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Now showing 1 - 10 of 61
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    Tackling unresolved questions in forest ecology: The past and future role of simulation models
    ([S.l.] : John Wiley & Sons, Inc., 2021) Maréchaux, Isabelle; Langerwisch, Fanny; Huth, Andreas; Bugmann, Harald; Morin, Xavier; Reyer, Christopher P.O.; Seidl, Rupert; Collalti, Alessio; Dantas de Paula, Mateus; Fischer, Rico; Gutsch, Martin; Lexer, Manfred J.; Lischke, Heike; Rammig, Anja; Rödig, Edna; Sakschewski, Boris; Taubert, Franziska; Thonicke, Kirsten; Vacchiano, Giorgio; Bohn, Friedrich J.
    Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.
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    Values in climate modelling: testing the practical applicability of the Moral Imagination ideal
    (Heidelberg : Springer, 2022) Pulkkinen, Karoliina; Undorf, Sabine; Bender, Frida A.-M.
    There is much debate on how social values should influence scientific research. However, the question of practical applicability of philosophers’ normative proposals has received less attention. Here, we test the attainability of Matthew J. Brown’s (2020) Moral Imagination ideal (MI ideal), which aims to help scientists to make warranted value-judgements through reflecting on goals, options, values, and stakeholders of research. Here, the tools of the MI ideal are applied to a climate modelling setting, where researchers are developing aerosol-cloud interaction (ACI) parametrizations in an Earth System Model with the broader goal of improving climate sensitivity estimation. After the identification of minor obstacles to applying the MI ideal, we propose two ways to increase its applicability. First, its tools should be accompanied with more concrete guidance for identifying how social values enter more technical decisions in scientific research. Second, since research projects can have multiple goals, examining the alignment between broader societal aims of research and more technical goals should be part of the tools of the MI ideal.
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    Drivers of diversity and community structure of bees in an agroecological region of Zimbabwe
    ([S.l.] : John Wiley & Sons, Inc., 2021) Tarakini, Gugulethu; Chemura, Abel; Tarakini, Tawanda; Musundire, Robert
    Worldwide bees provide an important ecosystem service of plant pollination. Climate change and land-use changes are among drivers threatening bee survival with mounting evidence of species decline and extinction. In developing countries, rural areas constitute a significant proportion of the country's land, but information is lacking on how different habitat types and weather patterns in these areas influence bee populations.This study investigated how weather variables and habitat-related factors influence the abundance, diversity, and distribution of bees across seasons in a farming rural area of Zimbabwe. Bees were systematically sampled in five habitat types (natural woodlots, pastures, homesteads, fields, and gardens) recording ground cover, grass height, flower abundance and types, tree abundance and recorded elevation, temperature, light intensity, wind speed, wind direction, and humidity. Zero-inflated models, censored regression models, and PCAs were used to understand the influence of explanatory variables on bee community composition, abundance, and diversity.Bee abundance was positively influenced by the number of plant species in flower (p < .0001). Bee abundance increased with increasing temperatures up to 28.5°C, but beyond this, temperature was negatively associated with bee abundance. Increasing wind speeds marginally decreased probability of finding bees.Bee diversity was highest in fields, homesteads, and natural woodlots compared with other habitats, and the contributions of the genus Apis were disproportionately high across all habitats. The genus Megachile was mostly associated with homesteads, while Nomia was associated with grasslands.Synthesis and applications. Our study suggests that some bee species could become more proliferous in certain habitats, thus compromising diversity and consequently ecosystem services. These results highlight the importance of setting aside bee-friendly habitats that can be refuge sites for species susceptible to land-use changes.
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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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    A Gini approach to spatial CO2 emissions
    (San Francisco, California, US : PLOS, 2020) Zhou, Bin; Thies, Stephan; Gudipudi, Ramana; Lüdeke, Matthias K.B.; Kropp, Jürgen P.; Rybski, Diego
    Combining global gridded population and fossil fuel based CO2 emission data at 1 km scale, we investigate the spatial origin of CO2 emissions in relation to the population distribution within countries. We depict the correlations between these two datasets by a quasi-Lorenz curve which enables us to discern the individual contributions of densely and sparsely populated regions to the national CO2 emissions. We observe pronounced country-specific characteristics and quantify them using an indicator resembling the Gini-index. As demonstrated by a robustness test, the Gini-index for each country arise from a compound distribution between the population and emissions which differs among countries. Relating these indices with the degree of socio-economic development measured by per capita Gross Domestic Product (GDP) at purchase power parity, we find a strong negative correlation between the two quantities with a Pearson correlation coefficient of -0.71. More specifically, this implies that in developing countries locations with large population tend to emit relatively more CO2, and in developed countries the opposite tends to be the case. Based on the relation to urban scaling, we discuss the implications for CO2 emissions from cities. Our results show that general statements with regard to the (in)efficiency of large cities should be avoided as it is subject to the socio-economic development of respective countries. Concerning the political relevance, our results suggest a differentiated spatial prioritization in deploying climate change mitigation measures in cities for developed and developing countries.
