Managing phenology for agronomic adaptation of global cropping systems to climate change

Der Klimawandel fordert die Anbausysteme heraus, um das derzeitige Produktionsniveau zu verbessern oder sogar aufrechtzuerhalten. Es wird erwartet, dass zukünftige Trends bei Temperatur und Niederschlag die Ernteproduktivität beeinträchtigen. Es ist daher notwendig, möglicher Lösungen zur Anpassung der Anbausysteme an den Klimawandel zu untersuchen. Ziel dieser Arbeit ist es, das Wissen über die Anpassung von weltweit relevanten Getreidepflanzen an den Klimawandel zu erweitern. Die zentrale Fragestellung ist, ob globale Anbausysteme an den Klimawandel angepasst werden können, indem die Phänologie der Kulturpflanzen durch Anpassung von Wachstumsperioden und Sorten gesteuert wird. Die Phänologie und die Ertragsreaktionen sowohl auf den Temperaturanstieg als auch auf die Sortenselektion werden zunächst anhand eines Ensembles von “Global Gridded Crop Models” bewertet. Anschließend wird die Komplexität der Anpassung durch phänologisches Management analysiert, insbesondere unter Berücksichtigung der bestehenden großen Wissenslücken bei der Auswahl von Pflanzensorten. Das Ergebnis der Analyse ist ein regelbasierter Algorithmus, der phänologische Zyklen der Kulturpflanzen auswählt, um die Zeit für die Ertragsbildung zu maximieren und Temperatur- und Wasserbelastungen während der Wachstumszyklen der Kulturpflanzen zu minimieren. Die berechneten Aussaatdaten und Wachstumsperioden werden verwendet, um globale Muster von Sorten zu parametrisieren, die an aktuelle und zukünftige Klimaszenarien angepasst sind. Diese Arbeit zeigt, dass die Auswirkungen des Klimawandels auf die Pflanzenproduktivität erheblich variieren können, je nachdem, welche Annahmen für das agronomische Management getroffen werden. Änderungen im Management zu vernachlässigen, liefert die pessimistischste Prognose für die zukünftige Pflanzenproduktion. Relativ einfache Ansätze zur Berechnung angepasster Aussaatdaten und Sorten bieten eine Grundlage für die Berücksichtigung autonomer Anpassungsschemata als integraler Bestandteil globaler Modellierungsrahmen.Climate change is challenging cropping systems to enhance or even maintain current production levels. Future trends in temperature and precipitation are expected to negatively impact crop productivity. It is therefore necessary to explore adaptation options of cropping systems to changing climate. The aim of this thesis is to advance knowledge on adaptation of world-wide relevant grain crops to climate change. The central research question is whether global cropping systems can be adapted to climate change by managing crop phenology through adjusting growing periods and cultivars. Phenology and yield responses to both temperature increase and cultivar selection are first assessed making use of an ensemble of Global Gridded Crop Models. Then, the complexity of adaptation through phenological management is analysed, particularly addressing the existing large knowledge gaps on crop cultivar choice. The outcome of the analysis is a rule-based algorithm that selects crop phenological cycles aiming at maximizing the time for yield formation and minimizing temperature and water stresses during the crop growth cycles. The computed sowing dates and growing periods are used to parametrize global patterns of cultivars adapted to present and future climate scenarios. This thesis demonstrates that the impacts of climate change on crop productivity can vary substantially depending on which assumptions are made on agronomic management. Neglecting any changes in management return the most pessimistic projection on future crop production. Relatively simple approaches to compute adapted sowing dates and cultivars provide a base for considering autonomous adaptation schemes as an integral component of global scale modelling frameworks

Global crop yields can be lifted by timely adaptation of growing periods to climate change

Adaptive management of crop growing periods by adjusting sowing dates and cultivars is one of the central aspects of crop production systems, tightly connected to local climate. However, it is so far underrepresented in crop-model based assessments of yields under climate change. In this study, we integrate models of farmers’ decision making with biophysical crop modeling at the global scale to simulate crop calendars adaptation and its effect on crop yields of maize, rice, sorghum, soybean and wheat. We simulate crop growing periods and yields (1986-2099) under counterfactual management scenarios assuming no adaptation, timely adaptation or delayed adaptation of sowing dates and cultivars. We then compare the counterfactual growing periods and corresponding yields at the end of the century (2080-2099). We find that (i) with adaptation, temperature-driven sowing dates (typical at latitudes >30°N-S) will have larger shifts than precipitation-driven sowing dates (at latitudes <30°N-S); (ii) later-maturing cultivars will be needed, particularly at higher latitudes; (iii) timely adaptation of growing periods would increase actual crop yields by ~12%, reducing climate change negative impacts and enhancing the positive CO2 fertilization effect. Despite remaining uncertainties, crop growing periods adaptation require consideration in climate change impact assessments

