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Record W4214497695 · doi:10.3389/fenvs.2022.803009

Senegalia senegal (L.) Britton Response to Microbial and Manure Amendments for the Rehabilitation of Waste Rock Dumps in the Essakane Gold Mining Site, Burkina Faso

2022· article· en· W4214497695 on OpenAlexafffund
Hendi Hermann Yonli, Godar Sene, Kadidia B. Sanon, Mahamadi Dianda, Damase P. Khasa

Bibliographic record

VenueFrontiers in Environmental Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsCenter for Northern Studies
FundersIAMGOLDNatural Sciences and Engineering Research Council of CanadaUniversité Cheikh Anta Diop de DakarMitacsUniversité Laval
KeywordsRhizophagus irregularisManureColonizationInoculationAgronomyBiologySubstrate (aquarium)HorticultureSymbiosisArbuscular mycorrhizalEcologyBacteria

Abstract

fetched live from OpenAlex

Senegalia senegal (L.) Britton (Fabaceae) is a widespread, multipurpose tree capable of colonizing disturbed Sub-Saharan mining sites given its adaptations to arid lands. The purpose of this study was to determine the potential of the association of microbial and/or manure amendments with S. senegal seedlings for the effective rehabilitation of the environment post mining. A multi-year factorial experiment involving this species was conducted in a nursery and on waste rock dumps (Essakane gold mine, NE Burkina Faso). Inoculation with arbuscular mycorrhizal (AM) fungi (native isolate Rhizophagus aggregatus DAOM2277128; commercial isolate Rhizophagus irregularis DAOM197198) and Mesorhizobium plurifarium strain ORS3588 was conducted on S. senegal seedlings. These were planted in black polythene bags filled with three substrate types: 100% sandy soil (substrate A); 75% sandy soil, 25% manure (substrate B); and 50% sandy soil, 50% manure (substrate C). Seedlings were then out-planted on waste rock to determine whether microbial inoculation improves their growth and survival rates. Under nursery conditions, manure-enriched substrates harboured less nodulation and AM colonization, but substantially increased plant height, and dry mass compared to un-amended substrate. Inoculation on manure-enrich substrates did not consistently increase root AM colonization and plant growth parameters among treatments. Plants that were inoculated with R. aggregatus alone or with R. irregularis or Mesorhizobium plurifarium ORS3588 showed the greatest increase in growth variables. On un-amended substrates, inoculation with R . aggregatus in combination with M. plurifarium or R. irregularis significantly enhanced root colonization rates, without altering plant growth parameters. Yet, inoculation with R. irregularis or M. plurifarium alone did not elicit increases in these parameters, although nodulation was greatly improved by the latter treatment. In field conditions, plant growth and survival were reduced under high rate manure amendments, likely due to less AM colonization and root nodulation that was observed for these treatments in nursery before out-planting. Strongly colonized plants on the un-amended substrate and moderately amended substrate showed greater survival after out-planting. Our results support the general conclusion that microbial inoculation and manure-enriched substrates are a viable option for mining site rehabilitation using S. senegal . They also suggest that manure amendments in forest nurseries should be cautiously applied given that high rates may impede establishment of plant symbioses, thereby affecting their performance on waste rock dumps following out-planting.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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 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

Citations5
Published2022
Admission routes2
Has abstractyes

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