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Figure 4 in Community structure of benthic invertebrates in the Allipén River basin, North Patagonia, Araucania region (38º S, Chile)

Figure 4. Mean abundance (individuals/m2) the families more representative of benthic macroinvertebrates at site 3 Las Hortensias in the Allipen river.

Figure 3 in Community structure of benthic invertebrates in the Allipén River basin, North Patagonia, Araucania region (38º S, Chile)

Figure 3. Mean abundance (individuals/m2) the families more representative of benthic macroinvertebrates at site 2 Huereré in the Allipen river.

Figure 1 in Community structure of benthic invertebrates in the Allipén River basin, North Patagonia, Araucania region (38º S, Chile)

Figure 1. Map of Allipen river, Tolten river basin, La Araucania Region Chile.Where S1 "Melipeuco" (265639 S, 5694829 W), S2: "Huerere" (758774 S- 5681448 W) and S3: "Las Hortensias" (746454 S; 5684086 W) represent the specific sampling stations, respectively.

Figure 2 in Community structure of benthic invertebrates in the Allipén River basin, North Patagonia, Araucania region (38º S, Chile)

Figure 2. Mean abundance (individuals/m2) the families more representative of benthic macroinvertebrates at site 1 Melipeuco in the Allipen river.

Figure 2 in Using deep-learning for automatic identification of images of marine benthic macro-invertebrate bycatch: a proof of concept

Figure 2. – Three images of organisms obtained by cropping images of lots; from left to right: Chalinidae (Porifera), Polyclinidae (Chordata), Hormatidae (Cnidaria).

Figure 3 in Using deep-learning for automatic identification of images of marine benthic macro-invertebrate bycatch: a proof of concept

Figure 3. – Image of a batch of macro-invertebrate bycatch organisms from Kerguelen Exclusive Economical Zone (Poker 4 survey, 2017), including corals, a crinoïd, an ophiurid, a sea urchin and a brachiopoda; organisms are incomplete and have been quickly spread out over a small plate to take the picture.

Figure 6 in Using deep-learning for automatic identification of images of marine benthic macro-invertebrate bycatch: a proof of concept

Figure 6. – Example of detection and classification obtained with an image including an Ophiuroid, a piece of coral and a sea star with network 2; red squares and annotations have been provided by the computer with no human action.

Figure 5 in Using deep-learning for automatic identification of images of marine benthic macro-invertebrate bycatch: a proof of concept

Figure 5. – Example of detection and classification obtained with an image including Ascidians and a sea star with network 2; red squares and annotations have been provided by the computer with no human action.

Рис. 2. ΔенΑрограмма схоΑства фаун Αонных беспозвоночных воΑотоков заповеΑника «КомсомоΛьский» (UPGMA, коэффициент Сёренсена) Fig. 2. Dendrogram of the fauna similarity of benthic invertebrates of the Komsomolsky Nature Reserve watercourses (UPGMA, Sorensen coefficient) in Taxonomic composition of benthic invertebrates of the Komsomolsky Nature Reserve watercourses (Khabarovsky Region)

Рис. 2. ΔенΑрограмма схоΑства фаун Αонных беспозвоночных воΑотоков заповеΑника «КомсомоΛьский» (UPGMA, коэффициент Сёренсена) Fig. 2. Dendrogram of the fauna similarity of benthic invertebrates of the Komsomolsky Nature Reserve watercourses (UPGMA, Sorensen coefficient)

Рис. 1. Карта-схема заповеΑника «КомсомоΛьский» с указанием станций отбора проб зообентоса (по: http://www.zapovedamur.ru) Fig. 1. Map of the Komsomolsky Reserve with indication of zoobenthos sampling stations (after: http://www.zapovedamur.ru) in Taxonomic composition of benthic invertebrates of the Komsomolsky Nature Reserve watercourses (Khabarovsky Region)

Рис. 1. Карта-схема заповеΑника «КомсомоΛьский» с указанием станций отбора проб зообентоса (по: http://www.zapovedamur.ru) Fig. 1. Map of the Komsomolsky Reserve with indication of zoobenthos sampling stations (after: http://www.zapovedamur.ru)

Figure 2 in Bendima: a database for marine macro-invertebrate bycatch data designed to improve reproducibility in benthic ecology

Figure 2. – The proportion of the various phyla represented in the Bendima database, based on the number of single organisms or colonies.

