Managing grasslands for both carbon sequestration and biodiversity conservation is increasingly challenging under climate change. We develop an integrated climate–ecological–economic modelling framework to evaluate biodiversity–carbon trade-offs in the Inner Mongolian typical steppe, where mowing and grazing are dominant management practices. Using butterflies as biodiversity indicators, carbon-sequestration estimates, regional opportunity-cost parameters, and downscaled climate projections under SSP1–2.6, SSP2–4.5, and SSP5–8.5, we applied the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to identify Pareto-optimal mowing–grazing configurations from 2025 to 2050. The simulations indicated that, within the parameterized water-limited response functions, projected precipitation differences were associated with larger shifts in biodiversity–carbon co-management potential than temperature differences. Under the assumptions of our modelling framework, optimized configurations were generally mowing-dominated, with mowing accounting for 77%–94% of the management-allocation matrix in representative 2030 solutions, although grazing-oriented patches remained important in biodiversity-priority outcomes by maintaining habitat heterogeneity. Opportunity-cost accounting provided a regional economic comparison layer for Pareto-optimal configurations, with temporal cost increases mainly reflecting the assumed annual escalation and cross-scenario differences reflecting the cost ranges of feasible Pareto-optimal solutions. Overall, the framework provides a transferable approach for linking climate scenarios, land-use allocation, ecological outcomes, and economic constraints in grassland biodiversity–carbon co-management, subject to recalibration with local ecological, management, and economic parameters.
This study examines generational renewal in Swedish agriculture by analysing farmers’ career trajectories over the life course. Using longitudinal register data covering the entire Swedish population of farmers during 1991–2022, we study three key transitions: whether individuals who work in agriculture remain in the sector over time, whether they transition into farm ownership, and when older farmers exit through retirement. The results show that around 60–65 percent of individuals who work in agriculture in their late teens leave the sector by age 25, but that younger cohorts are more likely than older cohorts to remain in agriculture, while differences in farm ownership are substantially smaller once the analysis is conditioned on continued participation in the sector. However, the youngest cohort shows signs of an earlier transition into farm ownership. This pattern coincides with greater exposure to the Support for young farmers and is consistent with, but does not establish, the hypothesis that the support brought forward entry into farm ownership. The study also shows that farmers retire substantially later than the general population and that younger cohorts postpone full retirement longer than older cohorts. Observable characteristics explain only a limited share of these cohort differences.
Aim To map literature on perceptions of patients, relatives, and healthcare professionals regarding the use of digital diaries in healthcare, to inform pre-implementation of an ICU diary by identifying factors relevant to feasibility, acceptability, and integration into ICU workflows. Methods The review followed the Joanna Briggs Institute (JBI) methodology and PRISMA-ScR reporting guidelines. Studies including patients, relatives, and healthcare professionals with experience of digital diary use in healthcare settings were eligible. Included studies reported perceptions of digital diaries. Data were synthesised using inductive content analysis. Findings From 679 identified records, 13 studies (2014–2025) were included, covering symptom diaries (n = 7) and ICU diaries (n = 6). The synthesis generated three overarching categories across user groups: relational connectedness and person-centred care; empowerment and meaning-making; and implementation and technological readiness. Across contexts, digital diaries were described as shaping communication, participation, and continuity of care, while also enabling reflection and meaning-making during illness and recovery. However, their perceived value was highly context-dependent and shaped by implementation conditions. Conclusions Digital diaries were perceived by patients, relatives, and healthcare professionals as influencing communication, continuity, and engagement in care. Patients highlighted reflection, increased awareness, and participation, while relatives emphasised connection and involvement. Healthcare professionals focused on usability, workflow integration, and organisational conditions shaping use. They were perceived as valuable when they supported communication and made patients' experiences more visible, but as less useful when poorly integrated into clinical routines. Their perceived value depended on how they were embedded in practice and shaped by interactions between users, technology, and organisational context. Implications for Clinical Practice Digital diaries have the potential to support communication, involvement, and continuity of care. However, realising this potential requires deliberate integration into clinical workflows, role definition, and user-centred design. Ongoing evaluation is essential, particularly in ICU contexts where experiential and person-centred outcomes remain underexplored.
NaOH and NaCl vapor are key alkali compounds released during the thermal conversion of high-alkali coal and municipal solid waste, and their accurate measurement is crucial for understanding the mechanisms of ash deposition, slagging, and other related issues. However, in-situ and species-specific measurement techniques with high sensitivity for NaOH and NaCl molecules in hash combustion environments remain largely underdeveloped. Based on photodissociation and laser atomic absorption spectroscopy, this study develops a quantitative diagnostic method for NaOH and NaCl applicable to high temperature combustion environments. During photodissociation process, the distinct photofragmentation properties of NaCl and NaOH provide straightforward component discrimination: 355 nm laser can photodissociate NaOH in generating Na atoms, while 266 nm laser photodissociate dominantly NaCl, which enables their differentiation. In subsequent measurements of photofragmentation-induced atomic concentrations, the absorption cross-section of photogenerated Na atoms at the 589.6 nm line was experimentally determined to ensure the measurement accuracy. The performance of two optical configurations (coaxial and orthogonal) was systematically compared, where the coaxial one is suitable for industrial applications, while the orthogonal one offers spatial resolution. Based on the photofragmentation and atomic absorption spectroscopy, a detection limit of 271 ppb and 303 ppb for NaOH and NaCl with a temporal resolution of 0.1 s was achieved using orthogonal configuration. Further applications in homogeneous reaction and heterogeneous coal pellet combustion demonstrate the technique's capability for accurate spatially resolved measurement. Besides, adaptability of this method to the combustion environments in a 100-kW pilotscale down-fired furnace was estimated, providing an effective tool for online monitoring of NaOH and NaCl release and transformation during combustion processes.
The purported immateriality of AI technologies is as illusory as the general understanding of conventional technologies as simply the application of politically neutral knowledge to nature. The materiality of technologies and their foundation in global inequalities has been illuminated by studies of ecologically unequal exchange (EUE). The aim of this article is to extend the applicability of EUE theory to digital technologies such as Artificial Intelligence (AI) by highlighting how even the data that they process have an inevitably biophysical history. AI technologies represent a novelty mainly in the sense that, in addition to exploiting extractive areas through EUE, they are based on the appropriation of data from the public. We argue for understanding the materiality of data as derived from lived human time. AI's dependence on data can thus be regarded as representing and embodying biophysical processes and asymmetric transfers implicating issues of justice.
