Article
Forestry
Yali Zhang, Sandeep Sharma, Manjit Bista, Mingshi Li
Summary: This study analyzed land cover and forest fragmentation trends in the Dhorpatan Hunting Reserve from 1993 to 2018. The results showed an increase in forest cover and a decrease in grasslands. The forest fragmentation situation was primarily affected by changes in forest area, with forest expansion being the dominant restoration process.
JOURNAL OF FORESTRY RESEARCH
(2022)
Article
Forestry
Shrabya Timsina, Lila Nath Sharma, Mark S. Ashton, Bishnu Hari Poudyal, Ian K. Nuberg, Srijana Baral, Edwin Cedamon, Sanjeeb Bir Bajracharya, Naya Sharma Paudel
Summary: In many developing countries, such as Nepal, public forest management tends to focus on either single-crop production or strict forest protection, disregarding the potential benefits of multipurpose management. This extreme approach can lead to degradation of forest ecosystems and hinder their ability to meet growing demands. Past narrow management outlooks have resulted in the loss of indigenous silvicultural practices and limited the development of new solutions to address current environmental concerns.
Article
Computer Science, Information Systems
Jing Sun, Suwit Ongsomwang
Summary: The study showed that land use and land cover changes due to urbanization in Hefei City have a significant impact on land surface temperature, with urban areas experiencing higher temperatures compared to non-urban areas.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2021)
Article
Ecology
Yisa Ginath Yuh, Wiktor Tracz, Damon Matthews, Sarah E. Turner
Summary: Machine learning (ML) models, including k-nearest neighbour (kNN), support vector machines (SVM), artificial neural networks (ANN), and random forests (RF), have been effectively applied to classify land use and land cover (LULC) types at various scales. However, their application in African tropical regions has been limited due to methodological challenges arising from the use of coarse-resolution satellite images. In this study, four ML algorithms were compared for LULC monitoring in northern Cameroon, and the random forests model showed the highest classification accuracy. Forest loss was observed in approximately 7% of the study area, with an expansion of croplands and built-up areas being the main factors. This research represents a novel application of ML approaches using coarse-resolution satellite images in an African tropical forest and savanna setting, providing important baseline data for policy development, conservation planning, and monitoring.
ECOLOGICAL INFORMATICS
(2023)
Article
Biodiversity Conservation
E. Collado, J. A. Bonet, J. G. Alday, J. Martinez de Aragon, S. de -Miguel
Summary: This study found that forest thinning intensities can have short-term effects on fungal communities in Mediterranean regions, particularly under heavy and light thinning intensities; climatic factors, especially the mean temperature of September and October, can influence the compositional response of fungi to forest thinning; however, forest thinning does not impact sporocarp species diversity (richness and evenness).
ECOLOGICAL INDICATORS
(2021)
Article
Forestry
Enric Vadell, Jesus Peman, Pieter Johannes Verkerk, Maitane Erdozain, Sergio De-Miguel
Summary: This study examines the development and trends of forest management practices in Spain since the mid-20th century, identifying challenges and decisions that may need to be reconsidered to promote multifunctionality in forestry.
FOREST ECOLOGY AND MANAGEMENT
(2022)
Article
Environmental Sciences
Bhagawat Rimal, Hamidreza Keshtkar, Nigel Stork, Sushila Rijal
Summary: The study highlights the increasing trend of forest area, both in the Lumbini Province of Nepal and globally. Scientific models predict a continued increase in forest cover in 2026 and 2036, with the support of policy, planning, and management factors.
Article
Forestry
Bradley D. Pinno, Kazi L. Hossain, Ted Gooding, Victor J. Lieffers
Summary: Although intensive silviculture could be justified in Alberta, it has not been implemented due to existing policies and ideologies. Intensive silviculture has the potential to increase commercial value by selecting good sites and thinning, but requires changes in attitude and policies.
Article
Environmental Sciences
Eleni Papadopoulou, Giorgos Mallinis, Sofia Siachalou, Nikos Koutsias, Athanasios C. Thanopoulos, Georgios Tsaklidis
Summary: This study aims to design, develop, and evaluate two deep learning architectures for agricultural land cover and crop type mapping. The results show that these architectures outperformed the traditional random forest algorithm in terms of accuracy. The study also highlights the importance of sampling strategy for handling dataset imbalance and spectral variability.
Review
Environmental Sciences
Daniel Escobar, Salim Belyazid, Stefano Manzoni
Summary: This article evaluates the feasibility of rewetting drained forested peatlands to restore their carbon sinks and explores how water table management affects greenhouse gas emissions using a literature review and causal loop diagrams. The results show that rewetting reduces greenhouse gas emissions from soils, but reports of carbon sinks in rewetted systems are scarce and CH4 emissions are often higher than in pristine peatlands. Long-term water table changes associated with rewetting impact various processes regulating greenhouse gas emissions. The study also proposes three phases of restoration following rewetting and concludes that while short-term gains in the greenhouse gas balance may be minimal, the long-term potential of restoring drained peatlands through rewetting remains promising.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Environmental Sciences
Pablo J. Ordonez, Kathy Baylis, Isabel Ramirez
Summary: More than half of Mexico's forests and about a third of the forests of the world are communally owned. Despite this, community forest management (CFM) is the least studied forest management policy, and existing studies have focused on the effects of CFM on deforestation.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Anni Vehola, Arttu Malkamaki, Anna-Kaisa Kosenius, Elias Hurmekoski, Anne Toppinen
Summary: Understanding landowners' willingness to act on climate change is crucial for effective climate policy. This study examines the factors that influence Finnish non-industrial private forest owners' preferences for different climate change mitigation strategies related to forests and wood usage. The results suggest that risk perception and political leaning play a significant role in determining support for various strategies, with higher risk perception and left-wing leaning with a university degree being associated with support for more disruptive strategies.
