Gurutzeta Guillera‐Arroita

Author

Also Known As

G Guillera-Arroita, G. Guillera‐Arroita, Guillera-Arroita, G., Guillera-Arroita, Gurutzeta, Gurutzeta GUILLERA‐ARROITA, Gurutzeta Guillera-Arroita, Gurutzeta Guillera‐Arroita

Publications

11.6K

Citations

H-Index

Concepts

All Affiliations

The University of Melbourne University of Kent Commonwealth Scientific and Industrial Research Organisation Swiss Ornithological Institute Zoological Society of London

About

Gurutzeta Guillera‐Arroita is an author at The University of Melbourne specializing in engineering, biodiversity, and conservation biology.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	29	33	6.3K
2	Social Sciences	19	20	4.6K
3	Natural Sciences	2	2	2.1K
4	Management	1	1	210
5	Public Health	1	1	16

Gurutzeta Guillera‐Arroita

Publications

10.1K

Citations

H-Index

Page 1

	Year	Citations
Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure David R. Roberts, Volker Bahn, Simone Ciuti, Ecography BiologyPhylogenetic StructureBiodiversityBlock Cross‐validationCausal Predictors	2016	2K
Is my species distribution model fit for purpose? Matching data and models to applications Gurutzeta Guillera‐Arroita, José J. Lahoz‐Monfort, Jane Elith, Global Ecology and Biogeography BiodiversityEngineeringEcological SimulationMolecular EcologyBiogeography	2015	908
A standard protocol for reporting species distribution models Damaris Zurell, Janet Franklin, Christian König, Ecography Species Distribution ModelsBiodiversityEngineeringBiogeographyBiodiversity Assessment	2020	839
Predictive performance of presence‐only species distribution models: a benchmark study with reproducible code Roozbeh Valavi, Gurutzeta Guillera‐Arroita, José J. Lahoz‐Monfort, Ecological Monographs BiodiversityEngineeringTheoretical EcologyEcological ModellingBenchmark Study	2021	716
<scp>block</scp> <scp>CV</scp> : An <scp>r</scp> package for generating spatially or environmentally separated folds for <i>k</i> ‐fold cross‐validation of species distribution models Roozbeh Valavi, Jane Elith, José J. Lahoz‐Monfort, Methods in Ecology and Evolution	2018	613
Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models Tianxiao Hao, Jane Elith, José J. Lahoz‐Monfort, Ecography BiologySpatial EcologyBiodiversityEnsemble ModellingSpecies Distribution Models	2020	435
Modelling of species distributions, range dynamics and communities under imperfect detection: advances, challenges and opportunities Gurutzeta Guillera‐Arroita Ecography Range DynamicsRange ShiftBiodiversityEngineeringBiogeography	2016	398
Imperfect detection impacts the performance of species distribution models José J. Lahoz‐Monfort, Gurutzeta Guillera‐Arroita, Brendan A. Wintle Global Ecology and Biogeography Spatial EcologyBiodiversityEnvironmental MonitoringEngineeringRobust Modeling	2013	270
Deep-sea diversity patterns are shaped by energy availability Skipton Woolley, Derek P. Tittensor, Piers K. Dunstan, Nature EngineeringDeep-sea EcologyMarine BiodiversityOceanographyMarine Biology	2016	264
Modelling species presence‐only data with random forests Roozbeh Valavi, Jane Elith, José J. Lahoz‐Monfort, Ecography BiodiversityEngineeringData ScienceDefault RfEcological Modelling	2021	253

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