Search

Your search keyword '"Schuettpelz, Eric"' showing total 264 results

Search Constraints

Start Over You searched for: Author "Schuettpelz, Eric" Remove constraint Author: "Schuettpelz, Eric"
264 results on '"Schuettpelz, Eric"'

Search Results

1. Are there too many fern genera?

3. Transcriptome sequencing reveals genome-wide variation in molecular evolutionary rate among ferns

5. Polyploid goldback and silverback ferns (Pentagramma) occupy a wider, colder, and wetter bioclimatic niche than diploid counterparts.

15. Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

25. Phlegmariurus pseudovarius Rouhan & A. R. Field, comb. nov

26. Antrophyopsis gigantea Rouhan, Boullet & Schuettp. 2021, comb. nov

27. Three new combinations and one lectotypification of fern and lycophyte taxa from the French overseas territories

35. Phylogeny and evolution of ferns (monilophytes) with a focus on the early leptosporangiate divergences

36. Phylogeny and biogeography of Caltha (Ranunculaceae) based on chloroplast and nuclear DNA sequences

37. Fern classification

40. Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

42. Extensive photobiont sharing in a rapidly radiating cyanolichen clade.

43. A community-derived classification for extant lycophytes and ferns

44. A community-derived classification for extant lycophytes and ferns

47. Geometry, Allometry and Biomechanics of Fern Leaf Petioles: Their Significance for the Evolution of Functional and Ecological Diversity Within the Pteridaceae

48. Figure 1d from: Schuettpelz E, Frandsen P, Dikow R, Brown A, Orli S, Peters M, Metallo A, Funk V, Dorr L (2017) Applications of deep convolutional neural networks to digitized natural history collections. Biodiversity Data Journal 5: e21139. https://doi.org/10.3897/BDJ.5.e21139

49. Figure 2d from: Schuettpelz E, Frandsen P, Dikow R, Brown A, Orli S, Peters M, Metallo A, Funk V, Dorr L (2017) Applications of deep convolutional neural networks to digitized natural history collections. Biodiversity Data Journal 5: e21139. https://doi.org/10.3897/BDJ.5.e21139

50. Supplementary material 1 from: Schuettpelz E, Frandsen P, Dikow R, Brown A, Orli S, Peters M, Metallo A, Funk V, Dorr L (2017) Applications of deep convolutional neural networks to digitized natural history collections. Biodiversity Data Journal 5: e21139. https://doi.org/10.3897/BDJ.5.e21139

Catalog

Books, media, physical & digital resources