EXPLAINING THE CLIMATE-DEPENDENT DISTRIBUTION OF CROPS IN SPACE –THE EXAMPLE OF CORN AND CORN-COB-MIX IN BADEN-WÜRTTEMBERG

This article analyses the current climate-dependent spatial distribution of corn and corn-cob-mix in Baden-Württemberg using 2007 data at the county and community level. We use OLS and spatial econometric models to estimate the effects of different climate and non-climate variables on the share of grain maize in UAA. Whereas the temperature effect is missed by means of OLS regression, the adequate spatial error model at the county level yields a highly significant positive effect of mean annual temperature. Additionally, it displays a temperature cut-off point after which corn share is less likely to rise due to temperature increase. These effects are supported by a non-spatial multinomial logit model at the community level. The latter further indicates that soil quality also plays a role. The positive effect of annual precipitation remains ambiguous.Spatial distribution of corn, spatial econometrics, multinomial logit, climate change, Agribusiness, Crop Production/Industries,

EU commodity market development: Medium-term agricultural outlook

The workshop on the 'EU commodity market development: Medium-term agricultural outlook' is an integral part of the intensive validation procedure of the results of the European Commission’s report on 'Prospects for EU agricultural markets and income'. It provides a forum for presentations on preliminary 10-year-ahead projections in EU agricultural commodity markets, and discussing in depth the EU prospects in a global context. This year the workshop was held on October 25-26 in Brussels. The workshop was jointly organised by the Joint Research Centre (JRC) and the Directorate-General for Agriculture and Rural Development (DG AGRI). Participants included policy makers, modelling and market experts from various countries, as well as stakeholders of the agri-food industry. This document summarises the presentations and discussions on the macroeconomic and energy assumptions associated with this outlook, and on each of the EU agricultural markets addressed (arable crops, biofuels, sugar, fruits/vegetables/olive oil/wine, milk and dairy, meat).JRC.D.4-Economics of Agricultur

EU commodity market development: Medium-term agricultural outlook. Proceedings of the October 2017 workshop.

The workshop on the 'EU commodity market development: Medium-term agricultural outlook' is an integral part of the intensive validation procedure of the results of the European Commission’s report on 'Prospects for EU agricultural markets and income'. It provides a forum for presentations on preliminary 10-year-ahead projections in EU agricultural commodity markets, and discussing in depth the EU prospects in a global context. This year the workshop was held on October 19-20 in Brussels. The workshop was jointly organised by the Joint Research Centre (JRC) and the Directorate-General for Agriculture and Rural Development (DG AGRI). Participants included policy makers, modelling and market experts from various countries, as well as stakeholders of the agri-food industry. This document summarises the presentations and discussions on the macroeconomic and energy assumptions associated with this outlook, and on each of the EU agricultural markets addressed (arable crops, biofuels, sugar, wine, milk and dairy, meat).JRC.D.4-Economics of Agricultur

Microeconometric analysis of the impacts of climate change on German agriculture : applications and extensions of the Ricardian approach

