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Spatio‐temporal development of forests – current trends in field methods and models

2004· article· en· W2143640401 on OpenAlexaff
Georg Gratzer, Charles D. Canham, Ulf Dieckmann, Anton Fischer, Yoh Iwasa, Richard Law, Manfred J. Lexer, Holger Sandmann, Thomas A. Spies, Bernhard E. Splechtna, Jerzy Szwagrzyk

Bibliographic record

VenueOikos · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsSimon Fraser University
FundersÖsterreichischen Akademie der Wissenschaften
KeywordsForest dynamicsTemporal scalesComputer scienceMoment (physics)Field (mathematics)EcologyForest ecologySpatial ecologyEcosystemMathematicsPhysics

Abstract

fetched live from OpenAlex

We present a critical review of current trends in research of spatio‐temporal development of forests. The paper addresses (1) field methods for the development of spatially‐explicit models of forest dynamics and their integration in models of forest dynamics, (2) strengths and limitations of traditional patch models versus spatially‐explicit, individual‐based models, and (3) the potential for moment‐based methods in the analysis of forest dynamics. These topics are discussed with reference to their potential for solving open questions in the studies of forest dynamics. The study of spatio‐temporal processes provides a link between pattern and process in plant communities, and plays a crucial role in understanding ecosystem dynamics. In the last decade, the development of spatially‐explicit, individual‐based models shifted the focus of forest dynamics modelling from the dynamics of discrete patches to the interactions among individual organisms, thus encapsulating the theory of “neighbourhood” dynamics. In turn, the stochastic properties and the complexity of spatially‐explicit, individual‐based models gave rise to the development of a new suite of so‐called moment‐based models. These new models describe the dynamics of individuals and of pairs of individuals in terms of their densities, thus directly capturing second‐order information on spatial structure. So far, this approach has not been applied to forests; we indicate extensions needed for such applications. Moment‐based models may be an important complement to spatially explicit individual‐based models in developing a general spatial theory of forest dynamics. However, both kinds of models currently focus on fine scales, whereas a critical issue in forest dynamics is to understand the interaction of fine‐scale processes with coarser‐scale disturbances. To obtain a more complete picture of forest dynamics, the relevant links and interactions between fine‐, intermediate‐, and coarse‐scale processes ought to be identified. Intensive links between modelling work and field studies designed across different scales are a promising means to create a new perspective on forest dynamics.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.335
Teacher spread0.305 · 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 teacher head, 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

Citations110
Published2004
Admission routes1
Has abstractyes

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