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Novel analytic methods for predicting extinctions in ecological networks.
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- Ecological Monographs, 2024, v. 94, n. 2, p. 1, doi. 10.1002/ecm.1601
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- Article
Predicting extinctions with species distribution models.
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- Cambridge Prisms: Extinction, 2023, v. 1, p. 1, doi. 10.1017/ext.2023.5
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- Article
Individual-based modelling of resource competition to predict density-dependent population dynamics: a case study with white storks.
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- Oikos, 2015, v. 124, n. 3, p. 319, doi. 10.1111/oik.01294
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The virtual ecologist approach: simulating data and observers.
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- Oikos, 2010, v. 119, n. 4, p. 622, doi. 10.1111/j.1600-0706.2009.18284.x
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- Article
The clustering of spatially associated species unravels patterns in tropical tree species distributions.
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- Ecosphere, 2023, v. 14, n. 6, p. 1, doi. 10.1002/ecs2.4589
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- Article
Fitting individual‐based models of spatial population dynamics to long‐term monitoring data.
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- Ecological Applications, 2024, v. 34, n. 4, p. 1, doi. 10.1002/eap.2966
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- Article
Reducing persecution is more effective for restoring large carnivores than restoring their prey.
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- Ecological Applications, 2021, v. 31, n. 5, p. 1, doi. 10.1002/eap.2338
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- Article
Advancing an interdisciplinary framework to study seed dispersal ecology.
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- AoB Plants, 2020, v. 12, n. 2, p. N.PAG, doi. 10.1093/aobpla/plz048
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The total dispersal kernel: a review and future directions.
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- AoB Plants, 2019, v. 11, n. 5, p. N.PAG, doi. 10.1093/aobpla/plz042
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- Article
Rapid changes in seed dispersal traits may modify plant responses to global change.
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- AoB Plants, 2019, v. 11, n. 3, p. N.PAG, doi. 10.1093/aobpla/plz020
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Employing plant functional groups to advance seed dispersal ecology and conservation.
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- AoB Plants, 2019, v. 11, n. 2, p. N.PAG, doi. 10.1093/aobpla/plz006
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- Article
Standardised empirical dispersal kernels emphasise the pervasiveness of long‐distance dispersal in European birds.
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- Journal of Animal Ecology, 2023, v. 92, n. 1, p. 158, doi. 10.1111/1365-2656.13838
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- Article
Early arrival at breeding grounds: Causes, costs and a trade‐off with overwintering latitude.
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- Journal of Animal Ecology, 2018, v. 87, n. 6, p. 1627, doi. 10.1111/1365-2656.12898
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- Article
The challenges of the first migration: movement and behaviour of juvenile vs. adult white storks with insights regarding juvenile mortality.
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- Journal of Animal Ecology, 2016, v. 85, n. 4, p. 938, doi. 10.1111/1365-2656.12525
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- Article
Large carnivore range expansion in Iberia in relation to different scenarios of permeability of human‐dominated landscapes.
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- Diversity & Distributions, 2023, v. 29, n. 1, p. 75, doi. 10.1111/ddi.13645
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- Article
Anthropogenic and environmental drivers shape diversity of naturalized plants across the Pacific.
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- Diversity & Distributions, 2021, v. 27, n. 6, p. 1120, doi. 10.1111/ddi.13260
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Born‐digital biodiversity data: Millions and billions.
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- Diversity & Distributions, 2020, v. 26, n. 5, p. 644, doi. 10.1111/ddi.12993
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- Article
Spatial gradients in country‐level population trends of European birds.
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- Diversity & Distributions, 2019, v. 25, n. 10, p. 1527, doi. 10.1111/ddi.12945
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- Article
Seasonal occurrence and abundance of dabbling ducks across the continental United States: Joint spatio‐temporal modelling for the Genus Anas.
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- Diversity & Distributions, 2019, v. 25, n. 9, p. 1497, doi. 10.1111/ddi.12960
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Use and categorization of Light Detection and Ranging vegetation metrics in avian diversity and species distribution research.
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- Diversity & Distributions, 2019, v. 25, n. 7, p. 1045, doi. 10.1111/ddi.12915
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- Article
Interannual climate variability improves niche estimates for ectothermic but not endothermic species.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-39637-x
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Causes and consequences of facultative sea crossing in a soaring migrant.
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- Functional Ecology, 2020, v. 34, n. 4, p. 840, doi. 10.1111/1365-2435.13539
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Can incomplete knowledge of species' physiology facilitate ecological niche modelling? A case study with virtual species.
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- Diversity & Distributions, 2017, v. 23, n. 10, p. 1157, doi. 10.1111/ddi.12606
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Population dynamics affect the capacity of species distribution models to predict species abundance on a local scale.
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- Diversity & Distributions, 2017, v. 23, n. 9, p. 1008, doi. 10.1111/ddi.12589
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- Article
Climate change decouples marine and freshwater habitats of a threatened migratory fish.
