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- ItemData-Driven Discovery of Stochastic Differential Equations(Beijing : Engineering Sciences Press, 2022) Wang, Yasen; Fang, Huazhen; Jin, Junyang; Ma, Guijun; He, Xin; Dai, Xing; Yue, Zuogong; Cheng, Cheng; Zhang, Hai-Tao; Pu, Donglin; Wu, Dongrui; Yuan, Ye; Gonçalves, Jorge; Kurths, Jürgen; Ding, HanStochastic differential equations (SDEs) are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different sources. The identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system's dynamics. The practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data resources. This study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning (SBL) technique to search for a parsimonious, yet physically necessary representation from the space of candidate basis functions. More importantly, we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series data. The effectiveness of the proposed framework is demonstrated using real data on stock and oil prices, bearing variation, and wind speed, as well as simulated data on well-known stochastic dynamical systems, including the generalized Wiener process and Langevin equation. This framework aims to assist specialists in extracting stochastic mathematical models from random phenomena in the natural sciences, economics, and engineering fields for analysis, prediction, and decision making.
- ItemWildlife-vehicle collisions in hurungwe safari area, northern zimbabwe(Amsterdam [u.a.] : Elsevier, 2020) Gandiwa, Edson; Mashapa, Clayton; Muboko, Never; Chemura, Abel; Kuvaoga, Phillip; Mabika, Cheryl T.This study is the first to assess wildlife-vehicle collisions (WVC) in Zimbabwe. The study analysed the impact and factors that influence vehicle collisions with large wild mammals along the Harare-Chirundu road section in the protected Hurungwe Safari Area, northern Zimbabwe. Data were retrieved from the Hurungwe Safari Area records and covered the period between 2006 and 2013. Descriptive statistics were used to analyse the recorded variables across the sampled area and to show trends of the prevalence of large wild mammals roadkill over time. Using STATISTICA version 10 for Windows, a two-tailed Mann-Whitney U test was used to determine differences between the number of wild mammal animal roadkills and seasons. A total of 47 large wild mammal animals were killed between 2006 and 2013. The large wild mammal animals that died as a result of vehicle collisions constituted a total of 11 species, with the African buffalo and spotted hyena being the most hit and killed animal species. Most WVC involved heavy haulage trucks and passenger buses. There was no significance difference (P = 0.936) between number of large wild mammal animals killed from WVC between dry and wet seasons. The large wild mammal animals were mostly killed in areas near water sources. We recommend for the inclusion of wildlife protection safeguards in road infrastructure network design and development, particularly on roads that traverse across protected areas in Zimbabwe and beyond. © 2020 The Author(s)
- ItemClimate change and specialty coffee potential in Ethiopia([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Chemura, Abel; Mudereri, Bester Tawona; Yalew, Amsalu Woldie; Gornott, ChristophCurrent climate change impact studies on coffee have not considered impact on coffee typicities that depend on local microclimatic, topographic and soil characteristics. Thus, this study aims to provide a quantitative risk assessment of the impact of climate change on suitability of five premium specialty coffees in Ethiopia. We implement an ensemble model of three machine learning algorithms to predict current and future (2030s, 2050s, 2070s, and 2090s) suitability for each specialty coffee under four Shared Socio-economic Pathways (SSPs). Results show that the importance of variables determining coffee suitability in the combined model is different from those for specialty coffees despite the climatic factors remaining more important in determining suitability than topographic and soil variables. Our model predicts that 27% of the country is generally suitable for coffee, and of this area, only up to 30% is suitable for specialty coffees. The impact modelling showed that the combined model projects a net gain in coffee production suitability under climate change in general but losses in five out of the six modelled specialty coffee growing areas. We conclude that depending on drivers of suitability and projected impacts, climate change will significantly affect the Ethiopian speciality coffee sector and area-specific adaptation measures are required to build resilience.
