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Figures 1–3. 1 in Nocturnal multi-species roosts of Cicindelidae (Coleoptera) in a Neotropical lowland rainforest
Figures 1–3. 1) Forest path #1 at the study site in lowland terra firme Venezuelan rainforest, February 1999. 2) Communal roost of Odontocheila Laporte de Castelnau spp. (O. confusa (Dejean) and O. angulipenis W. Horn/O. margineguttata (Dejean)) at the study site in lowland terra firme Venezuelan rainforest, June 1998. 3) Communal roost of Odontocheila Laporte de Castelnau spp. (O. confusa (Dejean) and O. angulipenis W. Horn/O. margineguttata (Dejean)) at the study site in lowland terra firme Venezuelan rainforest, May 1998.
FIG. 1 in Epiphyllous bryophyte diversity in lowland rain forest and lowland cloud forest of French Guiana
FIG. 1. ― Species accumulation curves and estimated total number of species (*) of epiphyllous bryophytes in the understory of lowland cloud forest (LCF) and lowland rain forest (LRF) at Nouragues, French Guiana.
Fig. 3 in Danger under wheels: mammal roadkills in the threaten lowland Atlantic Forest in southeast Brazil
Fig. 3. Roadkill hotspots of mammal species recorded along the RJ-122 highway (from Km 1 to Km 34) between October 2017 and January 2020, in the state of Rio de Janeiro, Brazil. The largest number of roadkills is concentrated in two regions (black location icon), Km 23/24 (N = 22 and N = 24) and Km 28/29 (N = 18 and N = 22).
Fig. 1 in Danger under wheels: mammal roadkills in the threaten lowland Atlantic Forest in southeast Brazil
Fig. 1. Biplot of the five most roadkilled species of mammals (Didelphis aurita, Coendou insidiosus, Cerdocyon thous, Dasypus novemcinctus and Callithrix jacchus) along the RJ-122 highway between October 2017 and January 2020, in the state of Rio de Janeiro, Brazil. Circle: mammal species; Triangle: months of the year.
Fig. 2 in Danger under wheels: mammal roadkills in the threaten lowland Atlantic Forest in southeast Brazil
Fig. 2. Frequency of roadkill mammals over every kilometer along the RJ- 122 highway between October 2017 and January 2020, in state of Rio de Janeiro, Brazil. Highlights are km 23, km 24, km 28 and km 29.
Spatial patterns in neighbourhood effects on woody plant selection and bark stripping by deer in a lowland alluvial forest
<p>This dataset presents the incidence of bark stripping (present or not) and its intensity by two deer species mapped over all woody individuals ≥ 1 cm diameter at breast height (DBH). Stripping intensity was measured as the maximal percentage of the stripped stem circumference at the part of the stem with the horizontally widest stripping wound. A four-hectare square research plot is located in the Ranšpurk old-growth forest reserve in the south-eastern part of the Czech Republic (N48°40´, E16°56´).</p> <p>Several treefalls damaged the fence around the reserve in late autumn 2017, allowing fallow deer (<em>Dama dama</em> L.) and red deer (<em>Cervus elaphus</em> L.) to enter the reserve from the deer enclosure. The number of fallow deer and red deer individuals in the reserve was unknown, and likely fluctuated over time as they could enter and leave the reserve at any time. Data were collected in July 2018, ca 9–10 months after the fence was damaged. Although the fence was not fixed at the time of data collection (deer could still enter and leave the reserve), stripping wounds were not fresh and were likely received between late autumn 2017 and early spring 2018.</p> <p>The datasets includes tree and shrub individuals that fell within species-specific DBH range (susceptible individuals). The range was defined for each tree and shrub species as DBH<sub>min </sub>≤ DBH ≤ DBH<sub>max</sub>, where DBH<sub>min</sub> and DBH<sub>max</sub> are DBH of the smallest and largest stripped individuals. Individuals smaller and larger than this range were excluded from analyses, because small and large individuals may be relatively less often stripped. Woody species with ≥ 70 individuals are presented, because stochasticity does not allow meaningful spatial point pattern analyses with fewer individuals per species.</p> <p>Data contains the x and y coordinates of each individual in a local coordinate system, the woody species, its code, diameter at breast height, the incidence of stripping (present = 1 or not = 0), and the intensity of stripping (%).</p> <p> </p> <p> </p>
Fig. 6 in New Details Of The Eurasian Beaver'S, Castor Fiber (Rodentia, Castoridae), Expansion In The Lowland Part Of Transcarpathia, Ukraine
Fig. 6. The channel's course at location 2 (see fig. 8). Fig. 7. The channel's course at location 3 (see fig. 8).