ENVIRONMENTAL SCIENCE & POLICY
(2022)
Article
Forestry
Olga Grigoreva, Elena Runova, Vera Savchenkova, Edward Hertz, Anna Voronova, Viktor Ivanov, Viktoria Shvetsova, Igor Grigorev, Mikhail Lavrov
Summary: Thinning in pine stands is a necessary and complex forestry activity, with varying effects on growth patterns and wood quality depending on the thinning technique used. Research results allow for optimizing management regimes in pine plantations, increasing thinning efficiency, and reducing labor intensity.
JOURNAL OF FORESTRY RESEARCH
(2022)
Article
Forestry
Umberto Di Salvatore, Maurizio Marchi, Paolo Cantiani
Summary: The study developed two equations to predict single-tree crown volumes for Pinus nigra plantations, based on an analysis of a database with 3578 trees. The fitted models were statistically significant, explaining 57.6% for crown radius at crown base and 87.1% for crown length. The power function model for calculating single-tree crown volumes showed varying levels of absolute errors for different parts of the crown.
ANNALS OF FOREST SCIENCE
(2021)
Article
Forestry
Benjamin Schram, Karen Potter-Witter, Emily Huff, Jagdish Poudel
Summary: Family forest owners have significant impact on the ecosystem services provided by forests. The study in Michigan on enrolled family forest owners shows that parcel characteristics can predict forest practices. It may be useful to use these data to understand the future management trajectories of private forests.
Article
Ecology
Whitney M. Woelmer, R. Quinn Thomas, Mary E. Lofton, Ryan P. McClure, Heather L. Wander, Cayelan C. Carey
Summary: Forecasts of ecological variables, particularly phytoplankton, are crucial for informing management and use of ecosystem services. This study examined the optimal model time step and time horizon for phytoplankton forecasts, as well as factors contributing to forecast uncertainty and scalability among sites. The results highlight the importance of matching the forecast model time step to the forecast horizon for improved accuracy.
ECOLOGICAL APPLICATIONS
(2022)
Review
Biodiversity Conservation
Mary E. Lofton, Dexter W. Howard, R. Quinn Thomas, Cayelan C. Carey
Summary: Near-term freshwater forecasts are urgently needed to mitigate freshwater risks and improve water quality management. Currently, freshwater forecasting mainly focuses on water quantity, while water quality forecasts are fewer and in the early stages of development. However, recent progress in forecasting methodology and end-user engagement suggests that near-term water quality forecasting is poised to make substantial advances.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Ecology
R. Quinn Thomas, Ryan P. McClure, Tadhg N. Moore, Whitney M. Woelmer, Carl Boettiger, Renato J. Figueiredo, Robert T. Hensley, Cayelan C. Carey
Summary: The standardized monitoring program of the US National Ecological Observatory Network (NEON) provides an unprecedented opportunity to compare ecosystem predictability. In this study, we developed a near-term, iterative water temperature forecasting system for all six NEON lakes in the conterminous US. Using a process-based hydrodynamic model updated with observations, we generated 1-day-ahead to 35-days-ahead forecasts. The forecast accuracy was positively associated with lake depth and water clarity, while negatively associated with fetch and catchment size.
FRONTIERS IN ECOLOGY AND THE ENVIRONMENT
(2023)
Editorial Material
Ecology
R. Quinn Thomas, Carl Boettiger, Cayelan C. Carey, Michael C. Dietze, Leah R. Johnson, Melissa A. Kenney, Jason S. McLachlan, Jody A. Peters, Eric R. Sokol, Jake F. Weltzin, Alyssa Willson, Whitney M. Woelmer
FRONTIERS IN ECOLOGY AND THE ENVIRONMENT
(2023)
Article
Biology
J. W. Smith Jr, L. R. Johnson, R. Q. Thomas
Summary: Hierarchical probability models are increasingly being used in environmental prediction and forecasting, with Bayesian approaches becoming popular. This study focuses on ecosystem models that can be treated as statistical state space models (SSMs). Using simulated data, the effects of changing the temporal resolution of observations and state processes on parameter estimates are examined. The study also introduces a method of tuning the time resolution of latent states to improve estimates.
