Landscape-scale assessment of soil properties, water quality and related nutrient fluxes under oil palm cultivation: a case study in Sumatra, Indonesia
Bibliographic record
Abstract
The rapid expansion of oil palm cultivation in Southeast Asia raises environmental concerns. Oil palm growers in Indonesia are faced with the challenge of sustaining high yields to keep pace with the growing global demand for oil and fats, while reducing the environmental impacts of oil palm cultivation. Environmental impacts associated with the deforestation at the initial phase of an oil palm plantation establishment are well documented, however the impacts of mature oil palm plantation on water quality remain poorly investigated. Oil palm is a perennial crop cultivated predominantly on weathered tropical soils, so high fertilizer input is necessary to sustain high yields, which is expected to endanger neighboring aquatic ecosystems. In Indonesia, 39 % of oil palm planted area is owned by smallholder farmers, who rely on mineral fertilizers to support oil palm production, and 52 % are large private plantations operated by private industries. In addition to mineral fertilizers, industrial plantations also apply mill byproducts as organic fertilizers. Soil characteristics and fertilizer management in oil palm plantations were expected to alter the soil fertility status and nutrient loads to waterways. Oil palm plantations generally extend over thousands of contiguous hectares, so the effect of fertilizer management on the soil response and nutrient loads to waterways requires landscape-scale studies accounting for soil variability and long-term fertilization sequences across the plantation. The first objective of the thesis was to (i) perform a literature review that provides an overview of the agricultural practices in oil palm plantations as well as hydrological processes involved in the nutrient transfers to waterways. Then I aimed to (ii) assess the effect of long term mineral and organic fertilizer sequences on the soil response, considering different soil types, (iii) characterize the dominant hydrological processes involved in the nutrient fluxes to waterways, and (iv) assess the effect of fertilizer management and soil characteristics on groundwater quality and nutrient fluxes to streams. The study area was located in Central Sumatra, Indonesia, which has a tropical humid climate and weathered soils (Ferralsols). The study area was a landscape including a 4000 ha industrial plantation and a 1500 ha smallholder plantation using rational fertilizer programs. Low-fertility Ferralsols responded significantly to continuous applications of organic fertilizers, with greater improvement on coarser-textured soils, compared to repeated applications of mineral fertilizers. I proposed that spatial fertilizer management at the landscape-scale should complement the current plot-scale fertilizer management to get higher nutrient use efficiency and improve soil fertility in an oil palm plantation. One year multi-site monitoring of stream water quality showed nutrient concentrations below Indonesian standards for water quality. In this case study, mature oil palm cultivation did not contribute to the eutrophication of aquatic ecosystems. This was ascribed to nutrient dilution in streams from the high rainfall as well as high nutrient demand by oil palm that was met with a rational fertilizer program. Assessment of nutrient fluxes from baseflow showed that loamy-sand uplands were more sensitive to nutrient losses than loamy lowlands, and organic fertilization helped to reduce nutrient losses to streams. The study also showed high dissolved organic matter content in streams, likely from natural sources. Oil palm agroecosystems in the study area are characterized by fast groundwater renewal indicating the potential for inputs to be quickly transported from soils to the streams. This may be of concern when unbalanced fertilizer management leads to over-application of nutrients or persistent agrochemicals like pesticides bind to dissolved organic matter, since they will be susceptible to contribute to nonpoint source pollution in streams.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".