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Record W3184008437

Ecological legacies of long-term plant management along the Central Coast of British Columbia

2021· dissertation· en· W3184008437 on OpenAlexaboutno aff
Alana Closs

Bibliographic record

VenueUWSpace (University of Waterloo) · 2021
Typedissertation
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)GeographyEcologyEnvironmental resource managementEnvironmental scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

Quantifying long-term human impacts to landscapes allows us to understand the ways in which ecosystems respond to constant human pressure and the effects this pressure has on permanently influencing ecological processes and functions. Permanent ecosystem changes due to human activity are described as ecological legacies. As the global population steadily increases and resource demands heighten, understanding how humans drive ecosystems can contribute to the effective development of strategies that protect sensitive species and manage resource landscapes responsibly. Many modern management techniques have devastating ecological consequences, resulting in species endangerment and extinction, habitat fragmentation, and the loss of ancient cultural landscapes similar to that of the Great Bear Rainforest of British Columbia (BC). Here, the Coastal Indigenous peoples of BC have been modifying the temperate rainforests to increase food sources for hundreds, in some cases, thousands of years, enhancing the biotic potential of the Pacific Northwest ecosystem through complex, sustainable methods of management. Since before colonization, Indigenous landscape management along the Pacific Northwest Coast has supported and enhanced ecological processes and functions, proving to be significantly less destructive than management techniques practiced by commercial industries today. Though discrete in nature, ecological and Indigenous methodologies can be used to uncover the legacies of these sustainable management systems, detectable in the present-day composition of plant communities, fire occurrence patterns, and local habitat structure. As modern resource management encroaches on coastal rainforests, these ecological legacies become increasingly threatened. Localized field surveys that identify present-day distributions and spatial boundaries of edible and economic plants, as well as highlight habitat and phenotypic characteristics can help protect and uphold cultural landscapes and valued species. \nThe objective of this study was to collect ecological data on the distribution, community composition, ecological niche, abundance, and species richness of culturally valued plants on a set of historic islands in the Great Bear Rainforest. The overarching goal of this study is to assess if the legacy effects of long-term Indigenous management still persist in these ecological variables today and collect data on the habitat, community composition, and phenotypic traits associated with large populations of edible species. Our goal is also to determine which sections of coastline surveyed in our study hold the greatest overall cultural significance and identify populations of edible plants that may have been subject to high human management. All field research was carried out in collaboration with Indigenous community and council members. One if the goals for this collaboration was to bridge the gap between western and Indigenous knowledge and identify components that led to meaningful relationships, stronger research, and the ability to exhibit “two-eyed seeing”. \nFrom the results of our study, we can conclude that the landscape surrounding all sampled sites holds high cultural and economic value, with higher richness and abundance of culturally valued species around places with known long-term human presence. Additionally, almost all of the plants identified in this study have some known management technique associated with them, with the highest managed plants subject to 11 unique and complex strategies. We believe our results are legacies of these management techniques traditionally utilized for thousands of years to increase productivity and richness of edible and economic plants. Data of this type will complement existing Indigenous Knowledge on the current location and spatial distribution of culturally important plants to support local Nations as they implement ecosystem-based-management strategies within their territories. In addition to the ecological data collected, pathways to work collaboratively with a diverse team of researchers who embody different ways of knowing were also uncovered. These included building trust, establishing respect, honoring diversity, communicating openly, and possessing cultural awareness. Our hope is that other research teams will reflect upon our experiences and use them as a path to guide their own knowledge collaborations.

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)0.001
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 score0.020
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.005
GPT teacher head0.164
Teacher spread0.159 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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