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    Future heat stress to reduce people’s purchasing power
    (San Francisco, Ca. : PLOS, 2021) Kuhla, Kilian; Willner, Sven Norman; Otto, Christian; Wenz, Leonie; Levermann, Anders
    With increasing carbon emissions rising temperatures are likely to impact our economies and societies profoundly. In particular, it has been shown that heat stress can strongly reduce labor productivity. The resulting economic perturbations can propagate along the global supply network. Here we show, using numerical simulations, that output losses due to heat stress alone are expected to increase by about 24% within the next 20 years, if no additional adaptation measures are taken. The subsequent market response with rising prices and supply shortages strongly reduces the consumers’ purchasing power in almost all countries including the US and Europe with particularly strong effects in India, Brazil, and Indonesia. As a consequence, the producing sectors in many regions temporarily benefit from higher selling prices while decreasing their production in quantity, whereas other countries suffer losses within their entire national economy. Our results stress that, even though climate shocks may stimulate economic activity in some regions and some sectors, their unpredictability exerts increasing pressure on people’s livelihood.
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    Characterizing the sectoral development of cities
    (San Francisco, California, US : PLOS, 2021) Rybski, Diego; Pradhan, Prajal; Shutters, Shade T.; Butsic, Van; Kropp, Jürgen P.; Xue, Bing
    Previous research has identified a predictive model of how a nation’s distribution of gross domestic product (GDP) among agriculture (a), industry (i), and services (s) changes as a country develops. Here we use this national model to analyze the composition of GDP for US Metropolitan Statistical Areas (MSA) over time. To characterize the transfer of GDP shares between the sectors in the course of economic development we explore a simple system of differential equations proposed in the country-level model. Fitting the model to more than 120 MSAs we find that according to the obtained parameters MSAs can be classified into 6 groups (consecutive, high industry, re-industrializing; each of them also with reversed development direction). The consecutive transfer (a → i → s) is common but does not represent all MSAs examined. At the 95% confidence level, 40% of MSAs belong to types exhibiting an increasing share of GDP from agriculture. In California, such MSAs, which we classify as part of an agriculture renaissance, are found in the Central Valley.
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    Climatic windows for human migration out of Africa in the past 300,000 years
    ([London] : Nature Publishing Group UK, 2021) Beyer, Robert M.; Krapp, Mario; Eriksson, Anders; Manica, Andrea
    Whilst an African origin of modern humans is well established, the timings and routes of their expansions into Eurasia are the subject of heated debate, due to the scarcity of fossils and the lack of suitably old ancient DNA. Here, we use high-resolution palaeoclimate reconstructions to estimate how difficult it would have been for humans in terms of rainfall availability to leave the African continent in the past 300k years. We then combine these results with an anthropologically and ecologically motivated estimate of the minimum level of rainfall required by hunter-gatherers to survive, allowing us to reconstruct when, and along which geographic paths, expansions out of Africa would have been climatically feasible. The estimated timings and routes of potential contact with Eurasia are compatible with archaeological and genetic evidence of human expansions out of Africa, highlighting the key role of palaeoclimate variability for modern human dispersals.
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    Climate signals in river flood damages emerge under sound regional disaggregation
    ([London] : Nature Publishing Group UK, 2021) Sauer, Inga J.; Reese, Ronja; Otto, Christian; Geiger, Tobias; Willner, Sven N.; Guillod, Benoit P.; Bresch, David N.; Frieler, Katja
    Climate change affects precipitation patterns. Here, we investigate whether its signals are already detectable in reported river flood damages. We develop an empirical model to reconstruct observed damages and quantify the contributions of climate and socio-economic drivers to observed trends. We show that, on the level of nine world regions, trends in damages are dominated by increasing exposure and modulated by changes in vulnerability, while climate-induced trends are comparably small and mostly statistically insignificant, with the exception of South & Sub-Saharan Africa and Eastern Asia. However, when disaggregating the world regions into subregions based on river-basins with homogenous historical discharge trends, climate contributions to damages become statistically significant globally, in Asia and Latin America. In most regions, we find monotonous climate-induced damage trends but more years of observations would be needed to distinguish between the impacts of anthropogenic climate forcing and multidecadal oscillations.
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    Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China
    ([London] : Nature Publishing Group UK, 2021) Xing, Xiaofan; Wang, Rong; Bauer, Nico; Ciais, Philippe; Cao, Junji; Chen, Jianmin; Tang, Xu; Wang, Lin; Yang, Xin; Boucher, Olivier; Goll, Daniel; Peñuelas, Josep; Janssens, Ivan A.; Balkanski, Yves; Clark, James; Ma, Jianmin; Pan, Bo; Zhang, Shicheng; Ye, Xingnan; Wang, Yutao; Li, Qing; Luo, Gang; Shen, Guofeng; Li, Wei; Yang, Yechen; Xu, Siqing
    As China ramped-up coal power capacities rapidly while CO2 emissions need to decline, these capacities would turn into stranded assets. To deal with this risk, a promising option is to retrofit these capacities to co-fire with biomass and eventually upgrade to CCS operation (BECCS), but the feasibility is debated with respect to negative impacts on broader sustainability issues. Here we present a data-rich spatially explicit approach to estimate the marginal cost curve for decarbonizing the power sector in China with BECCS. We identify a potential of 222 GW of power capacities in 2836 counties generated by co-firing 0.9 Gt of biomass from the same county, with half being agricultural residues. Our spatially explicit method helps to reduce uncertainty in the economic costs and emissions of BECCS, identify the best opportunities for bioenergy and show the limitations by logistical challenges to achieve carbon neutrality in the power sector with large-scale BECCS in China.