A Global Assessment of the State of Plant Health
Bibliographic record
Abstract
The Global Plant Health Assessment (GPHA) is a collective, volunteer-based effort to assemble expert opinions on plant health and disease impacts on ecosystem services based on published scientific evidence. The GPHA considers a range of forest, agricultural, and urban systems worldwide. These are referred to as (Ecoregion × Plant System), i.e., selected case examples involving keystone plants in given parts of the world. The GPHA focuses on infectious plant diseases and plant pathogens, but encompasses the abiotic (e.g., temperature, drought, and floods) and other biotic (e.g., animal pests and humans) factors associated with plant health. Among the 33 (Ecoregion × Plant System) considered, 18 are assessed as in fair or poor health, and 20 as in declining health. Much of the observed state of plant health and its trends are driven by a combination of forces, including climate change, species invasions, and human management. Healthy plants ensure (i) provisioning (food, fiber, and material), (ii) regulation (climate, atmosphere, water, and soils), and (iii) cultural (recreation, inspiration, and spiritual) ecosystem services. All these roles that plants play are threatened by plant diseases. Nearly none of these three ecosystem services are assessed as improving. Results indicate that the poor state of plant health in sub-Saharan Africa gravely contributes to food insecurity and environmental degradation. Results further call for the need to improve crop health to ensure food security in the most populated parts of the world, such as in South Asia, where the poorest of the poor, the landless farmers, are at the greatest risk. The overview of results generated from this work identifies directions for future research to be championed by a new generation of scientists and revived public extension services. Breakthroughs from science are needed to (i) gather more data on plant health and its consequences, (ii) identify collective actions to manage plant systems, (iii) exploit the phytobiome diversity in breeding programs, (iv) breed for plant genotypes with resilience to biotic and abiotic stresses, and (v) design and implement plant systems involving the diversity required to ensure their adaptation to current and growing challenges, including climate change and pathogen invasions.
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 | 0.000 | 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 | 0.000 |
| 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 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".