes in land productivity, changes in land cover and dynamics of soil organic carbon reserves. As an adjustment to the basic approach of the LDN, it is proposed to supplement it with regional data on soil characteristics. Th e following soil properties can be recommended as necessary for considering in the
evaluation model — the content of humus and nutrients, as well as pH, these characteristics, on the one hand, are
largely related to soil fertility, and on the other hand, they are most at risk of degradation changes during human
exploitation of soils. Modifi cation of the LDN methodology allows not only to clarify the central (umbrella) indicator,
but also to identify the relationship of the latter with indicators of agricultural production, in particular, gross crop
yields. Analysis of the data using the modifi ed LDN method showed that 64.8% of the region was degraded (which
is almost 2 times higher than the values obtained by the basic LDN method), which leads to a signifi cant loss of crop
yield. Th e article proposes an algorithm for assessing the relationship between land degradation and gross crop yields
based on correlation and regression analysis (spatial models).
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Received: 12/26/2022

Accepted: 02/27/2023

Accepted date: 04/01/2023

Keywords: soil degradation; degradation indicators; degradation and food security

DOI: 10.55959/MSU0137-0944-17-2023-78-2-106-116

Available in the on-line version with: 01.04.2023

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Issue 2, 2023