Comparative physiology of canopy tree leaves in evergreen and deciduous forests in lowland Thailand
<p><span>Three major forest types in lowland Thailand and its adjacent parts in Southeast Asia are mixed deciduous forest (MDF), dry dipterocarp forest (DDF) and dry evergreen forest (DEF). We report the leaf physiology of canopy trees in these forests. The leaf mass-based photosynthetic rates (<em>A</em><sub>max</sub>), stomatal conductance (<em>G</em><sub>max</sub>) and photosynthetic nitrogen use efficiency were significantly different between the deciduous forests (MDF and DDF) and the evergreen forest (DEF). The canopy trees of MDF with thick, eutrophic soils had the highest intrinsic water use efficiency (<em>A</em><sub>max</sub>/<em>G</em><sub>max</sub>) among the forest types. Forest-to-forest variations in leaf mass area were related to different nutrient use strategies (less vs. more conservative) associated with different soil nutrients rather than with leaf phenology/longevity. In the interspecific variations within each forest, <em>A</em><sub>max</sub> in MDF and DEF was limited by foliar phosphate, whereas that in DDF was limited by foliar nitrogen. The close association between leaf physiology and soil properties suggests that climate change and increasing human impacts will disrupt this association, leading to forest degradation and dysfunction.</span></p>
Comparative physiology of canopy tree leaves in evergreen and deciduous forests in lowland Thailand
<p>The major forest types in lowland Thailand and its adjacent parts in Southeast Asia with the distinct dry season are the mixed deciduous forest (MDF), dry dipterocarp forest (DDF) and dry evergreen forest (DEF). We report the first comprehensive data set in leaf physiology of canopy trees in these three forest types and clarify adaptive functional differences of woody plants among three forests. Unlike temperate forests, the forest variations in leaf mass per area (LMA) were related to nutrient use strategies (less vs. more conservative) associated with soil nutrients rather than with leaf phenology (evergreen vs. deciduous). In the interspecific variations within each forest, <em>A<sub>max</sub></em> in MDF and DEF was limited by foliar phosphate, whereas that in DDF was limited by foliar nitrogen. The close association between leaf physiology and soil properties suggests that climate change and increasing human impacts will disrupt this association, leading to forest degradation and dysfunction.</p>
Figure 1 in Checklist of oribatid mites (Acari, Oribatida) of the Transcarpathian lowland, Ukraine
Figure 1. Sampling sites of the Oribatida in the Transcarpathian lowland. – collected by the first author, – literature data (Melamud 2008, 2009).
Рис. 1. А – р. Зарафшан в среднем течении (предгорнаЯ река); В – р. Зарафшан в ниЖнем течении (равниннаЯ река). Фото Н. РуЗикуловой, 2019 г. Fig. 1. А – the Middle Zarafshan River (submountain river); B – the Lower Zarafshan River (lowland river). Photo by N. Ruzikulova, 2019. in Patterns of ecology and life cycles of aquatic molluscs from Central Asia
Рис. 1. А – р. Зарафшан в среднем течении (предгорнаЯ река); В – р. Зарафшан в ниЖнем течении (равниннаЯ река). Фото Н. РуЗикуловой, 2019 г. Fig. 1. А – the Middle Zarafshan River (submountain river); B – the Lower Zarafshan River (lowland river). Photo by N. Ruzikulova, 2019.
