Abstract
Soil degradation, biodiversity loss, and declining yields threaten smallholder farming in tropical regions under increasing climate pressures. Soil degradation in Mesoamerican maize-based systems is accelerated under continuous monocropping and residue burning. Crop diversification via legume integration and intercropping can regenerate soil functions, but impacts vary across contexts and sensitive indicators for monitoring of soil health effects are lacking. This study evaluated how diversified maize systems influence soil health and productivity and identified the most responsive and accessible soil health indicators. An on-farm trial in Chiapas, Mexico, compared three diversified cropping systems: (1) maize-pigeon pea single-row intercrop, (2) maize-pigeon pea double-row intercrop, and (3) maize-bean rotation, with a (4) conventional maize monoculture with residue burning (control). Four years post-implementation, we measured soil macrofauna, microbial communities (16S and ITS metabarcoding), enzyme activity, substrate-induced respiration rates (SIR), particulate organic matter (POM), permanganate oxidizable carbon (POXC), potentially mineralizable nitrogen (PMN), aggregate stability, and bulk density. Compared to the control, diversified systems significantly improved maize yield (271%), residue cover (210%), macrofauna abundance (253%), and fungal richness (52%), while enhancing aggregate stability (18%) and microbial activity (SIR rates 34% higher). POM, POXC, and PMN were the most sensitive physicochemical indicators, where sensitivity is expressed as responsiveness relative to variability. Macrofauna metrics and enzyme activity showed high responsiveness but greater variability. For smallholder contexts, we recommend a practical, low-cost core set of indicators: soil cover, POM, POXC, PMN, and macrofauna; SIR provides additional sensitivity when resources permit.
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Claims 10
Claim · model-written summary
Diversified systems improved maize yield by 271% over the control.
Zea maysOrganisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Compared to the control, diversified systems significantly improved maize yield (271%)”
Claim · model-written summary
Diversified systems improved residue cover by 210% over the control.
- Treatment
- diversified systemse0
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- residue covere0
- Direction
- improvede0
- Value
- 210%e0
- Comparator
- controle0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Compared to the control, diversified systems significantly improved maize yield (271%), residue cover (210%)”
Claim · model-written summary
Diversified systems improved macrofauna abundance by 253% over the control.
- Treatment
- diversified systemse0
- Outcome
- macrofauna abundancee0
- Direction
- improvede0
- Value
- 253%e0
- Comparator
- controle0
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Verbatim
e0“Compared to the control, diversified systems significantly improved maize yield (271%), residue cover (210%), macrofauna abundance (253%)”
Claim · model-written summary
Diversified systems improved fungal richness by 52% over the control.
- Treatment
- diversified systemse0
- Outcome
- fungal richnesse0
- Direction
- improvede0
- Value
- 52%e0
- Comparator
- controle0
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Verbatim
e0“Compared to the control, diversified systems significantly improved maize yield (271%), residue cover (210%), macrofauna abundance (253%), and fungal richness (52%)”
Claim · model-written summary
Diversified systems enhanced aggregate stability by 18% over the control.
- Treatment
- diversified systemse0
- Outcome
- aggregate stabilitye0
- Direction
- enhancinge0
- Value
- 18%e0
- Comparator
- controle0
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Verbatim
e0“Compared to the control, diversified systems significantly improved maize yield (271%), residue cover (210%), macrofauna abundance (253%), and fungal richness (52%), while enhancing aggregate stability (18%)”
Claim · model-written summary
Diversified systems had SIR rates 34% higher than the control.
Not reportedTaxon
Verbatim
e0“Compared to the control, diversified systems significantly improved maize yield (271%), residue cover (210%), macrofauna abundance (253%), and fungal richness (52%), while enhancing aggregate stability (18%) and microbial activity (SIR rates 34% higher)”
Claim · model-written summary
POM, POXC, and PMN were the most sensitive physicochemical indicators.
- Outcome
- most sensitive physicochemical indicatorse0
- Direction
- most sensitivee0
- Comparator
- POM, POXC, and PMNe0
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Verbatim
e0“POM, POXC, and PMN were the most sensitive physicochemical indicators, where sensitivity is expressed as responsiveness relative to variability”
Claim · model-written summary
Macrofauna metrics and enzyme activity showed high responsiveness but greater variability.
Not reportedTaxon
Verbatim
e0“Macrofauna metrics and enzyme activity showed high responsiveness but greater variability”
e1“POM, POXC, and PMN were the most sensitive physicochemical indicators”
Claim · model-written summary
The authors recommend soil cover, POM, POXC, PMN, and macrofauna as a practical low-cost core indicator set for smallholders.
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Verbatim
e0“For smallholder contexts, we recommend a practical, low-cost core set of indicators: soil cover, POM, POXC, PMN, and macrofauna”
Claim · model-written summary
The authors recommend SIR for additional sensitivity when resources permit.
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Verbatim
e0“SIR provides additional sensitivity when resources permit”