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Record W2002198107 · doi:10.1111/1365-2664.12041

Ecosystem function enhanced by combining four functional types of plant species in intensively managed grassland mixtures: a 3‐year continental‐scale field experiment

2013· article· en· W2002198107 on OpenAlexaff
John A. Finn, L. Kirwan, John Connolly, Maria‐Teresa Sebastià, Á. Helgadóttir, O. H. Baadshaug, Gilles Bélanger, Alistair Black, Caroline Brophy, R. P. Collins, J. Čop, Sigríður Dalmannsdóttir, Ignacio Delgado, A. Elgersma, M. Fothergill, B. E. Frankow‐Lindberg, An Ghesquiere, Barbara Golińska, P. Goliński, Philippe Grieu, Anne‐Maj Gustavsson, Mats Høglind, Olivier Huguenin‐Elie, Marit Jørgensen, Žydrė Kadžiulienė, Päivi Kurki, Rosa Llurba, Tor Lunnan, C. Porqueddu, Matthias Suter, Ulrich Thumm, A. Lüscher

Bibliographic record

VenueJournal of Applied Ecology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsAgriculture and Agri-Food Canada
FundersScience Foundation IrelandIrish Research Council for Science, Engineering and Technology
KeywordsMonocultureWeedAgronomySpecies evennessBiologyBiomass (ecology)SowingGrasslandPolycultureEcosystemField experimentSpecies richnessEcology

Abstract

fetched live from OpenAlex

Summary A coordinated continental‐scale field experiment across 31 sites was used to compare the biomass yield of monocultures and four species mixtures associated with intensively managed agricultural grassland systems. To increase complementarity in resource use, each of the four species in the experimental design represented a distinct functional type derived from two levels of each of two functional traits, nitrogen acquisition (N2‐fixing legume or nonfixing grass) crossed with temporal development (fast‐establishing or temporally persistent). Relative abundances of the four functional types in mixtures were systematically varied at sowing to vary the evenness of the same four species in mixture communities at each site and sown at two levels of seed density. Across multiple years, the total yield (including weed biomass) of the mixtures exceeded that of the average monoculture in >97% of comparisons. It also exceeded that of the best monoculture (transgressive overyielding) in about 60% of sites, with a mean yield ratio of mixture to best‐performing monoculture of 1·07 across all sites. Analyses based on yield of sown species only (excluding weed biomass) demonstrated considerably greater transgressive overyielding (significant at about 70% of sites, ratio of mixture to best‐performing monoculture = 1·18). Mixtures maintained a resistance to weed invasion over at least 3 years. In mixtures, median values indicate <4% of weed biomass in total yield, whereas the median percentage of weeds in monocultures increased from 15% in year 1 to 32% in year 3. Within each year, there was a highly significant relationship (P < 0·0001) between sward evenness and the diversity effect (excess of mixture performance over that predicted from the monoculture performances of component species). At lower evenness values, increases in community evenness resulted in an increased diversity effect, but the diversity effect was not significantly different from the maximum diversity effect across a wide range of higher evenness values. The latter indicates the robustness of the diversity effect to changes in species' relative abundances. Across sites with three complete years of data (24 of the 31 sites), the effect of interactions between the fast‐establishing and temporal persistent trait levels of temporal development was highly significant and comparable in magnitude to effects of interactions betweenN2‐fixing and nonfixing trait levels of nitrogen acquisition. Synthesis and applications. The design of grassland mixtures is relevant to farm‐level strategies to achieve sustainable intensification. Experimental evidence indicated significant yield benefits of four species agronomic mixtures which yielded more than the highest‐yielding monoculture at most sites. The results are relevant for agricultural practice and show how grassland mixtures can be designed to improve resource complementarity, increase yields and reduce weed invasion. The yield benefits were robust to considerable changes in the relative proportions of the four species, which is extremely useful for practical management of grassland swards.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.006
GPT teacher head0.186
Teacher spread0.179 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations369
Published2013
Admission routes1
Has abstractyes

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