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Record W7110663237

Towards benefit oriented rehabilitation to make degraded lakes more resilient to extreme climatic events

2024· article· en· W7110663237 on OpenAlexfundno aff

Bibliographic record

VenueTesis Doctorals en Xarxa (Consorci de Serveis Universitaris de Catalunya) · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
FundersCanadian Institute for Advanced Research
KeywordsBiosphereClimate changeEcosystemExtreme weatherStressorPrecipitationFreshwater ecosystemClimate extremes
DOInot available

Abstract

fetched live from OpenAlex

ENG- The delineation of the current geological epoch as the “Anthropocene,” derived from the prefix “anthro-” meaning “human,” aptly summarizes the sheer magnitude in which humans have affected the biosphere. For many ecosystems, these pressures have caused long-term degradations to their health and functions. Freshwater systems such as lakes are particularly susceptible as these lentic water bodies act as sentinels of change in the region by accumulating information from the whole catchment. With pressures from anthropogenic actions and climatic scenarios projected to continue, if not intensify, in the coming decades, there is concern regarding the impairment of lake ecosystems. Of the climatic projections, one of the more recent concerns is the intensifying frequency and severity of extreme climatic events (“ECEs”), or a climatic event such as a heatwave or precipitation that is in the tail ends (e.g. 99th percentile) of the distribution curve for that region or time of year. The potential for these events to instigate disproportionate disruptions within freshwater systems worldwide can be significant. Paired with other, non-climatic pressures derived from human actions, such as wide-spread land use change and pandemic outbreaks, there can be multiple pressures affecting the biosphere sequentially or in tandem. Depending upon the nature of the pressure, these can be categorized as “pulse” stressors which are generally short-lived events, such as heatwaves or extreme precipitation, and “press” stressors which have a long-lasting or chronic duration, such as ecosystem alterations (e.g. urbanization, dam construction, etc.) or climate change. Degradation of systems presents challenges not only for the biosphere itself but for human communities as our livelihoods are tied to and built upon the functions and values that the biosphere provides. If the trend of increasing pressures is permitted to continue without intervention, human health, well-being and economies could be impacted just as much as the ecosystem inhabitants. With lakes being the abundantly utilized and vulnerable systems that they are, approaching these multifaceted problems will require looking beyond just the science sector to address present and future challenges. In this thesis, the research traces the cause-effect relationship from 1) the occurrence of extreme event(s) to 2) their implications on ecosystem functions to 3) the effect on ecosystem service provisioning and 4) the implications that intersectoral collaborations could have on ecosystem remediation. This is conducted through an interdisciplinary approach with each chapter using different methodologies to tackle various aspects of this cause-effect chain. Maintaining status quo approaches to utilizing, studying and managing lakes will not be sufficient for improving or preserving ecosystem health and functions in the future. Navigating the razor’s edge of maintained lake functions and services in an extreme world requires informed, proactive, inclusive and holistic methods. By recognizing the urgency of the situation and adapting the approaches used for this new reality, the biosphere and dependent anthropogenic communities may be able to weather the extremes

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.255
Teacher spread0.241 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

Explore more

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