Article
Environmental Sciences
Jannis M. Hoch, Sophie P. de Bruin, Halvard Buhaug, Nina Von Uexkull, Rens van Beek, Niko Wanders
Summary: This study is the first to use machine learning methods to project sub-national armed conflict risk in Africa, showing variations in conflict risk under different scenarios and assessing the impact of climate change on armed conflict.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Environmental Sciences
Robail Yasrab, Jincheng Zhang, Polina Smyth, Michael P. Pound
Summary: Phenotyping involves quantitative assessment of plant traits, but natural growth cycles can be slow. Deep learning and machine learning-based high-throughput phenotyping offer solutions to automate and accelerate experimental processes. The study demonstrates predicting plant growth using segmentation masks and shows strong performance on public datasets.
Article
Public, Environmental & Occupational Health
Seema Patil, Sharnil Pandya
Summary: This research utilizes climatic variables to construct a dengue forecasting model, finding that humidity and mean maximum temperature are major climate factors with strong correlations to dengue incidences. Random Forest Regression, Support Vector Regression, and Facebook Prophet models are currently the most suitable prediction models.
FRONTIERS IN PUBLIC HEALTH
(2021)
Article
Engineering, Electrical & Electronic
EunGyeong Kim, M. Shaheer Akhtar, O-Bong Yang
Summary: The current photovoltaic power generation systems face irregularity in distribution. Accurate photovoltaic power forecasting is critical for grid-connected systems under changing environmental circumstances. Time series analysis is crucial for predicting photovoltaic output, especially where past solar radiation data or weather parameters are unavailable. This study utilizes various time-series methods, including deep learning and machine learning algorithms, to forecast photovoltaic power generation output for quick response to equipment and panel defects.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Environmental Sciences
Maria Letizia Vitelletti, Elisabetta Manea, Lucia Bongiorni, Antonio Ricchi, Lorenzo Sangelantoni, Davide Bonaldo
Summary: In this study, the distribution of coralligenous habitats in the Northern Adriatic Sea under climate change scenarios was investigated using different models. The results showed that salinity, temperature, and nitrate concentration were the most important variables affecting the distribution of these habitats. Climate change is expected to cause a shift in the distribution of these habitats and potentially result in a loss of biodiversity in the Northern Adriatic Sea.
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Plant Sciences
Ruiping Jiang, Meng Zou, Yu Qin, Guodong Tan, Sipei Huang, Huige Quan, Jiayu Zhou, Hai Liao
Summary: Using MaxEnt model, this study predicted the potential distribution of Fritillaria cirrhosa, Fritillaria unibracteata, and Fritillaria przewalskii, and found high niche overlap among these species. Spatial distribution was identified as one of the factors contributing to speciation diversification. The information obtained in this study provides new insight for the conservation and management of these species in the future.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Environmental Sciences
Sophie P. de Bruin, Jannis M. Hoch, Nina von Uexkull, Halvard Buhaug, Jolle Demmers, Hans Visser, Niko Wanders
Summary: Currently, little research has been done on projecting long-term conflict risks and they are not included in the development of socioeconomic scenarios or climate change impact assessments. However, projecting armed conflict risks in response to climate change, although uncertain, is important and necessary for shaping sustainable future policy agendas in climate change impact assessments.
GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
(2022)
Article
Environmental Sciences
Kailong Li, Guohe Huang, Shuo Wang, Saman Razavi, Xiaoyue Zhang
Summary: This study proposes a joint probabilistic rainfall-runoff model (JPRR) that effectively simulates high-to-extreme flow and outperforms conventional machine learning models. The study also highlights the importance of copulas with right tail dependence in streamflow simulations, particularly in mountainous basins. Furthermore, the research suggests that flood risks may be underestimated by traditional machine learning models under changing climatic conditions.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Liangliang Zhang, Zhao Zhang, Fulu Tao, Yuchuan Luo, Juan Cao, Ziyue Li, Ruizhi Xie, Shaokun Li
Summary: The study used a novel hybrid model to investigate the impacts of climate change on maize productivity in China, determining the timing and locations for hybrid adaptation, as well as the desirable traits for future hybrids.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Editorial Material
Environmental Sciences
Xiaoxing He, Jean-Philippe Montillet, Zhao Li, Gael Kermarrec, Rui Fernandes, Feng Zhou
Summary: This Special Issue focuses on the recent advances in modeling geodetic time series and their application in understanding geophysical information and associated uncertainties. Additionally, it emphasizes the study of natural phenomena related to the geodynamics of the earth's crust and climate change, which is of great significance in understanding environmental changes.
Article
Environmental Sciences
Jacy S. Bernath-Plaisted, Christine A. Ribic, W. Beckett Hills, Philip A. Townsend, Benjamin Zuckerberg
Summary: As climate change advances, there is a need to study climate conditions at ecologically relevant scales. This research focused on microclimates in temperate grasslands and found that they exhibit diversity and are influenced by primary productivity, canopy height, and topography. The heterogeneity of microclimates in grasslands is important for the management and conservation of biodiversity in the face of climate change.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
News Item
Multidisciplinary Sciences
Elizabeth Gibney
Summary: Using emissions data from different locations can assist researchers in minimizing the environmental impact of machine-learning experiments.
