Results 101 to 110 of about 9,630 (234)

Structured machine learning modeling to support conservation of deep‐sea benthic biodiversity

Conservation Biology, EarlyView.
Abstract Biodiversity monitoring programs need to deliver accurate, timely, and actionable predictions. To establish a predictive monitoring program for deep‐sea benthos of the Santos Basin, Brazil, we developed a two‐stage structured model that allowed comparison of biodiversity predictions obtained from environmental simulations (2M‐Sim).
Gustavo Fonseca, Danilo C. Vieira, Juliane C. Carneiro, Renato S. Carreira, Milena Ceccopieri, Thais N. Corbisier, Adriana Galindo Dalto, Alberto G. Figueiredo Jr., Fabiane Gallucci, Paula Gheller, Simone Brito de Jesus, Helena Passeri Lavrado, Letícia Lazzari, Eduardo Hilzendeger Marcon, Daniel Leite Moreira, Rafael Bendayan de Moura, Ellen Pape, Ana Cláudia Aoki Santarosa, João Regis dos Santos Filho, Silvia Helena de Mello e Sousa, Thaisa Marques Vicente, Luciana Erika Yaginuma, Cinthia Yamashita, Wandrey Watanabe   +23 more
wiley   +1 more source

Reconnaissance‐Scale Methods for the Identification of Groundwater Discharge to Streams

Groundwater Monitoring &Remediation, EarlyView.
Abstract Identifying groundwater discharge locations is critical for understanding and monitoring groundwater contributions to streams in terms of water quantity and quality. Streams and rivers are under increasing strain from factors, including increased urbanization, agricultural land use, groundwater extraction, and climate change, which can alter ...
Corey M. Zanatta, Andrew J. Wiebe, David L. Rudolph   +2 more
wiley   +1 more source

Computationally Efficient Ranking of Sampling Locations by Redundancy in Groundwater Monitoring Networks

Groundwater Monitoring &Remediation, EarlyView.
Abstract The long‐term and frequent sampling of groundwater monitoring networks is common practice for monitoring the concentrations of constituents of potential concern (CoPC) over space and time. Sampling can be a costly and time‐intensive process that also incurs health and safety risks. A redundancy‐based ranking of candidate sampling locations can
Peter Radvanyi, Claire Miller, Craig Alexander, Marnie Low, Luc Rock, Wayne Jones   +5 more
wiley   +1 more source

On Spatial Point Processes With Composition‐Valued Marks

International Statistical Review, EarlyView.
Summary Methods for marked spatial point processes with scalar marks have seen extensive development in recent years. While the impressive progress in data collection and storage capacities has yielded an immense increase in spatial point process data with highly challenging non‐scalar marks, methods for their analysis are not equally well developed ...
Matthias Eckardt, Mari Myllymäki, Sonja Greven   +2 more
wiley   +1 more source

G‐optimal grid designs for kriging models

Scandinavian Journal of Statistics
AbstractThis work is focused on finding G‐optimal designs theoretically for kriging models with two‐dimensional inputs and separable exponential covariance structures. For design comparison, the notion of evenness of two‐dimensional grid designs is developed.
Subhadra Dasgupta, Siuli Mukhopadhyay, Jonathan Keith   +2 more
openaire   +3 more sources

A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces

International Statistical Review, EarlyView.
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri, Bernardo Nipoti, Emilio Porcu, Philip White   +3 more
wiley   +1 more source

How Accurately Do Species Distribution Models Predict the Expansion of Invasive Insects, and Does Climate Data Choice Matter? Insights From the Invasion of Dryocosmus kuriphilus

Journal of Applied Entomology, EarlyView.
ABSTRACT Species distribution models (SDMs) are widely used to predict the spread of invasive species, yet their accuracy over time and the influence of climate data resolution remain unclear. Here, we examine the capacity of SDMs to predict the distribution and short‐term expansion of the invasive gall wasp Dryocosmus kuriphilus, and compare the ...
José Carlos Pérez‐Girón, Fernando Castedo‐Dorado, María Josefa Lombardero, Pedro Álvarez‐Álvarez   +3 more
wiley   +1 more source

Sediment transport and depositional hydrodynamics on the eastern Korean continental margin revealed by surface sediment granulometry

Sedimentology, EarlyView.
ABSTRACT Terrigenous sediments are transported from coastal areas and shelves to deeper continental margins by multiple processes. Understanding these processes is critical for evaluating the ecological impacts of fine‐grained sediment deposition and predicting future changes in sediment dispersal under rapid climate change.
Gyu Tae Sim, Jang Jun Bahk, Haedo Baek, Jun Ho Jang, In Kwon Um, Dong Eun Lee   +5 more
wiley   +1 more source

Mapping forest aboveground carbon stock of combined stratified sampling and RFRK model with mean annual temperature and precipitation

Scientific Reports
Accurately estimating forest aboveground carbon stock (ACS) is essential for achieving carbon neutrality. At present, most non-parametric models still have errors in estimating carbon stock in regions.
Min Peng, Mingrui Xu, Jialong Zhang, Bo Qiu, Chenkai Teng, Chaoqing Chen   +5 more
doaj   +1 more source

DAMAGE IDENTIFICATION METHOD BASED KRIGING MODEL

Jixie qiangdu, 2020
To improve damage identification efficiency,a damage identification method based on Kriging model was proposed. Sample points were chosen based on Latin hypercube sampling,and Kriging model was built using acceleration frequency response functions ...
MA JingJing, YIN Hong, PENG ZhenRui, DONG KangLi   +3 more
doaj