Article
Forestry
James A. Westfall, Barry T. Wilson
Summary: Nonresponse in national forest inventories can lead to empirical bias in sample-based estimates, especially when estimating change over time. This study found that systematic differences in nonresponse probabilities due to ownership and forest/nonforest status result in overall change estimates that are too small. Underestimation of change hinders detection of significant shifts in forest attributes and limits effective management and policy responses. Further research is needed to address this issue, including improved strategies for defining populations and alternative estimation methods that account for differential nonresponse probabilities.
Article
Engineering, Multidisciplinary
Luo Xuegang, Lv Junrui, Wang Juan
Summary: This study introduces a data reconstruction method based on spectral k-support norm minimization for NBIoT data, utilizing relative density-based clustering and matrix spectral k-support norm minimization algorithm to enhance reconstruction accuracy. The alternating direction method of multipliers is employed for optimal solution, with simulation results demonstrating good algorithm performance.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jeonghyeon Nam, Okkyun Lee
Summary: The study developed a calibration-based estimator for PCD-based x-ray computed tomography called the nearest neighborhood (NN)-based estimator, which outperformed the model-based maximum likelihood (ML) estimator in terms of efficiency and accuracy, especially in K-edge imaging for gold concentrations.
Article
Chemistry, Analytical
Yulong Deng, Chong Han, Jian Guo, Lijuan Sun
Summary: This paper presents a new missing data imputation method based on temporal and spatial nearest neighbor values (TSNN), which has been elaborated and tested on indoor and outdoor wireless sensor networks, showing improved accuracy and effectiveness in data imputation.
Article
Ecology
David M. M. Bell, Matthew J. J. Gregory, Derek J. J. Churchill, Annie C. C. Smith
Summary: Maps of species composition are important for assessing ecosystem functions in forested landscapes. Using remotely sensed data can improve the accuracy of these maps and help predict species occurrence and relative abundance. Climate, topography, and location were found to be important factors influencing species occurrence, while forest structure provided by remote sensing also played a role in predicting species relative abundance. Considering both environmental factors and remote sensing information is necessary for characterizing geospatial patterns in tree communities.
FRONTIERS IN FORESTS AND GLOBAL CHANGE
(2022)
Article
Thermodynamics
Xiang Yu
Summary: This paper evaluates parallelized support vector regression (SVR) and nearest neighbor regression (NNR) models for estimating daily global solar radiation, and finds that both SVR and NNR are effective for nonlinear regression. The variation comprising features with absolute PCCs no less than 0.3 achieves the most accurate estimation. The GPU-parallelized NNR model is the most efficient and scalable.
INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES
(2023)
Article
Thermodynamics
Priya Gupta, Rhythm Singh
Summary: This study employs a less time-complex ensemble model combined with multivariate empirical mode decomposition (MEMD) for solar irradiance forecasting. The results show that the MEMD-stacked model outperforms modern and more complex machine learning techniques, providing more accurate predictions with lesser time complexity. The model's performance is validated for three Indian locations, demonstrating its potential to achieve accurate global horizontal irradiance forecasts with simpler algorithms.
Article
Computer Science, Artificial Intelligence
Wenhao Bi, Junwen Ma, Xudong Zhu, Weixiang Wang, An Zhang
Summary: Military organization cloud cooperation is a new type of military organization that encapsulates combat resources into services and makes them available as a service. This paper proposes a cloud service selection method based on the weighted KD tree nearest neighbor search (WKDTNNS) algorithm for personalized search of cloud services with different weights in each dimension. A case study demonstrates the feasibility and effectiveness of the proposed method, showing better results with reduced computation time compared to other algorithms.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Teng Qiu, Yongjie Li
Summary: We have recently proposed a physically-inspired graph-theoretical method, Nearest Descent (ND), to organize a dataset into an in-tree structure suitable for data clustering. We have also introduced another graph-theoretical method, Hierarchical Nearest Neighbor Descent (HNND), which efficiently organizes the dataset into an in-tree. Experimental results demonstrate that HNND-based clustering achieves overall better performance and efficiency compared to ND-based clustering and some state-of-the-art methods.
PATTERN RECOGNITION
(2023)
Article
Water Resources
Kelly Deguzman, Thorsten Knappenberger, Eve Brantley, Yaniv Olshansky
Summary: This study investigates the impact of low-impact development (LID) techniques on runoff generation and presents a binomial regression model to assess the relationship between precipitation depth and runoff likelihood. The findings suggest that linear regression models may lead to invalid conclusions when analyzing runoff generation, highlighting the superiority of the binomial regression model.
HYDROLOGICAL PROCESSES
(2023)
Article
Computer Science, Information Systems
Omid Keivani, Kaushik Sinha
Summary: Recent research has shown that nearest neighbor search using random projection trees achieves superior performance compared to locality sensitive hashing, requiring users to maintain and search through a large number of trees for large-scale applications. To address this issue, this paper presents different search strategies to improve the performance of a single random projection tree by storing meaningful auxiliary information and designing priority functions. Empirical results demonstrate significant improvements in nearest neighbor search accuracy compared to baseline methods.
