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Record W2790177249 · doi:10.1080/11956860.2018.1439297

Contrasting responses of generalized/specialized mistletoe-host interactions under climate change

2018· article· en· W2790177249 on OpenAlexvenueno aff
Juan Francisco Ornelas, Yuyini Licona-Vera, Andrés Ernesto Ortiz-Rodríguez

Bibliographic record

VenueEcoscience · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsGeneralist and specialist speciesEcologyNicheHost (biology)Ecological nicheClimate changeEnvironmental niche modellingBiologySpecies distributionHabitat

Abstract

fetched live from OpenAlex

Considering that parasitic plant distributions are constrained by host availability, we measure the effects of adding information of host distributions to predict distributions of mistletoes under climate change using ecological niche modeling (ENM). We contrasted ecological niche models of two Psittacanthus mistletoe species, P. schiedeanus, a host-generalist species inhabiting cloud forests, and P. sonorae, a Bursera-specialist restricted to the Sonoran Desert. Mistletoe models that use only climate variables were contrasted with models that also take into account biotic interactions (i.e., host) to evaluate the potential effects that future climatic conditions have on the distributions of these mistletoe-host interactions. Current potential distributions of both mistletoe species were affected by environmental conditions under future climate change scenarios. However, future projected distributions differed between mistletoe species when including host interactions, with improved accuracy models for P. schiedeanus. Our results are consistent with previous studies showing that biotic interactions can be important in structuring species distributions at regional scales.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
Threshold uncertainty score0.573

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)0.0010.000

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 head0.067
GPT teacher head0.293
Teacher spread0.226 · 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 designBench or experimental
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

Citations10
Published2018
Admission routes1
Has abstractyes

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