From Alnus to Pinus: temperate peatland ecosystem transformation triggered by human-driven landscape change
Bibliographic record
Abstract
Abstract. Peatlands are invaluable archives of palaeoenvironmental and climate dynamics, play a central role in the global carbon cycle and hydrological processes, preserve biological diversity, and act as climatic microrefugia. Over the millennia, these ecosystems have been heavily modified by human land use, including drainage, overgrazing or peat extraction, leading to their large-scale degradation in many regions. Knowledge of the long-term dynamics of peatlands is crucial for determining their conservation and restoration needs as well as for predicting their evolution, including response to climate change, community changes, carbon sequestration potential. Here we adopted an interdisciplinary approach to investigate the relationships between climate, vegetation, tree growth, hydrology, and human activities in a peatland ecosystem in one of the poorly explored regions of Central Europe, the Solska Forest in southeastern Poland. We used different types of proxy data from natural and human archives: long-term meteorological data (1792–2020), tree-ring data (1729–2022) from living peatland pines, palaeoecological data from the peat sediment (pollen, plant macrofossils, testate amoebae and charcoal data) and archival written and cartographic sources to reconstruct local ecosystem and landscape dynamics and assess possible climatic and anthropogenic impacts. Our results document a complete transition of a peatland ecosystem from black alder bog forest to Scots pine bog forest, most likely triggered by several factors, mainly land use change and associated fire activity, among others, in particular the landscape-scale expansion of the pine forests and the resulting environmental acidification that triggered Sphagnum encroachment. Our multi-proxy environmental reconstruction of the last >2,300 years also revealed considerable hydrological instability of the peatland and a complex interplay of different landscape shaping influences. In addition, certain advantages, challenges and limitations of multi-proxy studies of landscape history and ecosystem dynamics were highlighted, such as the different temporal resolution and coverage of the archives studied (including the problem of periods with no or very little data) or inconsistency of the quantitative and qualitative data. With this study, we have demonstrated the multifaceted interactions between different biotic and abiotic factors affecting both landscape and peatland ecosystems, confirmed the importance of long-term environmental records for conservation ecology and land management, and emphasized the continuing need for further research on peatland ecology, including past and current changes. Further, linking nature and human archives allowed us to gain a deeper understanding of a complex environmental system, with added value from combining different approaches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".