Zobrazeno 1 - 10
of 155
pro vyhledávání: '"O. Finley"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 135, Iss , Pp 104224- (2024)
Modeling incompatible spatial data, i.e., data with different spatial resolutions, is a pervasive challenge in remote sensing data analysis. Typical approaches to addressing this challenge aggregate information to a common coarse resolution, i.e., co
Externí odkaz:
https://doaj.org/article/caf825611a5f498aa18daa2d85280eb3
Publikováno v:
Methods in Ecology and Evolution, Vol 15, Iss 6, Pp 1024-1033 (2024)
Abstract Numerous modelling techniques exist to estimate abundance of plant and animal populations. The most accurate methods account for multiple complexities found in ecological data, such as observational biases, spatial autocorrelation, and speci
Externí odkaz:
https://doaj.org/article/76dfdf84b7674be7a0be7cb3b5f55d61
Autor:
Arne Nothdurft, Andreas Tockner, Sarah Witzmann, Christoph Gollob, Tim Ritter, Ralf Kraßnitzer, Karl Stampfer, Andrew O. Finley
Publikováno v:
Remote Sensing, Vol 16, Iss 12, p 2181 (2024)
A novel Bayesian spatial distributional regression model is presented to predict forest structural diversity in terms of the distributions of the stem diameter at breast height (DBH) in the protection forests in Ebensee, Austria. The distributional r
Externí odkaz:
https://doaj.org/article/58ae75963a8449f2be3e67b87e3f6c85
Publikováno v:
Journal of Statistical Software, Vol 103, Pp 1-40 (2022)
This paper describes and illustrates functionality of the spNNGP R package. The package provides a suite of spatial regression models for Gaussian and non-Gaussian pointreferenced outcomes that are spatially indexed. The package implements several Ma
Externí odkaz:
https://doaj.org/article/e86d58d0135a43b2ab1aed213a376615
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
The nature of forest disturbances are changing, yet consequences for forest dynamics remain uncertain. Using a new index, Stanke et al. show the populations of over half of the most abundant tree species in the western US have declined in the last tw
Externí odkaz:
https://doaj.org/article/89fabc55607f4de8ba27496bdec2c529
Publikováno v:
Frontiers in Forests and Global Change, Vol 5 (2022)
The United States (US) Department of Agriculture Forest Service Forest Inventory and Analysis (FIA) program operates the national forest inventory of the US. Traditionally, the FIA program has relied on sample-based approaches—permanent plot networ
Externí odkaz:
https://doaj.org/article/6e525e64a40d42efb13a67814e497512
Publikováno v:
Ecosphere, Vol 11, Iss 5, Pp n/a-n/a (2020)
Abstract Semiarid and savanna‐type (SAST) ecosystems in East Africa have unique plant species compositions and characteristics that make quantifying this biome's seasonality and interannual variability difficult. Phenoregion classification offers a
Externí odkaz:
https://doaj.org/article/7d1e5638cc254d91965d8bbcf35ac750
spOccupancy: An R package for single‐species, multi‐species, and integrated spatial occupancy models
Publikováno v:
Methods in Ecology and Evolution. 13:1670-1678
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::318b6fbb81f1c5cc7d7400d93184ca8b
https://doi.org/10.1111/2041-210x.13897
https://doi.org/10.1111/2041-210x.13897
Autor:
Kelly A. Heilman, Michael C. Dietze, Alexis A. Arizpe, Jacob Aragon, Andrew Gray, John D. Shaw, Andrew O. Finley, Stefan Klesse, R. Justin DeRose, Margaret E. K. Evans
Publikováno v:
Global Change Biology. 28:2442-2460
Robust ecological forecasting of tree growth under future climate conditions is critical to anticipate future forest carbon storage and flux. Here, we apply three ingredients of ecological forecasting that are key to improving forecast skill: data fu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27050ec295d0b6eb2f13d1015899d266
https://doi.org/10.1111/gcb.16038
https://doi.org/10.1111/gcb.16038
Publikováno v:
Journal of Statistical Software, Vol 63, Iss 1, Pp 1-28 (2015)
In this paper we detail the reformulation and rewrite of core functions in the spBayes R package. These efforts have focused on improving computational efficiency, flexibility, and usability for point-referenced data models. Attention is given to alg
Externí odkaz:
https://doaj.org/article/f7c13acdcc2845baad2f08b9435d38e4