Agriculture and forestry remain vital sources of rural employment; yet both sectors face challenges of low labour productivity, demographic change, and structural inefficiencies. Modernisation improves productivity but often reduces labour demand, creating a policy dilemma between innovation and job preservation. Therefore, this study aims to quantify labour input across different land use types related to agriculture and forestry in Latvia. This study develops a multi-stage framework to quantify labour inputs across agricultural and forestry land uses in Latvia. The research results indicate that labour intensity decreases with farm size but varies more strongly by production type. Perennial plantations, vegetable and potato cultivation, and dairy and pig farming show the highest labour demands, whereas energy crops and grass-based systems require the least. In forestry, establishment and tending dominate labour needs, while mechanised harvesting reduces input requirements. These findings highlight the strategic role of labour-intensive, high-value activities in sustaining rural employment. Policy should prioritise targeted support for labour-intensive, high-value farming and forestry activities to maximise rural jobs and income growth.

Agriculture and forestry remain vital sources of rural employment; yet, both sectors face challenges of low labour productivity, demographic change, and structural inefficiencies. Modernisation improves productivity but often reduces labour demand, creating a policy dilemma between innovation and job preservation. Therefore, this study aims to quantify labour input across different land use types and farm sizes in agriculture and forestry. Latvia was used as a case region representing a sparsely populated territory suitable for both agricultural activities and forestry. This study develops a multi-stage framework to quantify labour inputs across agricultural and forestry land uses. The research findings suggest that labour use intensity decreases as farm size increases; however, it exhibits greater variation across agricultural production types. Perennial plantations, vegetable and potato cultivation, and dairy farming show the highest labour demands, whereas energy crops and grass-based systems require the least. In forestry, establishment and tending dominate labour needs, while mechanised harvesting reduces input requirements. These findings highlight the strategic role of labour-intensive, high-value activities in sustaining rural employment and the need for targeted rural development policies that recognise this pattern, supporting employment in rural areas without discouraging improvements in labour productivity.

Across production and processing systems, biological residuals are inconsistently defined, with the same materials treated as waste, by-products, or resources depending on context. This ambiguity constrains the identification of valorization pathways and limits the design of sustainable and resource-efficient operational strategies. This study addresses the issue by compiling a sector-resolved inventory of 94 bioresiduals across 12 bioeconomy-related activities. Analyzing 1763 firm–bioresidual observations from a national survey in Estonia using binomial logistic regression. The results show that bioresidual use is primarily shaped by operational and data-handling practices, particularly collection and accounting, rather than by structural firm characteristics. Separate collection emerges as a key precondition for higher-value use, while accounting practices are associated with external and energy-related pathways by increasing visibility and traceability. In contrast, irregular or seasonal bioresiduals tend to default to waste handling due to variability and perishability. The findings also indicate that many effective uses remain internal to production systems and are under-documented. Improving the definitions and monitoring practices of bioresiduals could support more efficient and sustainable resource management by reducing biowaste generation and enhancing coordination across value chains, thereby fostering the development of a circular bioeconomy.

This study examines risk attitudes among Estonian farmers, addressing evidence gaps for smaller EU countries. Using an online survey conducted in 2024 (n = 541), we measure risk attitudes on an 11-point scale across six context-specific items. We construct a latent overall risk-taking score via confirmatory factor analysis and estimate associations with demographic and farm characteristics using ordinary least squares regression; k-means clustering identifies risk profiles. Results show that agricultural area is positively associated with risk-taking, while age is negatively related to willingness to take risks. Higher education relates to greater willingness to take risks, especially with respect to experimentation with new crops and production practices. Willingness to use agricultural insurance is positively associated with risk-taking. Risk attitudes also vary by production type: horticulture and perennial crop farmers declare themselves to be more risk-taking than arable crop farmers, whereas livestock and dairy farmers do not differ. Clustering reveals distinct farmer profiles, suggesting scope for targeted risk management strategies.