The so-called Ricardian approach is an econometrics-based climate change impact assessment frequently used by agricultural and environmental economists. The intuition behind this approach is that, in the long run, the optimal behavior of farms is climate-dependent. In essence, the approach explores the role of climate in determining farm profitability and potential adaptation, by regressing economic or behavioral measures of agricultural outcomes against climatic and various other land and site attributes. The overall output of the approach enables (i) the identification of profitability differentials due to climate differentials, (ii) marginal implicit pricing of climate, and (iii) a probabilistic exploration of long-run adaptation strategies. This cumulative dissertation took up the challenge of improving specific conceptual and methodological aspects of the Ricardian approach in order to render it a more realistic impact assessment tool. In particular, we aimed at a more efficient treatment of the variables that proxy climate, and at the imposition of structure on equations that can reflect adaptation. Three empirical studies were pursued for over 270,000 German farms at three spatial scales: districts (N = 439), community associations (n = 3,515), and communities (n = 9,684). For this reason, secondary data of various formats (e.g., farm census records, measurements by weather stations, digital images) on a host of characteristics (e.g., farm-specific, climatic, topographical, geographical) were extensively processed (e.g., integrated, geocoded, spatially interpolated, zonally rearranged) and spatially matched. We took a multi-model and multi-stage approach from an instrumental-variables (IV) perspective, which we coupled with advances from the subfield of spatial econometrics. From an empirical viewpoint, our results showed that historical climate change has generally been beneficial to the sector as a whole. The impact of historical mean annual temperature (precipitation) on average land rental prices is positive (concave). Indicatively, permanent-crop and vegetable farms value temperature more than the rest farm types, whereas forage farms, and to a certain extent mixed farms, stand out for their resilience to precipitation. Climate change in the near decades is likely to be beneficial, but the magnitude of benefits depends on the farm type one looks at.Die Ricardische Analyse, basierend auf dem ökonometrischen Ansatz, ist eine häufig verwendete Methode von Agrar- und Umweltökonomen, um die ökonomischen Auswirkungen von Klimaveränderungen abzuschätzen. Die intuitive Idee dahinter ist, dass langfristig gesehen, das optimale Verhalten von landwirtschaftlichen Betrieben klimaabhängig ist. Man kann die Rolle des Klimas in Bezug auf die Profitabilität von Betrieben und deren Anpassungspotential erfassen, indem eine Regressionsanalyse durchführt wird, wobei ökonomische und verhaltenstechnische Variablen landwirtschaftlicher Einkommen, klimatischen und anderen lokationsspezifischen Variablen gegenüberstellt werden. Zusammenfassend kann man festhalten, dass der Ansatz Folgendes ermöglicht: (i) eine Identifikation klimainduzierter Veränderungen in der Profitabilität, (ii) marginal implizite Preisfestsetzung des Klimas und (iii) eine wahrscheinlichkeitsbasierte Untersuchung von langfristigen Anpassungsstrategien. Diese kumulative Dissertation hat sich der Herausforderung gestellt, spezifische konzeptionelle und methodische Aspekte der Ricardischen Analyse zu verbessern, mit dem Ziel einer realitätsgetreueren Analyse. Im Speziellen war die Zielsetzung, eine effizientere Handhabung der Proxi-Variablen für Klima zu erreichen und der Schaffung einer Struktur für Gleichungen, die die Anpassungsmaßnahmen beschreiben. Es wurden drei empirische Studien durchgeführt für über 270,000 deutsche landwirtschaftliche Betriebe auf drei Verwaltungsebenen: Kreisebene (N = 439), Gemeindeverbändeebene (n = 3,515) und Gemeindeebene (n = 9,684). Aus diesem Grund wurden verschiedene Sekundärdaten (z.B., landwirtschaftliche Zensusdaten, Wetterstationsaufzeichnungen, Rasteraufnahmen in Bezug auf Bodenqualität) räumlich kompatibel gemacht (z.B., integriert, geocodiert, räumlich interpoliert, zonenmäßig umgeordnet) und räumlich zusammengeführt. Wir verwendeten einen Multi-Model- und Multi-Stufen-Ansatz basierend auf Instrumentalvariablen (IV), die mit weiterentwickelten analytischen Ansätzen aus dem Feld der räumlichen Ökonometrie zusammenführt wurden. Von einem empirischen Gesichtspunkt aus zeigen unsere Ergebnisse, dass der Klimawandel historisch gesehen vorteilhaft für den gesamten Sektor war. Der Effekt auf die Landpachtpreise durch Einflüsse der historischen mittleren Jahresdurchschnittstemperatur (Jahresmittel der Niederschläge) ist positiv (konkav). Es gibt Anzeichen, dass Dauerkulturbetriebe und Gemüsebaubetriebe mehr von einer Erhöhung der Temperatur begünstigt sein könnten als andere Betriebstypen, wohingegen Grünlandbetriebe und bis zu einem gewissen Maße Gemischtbetriebe hervorstechen durch ihre Anpassungsfähigkeit an erhöhte Niederschlagsaufkommen. In naher Zukunft werden die Auswirkungen des Klimawandels auf die landwirtschaftlichen Betriebe wahrscheinlich positiv bleiben, jedoch die Richtung des Effekts ist abhängig vom Betriebstyp

Documentation of the European Commission’s EU module of the Aglink-Cosimo model: 2021 version

This report documents the EU module of the European Commission’s version of the Aglink-Cosimo model. Aglink-Cosimo is a recursive-dynamic, partial equilibrium, multi-commodity market model of world agriculture developed by the Organisation for Economic Cooperation and Development (OECD) and the Food and Agriculture Organization of the United Nations (FAO) Secretariats in collaboration with some OECD member countries. The model is used to simulate the development of annual supply, demand and prices for the main agricultural commodities produced, consumed, and traded worldwide. Aglink-Cosimo covers 35 individual countries, 12 regional aggregates, and 29 market-clearing prices at the world level. At the EU level, the model is used to produce the report “EU agricultural outlook for markets, income and environment” (henceforth, EU Outlook).JRC.D.4 - Economics of Agricultur

