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F I G U R E 1 in Variation in the post-smolt growth pattern of wild one sea-winter salmon (Salmo salar L.), and its linkage to surface warming in the eastern North Atlantic Ocean
F I G U R E 1 Hierarchical cluster analysis of intercirculus spacing for scales of Salmo salar. (a) The dendrogram for k = 20 using Euclidean distance and Ward linkage for z-scored and interpolated data. The five major sub-branches (A–E) and the 20 clusters are ordered sequentially from the left. (b) The standardized intercirculus spacing plots for the 20 clusters. Clusters are colour-coded and ordered as in (a). The LOESS fits for each cluster are shown as a black line and the number of fish per cluster (n) is also shown
F I G U R E 2 in Variation in the post-smolt growth pattern of wild one sea-winter salmon (Salmo salar L.), and its linkage to surface warming in the eastern North Atlantic Ocean
F I G U R E 2 Tabulation of significant under- and over-representation of the 10 most frequent growth pattern categories (and "Others") for Salmo salar scales amongst the 20 dendrogram clusters. Proportions of growth pattern frequency were compared to the overall population proportion of scales for k = 20 with Ward linkage, and clustering of the z-scored and interpolated data. Light shading (−) indicates significant under-representation and dark shading (+) indicates over-representation. Sample sizes (n) for each growth pattern across the time-series are shown
F I G U R E 4 in Variation in the post-smolt growth pattern of wild one sea-winter salmon (Salmo salar L.), and its linkage to surface warming in the eastern North Atlantic Ocean
F I G U R E 4 Time-series changes in ocean surface temperature and Salmo salar scale growth pattern. (a) Changes in monthly SST anomaly for the 250 and 500 km standard deviation spatially weighted kernels in the Norwegian Sea (April 1992 – March 2011). (b) Changes in frequency (proportion within years) of selected growth patterns. The three selected pattern groupings illustrate fish showing persistent Fast growth (F) throughout the post-smolt growth season, Slow growth followed by Fast growth (SF), and all patterns pooled that displayed one or more growth Checks. The growth pattern data for each capture year (b) are aligned with the SST anomaly in April of the previous year (a), coinciding with the commencement of annual smolt emigration
F I G U R E 5 in Variation in the post-smolt growth pattern of wild one sea-winter salmon (Salmo salar L.), and its linkage to surface warming in the eastern North Atlantic Ocean
F I G U R E 5 Monthly correlations between the SST anomalies throughout the post-smolt Salmo salar growth period and annual frequency of the Fast (F) and All Check growth patterns. The salmon data were lagged by -1 year to match the annual post-smolt growth seasons to the SST anomalies. Significant correlations (P <0.05; following adjustment of d.f. to allow for autocorrelation) are shown by the filled circles
Fig. 1 in Diversity of intestinal protozoa and clinical signs associated in wild-caught Phoneutria nigriventer kept in captivity for the anti-arachnid serum production
Fig. 1. Phoneutria nigriventer kept in glass containers with a humidified cotton ball and a cardboard substrate.
Fig. 2. – A and B in Diversity of intestinal protozoa and clinical signs associated in wild-caught Phoneutria nigriventer kept in captivity for the anti-arachnid serum production
Fig. 2. – A and B, Diarrheal stools, without differentiation of solid and liquid portion. C, Normal stools of Phoneutria nigriventer (red arrow). The white arrow indicates the urine portion, white in color due to urate. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
T A B L E 1 in Fruit production in coffee (Coffea arabica L.) crops is enhanced by the behaviour of wild bees (Hymenoptera: Apidae)
T A B L E 1 Relationship of management type (conventional and agroecological) on the diversity of floral visitors (abundance and Chao-1) and the most abundant floral visitors. Values in bold are those that were found to be statistically significant.
F I G U R E 1 in Fruit production in coffee (Coffea arabica L.) crops is enhanced by the behaviour of wild bees (Hymenoptera: Apidae)
F I G U R E 1 Location of all study sites. The map shows location of the study sites in the central and south-western regions of Guatemala, where pollination experiments and pollinator observations were performed. Blue crosses represent conventional sites, and lilac crosses represent agroecological sites.
F I G U R E 3 in Fruit production in coffee (Coffea arabica L.) crops is enhanced by the behaviour of wild bees (Hymenoptera: Apidae)
F I G U R E 3 Relationship between the weight of fruits and (a) the percentage of Apis mellifera that carried pollen (PolTran) on their legs/bodies. Relationship between fruit set and (b) nectary, the percentage of P. bilineata observed touching the nectary of the coffee flowers, and (c) the average number of flowers visited by P. bilineata. Lilac colour is used for agroecological sites 'a', and blue is used for conventional sites 'c'. Shaded lines indicate 95% confidence interval.
F I G U R E 2 in Fruit production in coffee (Coffea arabica L.) crops is enhanced by the behaviour of wild bees (Hymenoptera: Apidae)
F I G U R E 2 Distribution under conventional (blue) and agroecological (lilac) management of (a) abundance of floral visitors, (b) abundance of A. mellifera and (c) abundance of P. bilineata. The differences between variables considering management were analysed with paired -F-test. *p <0.05.