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
(2023)
Article
Ecology
Alyssa M. Willson, Hayden Gallo, Jody A. Peters, Antoinette Abeyta, Nievita Bueno Watts, Cayelan C. Carey, Tadhg N. Moore, Georgia Smies, R. Quinn Thomas, Whitney M. Woelmer, Jason S. McLachlan
Summary: Conducting ecological research requires a diverse and quantitatively trained workforce. Understanding the current landscape of ecology and environmental sciences undergraduate curriculum allows for targeted interventions to improve educational opportunities. Ecological forecasting can contribute to restructuring the curriculum and enhancing inclusivity.
ECOLOGY AND EVOLUTION
(2023)
Article
Multidisciplinary Sciences
Jacob H. Wynne, Whitney Woelmer, Tadhg N. Moore, R. Quinn Thomas, Kathleen C. Weathers, Cayelan C. Carey
Summary: Freshwater ecosystems are at risk from global change, particularly in relation to lake thermal dynamics. Uncertainty in future lake conditions is influenced by climate model and lake model selection. A study of a dimictic lake in the USA found that surface water temperature and total ice duration were primarily affected by climate model selection uncertainty, while bottom water temperature and stratification duration were dominated by lake model selection uncertainty.
Article
Environmental Sciences
Alexandria G. G. Hounshell, Brenda M. M. D'Acunha, Adrienne Breef-Pilz, Mark S. S. Johnson, R. Quinn Thomas, Cayelan C. C. Carey
Summary: Small freshwater reservoirs play an important role in global GHG budgets, but quantifying their annual GHG fluxes is challenging due to their limited surface area. We deployed an EC system in a small reservoir in Virginia, USA and found that the reservoir is a significant source of CO2 and CH4 to the atmosphere, with substantial variability at different timescales. We identified several key environmental variables that drive GHG fluxes in the reservoir.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2023)
Article
Environmental Sciences
Christopher M. M. Clark, R. Quinn Thomas, Kevin J. J. Horn
Summary: Analyzing data from a tree inventory and growth for the contiguous US, researchers found that long-term nitrogen deposition may not continue to stimulate tree carbon storage. Changes in nitrogen availability can affect the ability of forest ecosystems to store carbon. Their analysis showed that the effect of nitrogen deposition on aboveground carbon varies among species and regions in the US. In the Northeastern US, the recent estimate of this effect is weaker than in the 1980s-90s, suggesting a weakening of the US forest carbon sink.
COMMUNICATIONS EARTH & ENVIRONMENT
(2023)
Article
Environmental Sciences
John W. Smith, R. Quinn Thomas, Leah R. Johnson
Summary: In this paper, a novel method for parameterizing Lognormal state space models using moment matching is proposed. The method enforces the positivity constraint, allows for arbitrary mean evolution and variance structure, and has a closed-form Markov transition density. Experimental results show that the method performs well under model misspecification and fixing the observation variance improves both estimation and forecasting performance. The method also outperforms its competitor in predicting leaf area index over a 151-day horizon.
ENVIRONMENTAL AND ECOLOGICAL STATISTICS
(2023)
Correction
Environmental Sciences
John W. Smith, R. Quinn Thomas, Leah R. Johnson
ENVIRONMENTAL AND ECOLOGICAL STATISTICS
(2023)
Article
Biodiversity Conservation
Christopher M. Clark, Jennifer Phelan, Jeremy Ash, John Buckley, James Cajka, Kevin Horn, R. Quinn Thomas, Robert D. Sabo
Summary: Climate change and nitrogen and sulfur deposition have significant impacts on forest demography. The study projects changes in forest composition based on future scenarios of temperature, precipitation, and deposition. Results show that the effects of climate change and deposition vary among species, with potential shifts in the abundance of 60 species declining and 20 species increasing. The study suggests that reducing deposition alone may not be sufficient to offset the impacts of climate change on forest composition.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Forestry
Rachel L. Hammer, John R. Seiler, John A. Peterson, Valerie A. Thomas
Summary: Accurately predicting soil respiration (R-s) is crucial due to its impact on forest ecosystem productivity. This study investigated the effects of soil temperature, moisture, and vegetation composition on R-s. The results showed that soil temperature and moisture explained 82% of the variation in R-s. Monthly R-s rates varied among vegetation types, with cinnamon fern plots having higher rates in summer and hemlock plots having higher rates in dormant months.
Article
Ecology
Whitney M. Woelmer, Tadhg N. Moore, Mary E. Lofton, R. Quinn Thomas, Cayelan C. Carey
Summary: This study developed a teaching module to introduce ecological forecasting and uncertainty communication to undergraduate students. By embedding forecasting activities in an R Shiny application, students were able to actively engage in learning data science, ecological modeling, and forecasting concepts without advanced computational or programming skills.
Proceedings Paper
Geography, Physical
K. F. Huemmrich, P. E. K. Campbell, D. J. Harding, K. J. Ranson, R. Wynne, V Thomas, E. M. Middleton
Summary: This study successfully developed and tested multiple algorithms using data from the DLR Earth Sensing Imaging Spectrometer (DESIS) to remotely retrieve ecosystem productivity based on spectral reflectance. The algorithms demonstrated good accuracy across different locations, years, and times of observation.
1ST DESIS USER WORKSHOP - IMAGING SPECTROMETER SPACE MISSION, CALIBRATION AND VALIDATION, APPLICATIONS, METHODS
(2022)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)