Appendix

Appendices are any supplementary material that may be associated with a particular article. Most often they are uploaded as pdf:s, but may also consist of excel files, scripts, videos etc. Appendices are searchable via manuscript number, doi or author name.

Supplementary material must follow the guidelines given here: 

 

Article number Yearsort ascending Description Documents
ECOG-04687 2019

Gábor, L., Moudrý, V., Lecours, V., Malavasi, M., Barták, Fogl, M., Šímová, P., Rocchini, D. and Václavík, T. 2019. The effect of positional error on fine scale species distribution models increases for specialist species. – Ecography doi: 10.1111/ecog.04687

ecog-04687.pdf
ECOG-04799 2019

Schulz, T., Vanhatalo, J. and Saastamoinen, M. 2019. Long-term demographic surveys reveal a consistent relationship between average occupancy and abundance within local populations of a butterfly metapopulation. – Ecography doi: 10.1111/ecog.04799

ecog-04799.pdf
ECOG-04536 2019

Marescot, L., Lyet, A., Singh, R., Carter, N. and Gimenez, O. 2019. Inferring wildlife poaching in southeast Asia with multispecies dynamic occupancy models. – Ecography doi: 10.1111/ecog.04536

ecog-04536.pdf
ECOG-04656 2019

Carvalheiro, L. G., Biesmeijer, J. C., Franzén, M., Aguirre-Gutierrez, J., Garibaldi, L. A., Helm, A., Michez, D., Pöyry, J., Reemer, M., Schweiger, van den Berg, L., WallisDeVries, M. F. and Kunin, W. E. 2019. Soil eutrophication shaped the composition of pollinator assemblages during the past century. – Ecography doi: 10.1111/ecog.04656

ecog-04656.zip
ECOG-04627 2019

Feng, X., Liang, Y., Gallardo, B. and Papeş, M. 2019. Physiology in ecological niche modeling: using zebra mussel’s upper thermal tolerance to refine model predictions through Bayesian analysis. – Ecography doi: 10.1111/ecog.04627

ecog-04627.pdf
ECOG-04757 2019

Lindholm, M., Alahuhta, J., Heiono, J. and Toivonen, H. 2019. No biotic homogenisation across decades but consistent effects of landscape position and pH on macrophyte communities in boreal lakes. – Ecography doi: 10.1111/ecog.04757

ecog-04757.pdf
ECOG-04462 2019

Rodríguez-Tricot, L. and Arim, M. 2019. From Hutchinsonian ratios to spatial scaling theory: the interplay among limiting similarity, body size, and landscape structure. – Ecography doi: 10.1111/ecog.04462

ecog-04462.pdf
ECOG-04653 2019

Critchley, E. J., Grecian, W. J., Benninson, A., Kane, A., Wischnewski, S., Cañadas, A., Tierney, D., Quinn, J. L. and Jessopp, M. J. 2019. Assessing the effectiveness of foraging radius models for seabird distributions using biotelemetry and survey data. – Ecography doi: 10.1111/ecog.04653

ecog-04653.pdf
ECOG-04773 2019

Rovero, F., Ahumada, J., Jansen, P. A., Sheil, D., Alvarez, P., Boekee, K., Espinosa, S., Lima, M. G. G., Martin, E. H., O’Brien, T. G., Salvador, J., Santos, F., Rosa, M., Zvoleff, A., Sutherland, C. and Tenan, S. 2019. A standardized assessment of forest mammal communities reveals consistent functional composition and vulnerability across the tropics. – Ecography doi: 10.1111/ecog.04773

ecog-04773.pdf
ECOG-04772 2019

Benito, B. M., Gil-Romera, G. and Birks, H. J. B. 2019. Ecological memory at millennial time-scales: the importance of data constraints, species longevity, and niche features. – Ecography doi: 10.1111/ecog.04772

ecog-04772.pdf
ECOG-04571 2019

Manenti, R., Falaschi, M., Monache, D. D., Marta, S. and Ficetola, G. F. 2019. Network-scale effects of invasive species on spatially-structured amphibian populations. – Ecography doi: 10.1111/ecog.04571

ecog-04571.zip
ECOG-04291 2019

Hellegers, M., Ozing, W. A., van Hinsberg, A., Huijbregts, M. A. J., Hennekens, S. M., Schaminée, J. H. J., Dengler, J. and Schipper, A. M. 2019. Evaluating the ecological realism of plant species distribution models with ecological indicator values. – Ecography doi: 10.1111/ecog.04291

ecog-04291.pdf
ECOG-04504 2019

Henderson, C. J., Gilby, B. L., Schlacher, T. A., Connolly, R. M., Sheaves, M., Maxwell, P. S., Flint, N., Borland, H. P., Martin, T. S. H., Gorissen, B. and Olds, A. D. 2019. Landscape transformation alters functional diversity in coastal seascapes. – Ecography doi: 10.1111/ecog.04504

ecog-04504.pdf
ECOG-04678 2019

Parolari, A. J., Paul, K., Griffing, A., Condit, R., Perez, R., Aguilar, S. and Schnitzer, S. A. 2019. Liana abundance and diversity increase with rainfall seasonality along a precipitation gradient in Panama. – Ecography doi: 10.1111/ecog.04678

ecog-04678.pdf
ECOG-04568 2019

Bueno, A. S., Masseli, G. S., Kaefer, I. L. and Peres, C. A. 2019. Sampling design may obscure species–area relationships in landscape-scale field studies. – Ecography doi: 10.1111/ecog.04568

ecog-04568.pdf
ECOG-04532 2019

Millard, J. W., Freeman, F. and Newbold, T. 2019. Text-analysis reveals taxonomic and geographic disparities in animal pollination literature. – Ecography doi: 10.1111/ecog.04532

ecog-04532.pdf
ECOG-04630 2019

Chardon, N. I., Pironon, S., Peterson, M. L. and Doak, D. F. 2019. Incorporating intraspecific variation into species distribution models improves distribution predictions, but cannot predict species traits for a wide-spread plant species. – Ecography doi: 10.1111/ecog.04630

ecog-04630.pdf
ECOG-04632 2019

La Sorte, F. A. and Somveille, M. 2019. Survey completeness of a global citizen-science database of bird occurrence. – Ecography doi: 10.1111/ecog.04632

ecog-04632.pdf
ECOG-04680 2019

Kearney, M. R. and Porter, W. P. 2019. NicheMapR – an R package for biophysical modelling: the ectotherm and Dynamic Energy Budget models. – Ecography doi: 10.1111/ecog.04680

ecog-04680.pdf
ECOG-04707 2019

Brodie, S., Thorson, J. T., Carroll, G., Hazen, E. I., Bograd, S., Haltuch, M., Holsman, K., Kotwicki, S., Samhouri, J., Willis-Norton, E. and Selden, R. 2019. Trade-offs in covariate selection for species distribution models: a methodological comparison. – Ecography doi: 10.1111/ecog.04707

ecog-04707.pdf

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