Native forest conversion alters soil macroinvertebrate diversity and soil quality in tropical mountain landscapes of northern Ecuador
Bibliographic record
Abstract
Land use changes cause soil degradation and loss of biodiversity, thereby affecting ecological processes and soil-associated ecosystem services. However, land use change impacts on soil health have received little attention in the highland landscapes of the tropics. In this research, using the soil health framework, we assessed the impact of native forest conversion to anthropic systems (planted forests, pastures, and monocultures) on two ecosystem services: biodiversity conservation and soil fertility in the highlands of northern Ecuador. The biological dimension of our assessment focused on the diversity, abundance, and biomass of soil macroinvertebrate communities as proxies to soil functions, whereas soil chemical parameters were used to describe the soil fertility. The soil invertebrate communities and soil chemical parameters were studied in topsoil samples using 25 × 25 × 10 cm monoliths, obtained from 10 sampling sites randomly selected in each land use category. We hypothesized that native forests would present more diverse and even soil macroinvertebrate communities, and together with their soil chemical properties would indicate better soil quality than anthropic environments. Our results showed that the structure and composition of the edaphic macroinvertebrate communities significantly differed among the studied land use categories. As predicted, native forests presented greater values for richness, evenness and diversity of soil biota than did the other categories, demonstrating a significant loss of taxonomic biodiversity at order and genus levels. We also found a significant reduction of trophic diversity in native forests converted to anthropic environments. More trophic groups with greater abundances were found in native forests, where predators and detritivores stood out as dominant groups, indicating the good quality of the soil. The results from the soil chemical parameters also confirmed the distinction in soil health between native forests and anthropic environments. Our results highlight the risk associated with current trends of native forest loss and conversion to anthropic systems in high mountain ecosystems in the tropics, illustrating how these alterations could cause biodiversity loss and degradation of the chemical attributes of soil health. The findings of this research could contribute to the conservation and sustainable management of mountain agricultural landscapes in the study region.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".