Article
Agronomy
Fulu Tao, Liangliang Zhang, Zhao Zhang, Yi Chen
Summary: This study developed hybrid assessment models by combining crop models and machine learning algorithms to evaluate the impact of climate change on wheat productivity in China. The results showed that wheat yield is projected to decrease due to climate change, but with the CO2 effect, it may increase. Factors such as solar radiation, precipitation, temperature, cultivar traits, and CO2 are critical for wheat productivity. The study suggests that a significant portion of wheat planting grids would require cultivar renewal before 2050 to adapt to climate change.
EUROPEAN JOURNAL OF AGRONOMY
(2022)
Article
Environmental Sciences
Lei Gu, Jiabo Yin, Louise J. J. Slater, Jie Chen, Hong Xuan Do, Hui-Min Wang, Lu Chen, Zhiqiang Jiang, Tongtiegang Zhao
Summary: Anthropogenic climate warming is expected to increase the frequency of extreme hydrological droughts globally. This study integrates climate experiments, hydrological models, and multivariate analysis to examine the evolving characteristics and mechanisms of hydrological droughts. Results show that extreme hydrological droughts are projected to occur more frequently across catchments in different climate zones. Precipitation stress is currently the primary driver of historical droughts, but with climate warming, air temperature variations may become the new primary driver in high-latitude cold catchments.
WATER RESOURCES RESEARCH
(2023)
Article
Environmental Sciences
Abdul-Lateef Balogun, Abdulwaheed Tella
Summary: This study investigates the impact of climatic variables on ozone concentration in Malaysia and finds a strong positive correlation between temperature and ozone concentration. Wind speed also shows a moderate to strong correlation, while relative humidity exhibits a negative correlation. Machine learning algorithms, particularly random forest, demonstrate high predictive performances in assessing ozone concentration.
Article
Development Studies
Zohreh Moghfeli, Mehdi Ghorbani, Mohammad Reza Rezvani, Mohammad Amin Khorasani, Hossein Azadi, Juergen Scheffran
Summary: This study used Social Network Analysis (SNA) to analyze the role of social capital and leadership in improving the adaptive capacity of Iranian pistachio farmers. The results revealed that the network among farmers was not dense, with limited reciprocal and face-to-face relations. It was also found that there were few bridging links among the farmers, indicating a lack of bridging social capital. The study suggests that improving the quality of communication between individuals within and across networks can enhance the nature of relationships in social networks and improve farmers' adaptive capacity.
JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Qian Wang, Mengmeng Hao, David Helman, Fangyu Ding, Dong Jiang, Xiaolan Xie, Shuai Chen, Tian Ma
Summary: This study explores the relationship between climate variability under normal conditions and armed conflicts, finding that deviations from temperature and rainfall norms increase the risk of conflict. These findings provide empirical support for policymakers and relevant organizations.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Plant Sciences
Gabriel Mulero, Duo Jiang, David J. Bonfil, David Helman
Summary: The spectral-based photochemical reflectance index (PRI) and leaf surface temperature (T-leaf) are two indicative metrics of plant functioning. This study investigates how these metrics are influenced by drought and elevated carbon dioxide concentrations. It finds that there are relationships between PRI and radiation-use efficiency (RUE) as well as between T-leaf and leaf transpiration. The study also highlights the importance of leaf thickness in determining efficient thermoregulation.
PLANT CELL AND ENVIRONMENT
(2023)
Article
Environmental Studies
Tobias Ide, McKenzie F. Johnson, Jon Barnett, Florian Krampe, Philippe Le Billon, Lucile Maertens, Nina von Uexkull, Irene Velez-Torres
Summary: Interest in the intersections of environmental issues, peace, and conflict has grown in recent years. However, research on this topic is fragmented and lacks interdisciplinary and methodological interaction. This forum aims to fill this gap by bringing together six research streams on the environment, peace, and conflict and fostering dialogue on core findings, potential collaborations, and future research directions.
ENVIRONMENTAL POLITICS
(2023)
Article
International Relations
Tobias Ide
Summary: Climate change poses various threats to human, national, and planetary security. This study examines the impact of climate change on the national security of Australia, with a focus on climate-related threats within Australia and countries of high strategic importance. The findings suggest that climate change will likely undermine Australia's national security by disrupting infrastructure, challenging defense capabilities, increasing political instability in the region, diminishing partner countries' capabilities, and interrupting supply chains. These impacts will be most significant during co-occurring large-scale disasters or major international conflicts, while international wars, migration, and impacts on international partners are minor climate-related risks.
