Restoration, reclamation, and rehabilitation: on the need for, and positing a definition of, ecological reclamation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Within the burgeoning field of restoration ecology, defining the concept of reclamation relative to rehabilitation and ecological restoration is important to enhance comparability between studies, as well as to enable clear communication of project specific methods and goals. The Society for Ecological Restoration's international standards (SER Standards), second edition, defines reclamation as “the process of making severely degraded land fit for cultivation or a state suitable for some human use.” However, we posit that this definition, and its anthropogenic focus, does not well match how the term is often used by practitioners, and in some legal or agency documents. Further, the relationship between restoration, rehabilitation, and reclamation is unclear. We propose a more specific term and definition, ecological reclamation: “the process of assisting the recovery of severely degraded ecosystems to benefit native biota through the establishment of habitats, populations, communities, or ecosystems that are similar, but not necessarily identical to surrounding and naturally occurring ecosystems.” This definition emphasizes that the objective of a reclamation project may not be direct human use, and begins to better distinguish between ecological reclamation, rehabilitation, and ecological restoration; however, more work and discussion on these relationships is required. Distinguishing these terms will result in better comparisons between studies, improving current and future literature reviews. Further, this term will also enable practitioners to better define project goals, and enhance communication to stakeholders, practitioners, and researchers.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it