Article
Multidisciplinary Sciences
Joseph Friedman, Patrick Liu, Christopher E. Troeger, Austin Carter, Robert C. Reiner, Ryan M. Barber, James Collins, Stephen S. Lim, David M. Pigott, Theo Vos, Simon Hay, Christopher J. L. Murray, Emmanuela Gakidou
Summary: This study examines the predictive performance of 7 global COVID-19 forecasting models, finding that they show surprisingly good performance at six weeks despite the complexities of modeling human behavioral responses and government interventions. Additionally, the study reveals that these models have high accuracy in predicting the timing of peak daily mortality.
NATURE COMMUNICATIONS
(2021)
Article
Ecology
Andrii Zaiats, Megan E. Cattau, David S. Pilliod, Rongsong Liu, Juan M. Requena-Mullor, T. Trevor Caughlin
Summary: This study develops a framework for forecasting post-wildfire regeneration of sagebrush cover in the Great Basin region of the Western US. The research demonstrates that accounting for wildfire and within-wildfire spatial heterogeneity improves the accuracy of recovery predictions.
Article
Green & Sustainable Science & Technology
G. T. N. Veerendra, B. Kumaravel, P. Kodanda Rama Rao, Subhashish Dey, A. V. Phani Manoj
Summary: Modeling surface water quality is crucial for managing water resources, and this study proposes a MLT-based method that combines RS and GIS for spatial prediction. The findings suggest that MLT modeling is more realistic than experimental setting and can be used for pollution-free surface water management.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Economics
Weilun Zhou, Jiti Gao, David Harris, Hsein Kew
Summary: This paper discusses the estimation of a semi-parametric single-index regression model that allows for nonlinear predictive relationships. The presence of cointegrated predictors balances the nonstationarity properties of the predictors with the stationarity properties of asset returns and avoids the curse of dimensionality. In an empirical application, it is found that using cointegrated predictors produces better out-of-sample forecasts.
JOURNAL OF ECONOMETRICS
(2024)
Article
Multidisciplinary Sciences
Kookjin Lee, Jaideep Ray, Cosmin Safta
Summary: This study investigates the utility of using convolutional neural network models for epidemiological forecasting, finding that these models achieve higher accuracy in forecasting ILI compared to traditional models. The results suggest that using CNNs for epidemiological forecasting is feasible and their predictive skill is comparable to, and sometimes superior to, plain RNNs.
Review
Multidisciplinary Sciences
Cole Heasley, J. Johanna Sanchez, Jordan Tustin, Ian Young
Summary: This study systematically reviewed predictive models of fecal indicator bacteria at freshwater recreational sites in temperate climates, finding that most studies were conducted in the United States using E. coli as the indicator bacteria, with multiple linear regression being the most commonly used method to build predictive models. The frequently used predictors in best-fitting models included rainfall, turbidity, wave height, and wind speed and direction. The majority of predictive models had high accuracy rates and were more accurate than traditional methods, but limitations identified included unvalidated models, limited reporting of modeling assumptions, and lack of reporting on handling missing data. Further research is needed on the utility and accuracy of more advanced predictive modeling methods.
Article
Environmental Sciences
Elina Bennetsen, Sacha Gobeyn, Gert Everaert, Peter Goethals
Summary: Global river systems are under pressure due to human development, with the European Union proposing ecological status as the endpoint for management interventions. This paper introduces a novel method that combines monitoring data to identify key stressors in river systems and define management scenarios. By disassembling ecological status into individual components and using habitat suitability models, the method aims to optimize sustainable decisions in river management.
Article
Behavioral Sciences
Kent M. Lee, Fernando Ferreira-Santos, Ajay B. Satpute
Summary: The neural bases of affective experience are still unclear, as early models failed to identify specific brain regions responsible for emotional computations. Current research has shifted towards multivariate analyses and predictive processing models, but progress remains limited.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2021)
Article
Horticulture
Kazufumi Zushi, Miyu Yamamoto, Momoka Matsuura, Kan Tsutsuki, Asumi Yonehana, Ren Imamura, Hiromi Takahashi, Masaaki Kirimura
Summary: This study investigated the seasonal variation of strawberry firmness in different tissues and developed predictive models. The results showed that fruit properties and firmness decreased towards the end of the season, and the predictive models demonstrated adequate accuracy and usefulness.
SCIENTIA HORTICULTURAE
(2023)
Article
Construction & Building Technology
Ceren Kina, Harun Tanyildizi, Kazim Turk
Summary: Predicting the compressive strength of ground granulated blast furnace slag (GGBFS)-based geopolymer concrete (GPC) is an important research area. This study compares decision tree, bootstrap aggregating, and least-squares boosting models for the prediction of compressive strength. The results show that the least-squares boosting model achieves the highest accuracy and stability in prediction.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Plant Sciences
Thomas Thomidis, Konstantinos Michos, Fotis Chatzipapadopoulos, Amalia Tampaki
Summary: The study investigated the impact of temperature and leaf wetness on conidial germination of Venturia oleaginea. Results showed an optimal temperature range and minimum leaf wetness required for germination. Validation of predictive models for olive leaf spot disease showed differences in predicting infection severity.
