Javni dostop

Adaptive management for improving species conservation across the captive-wild spectrum

S Canessa, G Guillera-Arroita, JJ Lahoz-Monfort, DM Southwell, ...

Biological Conservation 199, 123-131, 2016

Zahteve: Australian Research Council

Two-stage Bayesian study design for species occupancy estimation

G Guillera-Arroita, MS Ridout, BJT Morgan

Journal of Agricultural, Biological, and Environmental Statistics 19, 278-291, 2014

Zahteve: Australian Research Council, UK Engineering and Physical Sciences Research …

Species occupancy estimation and imperfect detection: shall surveys continue after the first detection?

G Guillera-Arroita, JJ Lahoz-Monfort

AStA Advances in Statistical Analysis 101, 381-398, 2017

Zahteve: Australian Research Council

The score test for the two‐sample occupancy model

N Karavarsamis, G Guillera‐Arroita, RM Huggins, BJT Morgan

Australian & New Zealand Journal of Statistics, 2020

Zahteve: Australian Research Council

Na voljo nekje: 47

Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure

DR Roberts, V Bahn, S Ciuti, MS Boyce, J Elith, G Guillera‐Arroita, ...

Ecography 40 (8), 913-929, 2017

Zahteve: Australian Research Council, Natural Sciences and Engineering Research …

Is my species distribution model fit for purpose? Matching data and models to applications

G Guillera‐Arroita, JJ Lahoz‐Monfort, J Elith, A Gordon, H Kujala, ...

Global ecology and biogeography 24 (3), 276-292, 2015

Zahteve: Australian Research Council

A standard protocol for reporting species distribution models

D Zurell, J Franklin, C König, PJ Bouchet, CF Dormann, J Elith, G Fandos, ...

Ecography 43 (9), 1261-1277, 2020

Zahteve: US National Science Foundation, US Department of Defense, Australian …

blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models

R Valavi, J Elith, JJ Lahoz-Monfort, G Guillera-Arroita

Methods in Ecology and Evolution, DOI: 10.1111/2041-210X.13107, 2018

Zahteve: Australian Research Council

A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD

T Hao, J Elith, G Guillera‐Arroita, JJ Lahoz‐Monfort

Diversity and Distributions 25 (5), 839-852, 2019

Zahteve: Australian Research Council

Predictive performance of presence‐only species distribution models: a benchmark study with reproducible code

R Valavi, G Guillera‐Arroita, JJ Lahoz‐Monfort, J Elith

Ecological monographs 92 (1), e01486, 2022

Zahteve: Australian Research Council

Modelling of species distributions, range dynamics and communities under imperfect detection: advances, challenges and opportunities

G Guillera‐Arroita

Ecography 40 (2), 281-295, 2017

Zahteve: Australian Research Council

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Data integration for large-scale models of species distributions

NJB Isaac, MA Jarzyna, P Keil, LI Dambly, PH Boersch-Supan, ...

Trends in ecology & evolution 35 (1), 56-67, 2020

Zahteve: Australian Research Council, UK Natural Environment Research Council

Model averaging in ecology: A review of Bayesian, information‐theoretic, and tactical approaches for predictive inference

CF Dormann, JM Calabrese, G Guillera‐Arroita, E Matechou, V Bahn, ...

Ecological monographs 88 (4), 485-504, 2018

Zahteve: Australian Research Council, German Research Foundation, European Commission …

Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models

T Hao, J Elith, JJ Lahoz‐Monfort, G Guillera‐Arroita

Ecography 43 (4), 549-558, 2020

Zahteve: Australian Research Council

Imperfect detection impacts the performance of species distribution models

JJ Lahoz‐Monfort, G Guillera‐Arroita, BA Wintle

Global ecology and biogeography 23 (4), 504-515, 2014

Zahteve: Australian Research Council

When do we need more data? A primer on calculating the value of information for applied ecologists

S Canessa, G Guillera‐Arroita, JJ Lahoz‐Monfort, DM Southwell, ...

Methods in Ecology and Evolution 6 (10), 1219-1228, 2015

Zahteve: Australian Research Council

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Ignoring imperfect detection in biological surveys is dangerous: A response to ‘fitting and interpreting occupancy models'

G Guillera-Arroita, JJ Lahoz-Monfort, DI MacKenzie, BA Wintle, ...

PloS one 9 (7), e99571, 2014

Zahteve: Australian Research Council

Forecasting species range dynamics with process‐explicit models: matching methods to applications

NJ Briscoe, J Elith, R Salguero‐Gómez, JJ Lahoz‐Monfort, JS Camac, ...

Ecology Letters 22 (11), 1940-1956, 2019

Zahteve: Australian Research Council, UK Natural Environment Research Council

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Statistical approaches to account for false‐positive errors in environmental DNA samples

JJ Lahoz‐Monfort, G Guillera‐Arroita, R Tingley

Molecular Ecology Resources 16 (3), 673-685, 2016

Zahteve: Australian Research Council