Back

Beyond adoption rates: Farmer motivations and communication needs in straw management decision-making

Blennow, K.; Anander, E.

2025-08-29 scientific communication and education
10.1101/2025.08.25.672071 bioRxiv
Show abstract

Sustainable bioenergy is central to climate change mitigation, yet biomass supply depends not only on biophysical and economic assessments but also on farmers decision-making. Straw from cereal and oilseed crops can support renewable energy, but its availability is constrained by on-farm uses, management practices, and farmers access to knowledge of sustainable soil management. Because straw removal affects soil organic carbon (SOC) stocks, which underpins soil fertility, nutrient cycling, and carbon sequestration, understanding farmers motivations and informational needs is critical to support sustainable straw management. We examined the determinants of straw management among farmers in Scania County, southern Sweden, testing three hypotheses: that manure application increases the likelihood of straw removal, that a higher proportion of leased land promotes straw removal, and that humus-rich soils are associated with a higher probability of straw removal. Survey data from 2021 were analysed using Bayesian Additive Regression Trees (BART) and permutation tests, incorporating farmers expected utility. Results show that manure application increases removal probability, whereas a higher share of leased land reduces it. Removal was most frequent on soils with intermediate humus content. Cluster analysis identified three farmer profiles, revealing heterogeneous motivations and knowledge gaps, particularly regarding soil humus content, and underscoring the need for context-specific communication strategies. These findings demonstrate that similar straw management behaviours can arise from diverse motivations and local conditions. Linking expectations, soil properties, and practices provides actionable insights for targeted advisory and policy measures that balance agronomic and economic outcomes with long-term SOC-mediated fertility, carbon sequestration, and ecosystem services.

Published in GCB Bioenergy · not in our set (fewer than 10 published preprints to learn from) · training set

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.