Taxonomic, temporal, and spatial variation in the dynamics of High-Arctic arthropod populations
Bibliographic record
Abstract
ABSTRACT Time-series data on arthropod populations are critical for understanding the magnitude, direction, and drivers of abundance changes. However, most arthropod monitoring programs are short-lived and limited in taxonomic resolution and spatial extent. Consequently, variation in population dynamics among taxa and habitats remains poorly understood. Monitoring data from the Arctic are particularly underrepresented, yet important to assessments of species abundance changes because many anthropogenic drivers of change that are present in other regions are absent in polar regions. Here, we utilise 24 years of abundance data from Zackenberg in High-Arctic Greenland, which is the longest running Arctic arthropod monitoring program, to study temporal trends in abundance. Despite a strong warming signal in air temperature, we only find evidence of weak temporal trends in arthropod abundances across most taxa. These trends are more pronounced in the most recent decade, with change point analyses suggesting distinct non-linear dynamics within some functional groups such as predators and detritivores. Although the abundances of many taxa were correlated, we detected both positive and negative correlations, suggesting that multiple processes are affecting arthropod populations even in this relatively simple Arctic food web. Finally, we found clear differences among species within single families of arthropods, indicating that an apparent lack of change in abundance at broader taxonomic or functional levels could mask substantial species-specific trends. Our results reiterate the need for more basic research into the life-history, ecology, and adaptation of arthropod species to better understand their sensitivity to global changes. Significance statement Terrestrial arthropods, including insects and spiders, serve critical ecosystem functions and are excellent indicators of environmental change due to their physiology, short generation time, and abundance. The Arctic, with its rapid climate change and limited direct anthropogenic impact, is ideal for examining arthropod population dynamics. We use the most comprehensive, standardized dataset available on Arctic arthropods to evaluate the variability in population dynamics for the most common arthropod groups at various taxonomic levels across 24 years. Our results highlight that temporal trends of arthropod populations seem less directional in the Arctic than in temperate regions. Although abundances of some arthropod taxa are declining, particularly in recent decades, population trends still display high variation among time periods, taxa, and habitats.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".