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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact

Science: general issues --- Ecological science, the Biosphere --- biodiversity --- Antarctica --- global change --- eco-evo --- spatial scale --- temporal scale

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A groundbreaking approach to scale and scaling in ecological theory and practiceScale is one of the most important concepts in ecology, yet researchers often find it difficult to find ecological systems that lend themselves to its study. Scaling in Ecology with a Model System synthesizes nearly three decades of research on the ecology of Sarracenia purpurea-the northern pitcher plant-showing how this carnivorous plant and its associated food web of microbes and macrobes can inform the challenging question of scaling in ecology.Drawing on a wealth of findings from their pioneering lab and field experiments, Aaron Ellison and Nicholas Gotelli reveal how the Sarracenia microecosystem has emerged as a model system for experimental ecology. Ellison and Gotelli examine Sarracenia at a hierarchy of spatial scales-individual pitchers within plants, plants within bogs, and bogs within landscapes-and demonstrate how pitcher plants can serve as replicate miniature ecosystems that can be studied in wetlands throughout the United States and Canada. They show how research on the Sarracenia microecosystem proceeds much more rapidly than studies of larger, more slowly changing ecosystems such as forests, grasslands, lakes, or streams, which are more difficult to replicate and experimentally manipulate.Scaling in Ecology with a Model System offers new insights into ecophysiology and stoichiometry, demography, extinction risk and species distribution models, food webs and trophic dynamics, and tipping points and regime shifts.

Biotic communities --- Botanical chemistry. --- Statistical methods. --- Alternative stable state. --- Aristolochia. --- Assembly rules. --- Author. --- Autocorrelation. --- Bacteria. --- Biodiversity. --- Biogeography. --- Biological interaction. --- Biomass (ecology). --- Bovine serum albumin. --- Bromeliaceae. --- Carnivorous plant. --- Conditional probability. --- Copyright. --- Density dependence. --- Detritus. --- Drosera. --- Ecological niche. --- Ecological succession. --- Ecology. --- Ecosystem. --- Environment variable. --- Estimation. --- Evolution. --- Field experiment. --- Food chain. --- Food web. --- Forecasting. --- Herbivore. --- Histogram. --- Hysteresis. --- INaturalist. --- Inference. --- Inquiline. --- Insect. --- Invertebrate. --- Keystone species. --- Larva. --- Markov chain. --- Measurement. --- Metabolism. --- Microecosystem. --- Micronutrient. --- Microorganism. --- Model organism. --- Negative feedback. --- Nepenthes. --- Nitrogen. --- Null hypothesis. --- Nutrient. --- Obligate. --- Observational error. --- Organism. --- Parameter space. --- Peptide. --- Perennial plant. --- Phenotype. --- Phenotypic plasticity. --- Photosynthesis. --- Pitcher plant. --- Plant morphology. --- Pollination. --- Population decline. --- Population dynamics. --- Population growth. --- Population size. --- Population vector. --- Predation. --- Prediction. --- Princeton University Press. --- Probability. --- Proportionality (mathematics). --- Protein. --- Protozoa. --- Regime shift. --- Rotifer. --- Sarracenia purpurea. --- Sarracenia. --- Sarraceniaceae. --- Shrub. --- Soil. --- Spatial scale. --- Species distribution. --- Sphagnum. --- Spreadsheet. --- State variable. --- Stochastic simulation. --- Stoichiometry. --- Taxon. --- Taxonomy (biology). --- Time series. --- Trade-off. --- Trophic level. --- Uncertainty. --- Vegetation. --- Weather forecasting. --- Weather station. --- Wetland. --- Wyeomyia smithii.

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Geomorphometry is the science of quantitative terrain characterization and analysis, and has traditionally focused on the investigation of terrestrial and planetary landscapes. However, applications of marine geomorphometry have now moved beyond the simple adoption of techniques developed for terrestrial studies, driven by the rise in the acquisition of high-resolution seafloor data and by the availability of user-friendly spatial analytical tools. Considering that the seafloor represents 71% of the surface of our planet, this is an important step towards understanding the Earth in its entirety.This volume is the first one dedicated to marine applications of geomorphometry. It showcases studies addressing the five steps of geomorphometry: sampling a surface (e.g., the seafloor), generating a Digital Terrain Model (DTM) from samples, preprocessing the DTM for subsequent analyses (e.g., correcting for errors and artifacts), deriving terrain attributes and/or extracting terrain features from the DTM, and using and explaining those terrain attributes and features in a given context. Throughout these studies, authors address a range of challenges and issues associated with applying geomorphometric techniques to the complex marine environment, including issues related to spatial scale, data quality, and linking seafloor topography with physical, geological, biological, and ecological processes. As marine geomorphometry becomes increasingly recognized as a sub-discipline of geomorphometry, this volume brings together a collection of research articles that reflect the types of studies that are helping to chart the course for the future of marine geomorphometry.