- ItemRobustly forecasting maize yields in Tanzania based on climatic predictors([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Laudien, Rahel; Schauberger, Bernhard; Makowski, David; Gornott, ChristophSeasonal yield forecasts are important to support agricultural development programs and can contribute to improved food security in developing countries. Despite their importance, no operational forecasting system on sub-national level is yet in place in Tanzania. We develop a statistical maize yield forecast based on regional yield statistics in Tanzania and climatic predictors, covering the period 2009–2019. We forecast both yield anomalies and absolute yields at the sub-national scale about 6 weeks before the harvest. The forecasted yield anomalies (absolute yields) have a median Nash–Sutcliffe efficiency coefficient of 0.72 (0.79) in the out-of-sample cross validation, which corresponds to a median root mean squared error of 0.13 t/ha for absolute yields. In addition, we perform an out-of-sample variable selection and produce completely independent yield forecasts for the harvest year 2019. Our study is potentially applicable to other countries with short time series of yield data and inaccessible or low quality weather data due to the usage of only global climate data and a strict and transparent assessment of the forecasting skill.
- ItemA network-based microfoundation of Granovetter’s threshold model for social tipping([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Wiedermann, Marc; Smith, E. Keith; Heitzig, Jobst; Donges, Jonathan F.Social tipping, where minorities trigger larger populations to engage in collective action, has been suggested as one key aspect in addressing contemporary global challenges. Here, we refine Granovetter’s widely acknowledged theoretical threshold model of collective behavior as a numerical modelling tool for understanding social tipping processes and resolve issues that so far have hindered such applications. Based on real-world observations and social movement theory, we group the population into certain or potential actors, such that – in contrast to its original formulation – the model predicts non-trivial final shares of acting individuals. Then, we use a network cascade model to explain and analytically derive that previously hypothesized broad threshold distributions emerge if individuals become active via social interaction. Thus, through intuitive parameters and low dimensionality our refined model is adaptable to explain the likelihood of engaging in collective behavior where social-tipping-like processes emerge as saddle-node bifurcations and hysteresis. © 2020, The Author(s).
- ItemDynamic Network Characteristics of Power-electronics-based Power Systems([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Ji, Yuxi; He, Wei; Cheng, Shijie; Kurths, Jürgen; Zhan, MengPower flow studies in traditional power systems aim to uncover the stationary relationship between voltage amplitude and phase and active and reactive powers; they are important for both stationary and dynamic power system analysis. With the increasing penetration of large-scale power electronics devices including renewable generations interfaced with converters, the power systems become gradually power-electronics-dominant and correspondingly their dynamical behavior changes substantially. Due to the fast dynamics of converters, such as AC current controller, the quasi-stationary state approximation, which has been widely used in power systems, is no longer appropriate and should be reexamined. In this paper, for a better description of network characteristics, we develop a novel concept of dynamic power flow and uncover an explicit dynamic relation between the instantaneous powers and the voltage vectors. This mathematical relation has been well verified by simulations on transient analysis of a small power-electronics-based power system, and a small-signal frequency-domain stability analysis of a voltage source converter connected to an infinitely strong bus. These results demonstrate the applicability of the proposed method and shed an improved light on our understanding of power-electronics-dominant power systems, whose dynamical nature remains obscure.
- ItemThe ongoing nutrition transition thwarts long-term targets for food security, public health and environmental protection([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Bodirsky, Benjamin Leon; Dietrich, Jan Philipp; Martinelli, Eleonora; Stenstad, Antonia; Pradhan, Prajal; Gabrysch, Sabine; Mishra, Abhijeet; Weindl, Isabelle; Le Mouël, Chantal; Rolinski, Susanne; Baumstark, Lavinia; Wang, Xiaoxi; Waid, Jillian L.; Lotze-Campen, Hermann; Popp, AlexanderThe nutrition transition transforms food systems globally and shapes public health and environmental change. Here we provide a global forward-looking assessment of a continued nutrition transition and its interlinked symptoms in respect to food consumption. These symptoms range from underweight and unbalanced diets to obesity, food waste and environmental pressure. We find that by 2050, 45% (39–52%) of the world population will be overweight and 16% (13–20%) obese, compared to 29% and 9% in 2010 respectively. The prevalence of underweight approximately halves but absolute numbers stagnate at 0.4–0.7 billion. Aligned, dietary composition shifts towards animal-source foods and empty calories, while the consumption of vegetables, fruits and nuts increases insufficiently. Population growth, ageing, increasing body mass and more wasteful consumption patterns are jointly pushing global food demand from 30 to 45 (43–47) Exajoules. Our comprehensive open dataset and model provides the interfaces necessary for integrated studies of global health, food systems, and environmental change. Achieving zero hunger, healthy diets, and a food demand compatible with environmental boundaries necessitates a coordinated redirection of the nutrition transition. Reducing household waste, animal-source foods, and overweight could synergistically address multiple symptoms at once, while eliminating underweight would not substantially increase food demand.