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- Diversity & Distributions, 2017, v. 23, n. 7, p. 751, doi. 10.1111/ddi.12570
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- Article
Effects of functional traits on the prediction accuracy of species richness models.
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- Diversity & Distributions, 2016, v. 22, n. 8, p. 905, doi. 10.1111/ddi.12450
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Predicting to new environments: tools for visualizing model behaviour and impacts on mapped distributions.
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- Diversity & Distributions, 2012, v. 18, n. 6, p. 628, doi. 10.1111/j.1472-4642.2012.00887.x
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- Article
Potential sources of time lags in calibrating species distribution models.
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- Journal of Biogeography, 2024, v. 51, n. 1, p. 89, doi. 10.1111/jbi.14726
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Scale dependency of joint species distribution models challenges interpretation of biotic interactions.
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- Journal of Biogeography, 2021, v. 48, n. 7, p. 1541, doi. 10.1111/jbi.14106
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Immediate and carry‐over effects of insect outbreaks on vegetation growth in West Greenland assessed from cells to satellite.
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- Journal of Biogeography, 2020, v. 47, n. 1, p. 87, doi. 10.1111/jbi.13644
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Macroecology in the age of Big Data – Where to go from here?
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- Journal of Biogeography, 2020, v. 47, n. 1, p. 1, doi. 10.1111/jbi.13633
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Testing species assemblage predictions from stacked and joint species distribution models.
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- Journal of Biogeography, 2020, v. 47, n. 1, p. 101, doi. 10.1111/jbi.13608
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- Article
Do long‐distance migratory birds track their niche through seasons?
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- Journal of Biogeography, 2018, v. 45, n. 7, p. 1459, doi. 10.1111/jbi.13351
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- Article
Integrating demography, dispersal and interspecific interactions into bird distribution models.
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- Journal of Avian Biology, 2017, v. 48, n. 12, p. 1505, doi. 10.1111/jav.01225
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The niche through time: Considering phenology and demographic stages in plant distribution models.
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- Journal of Ecology, 2024, v. 112, n. 9, p. 1926, doi. 10.1111/1365-2745.14361
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- Article
Spatially explicit models for decision‐making in animal conservation and restoration.
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- Ecography, 2022, v. 2022, n. 4, p. 1, doi. 10.1111/ecog.05787
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- Article
RangeShiftR: an R package for individual‐based simulation of spatial eco‐evolutionary dynamics and species' responses to environmental changes.
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- Ecography, 2021, v. 44, n. 10, p. 1443, doi. 10.1111/ecog.05689
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RangeShifter 2.0: an extended and enhanced platform for modelling spatial eco‐evolutionary dynamics and species' responses to environmental changes.
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- Ecography, 2021, v. 44, n. 10, p. 1453, doi. 10.1111/ecog.05687
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Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes.
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- Ecography, 2020, v. 43, n. 10, p. 1448, doi. 10.1111/ecog.05117
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A standard protocol for reporting species distribution models.
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- Ecography, 2020, v. 43, n. 9, p. 1261, doi. 10.1111/ecog.04960
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Increasing synergistic effects of habitat destruction and hunting on mammals over three decades in the Gran Chaco.
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- Ecography, 2020, v. 43, n. 7, p. 954, doi. 10.1111/ecog.05053
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Do joint species distribution models reliably detect interspecific interactions from co‐occurrence data in homogenous environments?
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- Ecography, 2018, v. 41, n. 11, p. 1812, doi. 10.1111/ecog.03315
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sOAR: a tool for modelling optimal animal life‐history strategies in cyclic environments.
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- Ecography, 2018, v. 41, n. 3, p. 551, doi. 10.1111/ecog.03328
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Mechanistic modelling of animal dispersal offers new insights into range expansion dynamics across fragmented landscapes.
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- Ecography, 2014, v. 37, n. 12, p. 1240, doi. 10.1111/ecog.01041
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Does probability of occurrence relate to population dynamics?
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- Ecography, 2014, v. 37, n. 12, p. 1155, doi. 10.1111/ecog.00836
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Collinearity: a review of methods to deal with it and a simulation study evaluating their performance.
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- Ecography, 2013, v. 36, n. 1, p. 027, doi. 10.1111/j.1600-0587.2012.07348.x
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- Article
Uncertainty in predictions of range dynamics: black grouse climbing the Swiss Alps.
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- Ecography, 2012, v. 35, n. 7, p. 590, doi. 10.1111/j.1600-0587.2011.07200.x
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Static species distribution models in dynamically changing systems: how good can predictions really be?
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- Ecography, 2009, v. 32, n. 5, p. 733, doi. 10.1111/j.1600-0587.2009.05810.x
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- Article
Forecasting potential invaders to prevent future biological invasions worldwide.
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- Global Change Biology, 2024, v. 30, n. 7, p. 1, doi. 10.1111/gcb.17399
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Can dynamic occupancy models improve predictions of species' range dynamics? A test using Swiss birds.
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- Global Change Biology, 2021, v. 27, n. 18, p. 4269, doi. 10.1111/gcb.15723
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- Article