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Record W4416708570 · doi:10.1016/j.agee.2025.110117

Effects of landscape complexity on biodiversity of rice agroecosystems: A meta-analysis

2025· article· en· W4416708570 on OpenAlexaff
Gema Cambero-Conejero, Carles Alcaráz, Néstor Pérez‐Méndez

Bibliographic record

VenueAgriculture Ecosystems & Environment · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsContinental (Canada)
FundersIndiana Retired Teachers AssociationAgencia Estatal de InvestigaciónMinisterio de Economía y Competitividad
KeywordsBiodiversityHabitatFragmentation (computing)Habitat fragmentationSpatial heterogeneityAgricultureHabitat destructionTaxonomic rank

Abstract

fetched live from OpenAlex

Agricultural intensification is one of the primary drivers of landscape simplification and biodiversity loss. Understanding how different taxa respond to landscape complexity is key to address the challenge of enhancing biodiversity while sustaining food production. We performed a global-scale meta-analysis of biodiversity and landscape relationships, yielding 456 effect sizes from 18 papers across 9 countries. We specifically explored the effect across different taxonomic groups (2 vertebrate and 6 invertebrate orders) and landscape complexity dimensions (composition, configuration, heterogeneity). Despite the high heterogeneity among the data, we found a positive effect of landscape complexity on rice-associated biodiversity, yet the magnitude and sign of effects contrasted among specific orders and landscape dimensions. For instance, among vertebrates only amphibians showed a positive response to landscape composition. Among invertebrates, spiders and beetles responded positively to compositional complexity while true bugs responded negatively to configurational complexity. Our results suggest that promoting landscape compositional complexity at large spatial scales overall benefits biological communities in rice agroecosystems, specifically in major rice-producing regions. Yet the negative impact of configurational heterogeneity observed for certain groups of insects (i.e., true bugs) indicate that the spatial arrangement and degree of fragmentation of rice habitats is also an important factor shaping biodiversity outcomes. This highlights the need of considering different landscape dimensions and multiple groups of animals simultaneously when designing large scale habitat management plans to avoid potential trade-offs and maximize biodiversity in rice agroecosystems. • We did a meta-analysis to assess landscape effects on rice-associated biodiversity. • Landscape complexity overall enhanced biodiversity. • Amphibians responded positively to landscape composition complexity. • Spiders and beetles responded positively to landscape composition complexity. • True bugs responded negatively to landscape configurational complexity.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.015
GPT teacher head0.188
Teacher spread0.174 · 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 designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractyes

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