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Record W2952105322 · doi:10.7939/r3rj4999t

Influence of management and disturbance history on germinable seed bank composition and legume recruitment in Alberta’s Central Parkland and Dry Mixedgrass prairie

2018· article· en· W2952105322 on OpenAlexaboutno aff
Lysandra A. Pyle

Bibliographic record

VenueUniversity of Alberta Library · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsComposition (language)Disturbance (geology)LegumeCentral HighlandsAgronomyAgroforestryEcologyForestryGeographyBiology

Abstract

fetched live from OpenAlex

Seed banks (SB) are a cryptic component of grassland plant community (PC) diversity and are overlooked for their contribution of a significant ecological service in the form of plant propagules that replenish the aboveground plant community with new individuals and thereby aid in recovery following disturbance. SB composition often differs from the aboveground plant community, as it is a legacy of historical disturbance events, ongoing succession, and seasonal shifts in PC composition. Alberta’s Central Parkland (CP) fescue grasslands have been subject to significant anthropogenic disturbance through cultivation and changes in fire and grazing regime, with many grasslands now dominated by introduced forages, either intentionally seeded or those encroached under contemporary patterns of grazing. Dry Mixedgrass (DMG) prairie has experienced similar disturbances and is recognized as a region wherein industrial activity (e.g. oil and gas infrastructure) can cause a decline in native grassland and introduced vegetation invasion. In this study, germinable SBs in the topsoil of grasslands were characterized, including managed Parkland-Boreal pastures of central Alberta and native DMG prairie disturbed by natural gas pipelines. SBs were examined for their similarity to above-ground PC, and their composition linked to ongoing disturbances and/or specific management attributes. This research was conducted with a focus on potential legume recovery in the CP and examined legumes as invasive species along industrial disturbance. Legume emergence was tested further in an additional study looking at the recruitment and survival of native, agronomic, and escaped (potential weedy) agronomic legumes into native grasslands. In the CP, 102 pastures were sampled, and a previous history of cultivation was found to have a significant influence on both PCs and SBs, including a reduction in native plants, particularly perennial grasses. Unexpectedly, grazing systems (continuous vs. rotational) led to few differences in PCs, SBs, and soils, likely due to similar stocking rates. PCs and SBs each responded to unique historical management factors, with SB composition more responsive to livestock husbandry (i.e., manure spreading, bale grazing, etc.). Similarity in species richness between the SB and PC was related to a few key aspects of management: 1) low RH scores were associated with high similarity and greater SB densities of forbs, 2) previously cultivated and well-established pastures had a higher similarity comprised of mostly introduced forage grasses. Legumes like clovers formed persistent SBs and were resistant to management actions like recent herbicide use. In DMG prairie, both aboveground PCs and SBs exhibited legacy effects of natural gas pipeline installation, which were further influenced by pipeline diameter and age. Distinct legacy effects were also evident along spatial gradients with increasing distance (to 55 m) from the pipelines. SBs directly on pipeline trenches were associated with higher densities of introduced Melilotus spp. and two native grasses typically used to revegetate prairie disturbances; however, these were not representative of native grassland. Wide diameter pipelines were more likely to have greater seed densities of introduced grasses like Agropyron cristatum and Poa pratensis, which can be invasive in native grasslands. Legacy effects of pipeline disturbance were most pronounced for the cryptic biological soil crust (BSC) community, where the recovery of macro-lichens was nearly absent. BSCs were also linked to shifts in SB composition, where BSC elimination resulted in greater bare soil and higher densities of introduced species in the SB. Within both native and introduced grasslands of the CP and DMG, legume (six species) recruitment and survival from an artificial SB were monitored over three growing seasons. At all locations litter (ambient or reduced) and defoliation (defoliated or non-defoliated) were manipulated to emulate vegetation structural (i.e., competitive) and microclimate changes that could occur under contrasting management practices (grazing intensities or range health). Litter and defoliation treatments significantly influenced PC structure, with litter removal increasing light availability, and defoliation increasing soil temperature. Different legume species also exhibited unique establishment responses to treatments, likely reflecting contrasting seed ecology. Aspects of germination and recruitment were frequently linked to PC structure, composition, and competition, which were often influenced by the treatments imposed. Overall, this research greatly expanded our understanding of the influence of disturbance regimes on grassland range health, as well as aboveground vegetation, seed bank and cryptic BSC composition, within both introduced and native grasslands.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.572

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.180
Teacher spread0.168 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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