Global crop yields can be lifted by timely adaptation of growing periods to climate change

Adaptive management of crop growing periods by adjusting sowing dates and cultivars is one of the central aspects of crop production systems, tightly connected to local climate. However, it is so far underrepresented in crop-model based assessments of yields under climate change. In this study, we integrate models of farmers’ decision making with biophysical crop modeling at the global scale to simulate crop calendars adaptation and its effect on crop yields of maize, rice, sorghum, soybean and wheat. We simulate crop growing periods and yields (1986-2099) under counterfactual management scenarios assuming no adaptation, timely adaptation or delayed adaptation of sowing dates and cultivars. We then compare the counterfactual growing periods and corresponding yields at the end of the century (2080-2099). We find that (i) with adaptation, temperature-driven sowing dates (typical at latitudes >30°N-S) will have larger shifts than precipitation-driven sowing dates (at latitudes <30°N-S); (ii) later-maturing cultivars will be needed, particularly at higher latitudes; (iii) timely adaptation of growing periods would increase actual crop yields by ~12%, reducing climate change negative impacts and enhancing the positive CO2 fertilization effect. Despite remaining uncertainties, crop growing periods adaptation require consideration in climate change impact assessments

Uncertainty in land-use adaptation persists despite crop model projections showing lower impacts under high warming

Climate change is expected to impact crop yields and alter resource availability. However, the understanding of the potential of agricultural land-use adaptation and its costs under climate warming is limited. Here, we use a global land system model to assess land-use-based adaptation and its cost under a set of crop model projections, including CO2 fertilization, based on climate model outputs. In our simulations of a low-emissions scenario, the land system responds through slight changes in cropland area in 2100, with costs close to zero. For a high emissions scenario and impacts uncertainty, the response tends toward cropland area changes and investments in technology, with average adaptation costs between −1.5 and +19 US$05 per ton of dry matter per year. Land-use adaptation can reduce adverse climate effects and use favorable changes, like local gains in crop yields. However, variance among high-emissions impact projections creates challenges for effective adaptation planning

Global wheat production with 1.5 and 2.0°C above pre‐industrial warming

Efforts to limit global warming to below 2°C in relation to the pre‐industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre‐industrial period) on global wheat production and local yield variability. A multi‐crop and multi‐climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by −2.3% to 7.0% under the 1.5°C scenario and −2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980–2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter‐annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer—India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade

NH3 emissions from land application of manures and N-fertilisers: a review of the Italian literature

One of the major pathways of nitrogen (N) loss from agricultural systems is represented by ammonia (NH3) volatilisation. At the global scale, soil application of livestock manures and N-fertilisers represents one of the main sources of this atmospheric pollutant. A literature review was carried out over 78 field trials in order to collect and summarise the research on NH3 emission from land application of manure and N-fertiliser in Italy. Data availability proved to be still limited in terms of coverage of the national territory, representativeness of the measurement method used, type of fertiliser and application strategies explored. Coherently with their importance as NH3 emission sources, livestock manures and urea have been the most assessed materials. From a methodological perspective, the measurements were mostly performed on non-representative scales and the collected data present large weaknesses due to lacking information on the variables that regulate losses of this gas to the atmosphere. The measured emission factors (EFs) have proved to be consistent with the ranges reported by international literature, showing appreciable differences in magnitude among manures and synthetic N-fertilisers and among different field management practices. This is supported by the ALFAM model estimation, which has also shown a strong dependency upon the simulated measurement methods. The reviewed EFs for the different type of fertilisers were compared with the values used by the European and Italian emission inventories. Despite the agreement between these values, our analysis emphasized that the reviewed EFs cannot be regarded as representative for the national territory, mainly because of inconsistencies in the measurement methods

Alcol, sostanze d’abuso e stress in tempi di pandemia di COVID-19: trend evidenziati mediante analisi segmentale del capello