Figures 2 and 3 in Variation in the post-smolt growth pattern of wild one sea-winter salmon (Salmo salar L.), and its linkage to surface warming in the eastern North Atlantic Ocean
Figures 2 and 3 summarize the under/over-representation of the more common growth patterns and years, respectively, amongst the k = 20 clusters. The SF growth pattern was over-represented for four of the five clusters of sub-branch A, in association with general underrepresentation of patterns showing an initial Fast (F) sequence (Figure 2). Sub-branch B revealed an essentially inverse structure to sub-branch A, with sporadic over-representation of patterns commencing with a Fast sequence and under-representation of those with an initial Slow sequence. Sub-branches C and D were heterogeneous
F I G U R E 3 in Variation in the post-smolt growth pattern of wild one sea-winter salmon (Salmo salar L.), and its linkage to surface warming in the eastern North Atlantic Ocean
F I G U R E 3 Tabulation of significant under- and overrepresentation of the 20 dendrogram clusters amongst years of capture of return adult Salmo salar. Details as for Figure 2
Figure 4b in Variation in the post-smolt growth pattern of wild one sea-winter salmon (Salmo salar L.), and its linkage to surface warming in the eastern North Atlantic Ocean
Figure 4b shows that there was (a) a decrease in the frequency of fish showing consistently Fast growth throughout the post-smolt period, (b) an increase in the frequency of the SF growth pattern and (c) an increase in the frequency of growth patterns including one or more Check sequences. Furthermore, these time-series changes in circulus pattern were linked significantly to contemporaneous and anomalous warming of the Norwegian Sea (Figure 5). As shown in Figure 6, one proximate consequence of these changes is manifest in the backcalculated mean length of fish at the midpoint of the winter annulus, following the completion of the post-smolt growth season. This showed a marked and significant decrease across the final six capture years of the time series.
Figure 12 in Colotis lais (Butler, 1876) and Colotis euippe omphale (Godart, [1819]) use Cadaba aphylla (Thunb.) Wild LC as a host-plant at Tswalu Kalahari, Northern Cape Province, South Africa)
Figure 12 – Pupa of Colotis euippe omphale. This pupa was reared from a larva collected on 19 December 2021 on Cadaba aphylla shrub C aphy 14, north of the Dedeben Research Centre, Tswalu Kalahari, South Africa. The CRG reference number for this pupa is RFT21H79. Photo: R.F. Terblanche.
Figure 14 in Colotis lais (Butler, 1876) and Colotis euippe omphale (Godart, [1819]) use Cadaba aphylla (Thunb.) Wild LC as a host-plant at Tswalu Kalahari, Northern Cape Province, South Africa)
Figure 14 – Cadaba aphylla (CAPPARACEAE), C aphy 14, photographed on 26 September 2022, north of the Dedeben Research Centre, Tswalu Kalahari, South Africa. When conditions are favourable, many shoots with small leaves can be produced by some individuals of the species, as depicted here. No flowers were present on this plant when the photograph was taken. Photo: R.F. Terblanche.
Figure 11 in Colotis lais (Butler, 1876) and Colotis euippe omphale (Godart, [1819]) use Cadaba aphylla (Thunb.) Wild LC as a host-plant at Tswalu Kalahari, Northern Cape Province, South Africa)
Figure 11 – Pupa of Colotis lais. This pupa was reared from a larva collected on 19 September 2022 on a Cadaba aphylla shrub C aphy 13, north of the Dedeben Research Centre, Tswalu Kalahari, South Africa. The CRG reference number for this pupa is RFT22H43. Photo: R.F. Terblanche.
Figure 10 in Colotis lais (Butler, 1876) and Colotis euippe omphale (Godart, [1819]) use Cadaba aphylla (Thunb.) Wild LC as a host-plant at Tswalu Kalahari, Northern Cape Province, South Africa)
Figure 10 – Final instar larva of Colotis euippe omphale collected on 3 January 2022 on Cadaba aphylla shrub C aphy 11, near the Dedeben Research Centre in Tswalu Kalahari, South Africa. The CRG reference number for this larva is RFT22H2. Photo: R.F. Terblanche.
Figure 9 in Colotis lais (Butler, 1876) and Colotis euippe omphale (Godart, [1819]) use Cadaba aphylla (Thunb.) Wild LC as a host-plant at Tswalu Kalahari, Northern Cape Province, South Africa)
Figure 9 – Final instar larva of Colotis lais. The larva was collected on 19 December 2021 on Cadaba aphylla shrub C aphy 13, north of the Dedeben Research Centre, Tswalu Kalahari, South Africa. The larva had been successfully reared on new shoots (young stems with small leaves) of Cadaba aphylla. The CRG reference number for this larva is RFT21H78. Photo: R.F. Terblanche.
Figure 15 in Colotis lais (Butler, 1876) and Colotis euippe omphale (Godart, [1819]) use Cadaba aphylla (Thunb.) Wild LC as a host-plant at Tswalu Kalahari, Northern Cape Province, South Africa)
Figure 15 – Cadaba aphylla (CAPPARACEAE) photographed on 21 January 2019 at Tswalu Kalahari, South Africa. A commonly used English name for Cadaba aphylla is "leafless wormbush," because leaves are often not present or obscured by many leafless stems. Photo: R.F. Terblanche.
Figure 7 in Colotis lais (Butler, 1876) and Colotis euippe omphale (Godart, [1819]) use Cadaba aphylla (Thunb.) Wild LC as a host-plant at Tswalu Kalahari, Northern Cape Province, South Africa)
Figure 7 – Depiction of GPS-marked Cadaba aphylla host plants (white markers) selected for ecological monitoring, north and north-west of the Dedeben Research Centre at Tswalu Kalahari.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.