Andrew O Finley

Latest

• Addressing data integration challenges to link ecological processes across scales
• Working across space and time: nonstationarity in ecological research and application
• R package for Nearest Neighbor Gaussian Process models
• A case study competition among methods for analyzing large spatial data
• Characterizing functional relationships between technophony and biophony: A western New York soundscape case study
• Conjugate Nearest Neighbor Gaussian Process Models for Efficient Statistical Interpolation of Large Spatial Data
• EcoMem: An R package for quantifying ecological memory
• Efficient algorithms for Bayesian nearest neighbor Gaussian processes
• Assessing impact of exogenous features on biotic phenomena in the presence of strong spatial dependence: A lake sturgeon case study in natural stream settings
• Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations
• Regional-based mitigation to reduce wildlife--vehicle collisions
• Remote sensing to reduce the effects of spatial autocorrelation on design-based inference for forest inventory using systematic samples
• Spatial Factor Models for High-Dimensional and Large Spatial Data: An Application in Forest Variable Mapping
• A model-based approach to wildland fire reconstruction using sediment charcoal records
• Approaches for advancing scientific understanding of macrosystems
• Hierarchical Bayesian models for small area estimation of county-level private forest landowner population
• Joint hierarchical models for sparsely sampled high-dimensional LiDAR and forest variables
• Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics
• Evaluation of the USDA Forest Service National Woodland Owner Survey estimators for private forest area and landowners: a case study of Montana
• Hierarchical nearest-neighbor Gaussian process models for large geostatistical datasets
• Modeling forest biomass and growth: Coupling long-term inventory and LiDAR data
• Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis
• Observation-based blended projections from ensembles of regional climate models
• On nearest-neighbor Gaussian process models for massive spatial data
• Predicting tree biomass growth in the temperate--boreal ecotone: Is tree size, age, competition, or climate response most important?
• Seedling survival responses to conspecific density, soil nutrients, and irradiance vary with age in a tropical forest
• Spatial variation in nutrient and water color effects on lake chlorophyll at macroscales
• Synergistic effects of climate and land cover: grassland birds are more vulnerable to climate change
• Distribution of near-surface permafrost in Alaska: Estimates of present and future conditions
• Landscape fragmentation affects responses of avian communities to climate change
• LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients
• Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data
• Spatial analysis of anthropogenic landscape disturbance and Buruli ulcer disease in Benin
• Spatial scaling of temporal changes in avian communities
• Accounting for the space-varying nature of the relationships between temporal community turnover and the environment
• Approaches to advance scientific understanding of macrosystems ecology
• Bayesian hierarchical models for spatially misaligned data in R
• Dynamic spatial regression models for space-varying forest stand tables
• Editors are editors, not oracles
• Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system
• Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets
• Modeling complex spatial dependencies: Low-rank spatially varying cross-covariances with application to soil nutrient data
• Permafrost and organic layer interactions over a climate gradient in a discontinuous permafrost zone
• Should species distribution models account for spatial autocorrelation? A test of model projections across eight millennia of climate change
• Spatial regression methods capture prediction uncertainty in species distribution model projections through time
• Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory
• An analysis of asthma hospitalizations, air pollution, and weather conditions in Los Angeles County, California
• Approximate Bayesian inference for large spatial datasets using predictive process models
• Bayesian dynamic modeling for large space-time datasets using Gaussian predictive processes
• Multivariate spatial regression models for predicting individual tree structure variables using LiDAR data
• Spatial design for knot selection in knot-based dimension reduction models
• Tropical tree growth is correlated with soil phosphorus, potassium, and calcium, though not for legumes
• A hierarchical model for quantifying forest variables over large heterogeneous landscapes with uncertain forest areas
• Adaptive Gaussian predictive process models for large spatial datasets
• Comparing and blending regional climate model predictions for the American southwest
• Comparing spatially-varying coefficients models for analysis of ecological data with non-stationary and anisotropic residual dependence
• Effects of stand and inter-specific stocking on maximizing standing tree carbon stocks in the eastern United States
• Improving crop model inference through Bayesian melding with spatially varying parameters
• Variational Bayesian methods for spatial data analysis
• Hierarchical spatial process models for multiple traits in large genetic trials
• Nonlinear hierarchical models for predicting cover crop biomass using Normalized Difference Vegetation Index
• Spatial modelling of car ownership data: a case study from the United Kingdom
• Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial datasets
• Improving the performance of predictive process modeling for large datasets
• A Bayesian approach to multi-source forest area estimation
• Efficient k-nearest neighbor searches for multi-source forest attribute mapping
• Gaussian predictive process models for large spatial data sets
• Hierarchical multiresolution approaches for dense point-level breast cancer treatment data
• yaImpute: an R package for kNN imputation
• Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery
• spBayes: an R package for univariate and multivariate hierarchical point-referenced spatial models
• Applying an efficient k-nearest neighbor search to forest attribute imputation
• Thoreau, Muir, and Jane Doe: different types of private forest owners need different kinds of forest management
• Delineation of forest/nonforest land use classes using nearest neighbor methods
• Timber harvesting as ongoing disturbance in a landscape of diverse ownership