Article
Multidisciplinary Sciences
Tom R. Andersson, J. Scott Hosking, Maria Perez-Ortiz, Brooks Paige, Andrew Elliott, Chris Russell, Stephen Law, Daniel C. Jones, Jeremy Wilkinson, Tony Phillips, James Byrne, Steffen Tietsche, Beena Balan Sarojini, Eduardo Blanchard-Wrigglesworth, Yevgeny Aksenov, Rod Downie, Emily Shuckburgh
Summary: Accurate seasonal forecasts of sea ice are crucial in the context of global warming-induced sea ice loss. IceNet, a new machine learning tool, significantly improves the accuracy of sea ice forecasting compared to physics-based dynamical models. The unprecedented year-round reduction in Arctic sea ice extent due to anthropogenic warming highlights the importance of accurate seasonal sea ice forecasts in mitigating risks associated with rapid sea ice loss.
NATURE COMMUNICATIONS
(2021)
Article
Psychology, Multidisciplinary
Jessica Hoepfner, Nina Keith
Summary: Research shows that failing a high and specific goal can have detrimental effects on an individual's affect, self-esteem, and motivation, which may be crucial for organizational long-term outcomes. Therefore, organizations should consider potential undesirable effects when using goal-setting interventions.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Economics
Jan Capek, Jesus Crespo Cuaresma, Niko Hauzenberger, Vlastimil Reichel
Summary: This study provides a comprehensive assessment of the predictive power of combinations of dynamic stochastic general equilibrium (DSGE) models. The results show that using mixtures of DSGE models produces competitive forecasts compared to individual specifications.
INTERNATIONAL JOURNAL OF FORECASTING
(2023)
Review
Psychology, Multidisciplinary
Xiaofang Cheng
Summary: In recent decades, there has been a growing interest in studies on motivation related to second/foreign language learning. Research findings indicate that academic motivation plays a crucial role in students' success in their studies. One aspect of academic motivation is goal orientation, which explains why learners engage in achievement activities. Goal setting is considered an important cognitive interface that connects motivation to behavior. It serves as a motivating factor and promotes success in various fields. Achievement goal theory (AGT) and goal setting theory are two motivational theories that have been developed to explain motivation in the context of second/foreign language learning. This review aims to contribute to the existing literature on these theories and has pedagogical implications for English as a foreign language stakeholders.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Biodiversity Conservation
Christopher P. Catano, Tyler J. Bassett, Jonathan T. Bauer, Emily Grman, Anna M. Groves, Chad R. Zirbel, Lars A. Brudvig
Summary: Ecological restoration outcomes can be unpredictable due to different community assembly trajectories influenced by restoration actions and abiotic conditions. This study found that plant species and trait compositions converged more on resource-poor soils with frequent fires, while variation remained stable over time for trait composition regardless of soil resources or restoration actions. Monitoring multiple facets of biodiversity can provide insights into why outcomes vary and inform broad-scale restoration planning.
JOURNAL OF APPLIED ECOLOGY
(2022)
Article
Ecology
Louis W. Jochems, Jennifer A. Lau, Lars A. Brudvig, Emily Grman
Summary: The study found that future climate warming may reduce plant diversity in tallgrass prairies and impact the composition of restored prairies. It remains unclear whether locally adapted or warm-adapted seeds have an advantage in future warmer environments, and there is little evidence to support the superior performance of seeds from the southern region under warming conditions.
ECOLOGICAL APPLICATIONS
(2022)
Article
Ecology
Christopher P. Catano, Anna M. Groves, Lars A. Brudvig
Summary: The relationships between biodiversity and ecosystem functioning are influenced by the processes of community assembly. However, predicting these relationships is challenging due to the influence of historical factors and the poorly understood consequences of history on ecosystem functions. In a grassland restoration experiment, researchers examined the role of history by initiating assembly in different years and found that historical factors altered species and trait community trajectories, leading to changes in productivity, decomposition rates, and floral resources. The study highlights the importance of considering history in understanding biodiversity-ecosystem function relationships in natural ecosystems.
Article
Multidisciplinary Sciences
John L. Orrock, Lars A. Brudvig, Ellen I. Damschen, W. Brett Mattingly, Jennyffer Cruz, Joseph W. Veldman, Philip G. Hahn, Angela L. Larsen-Gray
Summary: Ecological restoration is crucial for preserving biodiversity in the face of global changes. A long-term experiment in longleaf pine savannas showed that seed additions and climatic variations significantly impacted plant establishment and persistence, highlighting the importance of considering these factors in future restoration and conservation efforts.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Ecology
Anna W. Paraskevopoulos, Christopher P. Catano, Lars A. Brudvig
Summary: Recovering biodiversity is a common goal of restoration, but the outcomes for animal communities can vary greatly. This study focused on the influence of seed mix diversity on ant community recovery in tallgrass prairies. The results showed that high diversity seed mixes for plant-focused restoration increased plant species richness, but did not consistently impact ant richness or composition. The interactions between realized plant richness, environmental structure, and ant community responses highlight the need for additional restoration strategies to benefit biodiversity.