geomorphology --- simulation --- accuracy --- spatial scale --- marine geomorphology --- surface roughness --- forage fish --- satellite imagery --- thalwegs --- digital elevation models (DEMs) --- Seabed 2030 --- Pacific sand lance --- Acoustic applications --- python --- Nippon Foundation/GEBCO --- Oceanic Shoals Australian Marine Park --- submarine topography --- multi beam echosounder --- sedimentation --- bedforms --- carbonate banks --- polychaete --- cold-water coral --- multiscale --- automated-mapping --- semi-automated mapping --- sediment habitats --- Atlantic Ocean --- Northwestern Australia --- random forest --- benthic habitat mapping --- paleoclimate --- submerged glacial bedforms --- seafloor --- currents --- Cenomanian–Turonian --- Multibeam bathymetry --- geomorphometry --- ArcGIS --- filter --- seabed mapping --- coral reefs --- eastern Brazilian shelf --- digital terrain analysis --- multibeam spatial resolution --- multibeam --- multibeam sonar --- Timor Sea --- seafloor geomorphometry --- shelf-slope-rise --- terrain analysis --- seafloor mapping technologies --- spatial analysis --- Canary Basin --- paleobathymetry --- Bonaparte Basin --- pockmarks --- benthic habitats --- Malin Basin --- geographic object-based image analysis --- seafloor mapping standards and protocols --- GIS --- Bering Sea --- object segmentation --- Barents Sea --- bathymetry --- carbonate mound --- underwater acoustics --- integration artefacts --- multibeam echosounder --- domes --- global bathymetry --- Random Forests --- North Sea --- spatial prediction --- Glaciated Margin --- marine geology --- image segmentation --- shelf morphology --- Alaska --- paleoceanography --- confidence --- swath geometry --- volcanoes --- deglaciation --- Cretaceous --- DEM --- habitat mapping --- marine remote sensing --- reconstruction --- acoustic-seismic profiling --- canyons

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Water resources are the most valuable resources of sustainable socio-economic development, which is significantly affected by climate change and human activities. Water resources assessment is an urgent need for implementation of the perfect water resources management, but it is difficult to accurately evaluate the quantity and quality of water resources, especially in arid regions and high-altitude regions with sparse gauged data. This book hosts 24 papers devoted to remote sensing in hydrology and water resources management, which summarizes the recent advancement in remote sensing technology for hydrology analysis such as satellite remote sensing for water resources management, water quality monitoring and evaluation using remote sensing data, remote sensing for detecting the global impact of climate extremes, the use of remote sensing data for improved calibration of hydrological models, and so on. In general, the book will contribute to promote the application of remote sensing technology in water resources.

Research & information: general --- precipitation datasets --- evaluation --- spatial scale --- temporal scale --- climate --- Yellow River Basin --- data assimilation --- WRF --- WRFDA --- 3DVar --- water levels --- surface areas --- volume variations --- hypsometry --- bathymetry --- lakes --- reservoirs --- remote sensing --- DAHITI --- modified strahler approach --- airborne LiDAR --- DEM --- flood inundation --- flood map --- flood model --- LiDAR --- terrestrial LiDAR --- evapotranspiration --- variability --- uncertainty --- unmanned aerial system --- sUAS --- multispectral --- viticulture --- water resources management --- California --- lake --- Tibetan Plateau --- hydrological changes --- water balance --- Chindwin basin --- hydrological modelling --- multi-variable calibration --- satellite-based rainfall product --- TRMM --- temporal resolution --- rainfall erosivity --- combined approach --- multi-objective optimization --- modeling uncertainty --- model constraint --- SWAT --- semiarid area --- hydrological variations --- normalized difference vegetation index --- total water storage change --- groundwater change --- extreme precipitation --- estimation --- TMPA 3B42-V7 --- regional frequency analysis --- China --- satellite datasets --- accuracy evaluation --- hydrological applicability --- Bosten Lake Basin --- actual evapotranspiration --- available water resources --- climate change --- vegetation greening --- VIP-RS model --- Lancang-Mekong river basin --- MSWEP --- AgMERRA --- APHRODITE --- CHIRPS --- PERSIANN --- error correction --- agricultural water management --- crop water consumption --- remote sensing model --- evapotranspiration allocation --- inland water --- IWCT --- Tianjin --- Landsat data --- Tarim River Basin --- desert-oasis ecotone --- land-use change --- CA-Markov model --- remote sensing in hydrology --- precipitation --- performance evaluation --- GPM --- Poyang Lake --- Yangtze River --- assimilation --- nonparametric modeling --- multi-source --- n/a --- landscape pattern --- spatiotemporal changes --- influencing factors --- watershed --- China SE --- satellite data --- LUE-GPP --- SPEI --- copula function --- conditional probability --- soil moisture --- neural network --- downscaling --- microwave data --- MODIS data