AUSTRALIAN JOURNAL OF INTERNATIONAL AFFAIRS
(2023)
Article
Multidisciplinary Sciences
Xiaolan Xie, Mengmeng Hao, Fangyu Ding, Tobias Ide, David Helman, Juergen Scheffran, Qian Wang, Yushu Qian, Shuai Chen, Jiajie Wu, Tian Ma, Quansheng Ge, Dong Jiang
Summary: Using Structural Equation Modeling and Boosted Regression Tree method, this study finds that COVID-19 pandemic has an impact on the risk of different types of conflicts worldwide, with the transmission risk of COVID-19 decreasing as temperature rises. COVID-19 has a substantial global impact on conflict risk, although regional variations exist. Testing a one-month lagged effect reveals a positive influence of COVID-19 on demonstrations and a negative relationship with non-state and violent conflict risk. Therefore, COVID-19 has a complex effect on conflict risk worldwide under climate change.
Article
Humanities, Multidisciplinary
Shuai Chen, Mengmeng Hao, Fangyu Ding, Dong Jiang, Jiping Dong, Shize Zhang, Qiquan Guo, Chundong Gao
Summary: Cybercrime is causing significant damage to the global economy, national security, social stability, and individual interests. This study examines cybercrime as a social phenomenon, considering social, economic, political, technological, and cybersecurity factors that influence cybercrime. By analyzing a unique cybersecurity dataset called FireHOL IP blocklist, the study identifies primary factors influencing cybercrime using generalized linear models (GLMs) and estimates the direct and indirect effects of various factors on cybercrime using structural equation modeling (SEM). The results show that socioeconomic factors play a crucial role in explaining cybercrime, with cybercrime closely linked to socioeconomic development and their effects varying depending on income levels. Additionally, the study reveals the causal relationships between cybercrime and contextual factors, highlighting the mediating role of technological factors between socioeconomic conditions and cybercrime.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2023)
Article
Biodiversity Conservation
Fang-Yu Ding, Hong-Han Ge, Tian Ma, Qian Wang, Meng-Meng Hao, Hao Li, Xiao-Ai Zhang, Richard James Maude, Li-Ping Wang, Dong Jiang, Li-Qun Fang, Wei Liu
Summary: This study assesses the impact of global climate change on Severe Fever with Thrombocytopenia Syndrome (SFTS) disease in China using an integrated multi-model, multi-scenario framework. The results suggest an expanded geographic distribution of the tick Haemaphysalis longicornis, which is associated with SFTS, and an increased incidence of SFTS in China. The study highlights the need for tick control and population awareness in endemic regions.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Multidisciplinary Sciences
Dong Jiang, Jiajie Wu, Fangyu Ding, Tobias Ide, Juergen Scheffran, David Helman, Shize Zhang, Yushu Qian, Jingying Fu, Shuai Chen, Xiaolan Xie, Tian Ma, Mengmeng Hao, Quansheng Ge
Summary: Human security is threatened by terrorism in the 21st century. Existing research on predicting terrorism has reached its limits using a single perspective. Here, we propose a deep learning framework that incorporates multi-scalar data to discover behavior patterns of terrorist groups, outperforming conventional models and providing insights into terrorism and organized violent crimes.
Editorial Material
Development Studies
Md. Nadiruzzaman, Juergen Scheffran
INTERNATIONAL DEVELOPMENT PLANNING REVIEW
(2023)
Article
Development Studies
Md. Nadiruzzaman, Sonali John, Verena Muehlberger, Jurgen Scheffran
Summary: The climate change and security nexus is an evolving field of research and policy. It has shifted from focusing on the adverse impacts of climate change on human well-being to critically examining the social, cultural, and political construction of vulnerabilities and understanding climate change as a risk multiplier. The academic scrutiny of different aspects of the conflict-security nexus and its future trajectories has grown in recent years.
INTERNATIONAL DEVELOPMENT PLANNING REVIEW
(2023)
Article
Nursing
Davina Jacobi, Tobias Ide
Summary: Concerns about violence against nurses and other medical personnel during the COVID-19 pandemic have led to limited systematic knowledge of such violence. This study analyzes the geographical distribution, motivations, and contexts of collective attacks against health workers during the pandemic. The results indicate that opposition to public health measures, fears of infection, and perceived lack of care are the most common reasons for attacks.
Article
Environmental Sciences
Lea S. Schroeder, Amol K. Bhalerao, Khondokar H. Kabir, Juergen Scheffran, Uwe A. Schneider
Summary: Tribal farmers in the Himalayas are vulnerable to climate change, but little is known about their adaptation decisions. This study provides empirical evidence on the adaptation decisions of tribal farmers in the Himalayas, highlighting the importance of agricultural training in increasing the adoption of soil and water conservation practices. Factors such as participation in civil society organizations, livestock ownership, high-altitude locations, and perception of increased droughts also influence adaptation decisions. The main motivations for adoption are improving livelihoods, sustaining natural resources, reducing workload, and preserving cultural aspects of cultivation.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2024)
Article
Geography
Huixiao Xu, Xiaoqing Song, Houxing Gao, Mingxuan Luo, Adamu Bala, Juergen Scheffran
Summary: This study analyzes the impacts of forest transition on urban shrinkage using a representative forest-based city in China as a case study. The results indicate that forest transition triggers urban shrinkage through a combination of socioeconomic dynamics and policies. The study provides important insights into the trade-off between NEC and LD, and proposes policy implications for achieving win-win options.
