Monitoring spatiotemporal changes in land use/land cover and its impacts on ecosystem services in southern Zambia
Bibliographic record
Abstract
Abstract Ecosystems play a vital role in human well-being, yet the widespread loss of ecosystem services due to human activities, including agricultural expansion and deforestation, remains a significant concern. Despite the wealth of research highlighting the importance of ecosystem conservation in Zambia, a critical gap exists in understanding the interplay between the conservation of ecosystem services and the socio-economic needs of local communities. This study presents a comparative analysis of ecosystem services in two distinct landscapes within southern Zambia: the protected area of Kafue National Park (KNP) and the agricultural landscape of Kalomo district between 2000–2020. Employing a combination of quantitative and qualitative methods, we evaluate the impacts of land/use and land cover (LULC) changes on selected ecosystem services, with a particular focus on carbon storage and the habitat quality of the trumpeter hornbill. The results of the comparison indicate that: (1) the Kalomo district has suffered from extensive land conversion, with forest changing to cropland, while KNP was well protected from encroachment, with forest area increasing over time; (2) carbon stocks and the habitat quality of trumpeter hornbills continually decreased in the Kalomo district but improved in KNP; (3) Kalomo district has suffered rapid environmental degradation due to an imbalance between economic development and environmental conservation, while strict enforcement in KNP has preserved ecosystems. The findings underscore the importance of integrated and inclusive land-use planning and natural resource governance for maintaining and enhancing ecosystem services in Zambia. To progress towards landscape management that is both sustainable and equitable, aligning with the objectives of the Global Biodiversity Framework, it is proposed that a comprehensive approach be adopted in the region. This approach should encompass a more thorough consideration of local livelihood requirements, as well as the wider political-economic and social factors at play.
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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 | 0.001 |
| 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".