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Quantitative models are crucial to almost every area of ecosystem science. They provide a logical structure that guides and informs empirical observations of ecosystem processes. They play a particularly crucial role in synthesizing and integrating our understanding of the immense diversity of ecosystem structure and function. Increasingly, models are being called on to predict the effects of human actions on natural ecosystems. Despite the widespread use of models, there exists intense debate within the field over a wide range of practical and philosophical issues pertaining to quantitative modeling. This book--which grew out of a gathering of leading experts at the ninth Cary Conference--explores those issues. The book opens with an overview of the status and role of modeling in ecosystem science, including perspectives on the long-running debate over the appropriate level of complexity in models. This is followed by eight chapters that address the critical issue of evaluating ecosystem models, including methods of addressing uncertainty. Next come several case studies of the role of models in environmental policy and management. A section on the future of modeling in ecosystem science focuses on increasing the use of modeling in undergraduate education and the modeling skills of professionals within the field. The benefits and limitations of predictive (versus observational) models are also considered in detail. Written by stellar contributors, this book grants access to the state of the art and science of ecosystem modeling.

Ecology --- Mathematical models. --- 3D modeling. --- Accuracy and precision. --- Adaptive management. --- Addition. --- Agriculture. --- Algorithm. --- Bayesian inference. --- Bayesian. --- Biodiversity. --- Biogeochemical cycle. --- Biogeochemistry. --- Biology. --- Biomass (ecology). --- Calculation. --- Calibration. --- Carbon cycle. --- Case study. --- Chlorophyll. --- Climate change. --- Climate. --- Computer simulation. --- Conceptual model. --- Curriculum. --- Data set. --- Decision-making. --- Differential equation. --- Ecological Society of America. --- Ecological forecasting. --- Ecology. --- Ecosystem ecology. --- Ecosystem management. --- Ecosystem model. --- Ecosystem. --- Empirical relationship. --- Environmental issue. --- Estimation theory. --- Estimation. --- Eutrophication. --- Experiment. --- Fertilizer. --- Food web. --- Forecasting. --- General circulation model. --- Global warming. --- Implementation. --- Inference. --- Initial condition. --- Institute of Ecosystem Studies. --- Learning. --- Likelihood function. --- Mass balance. --- Mathematics. --- Measurement. --- Monte Carlo method. --- National Science Foundation. --- Nitrogen cycle. --- Nitrogen. --- Nutrient. --- Organism. --- Parameter. --- Parametrization. --- Phytoplankton. --- Predation. --- Predictability. --- Prediction. --- Predictive modelling. --- Predictive power. --- Primary production. --- Probability. --- Propagation of uncertainty. --- Proportion (architecture). --- Quantity. --- Regression analysis. --- Remote sensing. --- Requirement. --- Result. --- Risk assessment. --- Scientific method. --- Scientist. --- Sensitivity analysis. --- Simulation. --- Soil organic matter. --- Soil. --- Spatial scale. --- State variable. --- Statistic. --- Statistical hypothesis testing. --- Statistics. --- Suggestion. --- Time series. --- Trade-off. --- Trophic level. --- Uncertainty analysis. --- Uncertainty. --- Variable (mathematics). --- Vegetation. --- Water column. --- Water quality. --- Weather forecasting. --- Zooplankton.