INFORMATION SCIENCES
(2021)
Article
Ecology
Nicolas Strebel, Cameron J. Fiss, Kenneth F. Kellner, Jeffery L. Larkin, Marc Kery, Jonathan Cohen
Summary: The study aims at quantifying absolute abundance in ecology and management. Time-to-detection (TTD) models have the potential for estimating occupancy, but are underutilized. The new TTD-N-mixture model shows promise for estimating abundance with less expensive data, suitable for single- and multiple-visit data.
METHODS IN ECOLOGY AND EVOLUTION
(2021)
Article
Environmental Sciences
David A. Olson, John H. Offenberg, Michael Lewandowski, Tadeusz E. Kleindienst, Kenneth S. Docherty, Mohammed Jaoui, Jonathan Krug, Theran P. Riedel
Summary: This research utilized data mining methods to analyze laboratory data and identified key factors influencing the formation of secondary organic aerosol (SOA).
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Multidisciplinary Sciences
Cem Kalyoncu, Ahmet Yasli, Huseyin Ademgil
Summary: Machine learning approaches have been increasingly used in optical devices and fibers in recent years. This work proposes the use of k-Nearest Neighbor Regression (KNNR) as a non-linear regression method to determine the loss characteristics of a photonic crystal fiber (PCF) based surface plasmon resonance (SPR) sensor in the presence of a bend. Experimental results show that KNNR outperforms Artificial Neural Network (ANN) and Linear Least Square Regression methods, and does not require lengthy training process.
Article
Environmental Sciences
Ke Rao, Xiang Zhang, Mo Wang, Jianfeng Liu, Wenqi Guo, Guangwei Huang, Jing Xu
Summary: The phytoplankton community is influenced by various environmental factors, making prediction of their dynamics challenging. Different phytoplankton groups respond differently to environmental factors, with reducing nutrients being effective in mitigating the adverse effects of warming and water project constructions.
ENVIRONMENTAL POLLUTION
(2021)
Article
Zoology
Yi-Chin Tseng, Bianca N. I. Eskelson, Kathy Martin, Valerie LeMay
Summary: Avian bioacoustics research has benefited from the use of autonomous recording units, enabling remote monitoring and large-scale studies. A logistic model based on sound frequency percentiles was developed to predict bird presence in audio recordings, achieving a 75% overall accuracy and potential for automatic analysis of large datasets.
BIOACOUSTICS-THE INTERNATIONAL JOURNAL OF ANIMAL SOUND AND ITS RECORDING
(2021)
Article
Forestry
Sushil Nepal, Bianca N. Eskelson, Martin Ritchie
Article
Forestry
Raphael D. Chavardes, Lori D. Daniels, Bianca N. Eskelson, Ze'ev Gedalof
TREE-RING RESEARCH
(2020)
Article
Ecology
Hyeyoung Woo, Bianca N. I. Eskelson, Vicente J. Monleon
Summary: This study explored a quasi-experimental method, propensity score matching, to estimate wildfire effects on aboveground forest woody carbon mass in Washington and Oregon. The results showed that DAPSM was the preferred method in balancing observed covariates and dealing with unobservable confounding variables through spatial adjustment.
ECOLOGICAL APPLICATIONS
(2021)
Article
Plant Sciences
Nguyet-Anh Nguyen, Bianca N. Eskelson, Sarah E. Gergel, Tasha Murray
Summary: This study examined the occurrence of invasive plant species in different types of greenspaces and the relationships with socio-economic, topographic, and land use variables. The results revealed that natural areas had significantly higher odds of species occurrence, while greenspaces in wealthier neighborhoods and areas with higher population density were more likely to experience invasive species occurrence.
URBAN FORESTRY & URBAN GREENING
(2021)
Article
Environmental Sciences
Flavie Pelletier, Bianca N. Eskelson, Vicente J. Monleon, Yi-Chin Tseng
Summary: Accurate assessment of burn severity after wildfires is crucial as their frequency and size increase. Remotely-sensed imagery allows for rapid assessment, but requires field validation. This study used ground-based inventory data and remotely-sensed data to determine the best matching methods for burn severity assessments.