- ItemUniversality in spectral condensation([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Pavithran, Induja; Unni, Vishnu R.; Varghese, Alan J.; Premraj, D.; Sujith, R. I.; Vijayan, C.; Saha, Abhishek; Marwan, Norbert; Kurths, JürgenSelf-organization is the spontaneous formation of spatial, temporal, or spatiotemporal patterns in complex systems far from equilibrium. During such self-organization, energy distributed in a broadband of frequencies gets condensed into a dominant mode, analogous to a condensation phenomenon. We call this phenomenon spectral condensation and study its occurrence in fluid mechanical, optical and electronic systems. We define a set of spectral measures to quantify this condensation spanning several dynamical systems. Further, we uncover an inverse power law behaviour of spectral measures with the power corresponding to the dominant peak in the power spectrum in all the aforementioned systems.
- ItemDecay radius of climate decision for solar panels in the city of Fresno, USA([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Barton-Henry, Kelsey; Wenz, Leonie; Levermann, AndersTo design incentives towards achieving climate mitigation targets, it is important to understand the mechanisms that affect individual climate decisions such as solar panel installation. It has been shown that peer effects are important in determining the uptake and spread of household photovoltaic installations. Due to coarse geographical data, it remains unclear whether this effect is generated through geographical proximity or within groups exhibiting similar characteristics. Here we show that geographical proximity is the most important predictor of solar panel implementation, and that peer effects diminish with distance. Using satellite imagery, we build a unique geo-located dataset for the city of Fresno to specify the importance of small distances. Employing machine learning techniques, we find the density of solar panels within the shortest measured radius of an address is the most important factor in determining the likelihood of that address having a solar panel. The importance of geographical proximity decreases with distance following an exponential curve with a decay radius of 210 meters. The dependence is slightly more pronounced in low-income groups. These findings support the model of distance-related social diffusion, and suggest priority should be given to seeding panels in areas where few exist.
- ItemMonsoon forced evolution of savanna and the spread of agro-pastoralism in peninsular India([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Riedel, Nils; Fuller, Dorian Q.; Marwan, Norbert; Poretschkin, Constantin; Basavaiah, Nathani; Menzel, Philip; Ratnam, Jayashree; Prasad, Sushma; Sachse, Dirk; Sankaran, Mahesh; Sarkar, Saswati; Stebich, MartinaAn unresolved issue in the vegetation ecology of the Indian subcontinent is whether its savannas, characterized by relatively open formations of deciduous trees in C4-grass dominated understories, are natural or anthropogenic. Historically, these ecosystems have widely been regarded as anthropogenic-derived, degraded descendants of deciduous forests. Despite recent work showing that modern savannas in the subcontinent fall within established bioclimatic envelopes of extant savannas elsewhere, the debate persists, at least in part because the regions where savannas occur also have a long history of human presence and habitat modification. Here we show for the first time, using multiple proxies for vegetation, climate and disturbances from high-resolution, well-dated lake sediments from Lonar Crater in peninsular India, that neither anthropogenic impact nor fire regime shifts, but monsoon weakening during the past ~ 6.0 kyr cal. BP, drove the expansion of savanna at the expense of forests in peninsular India. Our results provide unambiguous evidence for a climate-induced origin and spread of the modern savannas of peninsular India at around the mid-Holocene. We further propose that this savannization preceded and drove the introduction of agriculture and development of sedentism in this region, rather than vice-versa as has often been assumed.