Salinity impedes soil and crop productivity in over 900 million ha of arable lands worldwide due to the excessive accumulation of salt (NaCl). To utilize saline soils in agriculture, halophytes (salt-tolerant plants) are commonly cultivated. However, most food crops are glycophytes (salt-sensitive). Thus, to enhance the productivity of saline soils, gypsum (CaSO₄·2H₂O) as well as bio-organic (combined use of organic materials, such as compost and straw with the inoculation of beneficial microbes) amendments have been continuously recognized to improve the biological, physical and chemical properties of saline soils. CaSO₄·2H₂O regulates the exchange of sodium (Na⁺) for calcium (Ca²⁺) on the clay surfaces, thereby increasing the Ca²⁺/Na⁺ ratio in the soil solution. Intracellularly, Ca²⁺ also promotes a higher K⁺/Na⁺ ratio. Simultaneously, gypsum furnishes crops with sulfur (S) for enhanced growth and yield through the increased production of phytohormones, amino acids, glutathione and osmoprotectants, which are vital elicitors in plants’ responses to salinity stress. Likewise, bio-organic amendments improve the organic matter and carbon content, nutrient cycling, porosity, water holding capacity, soil enzyme activities and biodiversity in saline soils. Overall, the integrated application of gypsum and bio-organic amendments in cultivating glycophytes and halophytes is a highly promising strategy in enhancing the productivity of saline soils.

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

Conservation agriculture (CA) is widely recognized as the cornerstone of sustainable agriculture. It prioritizes minimizing soil disturbance, maintaining permanent soil cover, and diversifying crop species to restore soil health and ecosystem resilience. This review synthesizes the effects of CA on the soil’s physical–chemical and biological properties. It demonstrates its effectiveness in improving soil structure, enhancing organic carbon sequestration, promoting microbial activity, increasing water-use efficiency, and reducing erosion and nutrient losses. The paper then highlights the broad environmental, economic, and social benefits of CA. These include biodiversity conservation, reduced greenhouse gas emissions, improved yields, and increased food system resilience. The review explores the synergistic role of technological innovations such as precision agriculture, remote sensing, and digital tools in scaling CA for higher productivity and sustainability. The review then examines how socioeconomic conditions, institutional frameworks, and policy interventions shape CA adoption and impact. Despite its growing adoption, CA’s successful implementation will require strategies adapted for local needs, capacity-building, and supportive, inclusive policies. Finally, the review identifies key CA research gaps and future directions. This provides a comprehensive foundation to advance CA as a climate-smart, resilient, and sustainable pathway to ensure global food security and environmental stewardship.

The complimentary effects of a native rhizobia strain (SAMFIX 286), lime and single superphosphate (SSP) as components of ISFM were evaluated on the biomass, nodulation and N₂ fixation of cowpea (Vigna unguiculata L.). Lime was applied at the rate of 250 kg (Ca(OH)₂) ha⁻¹, while SSP was applied at 30 kg P ha⁻¹. The trial was carried out in a screen house with the treatments arranged in randomized complete block design. Results obtained show that the performance of SAMFIX 286 inoculated plants did not significantly (p < 0.05) differ from that of the un-inoculated treatment. Application of lime significantly increased root dry weight, shoot dry weight, nodule number and dry weight by 42.5%, 35.3%, 65.6% and 50%, respectively. Nodulation was significantly (p < 0.05) increased by SSP. The complimentary effect of lime with SSP significantly increased total shoot N concentration. Similarly, combined inoculation of SAMFIX 286 with lime and SSP increased N concentration by 31.9% and N derived from atmosphere (Ndfa) by 16.3% compared to the un-inoculated treatment. Inoculation of SAMFIX 286 with SSP was also effective on Ndfa by cowpea. It was concluded that lime and SSP were good combination with native rhizobia strain in improving cowpea nodulation and biological N₂ fixation.