Estimating the future economic effects of biodiversity loss and strategies to mitigate it: evidence from soil quality and pollination, and half-earth protection scenarios
Bibliographic record
Abstract
The global natural system faces significant pressure from societal and economic demands, threatening air, water, soil, and biodiversity. The financial sector increasingly recognises that its stability depends on climate, nature, and biodiversity, and their interconnected relationship. Governments seek to measure and reduce impacts on essential resources and integrate nature into financial decisions. Knowledge gap:• The macroeconomic effects of biodiversity loss at the sector and country level, considering its direct effects and indirect effects through trade and reallocation of production between sectors and countries.• Monetised costs and benefits of the measures that can abate the loss of biodiversity. In the first year of the project, BiROFin• developed global scenarios regarding the effects of biodiversity-loss-induced changes in pollination, and soil quality on crop productivity by 2050, and how those effects change under the presence of climate-change-induced extreme climate events;• estimated the macroeconomic impacts of these changes using the MAGNET general equilibrium model, which incorporates international trade, supply chain linkages, consumer market developments, and input substitution, enabling the project to estimate the varying impact of biodiversity loss on various sectors in different countries;• estimated the monetary costs and benefits of six nature-based measures, which can abate biodiversity, soil quality, and pollination loss, and at the same time increase crop productivity, in Brazil, France, Germany, Italy, the Netherlands, Spain, the United Kingdom, and the United States;• identified macroeconomic outcomes of an existing conservation policy that protects half of the Earth from biodiversity loss and thereby soil quality and pollination loss.From exposure to ecosystem services loss to estimating the effect of risks and opportunities to abate them 5 The document includes the following results from the first year of the BiROFin for specialists and practitioners in the financial sector, government, and other private sector organisations focusing on environment and nature topics:• Risks of human-induced biodiversity loss on crop productivity by 2050 due to declining soil quality and loss of insect pollinators under climate-change-induced extreme climate events.• Global macroeconomic repercussions of soil quality and pollination loss due to biodiversity loss, affecting economies and domestic and international markets through trade and supply chains by 2050.• Cost and benefit implications for implementing nature-based measures to abate soil quality and pollination losses caused by biodiversity decline by 2050 in Brazil, France, Germany, Italy, the Netherlands, Spain, the United Kingdom, and the United States.• Macroeconomic risks of implementing a conservation policy that protects half of the Earth from socio-economic activity to abate biodiversity loss, thereby soil quality and pollination loss by 2050.• For a shorter summary of the results presented in the document, please refer to our Executive Summary intended for policymakers. To understand the methodology and assumptions behind our scenarios, macroeconomic estimations and cost-benefit analyses, please visit the following appendices on our BiROFin website
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".