Results 61 to 70 of about 4,738 (165)
Diversity and Distributions, Volume 32, Issue 6, June 2026.ABSTRACT Aim This study aimed to test the effectiveness of a hierarchical, spatially explicit, Bayesian modelling framework combining Integrated Nested Laplace Approximation (INLA) with Stochastic Partial Differential Equation (SPDE) as an alternative to traditional Species Distribution Models (SDMs), particularly in cases where standard assumptions ...
Marco Gargano +8 more
wiley +1 more source
BMC Infectious Diseases, 2019 Background São José do Rio Preto is one of the cities of the state of São Paulo, Brazil, that is hyperendemic for dengue, with the presence of the four dengue serotypes. Objectives: to calculate dengue seroprevalence in a neighbourhood of São José do Rio
Francisco Chiaravalloti-Neto +14 more
doaj +1 more source
Ecosphere, Volume 17, Issue 5, May 2026.Abstract Urban areas alter the timings (phenologies) of seasonal processes for plants and animals, yet the effects on bird migration, particularly pre‐breeding migration, are not well understood. Higher temperatures, higher levels of artificial light at night, and earlier vegetation emergence in urban areas can advance spring seasonal processes ...
Carrie Ann Adams +4 more
wiley +1 more source
Fisheries Oceanography, Volume 35, Issue 3, Page 445-461, May 2026.ABSTRACT Lepidocybium flavobrunneum [Smith, 1843], commonly known as escolar, is a large pelagic species, important for global and local fisheries, particularly in the southwestern South Atlantic Ocean (SWAO), where it constitutes a significant portion of the catch.
Lucas Rodrigues +15 more
wiley +1 more source
Environmetrics, Volume 37, Issue 3, April 2026.ABSTRACT Holothurian populations in the Mediterranean are relatively understudied, with limited knowledge of their spatial distribution, habitat preferences, and ecological dynamics, making their monitoring a key challenge for ecosystem assessment and sustainable management.
Daniele Poggio +6 more
wiley +1 more source
Causal Inference for Geostatistical Data Using an INLA‐based Spatial Propensity Score
Environmetrics, Volume 37, Issue 3, April 2026.ABSTRACT In this paper, we propose a Bayesian approach for spatial causal inference based on combining spatial propensity scoring with Integrated Nested Laplace Approximation. The method models both local and spillover exposure effects via multiple likelihoods and treats counterfactuals as missing data, allowing inference also for non‐Gaussian outcomes.
Chiara Di Maria +3 more
wiley +1 more source
Spatial data fusion adjusting for preferential sampling using INLA and SPDE [PDF]
, 2023 Spatially misaligned data can be fused by using a Bayesian melding model that assumes that underlying all observations there is a spatially continuous Gaussian random field process.
Moraga, Paula +2 more
core +1 more source
Coarse‐to‐Fine Spatial Modeling: A Scalable, Machine‐Learning‐Compatible Framework
Geographical Analysis, Volume 58, Issue 2, April 2026.ABSTRACT This study proposes coarse‐to‐fine spatial modeling (CFSM) as a scalable and machine learning‐compatible alternative to conventional spatial process models. Unlike conventional covariance‐based spatial models, CFSM represents spatial processes using a multiscale ensemble of local models.
Daisuke Murakami +5 more
wiley +1 more source
Coherent Disaggregation and Uncertainty Quantification for Spatially Misaligned Data
Environmetrics, Volume 37, Issue 2, March 2026.ABSTRACT Spatial misalignment arises when datasets are aggregated or collected at different spatial scales, leading to information loss. We develop a Bayesian disaggregation framework that links misaligned data to a continuous‐domain model through an iteratively linearised integration scheme implemented with the Integrated Nested Laplace Approximation (
Man Ho Suen, Mark Naylor, Finn Lindgren
wiley +1 more source