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Record W3176344899 · doi:10.30564/jzr.v3i3.3102

A Review of the Engineering Role of Burrowing Animals: Implication of Chinese Pangolin as an Ecosystem Engineer

2021· review· en· W3176344899 on OpenAlexaff
Song Sun, Hongliang Dou, Shichao Wei, Yani Fang, Zexu Long, Jiao Wang, Fuyu An, Jinqian Xu, Tingting Xue, Huangjie Qiu, Yan Hua, Guangshun Jiang

Bibliographic record

VenueJournal of Zoological Research · 2021
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEcosystem engineerEcosystemEcologyBiodiversityHabitatAbundance (ecology)Keystone speciesTrophic levelEcosystem servicesEcological engineeringEnvironmental resource managementBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Ecosystem engineers are organisms that alter the distribution of resources in the environment by creating, modifying, maintaining and/or destroying the habitat. They can affect the structure and function of the whole ecosystem furthermore. Burrowing engineers are an important group in ecosystem engineers as they play a critical role in soil translocation and habitat creation in various types of environment.However, few researchers have systematically summarized and analyzed the studies of burrowing engineers. We reviewing the existing ecological studies of burrowing engineer about their interaction with habitat through five directions: (1) soil turnover; (2)changing soil physicochemical properties; (3) changing plant community structure; (4) providing limited resources for commensal animals;and/or (5) affecting animal communities. The Chinese pangolin (Manis pentadactyla) is a typical example of burrowing mammals, in part (5), we focus on the interspecific relationships among burrow commensal species of Chinese pangolin. The engineering effects vary with environmental gradient, literature indicates that burrowing engineer play a stronger role in habitat transformation in the tropical and subtropical areas.The most common experiment method is comparative measurements (include different spatial and temporal scale),manipulative experiment is relatively few. We found that most of the engineering effects had positive feedback to the local ecosystem, increased plant abundance and resilience, increased biodiversity and consequently improved ecosystem functioning. With the global background of dramatic climate change and biodiversity loss in recent decades, we recommend future studies should improving knowledge of long-term engineering effects on population scale and landscape scale, exploring ecological cascades through trophic and engineering pathways, to better understand the attribute of the burrowing behavior of engineers to restore ecosystems and habitat creation. The review is presented as an aid to systematically expound the engineering effect of burrowing animals in the ecosystem, and provided new ideas and advice for planning and implementing conservation management.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.723
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.108
GPT teacher head0.410
Teacher spread0.302 · 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 designOther design
Domainnot available
GenreReview

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

Citations13
Published2021
Admission routes1
Has abstractyes

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