Simulations using APSIM suggest that Conservation Agriculture sustains protein yield under changing climate dynamics in Northern Mozambique

Conservation Agriculture (CA) is based on the simultaneous practice of three principles: (i) no or minimum mechanical soil disturbance, (ii) permanent soil cover, and (iii) crop diversity e.g. crop rotation and/or intercropping systems. In parts of Sub Saharan Africa (SSA), conventional tillage practice is still pervasive and includes the practice of crop burning, resulting in severe soil erosion. Moreover, there is heavy reliance on maize, which contributes to limited dietary diversity. Crop modelling efforts allow for future scenarios to be explored to support policy formulation and farmer decision making. Research exploring potential benefits of CA on food and nutrition security has been limited and existing crop modelling efforts have failed to model the full CA system and/or have been limited to comparisons against monocultures or a narrow range of crops. The APSIM crop model was used to simulate the productivity and protein yield of a variety of intercropping systems involving three crops (maize, cowpea and pigeonpea) under full CA practice relative to conventional tillage (CV) with the same intercropping system. A baseline scenario used site-specific daily historical weather data acquired between 1997 and 2015 for Pemba-Metuge district in Cabo Delgado province (Northern Mozambique). A second set of simulations used incremental changes in temperature corresponding to future climate scenarios. Results showed that temperature plays the most important role, contributing to nearly 60% of the variance in the combined protein yield. Projected trends further indicated that the combined protein yield of the three crops decreased from a median of 207 kg ha⁻¹ in the baseline scenario to 121 kg ha⁻¹ under a 4 °C temperature increase in the CV system. In the CA system, the median combined protein yield decreased from 230 to 135 kg ha⁻¹ under the same temperature scenarios. Median grain yields declined from the baseline scenario to a 4 °C temperature increase by 267, 97, and 29 kg ha⁻¹ for cowpea, pigeonpea, and maize, respectively, under the CV system. Under the CA system, the corresponding declines were 291, 107, and 27 kg ha⁻¹. Nevertheless, protein yields and overall productivity remained consistently higher under the CA system. Our simulation work provides preliminary evidence that suggests Conservation Agriculture can sustain protein yield under changing climate dynamics in Northern Mozambique.

Authors

Institutions

Publication Details

Journal
BMC Plant Biology
Published
2025-11-13
DOI
https://doi.org/10.1186/s12870-025-07418-5
Primary Topic
Climate change impacts on agriculture
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulations using APSIM suggest that Conservation Agriculture sustains protein yield under changing climate dynamics in Northern Mozambique

David Parsons, Baqir Lalani, Mukhtar Ahmed, Uttam Kumar
BMC Plant Biology
Climate change impacts on agriculture
article

Simulations using APSIM suggest that Conservation Agriculture sustains protein yield under changing climate dynamics in Northern Mozambique

David Parsons, Baqir Lalani, Mukhtar Ahmed, Uttam Kumar
article en

Abstract

Conservation Agriculture (CA) is based on the simultaneous practice of three principles: (i) no or minimum mechanical soil disturbance, (ii) permanent soil cover, and (iii) crop diversity e.g. crop rotation and/or intercropping systems. In parts of Sub Saharan Africa (SSA), conventional tillage practice is still pervasive and includes the practice of crop burning, resulting in severe soil erosion. Moreover, there is heavy reliance on maize, which contributes to limited dietary diversity. Crop modelling efforts allow for future scenarios to be explored to support policy formulation and farmer decision making. Research exploring potential benefits of CA on food and nutrition security has been limited and existing crop modelling efforts have failed to model the full CA system and/or have been limited to comparisons against monocultures or a narrow range of crops. The APSIM crop model was used to simulate the productivity and protein yield of a variety of intercropping systems involving three crops (maize, cowpea and pigeonpea) under full CA practice relative to conventional tillage (CV) with the same intercropping system. A baseline scenario used site-specific daily historical weather data acquired between 1997 and 2015 for Pemba-Metuge district in Cabo Delgado province (Northern Mozambique). A second set of simulations used incremental changes in temperature corresponding to future climate scenarios. Results showed that temperature plays the most important role, contributing to nearly 60% of the variance in the combined protein yield. Projected trends further indicated that the combined protein yield of the three crops decreased from a median of 207 kg ha⁻¹ in the baseline scenario to 121 kg ha⁻¹ under a 4 °C temperature increase in the CV system. In the CA system, the median combined protein yield decreased from 230 to 135 kg ha⁻¹ under the same temperature scenarios. Median grain yields declined from the baseline scenario to a 4 °C temperature increase by 267, 97, and 29 kg ha⁻¹ for cowpea, pigeonpea, and maize, respectively, under the CV system. Under the CA system, the corresponding declines were 291, 107, and 27 kg ha⁻¹. Nevertheless, protein yields and overall productivity remained consistently higher under the CA system. Our simulation work provides preliminary evidence that suggests Conservation Agriculture can sustain protein yield under changing climate dynamics in Northern Mozambique.

BMC Plant BiologyVol. 25(1)
Pir Mehr Ali Shah Arid Agriculture University (PK), Aarhus University (DK), Swedish University of Agricultural Sciences (SE), Natural Resources Institute (GB), University of Greenwich (GB), Wageningen University & Research (NL)
University of Greenwich, Sveriges Lantbruksuniversitet
Openalex Percentile: Top 74%
Climate change impacts on agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.