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Response of Forest to Climatic Events and Human Management at Fort Leavenworth, Kansas

2002· article· en· W4406784078 on OpenAlexaff
James S. Aber, Juliet Wallace, Matthew C. Nowak

Bibliographic record

VenueBulletin (Kansas Geological Survey) · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of Waterloo
FundersOffice of Experimental Program to Stimulate Competitive ResearchEmporia State UniversityNational Aeronautics and Space Administration
KeywordsGeographyEnvironmental sciencePhysical geographyForestry

Abstract

fetched live from OpenAlex

Characteristics and temporal changes in forest cover from 1987 to 1997 were documented on the basis of remote sensing for two study forests at Fort Leavenworth, northeastern Kansas. Eight Landsat 5 Thematic Mapper (TM) datasets from the month of July cover the study period, which included a major drought in 1988-1989 and flooding along the Missouri River in 1993. Other data sources included kite aerial photographs, digital orthophotos, tree-ring cores, climatic records, and ground observations. Three study areas were evaluated from Landsat TM datasets: (1) the entire Fort Leavenworth area; (2) an upland, hardwood forest composed mainly of oaks; and (3) a bottomland, softwood forest dominated by cottonwood. Normalized Difference Vegetation Index (NDVI) values were derived from these three study sets and subjected to image differencing and principal-component analysis. The TM band 5:4 ratio was also analyzed for the two study forests. Values and trends derived from Landsat imagery were compared to data on tree-ring growth in upland oaks and regional climatic events. Annual growth of tree rings in upland oaks is tied closely to precipitation and the Palmer Drought Severity Index (PDSI); however, changes in NDVI values lag one to two years behind the onset of climatic events, particularly drought episodes. During the first year of drought (1988), vegetation cover in the upland and bottomland forests reacted in different ways: with a slight decline in the upland forest and a slight increase in the bottomland forest. The increased vegetation in the bottomland forest presumably resulted from more understory growth in dry hollows and potholes. In the second year of drought (1989), both forests suffered a marked decline in vegetation cover. NDVI values reached their minima for all categories (whole area, upland forest, and bottomland forest) in 1990, even though precipitation and tree-ring growth increased substantially that year. We conclude that changes in Landsat-derived NDVI values are out of phase with climatic events and variations in tree-ring growth for both upland and bottomland forests in northeastern Kansas and northwestern Missouri. Overall change (1987 to 1997) for NDVI values is down slightly for all categories of evaluation. This probably reflects reduced precipitation throughout the study period compared to the long-term average. Changes in vegetation took place mainly on the forest margins. Such changes are thought to result from microclimatic stress at forest edges. The bottomland study forest also was impacted by severe flooding in 1993. Routine human activities may have resulted in minor changes along the margins of both study forests. The bottomland forest was affected by intentional burning of the adjacent prairie in April 2000. Cottonwood trees at the forest edge were killed or injured by the prairie fire, which penetrated the forest understory some distance.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.720

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.020
GPT teacher head0.226
Teacher spread0.206 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2002
Admission routes1
Has abstractyes

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