Review of: Tracking changes in birds' interaction milieu. Round#2/Reviewer#1
Bibliographic record
Abstract
Documenting species interactions is quite a difficult task (Jordano, 2016), especially for rare or endangered species as interactions are often identified using invasive methods and because sampling methods affect interaction network properties (Gibson et al., 2011, Brimacombe et al., 2023).By contrast, species associations or co-occurrences are much easier to assess and can inform about the interaction milieu of species and communities (McGill et al., 2006).Changes in associations can be due to the loss of one of the associated species (e.g. through land-use changes and a decrease in habitat suitability), external environmental variables differently affecting species abundances (e.g.disruption of association through phenological desynchronization induced by climate change), or the introduction or removal of some other species (e.g.invasion of the community by a dominant competitor).Therefore, monitoring changes in species associations can serve as a valuable indicator of the impacts of global changes.Evaluating shifts in these associations is a first important step toward understanding changes of functional interactions within ecological communities.Rigal et al. (2025) elegantly address the analysis of association networks among common bird species by combining convergent cross-mapping to evidence significant associations (Sugihara et al., 2012) with generalized linear models to assess both the functional relevance of such associations and the temporal trends affecting the association network.This study reports a decline in species richness together with an increase in association connectance and a decrease of the evenness of the number of associations per species.Such findings suggest 1 that, despite a simplification of bird communities in farmland and forest habitats, associations could be more resilient than expected to further changes as they might involve a higher proportion of association generalists.Reassuringly, Rigal et al. ( 2025) did not find changes in association modularity, which might play out as a barrier against further disruptions of these association networks.Taken together, these results raise an alarm -common bird species are declining -but stress some potential properties of association networks that can increase their resilience against further changes.This study is remarkable for its ability to identify certain patterns in species associations that raise questions about the resilience of common bird communities to future anthropogenic disturbances in their habitats.While classic community studies can assess trends in diversity, they are blind to species associations and thus tend to consider communities as lists of species names, not interacting entities contributing to some ecosystem functions (McGill et al., 2006).The results of this study thus highlight the importance of taking into account pairwise species associations when investigating the effects of community trends.As interaction milieu explicitly accounts for habitats, one can only hope that such a study will pave the way for the exploration of the empirical "keystoneness" of some habitats for the maintenance of species associations within complex landscape mosaics.And as new, less invasive methods become available to identify species and interactions (Hye et al., 2021), hopefully such analyses will eventually be applied to interactions rather than associations.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".