A meta-analysis of the relationship between climate change experience and climate change perception

Will climate change experience shape people\u27s climate change perception? To examine the evidence, we performed a pre-registered meta-analysis using data from 302 studies, covering 351,378 observations. Our results find that climate change experience only has a weak positive correlation with climate change awareness in general (r = 0.098, 95% CI 0.0614, 0.1348), and the effect sizes vary considerably across different climate events. General hazard and temperature anomalies experiences have significant correlations, but other events exhibit no or neglectable effects. The moderator analysis showed that self-reported studies result in higher correlations, whereas studies based on victims\u27 actual experiences report lower effect sizes. Our study suggests that people\u27s climate change experiences may not be effective in shaping their awareness of climate change, which is likely due to people\u27s attribution style and adaptability. The importance of proactive education thus is further emphasized to raise the awareness of climate change

A second-order meta-analysis of nudging

Nudges are increasing their use in the daily lives of the general public. Particularly on the issue of COVID-19 and climate change. However, as a low-cost, large-sample intervention, it remains uncertain whether nudge interventions are effective. Some studies point to the large intervention effect of nudges, while others suggest that nudges may be ineffective. Based on second-order meta-analysis, this study conducted a systematic search of meta-analyses currently applied to nudges to clarify the effectiveness of nudges at a larger data base and evidence level

A Bibliometric Analysis of Global Fine Roots Research in Forest Ecosystems during 1992–2020

(1) Background: Fine roots (≤2 mm in diameter) play a critical role in forest ecosystem ecological processes and has been widely identified as a major research topic. This study aimed to synthesize the global literature based on the Web of Science Core Collection scientific database from 1992 to 2020 and summarize the research trends and prospects on research of fine roots in forest ecosystems. A quantitative bibliometric analysis was presented with information related to authors, countries, institutions, journals, top cited publications, research hotspots, trends, and prospects. (2) Results: The results showed that the amount of publications has increased exponentially. USA, China, and Germany were the most productive countries. Chinese Academy of Science was the most productive institution on fine roots research and also has a key position in both domestic and international cooperation networks. Leuschner C and Hertel D were the most productive authors. Six core journals were confirmed from 471 journals based on Bradford’s law. The distribution of the frequency of authors and the number of their publications were fitted with Lotka’s Law. Author collaboration network was mainly limited in the same countries/territories and institutions. Keywords analysis indicates that the hotspots are biomass, decomposition, and respiration of fine roots, especially under climate change. (3) Conclusion: Our results provide a better understanding of global characteristics and trends of fine roots that have emerged in this field, which could offer reference for future research

A Bibliometric Analysis of Global Fine Roots Research in Forest Ecosystems during 1992–2020

(1) Background: Fine roots (≤2 mm in diameter) play a critical role in forest ecosystem ecological processes and has been widely identified as a major research topic. This study aimed to synthesize the global literature based on the Web of Science Core Collection scientific database from 1992 to 2020 and summarize the research trends and prospects on research of fine roots in forest ecosystems. A quantitative bibliometric analysis was presented with information related to authors, countries, institutions, journals, top cited publications, research hotspots, trends, and prospects. (2) Results: The results showed that the amount of publications has increased exponentially. USA, China, and Germany were the most productive countries. Chinese Academy of Science was the most productive institution on fine roots research and also has a key position in both domestic and international cooperation networks. Leuschner C and Hertel D were the most productive authors. Six core journals were confirmed from 471 journals based on Bradford’s law. The distribution of the frequency of authors and the number of their publications were fitted with Lotka’s Law. Author collaboration network was mainly limited in the same countries/territories and institutions. Keywords analysis indicates that the hotspots are biomass, decomposition, and respiration of fine roots, especially under climate change. (3) Conclusion: Our results provide a better understanding of global characteristics and trends of fine roots that have emerged in this field, which could offer reference for future research

SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction

Analyzing and forecasting trajectories of agents like pedestrians and cars in complex scenes has become more and more significant in many intelligent systems and applications. The diversity and uncertainty in socially interactive behaviors among a rich variety of agents make this task more challenging than other deterministic computer vision tasks. Researchers have made a lot of efforts to quantify the effects of these interactions on future trajectories through different mathematical models and network structures, but this problem has not been well solved. Inspired by marine animals that localize the positions of their companions underwater through echoes, we build a new anglebased trainable social interaction representation, named SocialCircle, for continuously reflecting the context of social interactions at different angular orientations relative to the target agent. We validate the effect of the proposed SocialCircle by training it along with several newly released trajectory prediction models, and experiments show that the SocialCircle not only quantitatively improves the prediction performance, but also qualitatively helps better simulate social interactions when forecasting pedestrian trajectories in a way that is consistent with human intuitions.Comment: CVPR 2024 accepte

A meta-analytical review of intervention experiments to reduce food waste

To reduce food waste, many behavioural intervention experiments have been conducted worldwide, but their effectiveness remains unclear. To assess their impacts, we present a meta-analysis based on 58 studies, selected after screening 1143 papers, which were conducted between 2011 and 2021 covering 26 533 participants. We confirm that behavioural interventions have a moderate effect ( $z$ = 0.22) on food waste reduction, with education programs having the most significant impact and informational feedback having the least. We also show that interventions in elementary and middle school settings marginally improve the overall effect size ( P < 0.1), and controlled experiments exhibit a higher effect size compared to pre-post experiments in education interventions ( P < 0.05). Finally, we present a roadmap to guide future research in the next decade to further improve our understanding on the effects of behavioural interventions to reduce food waste