Analyzing the global impacts of food and feed production, trade and consumption on terrestrial and marine ecosystems
Bibliographic record
Abstract
Global food supply chains play a crucial role in the functioning of both social and ecological systems, providing essential resources like food and feed products. However, the supply of food to humanity is accompanied by the alteration of planetary boundaries such as biosphere integrity, biogeochemical cycles and climate stability, potentially leading to irreversible tipping points and threatening the ability of future generations to meet their needs. Furthermore, the globalization of trade has increased the spatial disconnect between producers and consumers, meaning that local impacts of agricultural production are driven by consumption in geographically distant places. Feeding the world sustainably in a context of population growth and climate change requires then transformative changes of current production and consumption patterns, as advocated by numerous international initiatives, such as the UN Sustainable Development Goals, the Convention on Biological Diversity and the EU European Green Deal. This thesis analyzes and quantifies how global terrestrial and marine ecosystems are affected by production, trade and consumption of agricultural products in a telecoupled world. Building on multiple approaches from different disciplines, it addresses specific cases of human-nature metabolism at different spatial scales by exploring: A. The role of trade and consumption of agricultural products in driving global biodiversity loss, B. How spatial patterns of agricultural expansion vs. intensification drive environmental impacts, C. What environmental indicators best describes different aspects of biodiversity loss, and D. How production intensities, i.e. impact per unit product, vary between food commodities. The work on these themes has resulted in three research papers. The thesis is structured around six interrelated chapters delineating the context inspiring my research, discussing the methodological orientation of my work, summarizing major findings and how they contribute knowledge to the general themes at the heart of my dissertation, and reflecting on implications for policy and practice. In the first paper, I investigated how the transfer of 151 crops through global trade networks spreads the responsibility of oxygen depletion impacts on local marine ecosystems in the country where production takes place to geographically distant consumers. I used a spatially explicit Life Cycle Assessment (LCA)-based model and global data on synthetic fertilizers, manure and nitrogen fixation to estimate production intensities (i.e. oxygen depletion impact per kcal of produced crop) and extent of oxygen depletion in 66 Large Marine Ecosystems (LMEs). Linking this information with crop trade data allowed me to disaggregate the estimated impacts across traded and non-traded agricultural products. Results show large differences between impacts driven by production for domestic consumption and production for export, depending on the type of crop, country and affected LMEs. I found that production of cereals and oil crops accounts for the bulk of oxygen depletion impacts, with export-driven production accounting for 15.9% of total global impact. However, for some large exporting countries like Canada, Argentina or Malaysia, this share often makes up to three-quarters of their production impacts, while for some importing countries located in eutrophication sensitive LMEs like Japan, South Korea, Finland or Italy, importing of crops can reduce pressure on already highly affected coastal ecosystems. The second paper adds breadth to the current debate on the environmental costs of animal-based protein supply and is relevant for an improved understanding of the contribution of livestock production to the ongoing biodiversity and climate crises. I made use of three indicators that have not yet been systematically assessed for livestock products: deforestation, biodiversity loss and marine eutrophication. I used global biophysical data on the production, trade and consumption of primary crops and grazed biomass utilized as livestock feed, as well as livestock production data, to determine the environmental impact intensities of livestock feed per ton of livestock protein produced. Results locate the largest deforestation and biodiversity impact intensities in the tropics in Central and South America, Southeast Asia and Central Western Africa, while the highest marine eutrophication intensities can be found in countries in Northern Europe and in South and in East Asia. The third paper highlights the importance of using spatially explicit biodiversity indicators to better address the multidimensionality of the biodiversity concept. I report on the development of two complementary and contrasting spatial scale indicators to estimate the impending terrestrial vertebrate species loss (across four taxa: reptiles, amphibians, birds and mammals) at the landscape (grid) and global level.
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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 | 0.000 |
| 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".