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 | Year | Description | Documents |
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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-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-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-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-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-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-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-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-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-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-04240 | 2019 | Bastille-Rousseau, G., Wall, J., Douglas-Hamilton, I., Lesowapir, B., Loloju, B., Mwangi, N. and Wittenmyer, G. 2019. Landscape-scale habitat response of African elephants shows strong selection for foraging opportunities in a human dominated ecosystem. – Ecography doi: 10.1111/ecog.04240 | ![]() |
ECOG-04729 | 2019 | Van doninck, J., Jones, M. M., Zuquim, G., Ruokolainen, K., Moulatlet, G. M., Sirén, A., Cárdenas, G., Lehtonen, S. and Tuomisto, H. 2019. Multispectral canopy reflectance improves spatial distribution models of Amazonian understory species. – Ecography doi: 10.1111/ecog.04729 | ![]() |
ECOG-04485 | 2019 | Cunningham, C. X., Scoler, V., Johnson, C. N., Barmuta, L. A. and Jones, M. E. 2019. Temporal partitioning of activity: rising and falling top-predator abundance triggers community-wide shifts in diel activity. – Ecography doi: 10.1111/ecog.04485 | ![]() |
ECOG-04492 | 2019 | Chalmandrier, L., Pansu, J., Zinger, L., Boyer, F., Coissac, E., Génin, A., Gielly, L., Lavergne, S., Legay, N., Schilling, V., Taberlet, P., Münkermüller, T. and Thuiller, W. 2019. Environmental and biotic drivers of soil microbial β-diversity across spatial and phylogenetic scales. – Ecography doi: 10.1111/ecog.04492 | ![]() |
ECOG-04507 | 2019 | Farneda, F. Z., Grelle, C. E. V., Rocha, R., Ferreira, D. F., López-Baucells, A. and Meyer, C. F. J. 2019. Predicting biodiversity loss in island and countryside ecosystems through the lens of taxonomic and functional biogeography. – Ecography doi: 10.1111/ecog.04507 | ![]() |
ECOG-04365 | 2019 | Frishkoff, L. O., Mahler, D. L. and Fortin, M.-J. 2019. Integrating over uncertainty in spatial scale of response within multispecies occupancy models yields more accurate assessments of community composition. – Ecography doi: 10.1111/ecog.04365 | ![]() |
ECOG-04461 | 2019 | Olivier, P., Frelat, R., Bonsdorff, E., Kortsch, S., Kröncke, I., Möllmann, C., Neumann, H., Sell, A. F. and Nordström, M. C. 2019. Exploring the temporal variability of a food web using long-term biomonitoring data. – Ecography doi: 10.1111/ecog.04461 | ![]() |
ECOG-04611 | 2019 | Srinivasan, U., Elsen, P. R. and Wilcove, D. S. 2019. Annual temperature variation influences the vulnerability of montane bird communities to land-use change. – Ecography doi: 10.1111/ecog.04611 | ![]() |
ECOG-04559 | 2019 | Fay, R., Michler, S., Laesser, J. and Schaub, M. 2019. Integrated population model reveals that kestrels breeding in nest boxes operate as a source population. – Ecography doi: 10.1111/ecog.04559 | ![]() |
ECOG-04537 | 2019 | Donati, G. F. A., Parravicini, V., Leprieur, F., Hagen, O., Gaboriau, T., Heine, C., Kulbicki, M., Rolland, J., Salamin, N., Albouy, C. and Pellissier, L. 2019. A process-based model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages. – Ecography doi: 10.1111/ecog.04537 | ![]() |