Extreme Weather and Global Agricultural Markets: Experimental Analysis of the Impacts of Heat Waves on Wheat Markets

Extreme-weather events frequently drive production fluctuations, price volatility, and hence uncertainty on agricultural commodity markets. Simulation models of global agriculture typically assume normal weather in deterministic scenarios, contain no explicit parameterization of weather elements on the supply side, and confound multitudinous sources of yield fluctuation in exogenous yield shocks. As a part of a wider project on extreme events modelling, in this paper we present the experimental design of a first attempt to explicitly parameterize extreme weather into a partial equilibrium model of global agriculture (Aglink-Cosimo). We outline the main model additions and present preliminary estimates of wheat yield-to-heat elasticities for key regions. We also present the potential wheat market impacts from a counterfactual heat-wave scenario in Australia. Finally, we outline ongoing and future work on multi-scenario analysis in the context of extreme weather and global markets

Large-scale fine-grained semantic indexing of biomedical literature based on weakly-supervised deep learning

Semantic indexing of biomedical literature is usually done at the level of MeSH descriptors, representing topics of interest for the biomedical community. Several related but distinct biomedical concepts are often grouped together in a single coarse-grained descriptor and are treated as a single topic for semantic indexing. This study proposes a new method for the automated refinement of subject annotations at the level of concepts, investigating deep learning approaches. Lacking labelled data for this task, our method relies on weak supervision based on concept occurrence in the abstract of an article. The proposed approach is evaluated on an extended large-scale retrospective scenario, taking advantage of concepts that eventually become MeSH descriptors, for which annotations become available in MEDLINE/PubMed. The results suggest that concept occurrence is a strong heuristic for automated subject annotation refinement and can be further enhanced when combined with dictionary-based heuristics. In addition, such heuristics can be useful as weak supervision for developing deep learning models that can achieve further improvement in some cases.Comment: 48 pages, 5 figures, 9 tables, 1 algorith

EU commodity market development: Medium-term agricultural outlook

The workshop ‘EU commodity market development: Medium-term agricultural outlook’ is an integral part of the validation process of the outlook published in the European Commission’s report on ‘Prospects for EU agricultural markets and income’. The workshop provides a forum for exchanges on preliminary projections to 2030 of EU agricultural commodity markets and for discussing in-depth the EU prospects in a global context. This report contains key messages of the presentations and discussions from the Outlook Workshop 2019, held on 23 and 24 October at the University Foundation in Brussels. The workshop was jointly organised by the Sustainable Resources Directorate of the European Commission’s Joint Research Centre and the Directorate- General for Agriculture and Rural Development.JRC.D.4 - Economics of Agricultur

Rotation and Internal Structure of Population III Protostars

We analyze the cosmological simulations performed in the recent work of Greif et al. (2012), which followed the early growth and merger history of Pop III stars while resolving scales as small as 0.05 R_sol. This is the first set of cosmological simulations to self-consistently resolve the rotation and internal structure of Pop III protostars. We find that Pop III stars form under significant rotational support which is maintained for the duration of the simulations. The protostellar surfaces spin from ~50% to nearly 100% of Keplerian rotational velocity. These rotation rates persist after experiencing multiple stellar merger events. In the brief time period simulated (~ 10 yr), the protostars show little indication of convective instability, and their properties furthermore show little correlation with the properties of their host minihaloes. If Pop III protostars within this range of environments generally form with high degrees of rotational support, and if this rotational support is maintained for a sufficient amount of time, this has a number of crucial implications for Pop III evolution and nucleosynthesis, as well as the possibility for Pop III pair-instability supernovae, and the question of whether the first stars produced gamma-ray bursts.Comment: 19 pages, 12 figures, to appear in MNRA

Analysing the resilience of agricultural production systems with ResiPy, the Python production resilience estimation package

Abstract We present ResiPy, a Python object-oriented software to compute the annual production resilience indicator. This indicator can be applied to different anthropic and natural systems, e.g., agricultural production, natural vegetation and water resources, to quantify their stabilities and the risk of adverse events. We propose an illustrative application of ResiPy to agricultural production in Europe, expressed in economic terms. After estimating the single-country or single-crop resilience, we evaluate the overall resilience of diversified production systems, composed of different crops and different cultivation areas. ResiPy also includes a powerful graphical tool to visually estimate the impact of diversity on complex production systems. The robustness of the indicator and the simplicity of the code ensure its effective applicability in many fields and with different datasets