RESTORATION ECOLOGY
(2023)
Article
Ecology
Christopher R. Warneke, Stephanie G. Yelenik, Lars A. Brudvig
Summary: Plant-soil feedbacks (PSFs) play an important role in shaping plant diversity, but their interactions with environmental factors, such as fire, have received little attention. This study examined how a recent fire altered PSFs of two nitrogen-fixing tree species in Hawaii. The results showed that fire weakened the PSFs and pairwise PSFs between the tree species, indicating that the legume-rhizobia symbiosis was affected. These findings highlight the importance of considering environmental context when studying PSFs.
Article
Biodiversity Conservation
Joe Atkinson, Anna M. Groves, Isaac R. Towers, Christopher P. Catano, Lars A. Brudvig
Summary: The variability in ecological restoration outcomes is influenced by the interannual variation in environmental conditions during the first year of restoration, known as year effects. However, the extent to which year effects influence the traits of plant communities is currently unknown.
JOURNAL OF APPLIED ECOLOGY
(2023)
Article
Ecology
Riley B. Pizza, Jared Foster, Lars A. Brudvig
Summary: During the decade of restoration, it is important to understand how to effectively re-establish native plant populations. The impact of seed sourcing decisions on plant establishment and abundance is unclear, as this assumption has not been tested in realistic restoration settings. However, using less-local seed sources may affect flowering phenology.
ECOLOGICAL SOLUTIONS AND EVIDENCE
(2023)
Article
Plant Sciences
Margaret B. Fleming, Lauren Stanley, Robyn Zallen, Matthew T. Chansler, Lars A. Brudvig, David B. Lowry, Marjorie Weber, Frank W. Telewski
Summary: The experiment studied the longevity of seeds in soil by burying glass bottles filled with seeds and sand for over a century. The results showed that a significant percentage of Verbascum seeds can still germinate after 141 years. This long-term experiment provides valuable insights into the viability of seeds in natural soil conditions.
AMERICAN JOURNAL OF BOTANY
(2023)
Article
Ecology
Diana Bertuol-Garcia, Emma Ladouceur, Lars A. Brudvig, Daniel C. Laughlin, Seth M. Munson, Michael F. Curran, Kirk W. Davies, Lauren N. Svejcar, Nancy Shackelford
Summary: Ecological restoration is crucial for recovering degraded ecosystems, but its success and predictability are often low. This study analyzed data from 11 grassland restoration projects and found that the predictability of restoration outcomes did not follow a decreasing order from physical structure to taxonomic composition, and predictability did not consistently increase with more severe environmental conditions. Restoration outcomes related to dominant species were more predictable, while those relating to rare species were harder to predict.
ECOLOGICAL APPLICATIONS
(2023)
Article
Ecology
Nathan I. Wisnoski, Riley Andrade, Max C. N. Castorani, Christopher P. Catano, Aldo Compagnoni, Thomas Lamy, Nina K. Lany, Luca Marazzi, Sydne Record, Annie C. Smith, Christopher M. Swan, Jonathan D. Tonkin, Nicole M. Voelker, Phoebe L. Zarnetske, Eric R. Sokol
Summary: The relationship between biodiversity and stability is complex and multidimensional. Temporal variability is lower in communities with higher species diversity, both at local and regional scales. However, compositional shifts may potentially destabilize communities despite high diversity. This study examines the relationship between diversity and variability across different spatial scales and taxa, using a large collection of long-term metacommunity data. The results suggest that high gamma-diversity alone does not consistently stabilize aggregate properties at regional scales without sufficient spatial beta-diversity to reduce spatial synchrony.
Article
Ecology
Emma Ladouceur, Nancy Shackelford, Karma Bouazza, Lars Brudvig, Anna Bucharova, Timo Conradi, Todd E. Erickson, Magda Garbowski, Kelly Garvy, W. Stanley Harpole, Holly P. Jones, Tiffany Knight, Mlungele M. Nsikani, Gustavo Paterno, Katharine Suding, Vicky M. Temperton, Peter Torok, Daniel E. Winkler, Jonathan M. Chase
Summary: The Decade on Ecosystem Restoration aims to provide the means and incentives for upscaling restoration efforts worldwide. Effective ecological restoration requires knowledge and data sharing to inform synthesis for robust restoration science. Sharing species-level, fine-scale ecological community data can help improve restoration outcomes and increase predictive capacity. Integrated data, analysis, and knowledge sharing can support shared success in restoration ecology.
ECOLOGICAL SOLUTIONS AND EVIDENCE
(2022)