Article
Forestry
Ignacio Barbeito, Bianca N. I. Eskelson, Grace Carsky
Summary: The study found that mixing lodgepole pine and interior hybrid spruce as well as planting at high densities can decrease weevil attacks in spruce, reducing timber quality loss. However, mixing with spruce can lead to decreased quality in lodgepole pine due to larger crowns.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Book Review
Biology
Bianca N. I. Eskelson
Article
Forestry
Alexis Achim, Guillaume Moreau, Nicholas C. Coops, Jodi N. Axelson, Julie Barrette, Steve Bedard, Kenneth E. Byrne, John Caspersen, Adam R. Dick, Loic D'Orangeville, Guillaume Drolet, Bianca N. Eskelson, Cosmin N. Filipescu, Maude Flamand-Hubert, Tristan R. H. Goodbody, Verena C. Griess, Shannon M. Hagerman, Kevin Keys, Benoit Lafleur, Miguel Montoro Girona, Dave M. Morris, Charles A. Nock, Bradley D. Pinno, Patricia Raymond, Vincent Roy, Robert Schneider, Michel Soucy, Bruce Stewart, Jean-Daniel Sylvain, Anthony R. Taylor, Evelyne Thiffault, Nelson Thiffault, Udaya Vepakomma, Joanne C. White
Summary: Climate change is rapidly altering forest ecosystems, leading to a diversification of public expectations regarding sustainable forest resource use. Silviculturists are transitioning from empirically derived scenarios to new approaches, focusing on observe, anticipate, and adapt. Utilizing remote sensing, developing state-of-the-art models, and implementing spatially explicit guidance are key strategies to ensure adaptive silvicultural actions in rapidly changing environments.
Article
Forestry
Raphael D. Chavardes, Lori D. Daniels, Jill E. Harvey, Gregory A. Greene, Helene Marcoux, Bianca N. Eskelson, Ze'ev Gedalof, Wesley Brookes, Rick Kubian, Jared D. Cochrane, John H. Nesbitt, Alexandra M. Pogue, Olivier Villemaire-Cote, Robert W. Gray, David W. Andison
Summary: Understanding the historical relationship between fires and climate in the Montane Cordillera Ecozone of Canada is crucial due to the projected increase in large fires caused by climate change. The study found that below-average annual precipitation and summer drought synchronized fires, while wet summers preceded years of high fire synchrony. After 1945, decreased fire occurrence was attributed to fire exclusion, suppression and climate variability, impacting the susceptibility of dry forests to synchronous fires. Global climate change is leading to longer fire seasons and increased drought, making wildfires more difficult to suppress, as seen in British Columbia's record-breaking fire seasons in 2017, 2018, and 2021.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2022)
Article
Agronomy
Sarah M. Smith-Tripp, Bianca N. I. Eskelson, Nicholas C. Coops, Naomi B. Schwartz
Summary: Disturbed forest canopies have significant impacts on microclimate, particularly in terms of temperature and moisture. Lower and more disturbed canopies lead to higher soil temperatures, while there is a weak negative relationship between canopy height and soil moisture. Additionally, summarizing canopy height at moderate resolution better explains temperature differences, which has important implications for producing gridded microclimate datasets in the future.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Forestry
Stella Britwum Acquah, Peter L. Marshall, Bianca N. I. Eskelson, Ignacio Barbeito
Summary: Understanding the spatial patterns and interactions of trees in forest stands is crucial for understanding forest development processes. In this study, we analyzed the temporal changes in tree spatial patterns in uneven-aged Douglas-fir dominated stands in British Columbia, Canada. Our results showed that unthinned plots had clustered spatial patterns, while plots with moderate and heavy thinning treatments had random or regular patterns. We also found that tree diameters were not spatially autocorrelated in thinned plots, but there was positive spatial correlation in unthinned plots. Dead trees were smaller in size and clustered at all spatial scales, and there was no spatial relationship between dead and surviving trees.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Forestry
Yudel L. Huberman, Bianca N. I. Eskelson
Summary: There is increasing interest in using mixed conifer-broadleaf stands to enhance forest diversity and productivity. This study investigated the effects of different densities of planted broadleaf trees on the performance of conifers, total stand productivity, and understory plant cover after 20 years. The results showed that conifer volume was significantly lower in most broadleaf treatments, primarily due to lower volumes of western hemlock and western redcedar. However, Douglas-fir volume was higher in the broadleaf treatments, although not significantly. Shrub cover was significantly higher in low and high alder treatments compared to the control.
CANADIAN JOURNAL OF FOREST RESEARCH
(2023)
Article
Forestry
Sushil Nepal, Bianca N. I. Eskelson, Martin W. Ritchie, Sarah E. Gergel
Summary: This study reconstructed the ecological conditions of historical forests in North America using forest inventory data from 1934. The analysis revealed spatial patterns in species dominance and vigor classes, and identified topographic and edaphic variables associated with these patterns.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Biodiversity Conservation
Aeryn Ng, Sarah E. Gergel, Bianca N. I. Eskelson
Summary: Inequality in urban greenspaces distribution is a global issue, with higher greenspaces in neighborhoods with higher socioeconomic status, but can also trigger allergenic responses causing negative costs. A study in Vancouver found that schools in higher income areas had more greenspaces and allergenic vegetation cover surrounding them.
ECOSYSTEMS AND PEOPLE
(2021)