Figure 1 in Bendima: a database for marine macro-invertebrate bycatch data designed to improve reproducibility in benthic ecology

Figure 1. – Images and samples collection; sorting of the caught organisms (A), full photographing (B), taxa identification/counting/measurement and storage in the Bendima database in the form of cropped images (C), conservation of representative sub-samples for taxonomy and DNA barcoding (D).

Figure 3 in Bendima: a database for marine macro-invertebrate bycatch data designed to improve reproducibility in benthic ecology

Figure 3. – The geographical coverage of the Bendima database; the location of the zoomed area is in provided in the inset world map; stations are aggregated into presence data according to a grid of cells of 1°; the letters and num- bers relate to the name of the French Economic Exclusive Zones (EEZ) and various geomorphic structures located in international waters: A: Kerguelen EEZ, B: Crozet EEZ, C: Saint-Paul et Amsterdam EEZ, 1: Del Cano ridge, 2: Elan Bank, 3: Ob et Lena Bank, 4 and 5: Antarctica shelf.

opencc-by-4.0Jul 2017View details →

Figure. The proportion of benthic abundance for different invertebrate orders relative to the total benthic abundance [%] of the Munzur and Pülümür rivers, representing the mean value of the 2 sites per river. in Macroinvertebrate composition in the metarhithral zones of the Munzur and Pülümür rivers: a preliminary study

Figure. The proportion of benthic abundance for different invertebrate orders relative to the total benthic abundance [%] of the Munzur and Pülümür rivers, representing the mean value of the 2 sites per river.

Figure 3 in Benthic invertebrates associated with subfossil cold-water coral frames and hardgrounds in the Albanian deep waters (Adriatic Sea)

Figure 3. Cnidaria recorded from the study area: a) Leiopathes glaberrima (AL16SA1); b) Dendrophyllia cornigera (AL16SA1); c) Isidella elongata (AL16SE2); d, d1) Caryophyllia calveri (AL15SE1); e) Stenocyathus vermiformis (AL16SE2); f, f ) Lophelia pertusa 1 (AL15SE1); g) Nausithoe sp. (AL15SE1)

Figure 5 in Benthic invertebrates associated with subfossil cold-water coral frames and hardgrounds in the Albanian deep waters (Adriatic Sea)

Figure 5. Annelids associated with Lophelia subfossil colonies from stations AL15SE1 and AL16SE2: a) Hyalopomatus madreporae, b, c) Serpulidae sp. 1, d) Filogranula gracilis, e) 1: Metavermilia multicristata, 2: Janita fimbriata, f) Metavermilia multicristata.

Figure 4 in Benthic invertebrates associated with subfossil cold-water coral frames and hardgrounds in the Albanian deep waters (Adriatic Sea)

Figure 4. Mollusks associated with the Lophelia pertusa and Dendrophyllia cornigera subfossil colonies collected at AL15SE1 and AL16SE2, and AL16SA1: a) Ranella olearia; b) Orania fusulus; c) Nassarius lima; d) Pagodula echinata; e) Putzeysia wiseri; f) Eulimella bogii; g) Emarginula adriatica; h) Yoldiella philippiana; i) Kelliella miliaris; j) Spondylus gussoni; k) Timoclea ovata; l) Tropidomya abbreviata.

Figure 6 in Benthic invertebrates associated with subfossil cold-water coral frames and hardgrounds in the Albanian deep waters (Adriatic Sea)

Figure 6. SEM images of bryozoans: a) Neolagenipora eximia, stat. AL15SE1; b) Idmidronea sp. 1., stat. AL15SE1.

opencc-by-4.0Oct 2021View details →

Fig. 6 in Diversity and microhabitat use of benthic invertebrates in an urban forest stream (Southeastern Brazil)

Fig. 6. NMDS ordination (stress = 0.18) of each microhabitat type (litter, sand, and stone) sampled at the Tijuca River, located at the Tijuca Forest, Rio de Janeiro, Brazil.