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Now showing 1 - 10 of 31
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    Climate change and potential distribution of potato (Solanum tuberosum) crop cultivation in Pakistan using Maxent
    (Springfield, MO : AIMS Press, 2021) Khalil, Tayyaba; Asad, Saeed A.; Khubaib, Nusaiba; Baig, Ayesha; Atif, Salman; Umar, Muhammad; Kropp, Jürgen P.; Pradhan, Prajal; Baig, Sofia
    The impacts of climate change are projected to become more intense and frequent. One of the indirect impacts of climate change is food insecurity. Agriculture in Pakistan, measured fourth best in the world, is already experiencing visible adverse impacts of climate change. Among many other food sources, potato crop remains one of the food security crops for developing nations. Potatoes are widely cultivated in Pakistan. To assess the impact of climate change on potato crop in Pakistan, it is imperative to analyze its distribution under future climate change scenarios using Species Distribution Models (SDMs). Maximum Entropy Model is used in this study to predict the spatial distribution of Potato in 2070 using two CMIP5 models for two climate change scenarios (RCP 4.5 and RCP 8.5). 19 Bioclimatic variables are incorporated along with other contributing variables like soil type, elevation and irrigation. The results indicate slight decrease in the suitable area for potato growth in RCP 4.5 and drastic decrease in suitable area in RCP 8.5 for both models. The performance evaluation of the model is based on AUC. AUC value of 0.85 suggests the fitness of the model and thus, it is applicable to predict the suitable climate for potato production in Pakistan. Sustainable potato cultivation is needed to increase productivity in developing countries while promoting better resource management and optimization.
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    Chapter scientists in the IPCC AR5-experience and lessons learned
    (Amsterdam [u.a.] : Elsevier, 2015) Schulte-Uebbing, Lena; Hansen, Gerrit; Hernández, Ariel Macaspac; Winter, Marten
    IPCC Assessment Reports provide timely and accurate information on anthropogenic climate change to policy makers and the public. The reports are written by hundreds of scientists in a voluntary, collaborative effort. Growing amounts of literature and complex procedural and administrative requirements, however, make this effort a substantial management challenge next to a scientific one. During the 5th Assessment Cycle, IPCC Working Groups II and III initiated a program that recruited volunteer scientific assistants who provided technical and logistical support to author teams. In this paper we describe and analyze strengths and weaknesses of this ‘Chapter Scientist program’, based on an extensive survey among Chapter Scientists (CS) and interviews with other stakeholders. We conclude that the program was a useful innovation that that enabled authors to focus more on their core scientific tasks and that contributed to improving the quality of the assessment. We highly recommend similar programs for future scientific assessments. Key criteria for success that we identified are (a) involvement of early-career scientists as CS, (b) close integration of CS in the assessment process, (c) recruitment of CS through an open call to achieve transparency, and (d) provision of funds for such a program to support travel costs and compensation of CS.
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    Perspectives from CO+RE: How COVID-19 changed our food systems and food security paradigms
    (Amsterdam : Elsevier, 2020) Bakalis, Serafim; Valdramidis, Vasilis P.; Argyropoulos, Dimitrios; Ahrne, Lilia; Chen, Jianshe; Cullen, P.J.; Cummins, Enda; Datta, Ashim K.; Emmanouilidis, Christos; Foster, Tim; Fryer, Peter J.; Gouseti, Ourania; Hospido, Almudena; Knoerzer, Kai; LeBail, Alain; Marangoni, Alejandro G.; Rao, Pingfan; Schlüter, Oliver K.; Taoukis, Petros; Xanthakis, Epameinondas; Van Impe, Jan F.M.
    [no abstract available]
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    Anticipation-induced social tipping: can the environment be stabilised by social dynamics?
    (Berlin ; Heidelberg : Springer, 2021) Müller, Paul Manuel; Heitzig, Jobst; Kurths, Jürgen; Lüdge, Kathy; Wiedermann, Marc
    In the past decades, human activities caused global Earth system changes, e.g., climate change or biodiversity loss. Simultaneously, these associated impacts have increased environmental awareness within societies across the globe, thereby leading to dynamical feedbacks between the social and natural Earth system. Contemporary modelling attempts of Earth system dynamics rarely incorporate such co-evolutions and interactions are mostly studied unidirectionally through direct or remembered past impacts. Acknowledging that societies have the additional capability for foresight, this work proposes a conceptual feedback model of socio-ecological co-evolution with the specific construct of anticipation acting as a mediator between the social and natural system. Our model reproduces results from previous sociological threshold models with bistability if one assumes a static environment. Once the environment changes in response to societal behaviour, the system instead converges towards a globally stable, but not necessarily desired, attractor. Ultimately, we show that anticipation of future ecological states then leads to metastability of the system where desired states can persist for a long time. We thereby demonstrate that foresight and anticipation form an important mechanism which, once its time horizon becomes large enough, fosters social tipping towards behaviour that can stabilise the environment and prevents potential socio-ecological collapse.
