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Land Use Changes, Disturbances, and Their Interactions on Future Forest Aboveground Biomass Dynamics in the Northern US

Wu Ma, Grant M. Domke, Christopher W. Woodall, Anthony W. D'Amato
2019 Forests  
Total forest AGB predictions were based on simulations of diameter growth, mortality, and recruitment using matrix growth models under varying levels of LUC and disturbance severity (low (L), medium (M  ...  Here we quantified how these activities and events may influence future aboveground biomass (AGB) dynamics in forests using national forest inventory (NFI) and Landsat time series data in the Northern  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/f10070606 fatcat:53gcajni6rb7tbdtnoikeotej4

Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields

Ephrem Habyarimana, Faheem S. Baloch, Jie Zhang
2021 PLoS ONE  
This work aimed therefore at closing this gap by evaluating the performance of machine learning modelling of in-season sorghum biomass yields based on Sentinel-2-derived fAPAR and simpler high-throughput  ...  Bayesian ridge regression showed good cross-validated performance, and high reliability (R2 = 35%) and low bias (mean absolute prediction error, MAPE = 0.4%) during the validation step.  ...  To avoid overfitting, the "one standard error" rule of Breiman et al.  ... 
doi:10.1371/journal.pone.0249136 pmid:33765103 fatcat:jv5q3osttfamxf3zet5du62uee

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

Dengsheng Lu, Qi Chen, Guangxing Wang, Lijuan Liu, Guiying Li, Emilio Moran
2014 International Journal of Digital Earth  
Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades.  ...  Additionally, we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure.  ...  Cycling in Forest Ecosystems and Carbon Sequestration at Zhejiang A&F University, and the Center for Global Change and Earth Observations at Michigan State University.  ... 
doi:10.1080/17538947.2014.990526 fatcat:bkc3syq3pfgzxkawig2pog7i3y

Spatial validation reveals poor predictive performance of large-scale ecological mapping models

Pierre Ploton, Frédéric Mortier, Maxime Réjou-Méchain, Nicolas Barbier, Nicolas Picard, Vivien Rossi, Carsten Dormann, Guillaume Cornu, Gaëlle Viennois, Nicolas Bayol, Alexei Lyapustin, Sylvie Gourlet-Fleury (+1 others)
2020 Nature Communications  
Mapping aboveground forest biomass is central for assessing the global carbon balance.  ...  A standard nonspatial validation method suggests that the model predicts more than half of the forest biomass variation, while spatial validation methods accounting for SAC reveal quasi-null predictive  ...  Acknowledgements P.P. was supported by a postdoctoral grant from the 3DForMod project. 3DForMod was funded in the framework of the ERA-NET FACCE ERA-GAS (ANR-17-EGAS-0002-01), which has received funding  ... 
doi:10.1038/s41467-020-18321-y pmid:32917875 fatcat:a3uihmrqevhvlkpd4kbtktutia

A Tale of Two "Forests": Random Forest Machine Learning Aids Tropical Forest Carbon Mapping

Joseph Mascaro, Gregory P. Asner, David E. Knapp, Ty Kennedy-Bowdoin, Roberta E. Martin, Christopher Anderson, Mark Higgins, K. Dana Chadwick, Ben Bond-Lamberty
2014 PLoS ONE  
., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved  ...  In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area,  ...  From the large extent of the input data, we performed all upscaling on an area bounding the entire Marañ on Watershed to avoid edge effects for our focal area of 16 million hectares. Stratification.  ... 
doi:10.1371/journal.pone.0085993 pmid:24489686 pmcid:PMC3904849 fatcat:mouqoiahg5h4fkptnwodclezii

Integration of Process-based Soil Respiration Models with Whole-Ecosystem CO2 Measurements

J. M. Zobitz, D. J. P. Moore, W. J. Sacks, R. K. Monson, D. R. Bowling, D. S. Schimel
2008 Ecosystems  
example, nitrogen) on the microbe biomass.  ...  We integrated soil models with an established ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to investigate the influence of soil processes on modelled values  ...  Fundamental to the approach of SIPNET is the introduction of additional complexity only when needed to avoid overfitting data.  ... 
doi:10.1007/s10021-007-9120-1 fatcat:53i64zl3ivhktcifjywblksiqm

Characterizing forest canopy structure with lidar composite metrics and machine learning

Kaiguang Zhao, Sorin Popescu, Xuelian Meng, Yong Pang, Muge Agca
2011 Remote Sensing of Environment  
Using coincident lidar and field data over an Eastern Texas forest in USA, we conducted a case study to demonstrate the ubiquitous power of the lidar composite metrics in predicting multiple forest attributes  ...  , 5.34 (8.51) m 2 /ha for basal area, 21.4 (40.5) Mg/ha for aboveground biomass, 6.54 (9.88) Mg/ha for belowground biomass, 0.75 (2.76) m for canopy base height, 2.2 (2.76) m for canopy ceiling height,  ...  Duncan Lutes at the Rocky Mountain Research Station of US Forest service for their help in instructing on the use of FuelCalc.  ... 
doi:10.1016/j.rse.2011.04.001 fatcat:h5rr3urjnzhkxbdztasnhnfs64

Wood CO2efflux in a primary tropical rain forest

MOLLY A. CAVALERI, STEVEN F. OBERBAUER, MICHAEL G. RYAN
2006 Global Change Biology  
Small diameter wood, only 15% of total woody biomass, accounted for 70% of total woody tissue CO 2 efflux from the forest; while lianas, only 3% of total woody biomass, contributed one-fourth of the total  ...  in a primary tropical rain forest in Costa Rica.  ...  Acknowledgements We thank the Organization of Tropical Studies (OTS) and the Ministry of the Environment and Energy of Costa Rica (MINAE) for providing logistical support.  ... 
doi:10.1111/j.1365-2486.2006.01269.x fatcat:ak2stpywk5gepe237vhrnz3mp4

