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\begin{document}

\title{Assessing land degradation neutrality in data scarce semi-arid drylands
agroecosystems to improve land resources management: a case study in
Matabeleland North Province of Zimbabwe.}



\author[1]{Bright Chisadza}%
\author[2]{Onalenna Gwate}%
\author[1]{Simon Peter Musinguzi}%
\affil[1]{Uganda Martyrs University Faculty of Agriculture}%
\affil[2]{Lupane State University Faculty of Agricultural Sciences}%


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  \date{May 27, 2024}


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\begin{abstract}
Semi-arid agroecosystems have a crucial function in supplying food and
ecosystem services. However, these ecosystems are under severe threat
due to land degradation. To enhance our understanding of environmental
trends and their causes and to identify more sustainable land management
techniques, it is important to track land degradation in space and time.
This study uses land cover, soil organic carbon, and land productivity
dynamics maps to evaluate land degradation neutrality (as per
Sustainable Development Goal 15, indicator 15.3.1). In this regard, we
employed the trends.earth tool in QGIS 3.3, utilising the European Space
Agency Climate Change Initiative (ESA CCI) classified LULC maps for
1992, 2000, 2010, and 2020 to assess land degradation. Additionally, we
predicted 2050 LULC maps using the MOLUSCE plugin in QGIS, which
integrates an artificial neural network (ANN) in cellular automata (CA)
modeling (CA-ANN) based on the 2015 LULC map and independent variables
such as digital elevation model (DEM) and slope. Our results indicated a
significant decrease in bare areas (71\%) and an increase in settlements
(built-up areas) (163\%) between 1992 and 2020. Furthermore, the
predicted land cover map shows a significant increase in bare land
(238\%) and settlements (72\%), accompanied by a decrease in water
bodies (23\%) and forested areas (3.5\%). In terms of land degradation,
approximately 26.46\% of the province exhibited degraded land,
accounting for approximately 20,146.35 km \textsuperscript{2}, while
approximately 59.55\% (45,337.84 km \textsuperscript{2}) of the land
remained stable. Land cover conversions, particularly from forests to
grasslands and settlements, are among the potential drivers of land
degradation. Identifying land cover transitions and assessing land
degradation is paramount for effective monitoring and planning. By
understanding these dynamics, targeted interventions can be developed to
mitigate land degradation and promote sustainable land use practices in
semi-arid agroecosystems.%
\end{abstract}%



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\verb`Land Use PAPER_BC_Rx.docx`  available at \url{https://authorea.com/users/641152/articles/655660-assessing-land-degradation-neutrality-in-data-scarce-semi-arid-drylands-agroecosystems-to-improve-land-resources-management-a-case-study-in-matabeleland-north-province-of-zimbabwe}

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