Projektbeschreibung
Die Geheimnisse der Wiederherstellung und Bewahrung unserer wertvollen Böden aufdecken
Die Bodendegradation, eine vielschichtige und dringende Herausforderung, löst eine Kettenreaktion mit katastrophalen Folgen aus. Sie treibt den Klimawandel, den Verlust an biologischer Vielfalt und die Wasserverschmutzung an und verringert die weltweite landwirtschaftliche Produktivität. Zur Lösung dieses Problems wurde im Rahmen des ERC-finanzierten Projekts SHARE-CTD ein ganzheitlicher Ansatz entwickelt. Durch die Kombination von globalen Messungen, ökonometrischen Forschungsdesigns und innovativem maschinellen Lernen werden projektintern wertvolle Erkenntnisse für die Wissenschaft, den Bereich der politischen Entscheidungen und die Öffentlichkeit geliefert. Insbesondere werden die kausalen Auswirkungen öffentlicher Maßnahmen auf die Bodenbedingungen ins Licht gerückt, Kosten-Nutzen-Verhältnisse verglichen und Faktoren ermitteln, welche deren Leistungsfaktoren beeinflussen. Verbesserte politische Strategien und abgemilderte schädliche Auswirkungen der Bodendegradation werden die Folge sein.
Ziel
Land degradation is one of the major sustainability challenges of our time. It is a driver of climate change, biodiversity loss, and water pollution, and reduces global agricultural productivity. This requires effective and economically efficient policies.
Here, I outline a project that combines the global measurement and modelling of land degradation trends with econometric research designs to estimate policy effectiveness, their benefit cost ratios, and how design features and contextual factors explain policy performance. This research builds on the unique expertise I have developed over the last 5 years.
The project consists of four work packages. In the first WP, global datasets will be build, including a new database of public policies relevant to land conditions, maps of different land degradation indicators, such as soil productivity trends, vegetation and agricultural yield changes, soil erosion and pollution, and land cover changes, such as cropland expansion and forest loss.
In the second WP, econometric research designs (such as difference-in-differences, difference-in discontinuities, and synthetic control) will be used to estimate the causal effect(s) of public policies on land conditions. The comprehensiveness and global scope of the analysis means that for the first time, we will have the “full picture”, largely free of selection and publication biases, and methodologically unified.
In the third WP, all the policies’ costs and benefits will be compared to each other and we will quantify how much benefit each policy has been generating per its costs.
In the fourth WP, we will use both conventional econometric techniques and novel machine learning approaches to systematically explain when and why some public policies perform better than others.
This research will generate new insights on how to improve public policies to mitigate and reverse land degradation. I expect it will generate high interest among academics, policy makers, and the public.
Wissenschaftliches Gebiet
- social sciencespolitical sciencespolitical policiespublic policies
- social scienceseconomics and businesseconomicseconometrics
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- natural sciencesearth and related environmental sciencesenvironmental sciencespollution
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Schlüsselbegriffe
Programm/Programme
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Thema/Themen
Finanzierungsplan
HORIZON-ERC - HORIZON ERC GrantsGastgebende Einrichtung
53113 Bonn
Deutschland