Regional specialization and market integration: agroecosystem energy transitions in Upper Austria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We investigate agroecosystem energy flows in two Upper Austrian regions, the lowland region Sankt Florian and the prealpine region Grünburg, at five time points between 1830 and 2000. Energetic agroecosystem productivity (energy contents of crops, livestock products, and wood per unit area) is compared to different types of energy inputs, i.e., external inputs from society (labor, industrial inputs, and external biomass inputs) and biomass reused from the local agroecosystem (feed, litter, and seeds). Energy transfers between different compartments of the agroecosystem (agricultural land, forest, and livestock) are also quantified. This allows for delineating an agroecosystem energy transition: In the first stage of this transition, i.e., in the nineteenth century, agroecosystem productivity was low (final produce ranged between 14 and 27 GJ/ha/yr), and local biomass reused made up 97% of total energy inputs in both regions (25-61 GJ/ha/yr). In this period, agroecosystem productivity increase was achieved primarily through more recycling of energy flows within the agroecosystems. In the second stage of the agroecosystem energy transition, i.e., after World War II, external energy inputs increased by factors 2.5 (Sankt Florian) and 5.0 (Grünburg), partly replacing local energy transfers. Final produce per area increased by factors 6.1 (Sankt Florian) and 2.9 (Grünburg). The difference in the resulting energy returns on investment (EROI) owes to regional specialization on cropping versus livestock rearing and to increasing market integration. Our results suggest that sustainable land-use intensification may benefit from some regional specialization harnessing local production potentials based on a mix of local and external inputs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it