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Record W4410825948 · doi:10.3897/aca.8.e147461

How ‘long term’ is long term enough? Bridging neo- and paleo-ecological timescales

2025· article· en· W4410825948 on OpenAlexaffabout
Richard Bindler, Carsten Meyer‐Jacob

Bibliographic record

VenueARPHA Conference Abstracts · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsTerm (time)Bridging (networking)EcologyEnvironmental sciencePhysicsBiologyComputer scienceAstronomy

Abstract

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A challenge in assessing the impacts of ongoing human-driven environmental and climate changes is the limited long-term data from monitoring programs and field studies, which rarely span more than a few decades (Nevalainen et al. 2020, Dodds et al. 2012). In line with common usage of ‘long term’ in ecology, Dodds et al. (2012) fined a “long-term ecological data set as data that are measured systematically through time using standardized methods that allow for the elucidation of ecological system responses (e.g., linear, lag, threshold, regime shift) to drivers, disturbances (e.g., presses or pulses), recovery from disturbances, and relevant interactions for a given hypothesis.” However, while experimental, field, and monitoring data are essential to develop insights into mechanisms and possibly reveal emerging trends, these time series provide limited insights into long-term – i.e., decadal–centennial–millennial – dynamics that enable defining reference conditions and possible underlying trajectories, which are required for identifying ongoing super-imposed changes. Since national monitoring programs in Sweden began in the early-1980’s, lake-water organic carbon (LW-TOC; Fig. 1) has been increasing in many lakes (de Wit et al. 2016), which affects light penetration and freshwater ecology (Horppila et al. 2024). Increasing LW-TOC has been attributed to decreasing S deposition, increasing temperature and wetness (de Wit et al. 2016, Monteith et al. 2007), and increasing forest cover (Finstad et al. 2016). Since precipitation monitoring began in 1978–1980, S deposition has decreased and precipitation pH increased by ~0.75–1 pH units. Temperatures have been increasing over the timeframe available from the longest continuous time series: in Lund, southern Sweden, June temperatures have increased 2°C since 1859, and in Mora, central Sweden, show a similar ~2°C increase since 1941. Finally, the Swedish National Forest Inventory indicates forests in southwestern Sweden have increased 2–4 fold and in central Sweden by ~60% since 1923. Because these long-term data for S deposition, climate, and forest growth have been changing at the same time as LW-TOC increases (Fig. 1), disentangling the relative importance of these factors. Furthermore, none of these time series provide information on reference conditions or the full timeframe of current trajectories. Using monitoring data from Sweden and specifically LW-TOC, we demonstrate the importance of integrating contemporary instrumental data with sedimentary records; that is, bridging instrumental and paleolimnological timescales (Fig. 2). This research has entailed developing calibrations between instrumental data and sediment proxies (VNIRS-inferred LW-TOC; (Meyer-Jacob et al. 2015, Meyer-Jacob et al. 2017, Rosén 2005), demonstrating the proxy signal is preserved in sediments, and assessing the trends from monitoring in relation to longer-term patterns (Meyer-Jacob et al. 2015, Meyer-Jacob et al. 2019, Meyer-Jacob et al. 2017, Myrstener et al. 2021). Our research has shown the importance of acidification/recovery, climate changes, and/or land-use changes has varied within Sweden and in other northern areas. Focusing on data from Sweden (Fig. 3), LW-TOC increased with post-glacial landscape development and thereafter remained high and stable through most of the Holocene (Meyer-Jacob et al. 2015, Myrstener et al. 2021). In northern Finland LW-TOC was also associated climate (). However, in Sweden, centuries-long traditional use led to declining LW-TOC, which began c. 700 CE in southwestern Sweden and c. 1400 in central Sweden – declining by ~50% by the 1800’s. The association with human impacts is evidenced by declining arboreal pollen, increasing pollen of plants favored by human disturbance, and occurrence of pollen from cultivated plants. In southwestern Sweden, where 20 th -century impacts of acidification were greatest, LW-TOC decreased even further. The current levels of LW-TOC in these lakes are still far below the ‘natural’ levels preceding human impacts. In Canada, where historical land uses did not have the same impact as in Sweden, it has been possible to tease apart the influence of acidification and climate on recent increases in LW-TOC (Meyer-Jacob et al. 2019). During the 20 th century acidification in the highest S deposition areas has been the most important driver of LW-TOC decreases – similar to the 20 th -century decline in southwestern Sweden. Thus, increasing LW-TOC is mainly a response to acidification recovery. In contrast, outside of high S deposition areas LW-TOC decreased less during the mid-20 th century due to S deposition, the increasing LW-TOC has in some cases exceeded pre-acidification values, indicating a climate contribution to the trend. Taken together, these centennial–millennial long records of past environmental changes have been able to identify important long-term patterns and levels in LW-TOC, and to disentangle the importance of key processes identified through field and experimental studies. The paleolimnological studies indicate there are regionally different drivers underlying the observed increases in LW-TOC in northern lakes.

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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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.266
Teacher spread0.237 · 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.

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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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