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Record W578309103

Agricultural land use change in relation to agroecosystem health

2000· book· en· W578309103 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Atrium (University of Guelph) · 2000
Typebook
Languageen
FieldEnvironmental Science
TopicSustainable Agricultural Systems Analysis
Canadian institutionsnot available
FundersMinistère de l’Éducation, Gouvernement de l’OntarioBộ Giáo dục và Ðào tạo
KeywordsAgroecosystemRelation (database)AgricultureGeographyAgroforestryAgricultural landEnvironmental scienceComputer scienceArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This thesis develops and tests a conceptual framework for assessing the changes in agroecosystem health from the perspective of agricultural land use. To understand the dynamic relationships in agroecosystems, a general conceptual model is developed with reference to patterns, processes, and forces of change in agricultural land use at different spatial scales. The definition of agroecosystem health adopted for this research is defined as the system's ability to realize its functions desired by society and to maintain its structure needed both by its functions and by society over a long time period. General criteria for characterizing the structural, functional, organizational, and dynamic health of agroecosystems are identified, and their potential utility assessed. The identified general criteria are further developed as five agroecosystem health indicators relating to different aspects of changes in agricultural land use. They are changes in agricultural land resource availability, land use diversity, productivity, self-dependence, and land use stability. A conceptual framework is then developed to further an understanding of the stress-response relationships involved in these aspects of changes in agricultural land use. The framework also facilitates the identification of driving factors/attributes related to macro-level environments. The proposed framework for assessing agroecosystem health is tested in two case studies. The first case study investigates the changes in agricultural land use to southern Ontario over a twenty year period from 1971 to 1991, and the second in Wellington County over the period 1986-91. Using four measurable indicators of land use change and secondary census data, the macro-scale study identifies that both structural and organizational health of the southern Ontario agroecosystem have deteriorated noticeably while the functional health has improved greatly. The macro-scale case study also concludes that the changes in agroecosystem health are significantly associated with the various forces related to biophysical conditions, changes in technology, changes in economic conditions, and modifications in institutional and social settings. According to two indicators of land resource availability and diversity, the county level study identifies that the structural health of the agroecosystem has also undergone a decline. The study reveals that the level of decline in the structural health is higher in northeastern Wellington than in the southwestern part of the county. Also, the changes are associated with different processes of land use conversion among agricultural land, forest, scrubland, and urban related uses. The analytical approach in the first case study demonstrates the utility of censuses and other secondary information for assessing the dynamics of agroecosystem health at a macro scale. It shows how the specific health indicators can be measured, and how GIS and statistical methods can be used to analyze the relationships in the changes of agroecosystem health. The second case study illustrates the utility and limitation of the remote sensing approach for studying the short term change in agroecosystem health at a meso-scale. (Abstract shortened by UMI.)

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.015
GPT teacher head0.196
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it