Retrieval of aboveground crop nitrogen content with a hybrid machine learning method

Katja Berger, Jochem Verrelst, Jean-Baptiste Féret, Tobias Hank, Matthias Wocher, Wolfram Mauser, Gustau Camps-Valls
2020 International Journal of Applied Earth Observation and Geoinformation  
We conclude that GP algorithms, and in particular the heteroscedastic GP, should be implemented for global agricultural monitoring of aboveground N from future imaging spectroscopy data.  ...  Moreover, most studies solely relied on the correlation of chlorophyll content with nitrogen, and thus neglected the fact that most N is bound in proteins.  ...  GP-BAT includes an iterative backward greedy algorithm, in which the impact of the inputs on the prediction error is evaluated in the context or absence of the other predictors.  ... 
doi:10.1016/j.jag.2020.102174 fatcat:ycasxkxp2neifjy6aucl4tvqp4

When tree rings go global: Challenges and opportunities for retro- and prospective insight

Flurin Babst, Paul Bodesheim, Noah Charney, Andrew D. Friend, Martin P. Girardin, Stefan Klesse, David J.P. Moore, Kristina Seftigen, Jesper Björklund, Olivier Bouriaud, Andria Dawson, R. Justin DeRose (+11 others)
2018 Quaternary Science Reviews  
The demand for large-scale and long-term information on tree growth is increasing rapidly as environmental change research strives to quantify and forecast the impacts of continued warming on forest ecosystems  ...  A series of challenges related to how, where, and when samples have been collected is complicating the transition of tree rings from a local to a global resource on the question of tree growth.  ...  An example is the scaling of forest biomass increment from a sample of 0.1-ha forest plots to a 10,000-ha landscape.  ... 
doi:10.1016/j.quascirev.2018.07.009 fatcat:j5xyrlogjbd6lioyknvs6bpahm

A combinatorial analysis using observational data identifies species that govern ecosystem functioning

Benoît Jaillard, Philippe Deleporte, Michel Loreau, Cyrille Violle, RunGuo Zang
2018 PLoS ONE  
We evaluate the quality of each species clustering, that is its ability to predict an ecosystem function, by the coefficient of determination of the ecosystem classification.  ...  Clustering species in functional groups generates a classification of ecosystems based on their assembly motif.  ...  Acknowledgments The authors gratefully thank Dr Silke Langenheder and the University of Minnesota for having put at their disposal the datasets discussed in this paper.  ... 
doi:10.1371/journal.pone.0201135 pmid:30067797 pmcid:PMC6070253 fatcat:dhb27xglkvdk7m743tmw6vuzam

Forest restoration: Expanding agriculture

Ruth Delzeit, Julia Pongratz, Julia M. Schneider, Franziska Schuenemann, Wolfram Mauser, Florian Zabel, Jennifer Sills
2019 Science  
All authors read and provided feedback on the draft manuscript. Competing interests: The authors declare that they have no competing interests.  ...  Data and materials availability: All data, explanations of calculations, and references to literature-derived values are presented in Table 1 .  ...  Our model predicts the expected optimal tree cover from a combination of 10 environmental variables that were selected through a variable selection procedure to avoid overfitting issues.  ... 
doi:10.1126/science.aaz0705 fatcat:qnw5h6v3vzhftefribro43j57q

Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

C. L. Shope, G. R. Maharjan, J. Tenhunen, B. Seo, K. Kim, J. Riley, S. Arnhold, T. Koellner, Y. S. Ok, S. Peiffer, B. Kim, J.-H. Park (+1 others)
2014 Hydrology and Earth System Sciences  
Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially  ...  of the hydroecological impact.  ...  This manuscript was significantly improved through the critical reviews of M. Volk and K. Bieger.  ... 
doi:10.5194/hess-18-539-2014 fatcat:utixphui2vgshpdb4f5r57eugy

Model-data synthesis of diurnal and seasonal CO2 fluxes at Niwot Ridge, Colorado

WILLIAM J. SACKS, DAVID S. SCHIMEL, RUSSELL K. MONSON, BOBBY H. BRASWELL
2006 Global Change Biology  
In this study, we used a model-data synthesis approach with the Simplified PnET (SIPNET) flux model to extract process-level information from 5 years of eddy covariance data at an evergreen forest in the  ...  in the summer and winter, possibly because of the existence of distinct microbial communities at these two times.  ...  When performing a parameter estimation, the model's dimensionality should be carefully assessed relative to the dimensionality in the data to avoid overfitting.  ... 
doi:10.1111/j.1365-2486.2005.01059.x fatcat:wwdlaiocd5f5lo77bjxo5akxj4

Terrestrial animals Terrestrial animals [chapter]

Timothy J. Bradley
2008 Animal Osmoregulation  
increasing function of aboveground primary production, and in a subsequent review of 22 aquatic ecosystems, Cyr and Pace (1993) found the herbivore biomass of watery habitats also increases in response  ...  The results of this exercise were then compared with the output of an individualbased spatially explicit model developed -to investigate impacts of habitat availability on the evolution of dispersal in  ... 
doi:10.1093/acprof:oso/9780198569961.003.0008 fatcat:tus6tlb6znhsloj6sxtcfetqsi
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