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
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
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-04240.pdf
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-04729.pdf
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-04485.pdf
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-04492.pdf
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-04507.pdf
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-04365.pdf
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-04461.pdf
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-04611.pdf
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-04559.pdf
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

ecog-04537.pdf
ECOG-04665 2019

Liu, C., Comte, L., Xian, W., Chen, Y. and Olden, J. D. 2019. Current and projected future risks of freshwater fish invasions in China. – Ecography doi: 10.1111/ecog.04665

ecog-04665.pdf
ECOG-04560 2019

Connan, M., Dilley, B. J., Whitehead, O., Davies, D., McQuaid, C. D. and Ryan, P. G. 2019. Multidimensional stable isotope analysis illuminates resource partitioning in a sub-Antarctic island bird community. – Ecography doi: 10.1111/ecog.04560

ecog-04560.pdf
ECOG-04592 2019

Stubbington, R., Sarremejane, R. and Datry, T. 2019. Alpha and beta diversity of connected benthic–subsurface invertebrate communities respond to drying in dynamic river ecosystems. – Ecography doi: 10.1111/ecog.04592

ecog-04592.pdf
ECOG-04635 2019

Cunningham, C. X., Johnson, C. N., Hollings, T., Kreger, K. and Joners, M. E. 2019. Trophic rewilding establishes a landscape of fear: Tasmanian devil introduction increases risk-sensitive foraging in a key prey species. – Ecography doi: 10.1111/ecog.04635

ecog-04635.pdf

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