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    The GGCMI Phase 2 experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
    (Katlenburg-Lindau : Copernicus, 2020) Franke, James A.; Müller, Christoph; Elliott, Joshua; Ruane, Alex C.; Jägermeyr, Jonas; Balkovic, Juraj; Ciais, Philippe; Dury, Marie; Falloon, Pete D.; Folberth, Christian; François, Louis; Hank, Tobias; Hoffmann, Munir; Izaurralde, R. Cesar; Jacquemin, Ingrid; Jones, Curtis; Khabarov, Nikolay; Koch, Marian; Li, Michelle; Liu, Wenfeng; Olin, Stefan; Phillips, Meridel; Pugh, Thomas A. M.; Reddy, Ashwan; Wang, Xuhui; Williams, Karina; Zabel, Florian; Moyer, Elisabeth J.
    Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.
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    Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites
    (Katlenburg-Lindau : Copernicus, 2020) Lasch-Born, Petra; Suckow, Felicitas; Reyer, Christopher P. O.; Gutsch, Martin; Kollas, Chris; Badeck, Franz-Werner; Bugmann, Harald K. M.; Grote, Rüdiger; Fürstenau, Cornelia; Lindner, Marcus; Schaber, Jörg
    The process-based model 4C (FORESEE) has been developed over the past 20 years to study climate impacts on forests and is now freely available as an open-source tool. The objective of this paper is to provide a comprehensive description of this 4C version (v2.2) for scientific users of the model and to present an evaluation of 4C at four different forest sites across Europe. The evaluation focuses on forest growth as well as carbon (net ecosystem exchange, gross primary production), water (actual evapotranspiration, soil water content), and heat fluxes (soil temperature) using data from the PROFOUND database. We applied different evaluation metrics and compared the daily, monthly, and annual variability of observed and simulated values. The ability to reproduce forest growth (stem diameter and biomass) differs from site to site and is best for a pine stand in Germany (Peitz, model efficiency ME=0.98). 4C is able to reproduce soil temperature at different depths in Sorø and Hyytiälä with good accuracy (for all soil depths ME > 0.8). The dynamics in simulating carbon and water fluxes are well captured on daily and monthly timescales (0.51 < ME < 0.983) but less so on an annual timescale (ME < 0). This model–data mismatch is possibly due to the accumulation of errors because of processes that are missing or represented in a very general way in 4C but not with enough specific detail to cover strong, site-specific dependencies such as ground vegetation growth. These processes need to be further elaborated to improve the projections of climate change on forests. We conclude that, despite shortcomings, 4C is widely applicable, reliable, and therefore ready to be released to the scientific community to use and further develop the model.
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    Climate change and international migration: Exploring the macroeconomic channel
    (San Francisco, California, US : PLOS, 2022) Rikani, Albano; Frieler, Katja; Schewe, Jacob
    International migration patterns, at the global level, can to a large extent be explained through economic factors in origin and destination countries. On the other hand, it has been shown that global climate change is likely to affect economic development over the coming decades. Here, we demonstrate how these future climate impacts on national income levels could alter the global migration landscape. Using an empirically calibrated global migration model, we investigate two separate mechanisms. The first is through destination-country income, which has been shown consistently to have a positive effect on immigration. As countries' income levels relative to each other are projected to change in the future both due to different rates of economic growth and due to different levels of climate change impacts, the relative distribution of immigration across destination countries also changes as a result, all else being equal. Second, emigration rates have been found to have a complex, inverted U-shaped dependence on origin-country income. Given the available migration flow data, it is unclear whether this dependence-found in spatio-temporal panel data-also pertains to changes in a given migration flow over time. If it does, then climate change will additionally affect migration patterns through origin countries' emigration rates, as the relative and absolute positions of countries on the migration "hump" change. We illustrate these different possibilities, and the corresponding effects of 3°C global warming (above pre-industrial) on global migration patterns, using climate model projections and two different methods for estimating climate change effects on macroeconomic development.
