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Consequences of species loss for ecosystem functioning: meta-analyses of data from biodiversity experiments

2009· book-chapter· en· W2506326843 on OpenAlexaff
Bernhard Schmid, Patricia Balvanera, Bradley J. Cardinale, Jasmin A. Godbold, Andrea B. Pfisterer, David Raffaelli, Martin Solan, Diane S. Srivastava

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiodiversityTrophic levelEcosystemSpecies richnessEcologyGlobal biodiversityRange (aeronautics)Species diversityBiologyGeography

Abstract

fetched live from OpenAlex

Abstract A large number of studies have now explicitly examined the relationship between species loss and ecosystem function. Analyzed by two independent groups, the results from such experiments show that reductions in species diversity generally result in reduced ecosystem functioning, across a wide range of ecosystems, diversity manipulations, and functions. This chapter analyzes both data sets in parallel to explain variation in the observed functional effects of biodiversity. This chapter concludes: 1) the functional effects of biodiversity differ among ecosystem types (but not between terrestrial and aquatic systems), 2) increases in species richness enhance community responses but negatively affect population responses, 3) stocks are more responsive than rates, 4) diversity reductions often reduce function at an adjacent trophic level, 5) increased biodiversity results in increased invasion resistance. This chapter also analyzes the shape of the relationship between biodiversity and function, and discuss consequences of different relationships.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.009
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.288
GPT teacher head0.337
Teacher spread0.049 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
DomainMethods
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

Citations127
Published2009
Admission routes1
Has abstractyes

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