Il Coronavirus ha avuto un impatto senza precedenti sulla nostra società, in tutte le sue dimensioni ed ambiti. Le misure di contenimento più restrittive, il timore di ammalarsi e l’instabilità economica hanno gravemente inficiato il benessere psico-fisico delle persone che si sono trovate a combattere emozioni negative come la solitudine, la paura e l’incertezza. In secondo luogo, è indubbio come la pandemia di COVID-19 abbia determinato cambiamenti anche nel consumo di droghe: i risultati dell’indagine dell’agenzia europea che monitora il consumo di droghe d’abuso (European Monitoring Centre for Drugs and Drug Addiction, EMCDDA), mostrano un calo complessivo del consumo di sostanze d’abuso. Tale declino può essere facilmente spiegato dalle misure di confinamento, dalla chiusura dei luoghi di incontro e di intrattenimento e dalla difficoltà nel rifornire la filiera del mercato illegale della droga, le quali risultano in un calo dell’approvvigionamento da parte dei consumatori finali. In questo contesto si colloca il presente studio che mira a determinare, mediante l'analisi segmentale del capello, i trend dei livelli di stress, del consumo di alcol e di sostanze d'abuso in tre periodi temporali individuati nel lockdown, nei mesi immediatamente precedenti e nella fase successiva all'allentamento delle restrizioni. A tal fine, 87 campioni di capelli, prelevati a soggetti pervenuti presso il laboratorio per accertamenti medico-legali, sono stati segmentati in tre porzioni ed analizzati per cortisolo, etilglucuronide (EtG) e le più comuni sostanze stupefacenti. In particolare, il cortisolo, quale marcatore dello stress, è stato determinato mediante la messa a punto e la validazione di un metodo estrattivo e strumentale in UHPLC-MS/MS. I risultati hanno evidenziato un trend in aumento dei livelli di cortisolo non solo tra il pre-lockdown e il lockdown, ma anche tra quest’ultimo ed il periodo ad esso successivo. Inoltre, si è registrato un chiaro aumento dei consumi di bevande alcoliche e, in accordo con quanto riportato dall’EMCDDA, una tendenziale diminuzione dell’impiego di droghe, seppure con qualche eccezione

The importance of management information and soil moisture representation for simulating tillage effects on N₂O emissions in LPJmL5.0-tillage

No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to great uncertainties as the processes producing the emissions are complex and strongly nonlinear. Previous findings have shown deviations between the LPJmL5.0-tillage model (LPJmL: Lund-Potsdam-Jena managed Land) and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management, the representation of soil water dynamics or both. Model results were compared to observational data and outputs from field-scale DayCent model simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer database for comparison than noncontinuous measurements at experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions and the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to overestimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water and N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management and improvements in soil moisture highlights the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions.</p

Global crop production: adaptation options to temperature increase

Climate change is already and will continue affecting the productivity of agricultural systems, therefore demanding for adaptation strategies to avoid production losses. Due to the complexity and heterogeneity of crop-climate-soil systems, adaptation options are mostly implemented and evaluated locally. Nevertheless, global-scale estimates are needed because e.g. the efficiency of adaptation measures needs to be discussed in the context of costs and opportunities elsewhere. Global gridded crop models (GGCMs) can be informative at both local and larger scales by consistently simulating the entire global crop-land while accounting at the same time for local conditions. Here we present the first systematic study on cropping systems adaptation to temperature increase based on a GGCMs ensemble sensitivity analysis. The models consistently implemented two management options that can alleviate impacts of temperature increase on major grain crops: first an adoption of new cultivars to maintain the original growing period (a measure to counteract accelerated crop phenology) and then a full irrigation (with the aim of avoiding increased water stress due to increased atmospheric vapor pressure deficit (VPD) under warming). We assess the effectiveness of these two options, as well as their combination, in avoiding yield losses of four major crops (maize, wheat, rice and soybean). First results show that, at the global aggregation, irrigation and the unaltered growing period both allow for increasing yields under most warming scenarios, and that the most positive effects occur when these strategies are combined. We also study how adaptation effectiveness varies across regions of the global crop land. In temperate regions a cultivar shift typically has positive effects by reducing yield losses and often even leads to fully maintaining or exceeding the baseline yield levels across various levels of warming. On the other hand, in warmer areas, such as the tropics, this strategy only shows limited effects, even when combined with irrigation and already at moderate warming levels. This suggests that in such environment temperature is already a strong limiting factor that cannot be alleviated by altered crop phenology. This poses a challenge to identify and model alternative adaptation strategies. Irrigation typically helps to increase yields in water-scarce growing environments, but this is also true for most baseline conditions. Irrigation becomes a true adaptation measure only if the yield increase is larger under warming than under baseline conditions. This can e.g. occur in regions where the additional warming leads to substantial increases in VPD