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Record W6986303380

Patterns and drivers of terrestrial arthropod biodiversity in northern Canada

2015· dissertation· en· W6986303380 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2015
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityArthropodPredationDominance (genetics)HabitatTrophic levelAssemblage (archaeology)Invertebrate
DOInot available

Abstract

fetched live from OpenAlex

The overarching goal of this thesis was to describe patterns of terrestrial arthropod biodiversity and community structure in northern Canada, and to explore the underlying drivers and mechanisms that are responsible for these patterns. The term “biodiversity” is used here in a broad sense that includes both taxonomic (TD) and functional (FD) diversity. Ground-dwelling arthropods, especially beetles (Coleoptera), were used as model taxa, and were collected using standardized methods from twelve locations in the three northernmost ecoclimatic zones of Canada. Beetle biodiversity changes over time and space. Over the course of one active season, rapid species and functional turnover were observed in two major habitats in one subarctic location (Kugluktuk, Nunavut). While some functional groups were apparent only for brief periods of time, entomophagous predators consistently dominated the assemblage structure in biomass and abundance. This dominance by carnivores was observed consistently throughout the study, regardless of spatial or taxonomic scope. This inverted trophic structure suggests that predators may rely on alternative, non-epigeic prey items. A natural history study of previously unknown host-parasite interactions between beetles and nematomorphs (Gordionus n. sp.) suggests that beetles use alate insects with aquatic larval stages as an important nutrient subsidy. Across the entire study region, beetle TD and FD, as well as overall assemblage structure, display strong negative relationships with latitude, which conforms to the classical latitudinal gradient of diversity. After considering many spatial, environmental and climatic variables, the most significant driver of beetle biodiversity and assemblage structure over time and space was climate, particularly temperature. When the taxonomic scope of the research was expanded to include all ground-dwelling macroarthropod taxa, and the functional scope refined with a multidimensional functional trait-based approach, the same patterns and processes were observed. Additionally, it was found that functional redundancy was greater in the high arctic than in the warmer ecoclimatic zones further south, despite a paucity of taxa in the high arctic. This supports the hypothesis that environmental constraints are more important in regions with harsh climates, and play a greater role in diversity and community assembly processes than niche differentiation. The biodiversity (TD and FD) and structure of terrestrial macroarthropod communities in northern Canada have several consistent patterns: (1) large-scale negative relationships between biodiversity/assemblage structure and latitude; (2) strong correlations between TD and FD; and (3) the dominance of active predatory taxa. The most important finding of this study is that climate (temperature) gradients provide the best explanation for the variability observed in arthropod biodiversity and assemblage structure over time and across space. Lastly, the effects of climate on biodiversity and community assembly seem to be more pronounced in the high arctic than in more southerly biomes. Given the rapid and significant rise in temperature projected for northern biomes and the fact that predatory taxa are often more sensitive to changes in their environments, major changes to arthropod diversity are expected in the north, with implications for the stability of northern ecosystems.  

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.696

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 head0.017
GPT teacher head0.200
Teacher spread0.183 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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