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    Global cotton production under climate change – Implications for yield and water consumption
    (Munich : EGU, 2021) Jans, Yvonne; von Bloh, Werner; Schaphoff, Sibyll; Müller, Christoph
    Being an extensively produced natural fiber on earth, cotton is of importance for economies. Although the plant is broadly adapted to varying environments, the growth of and irrigation water demand on cotton may be challenged by future climate change. To study the impacts of climate change on cotton productivity in different regions across the world and the irrigation water requirements related to it, we use the process-based, spatially detailed biosphere and hydrology model LPJmL (Lund Potsdam Jena managed land). We find our modeled cotton yield levels in good agreement with reported values and simulated water consumption of cotton production similar to published estimates. Following the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) protocol, we employ an ensemble of five general circulation models under four representative concentration pathways (RCPs) for the 2011 2099 period to simulate future cotton yields. We find that irrigated cotton production does not suffer from climate change if CO2 effects are considered, whereas rainfed production is more sensitive to varying climate conditions. Considering the overall effect of a changing climate and CO2 fertilization, cotton production on current cropland steadily increases for most of the RCPs. Starting from _ 65 million tonnes in 2010, cotton production for RCP4.5 and RCP6.0 equates to 83 and 92 million tonnes at the end of the century, respectively. Under RCP8.5, simulated global cotton production rises by more than 50% by 2099. Taking only climate change into account, projected cotton production considerably shrinks in most scenarios, by up to one-Third or 43 million tonnes under RCP8.5. The simulation of future virtual water content (VWC) of cotton grown under elevated CO2 results for all scenarios in less VWC compared to ambient CO2 conditions. Under RCP6.0 and RCP8.5, VWC is notably decreased by more than 2000m3 t1 in areas where cotton is produced under purely rainfed conditions. By 2040, the average global VWC for cotton declines in all scenarios from currently 3300 to 3000m3 t1, and reduction continues by up to 30% in 2100 under RCP8.5. While the VWC decreases by the CO2 effect, elevated temperature acts in the opposite direction. Ignoring beneficial CO2 effects, global VWC of cotton would increase for all RCPs except RCP2.6, reaching more than 5000m3 t1 by the end of the simulation period under RCP8.5. Given the economic relevance of cotton production, climate change poses an additional stress and deserves special attention. Changes in VWC and water demands for cotton production are of special importance, as cotton production is known for its intense water consumption. The implications of climate impacts on cotton production on the one hand and the impact of cotton production on water resources on the other hand illustrate the need to assess how future climate change may affect cotton production and its resource requirements. Our results should be regarded as optimistic, because of high uncertainty with respect to CO2 fertilization and the lack of implementing processes of boll abscission under heat stress. Still, the inclusion of cotton in LPJmL allows for various large-scale studies to assess impacts of climate change on hydrological factors and the implications for agricultural production and carbon sequestration. © 2021 BMJ Publishing Group. All rights reserved.
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    State-of-the-art global models underestimate impacts from climate extremes
    ([London] : Nature Publishing Group UK, 2019) Schewe, Jacob; Gosling, Simon N.; Reyer, Christopher; Zhao, Fang; Ciais, Philippe; Elliott, Joshua; Francois, Louis; Huber, Veronika; Lotze, Heike K.; Seneviratne, Sonia I.; van Vliet, Michelle T. H.; Vautard, Robert; Wada, Yoshihide; Breuer, Lutz; Büchner, Matthias; Carozza, David A.; Chang, Jinfeng; Coll, Marta; Deryng, Delphine; de Wit, Allard; Eddy, Tyler D.; Folberth, Christian; Frieler, Katja; Friend, Andrew D.; Gerten, Dieter; Gudmundsson, Lukas; Hanasaki, Naota; Ito, Akihiko; Khabarov, Nikolay; Kim, Hyungjun; Lawrence, Peter; Morfopoulos, Catherine; Müller, Christoph; Müller Schmied, Hannes; Orth, René; Ostberg, Sebastian; Pokhrel, Yadu; Pugh, Thomas A. M.; Sakurai, Gen; Satoh, Yusuke; Schmid, Erwin; Stacke, Tobias; Steenbeek, Jeroen; Steinkamp, Jörg; Tang, Qiuhong; Tian, Hanqin; Tittensor, Derek P.; Volkholz, Jan; Wang, Xuhui; Warszawski, Lila
    Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
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    Environmental co-benefits and adverse side-effects of alternative power sector decarbonization strategies
    ([London] : Nature Publishing Group UK, 2019) Luderer, Gunnar; Pehl, Michaja; Arvesen, Anders; Gibon, Thomas; Bodirsky, Benjamin L.; de Boer, Harmen Sytze; Fricko, Oliver; Hejazi, Mohamad; Humpenöder, Florian; Iyer, Gokul; Mima, Silvana; Mouratiadou, Ioanna; Pietzcker, Robert C.; Popp, Alexander; van den Berg, Maarten; van Vuuren, Detlef; Hertwich, Edgar G.
    A rapid and deep decarbonization of power supply worldwide is required to limit global warming to well below 2 °C. Beyond greenhouse gas emissions, the power sector is also responsible for numerous other environmental impacts. Here we combine scenarios from integrated assessment models with a forward-looking life-cycle assessment to explore how alternative technology choices in power sector decarbonization pathways compare in terms of non-climate environmental impacts at the system level. While all decarbonization pathways yield major environmental co-benefits, we find that the scale of co-benefits as well as profiles of adverse side-effects depend strongly on technology choice. Mitigation scenarios focusing on wind and solar power are more effective in reducing human health impacts compared to those with low renewable energy, while inducing a more pronounced shift away from fossil and toward mineral resource depletion. Conversely, non-climate ecosystem damages are highly uncertain but tend to increase, chiefly due to land requirements for bioenergy.