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Record W2195445045

Vplyv klimatických zmien na vývoj lesných ekosystémov hornej hranice lesa

2012· article· sk· W2195445045 on OpenAlexaboutno aff
J. Minďáš, Jaroslav Škvarenina

Bibliographic record

VenueOecologia Montana · 2012
Typearticle
Languagesk
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceClimate changeEcosystemForest ecologyForestryTree lineAtmospheric sciencesEcologyClimatologyPhysical geographyGeographyBiologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

Analyses of dynamic changes of natural ecosystems of the upper three line using the Forest Gap Model was applied to predict effects of climate changes after doubling the concentration of carbon dioxide (CO2). The Forest Gap Models belong into the group of dynamic models that are able to calculate varied parameters of forest trees in time series. The models are based on simulations of natural regeneration, growth, mortality of each tree in the studied ecosystem. To simulate effects of double increased concentration of carbon dioxide expected in the year 2070, the regional models of climate change (regional interpretation of the values of climatic elements based on general atmospheric circulation models) from the territory of the Slovak Republic were applied. The values the regional models of climate change were also derived from the Canadian Climate Centre Model (CCCM). The following input parameters of individual forest trees were used in the simulation: the maximal age of tree, the maximal tree width (1.3 m), the maximal height, and the parameters of natural tree regenerations. The model includes several response functions that cover environmental effect of individual trees such as the lights requirements, the temperature requirements, and moisture requirements. Characteristics of individual tree species (age, diameter, height) incorporated in the simulation algorithms were collected in the three long term monitoring plots in the nature reserves by the Forestry Research Institute in Zvolen. Two monitoring plots located in the Piľsko (1 250 m a.s.l.), Oravske Beskydy Mts., and in the Vajskovska valley (1 300 m a.s.l.), Nizke Tatry Mts., represented mountain forest ecosystems dominated by Fagus sylvatica, Picea abies, Abies alba, and Sorbus aucuparia. The third monitoring plot dominated by Pinus mugo, Picea abies, and Sorbus aucuparia was also sited in the Vajskovska valley, 1 700 m a.s.l., represented the dwaft pine communities above the upper tree line (subalpine zone). Simulations of the climate change effects on tree species were based on climatic amplitudes of their geographic range. The model simulations were carried out for the current climate conditions (means 1951-80) and for the expected climatic conditions following the model CCCM. The model simulations showed significant changes in the potential forest production and distributional patterns of tree species in each studied site. The computer simulations of the two sites located in the mountain forest zone showed significant increase of relative abundance of Fagus sylvatica and Acer pseudoplatanus, significant decrease or almost absence of relative abundance of Picea abies, and increase of the total biomass production for 17–30 %. The simulations showed the most drastic changes in the subalpine zone. The original dwarft pine community will be dominated by Picea abies, dominance of other tree species will also increase, yet Pinus mugo will decline, and the total biomass production will increase for 200–300 %. The results should be, however,. interpreted carefully since the applied models did not incorporate possible effects of chemical climate change e.g., increased concentration of tropospheric ozone, increased UV-B radiation, immissions, etc.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.233
Teacher spread0.220 · 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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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