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Record W32080941 · doi:10.1002/eap.2095

Sekresi Asam Malat oleh Akar Tanaman Padi pada Kondisi Cekaman Aluminium.

2008· article· en· W32080941 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

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Conservation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAluminiumMetallurgyMaterials science

Abstract

fetched live from OpenAlex

Ecosystem functions provided by forests are threatened by direct and indirect effects of global change drivers such as climate warming land-use change, biological invasions, and shifting natural disturbance regimes. To develop resilience-based forest management, new tools and methods are needed to quantitatively estimate forest resilience to management and future natural disturbances. We propose a multidimensional evaluation of ecological resilience based on species functional response traits (e.g., functional response diversity and functional redundancy) and network properties of forested patches (e.g., connectivity, modularity, and centrality). Using a fragmented rural landscape in temperate south-eastern Canada as a reference landscape, we apply our multidimensional approach to evaluate two alternative management strategies at three levels of intensity: (1) functional enrichment of current forest patches and (2) multi-species plantations in previously non-forested patches. Within each management strategy, planted species are selected to maximize functional diversity, drought tolerance, or pest resistance. We further compare how ecological resilience under these alternative management strategies responds to three simulated disturbances: drought, pest outbreak, and timber harvesting. We found that both management strategies enhance resilience at the landscape scale by increasing functional response diversity and connectivity. Specifically, when the less functionally diverse patches are prioritized for management, functional enrichment is more effective than the establishment of new multi-species plantations in increasing resilience. In addition, randomly allocated multi-species plantations increased connectivity more than those allocated in riparian areas. Our results show that across various management strategies, planting species to enhance biodiversity led to the highest increase in functional response diversity while planting pest-resistant species led to the highest increase in landscape connectivity. Planting biodiversity-enhancing species (i.e., species that maximize functional diversity) mitigated drought effects equally well as planting with drought-tolerant species. Our multidimensional approach facilitates the characterization at the landscape scale of forest resilience to disturbances using both functional diversity and network properties while accounting for the importance of response traits to future disturbances. The simulation approach we used can be applied to forest landscapes across different biomes for the evaluation and comparison of forest management initiatives to enhance resilience.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.998

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)0.0030.000

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 head0.021
GPT teacher head0.178
Teacher spread0.157 · 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

Quick stats

Citations3
Published2008
Admission routes2
Has abstractyes

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