Electronic Supplementary Material for: The biogeography of population resilience in lowland South America
<p>## Electronic Supplementary Information for "The biogeography of population resilience in lowland South America" chapter</p> <p>This repository holds the code and data for reproducing the analysis in the chapter "The biogeography of population resilience in lowland South America", forthcoming in the Oxford Handbook of Resilience in Climate History. It also contains supplementary information on the statistical modelling undertaken as part of the aforementioned work. </p> <p>The code comprises five principal sections, plus setup:</p> <p>0. Setup & data loading<br>1. Data processing and display<br>2. Radiocarbon analysis<br>3. Statistical modelling<br>4. Output<br>5. Supplementary output</p> <p>The code features an extended version of the p2pPerm function: (https://github.com/philriris/p2pPerm) that was first introduced in Riris and De Souza (2021) (https://doi.org/10.3389/fevo.2021.740629), here called the `resmet` (RESilience METrics) function. </p> <p>In addition, the code is accompanied by three datasets:</p> <p>- A table containing archaeological radiocarbon dates from lowland tropical South America <br>- A shapefile of South American ecoregions, original data available here: http://ecologicalregions.info/data/sa/<br>- A table of domesticated Neotropical plants resolved in Amazonian palaeoecological records, after Iriarte et al. (2020)(https://doi.org/10.1016/j.quascirev.2020.106582)</p> <p>Briefly, the georeferenced radiocarbon data used in the paper have been compiled from a wide range of sources, including Goldberg et al. (2016), Riris & Arroyo-Kalin (2019), Napolitano et al. (2019) Arroyo-Kalin & Riris (2021), De Souza & Riris (2021), and Bird et al. (2022). These sources have been extensively cross-checked for duplicate lab codes, variation in site naming conventions, and reported locations, in order to minimise errors arising from these variables. It does not purport to be error-free, although it is adequate for the current analysis. </p> <p>As well as its use in the production of Figure 1, the ecoregions shapefile has been intersected with the radiocarbon date locations to append this information to `rhdata.csv`. An extended description and rationale for its use can be found in the main text. </p> <p>For the convenience of the end-user, an additional file containing the main results (metrics_regular.csv) is included. The data contained in this table is the subject of section 3 of the code, Statistical Modelling. It forms the basis of the discussion in the chapter. </p> <p>Data cleaning was carried out manually on the raw output of the `resmet` function to remove false positives from the table. These "events" are either: a) statistically significant downturns present in periods where, logically, no humans should be present, e.g. in the Greater Antilles before ~6000 cal BP, or: b) downturns where there are no minima in the summed probability distributions of calibrated radiocarbon dates, returning nonsensical resilience metrics. Removing these data rows introduces errors to the variable Cumulative, which counts the cumulative number of downturns detected by the `permTest` function in `rcarbon`. The file version of the output in this repository should be considered authoritative for present purposes, as these counting errors in Cumulative have been manually fixed too. </p> <p>### References</p> <p>- Arroyo-Kalin, M. and Riris, P. 2021. Did pre-Columbian populations of the Amazonian biome reach carrying capacity during the Late Holocene? *Phil. Trans. R. Soc. B* 376: 20190715 http://doi.org/10.1098/rstb.2019.0715</p> <p>- Bird, D., Miranda, L., Vander Linden, M., Robinson, E., Bocinsky, R.K., Nicholson, C., Capriles, J.M., Finley, J.B., Gayo, E.M., Gil, A. and d’Alpoim Guedes, J. 2022. p3k14c, a synthetic global database of archaeological radiocarbon dates. *Scientific Data* 9: 1-19. https://doi.org/10.1038/s41597-022-01118-7</p> <p>- De Souza, J.G. & Riris, P. 2021. Delayed demographic transition following the adoption of cultivated plants in the eastern La Plata Basin and Atlantic coast, South America. *Journal of Archaeological Science*. 125: 105293. https://doi.org/10.1016/j.jas.2020.105293</p> <p>- Goldberg, A., Mychajliw, A.M. and Hadly, E.A. 2016. Post-invasion demography of prehistoric humans in South America. *Nature* 532: 232-235. https://doi.org/10.1038/nature17176 </p> <p>- Iriarte, J., Elliott, S., Maezumi, S.Y., Alves, D., Gonda, R., Robinson, M., de Souza, J.G., Watling, J. and Handley, J. 2020. The origins of Amazonian landscapes: Plant cultivation, domestication and the spread of food production in tropical South America. _Quaternary Science Reviews_ 248: 106582. https://doi.org/10.1016/j.quascirev.2020.106582 </p> <p>- Napolitano MF, DiNapoli RJ, Stone JH, Levin MJ, Jew NP, Lane BG, O’Connor JT, Fitzpatrick SM. 2019. Reevaluating human colonization of the Caribbean using chronometric hygiene and Bayesian modeling. _Science Advances_. 5: eaar7806. https://doi.org/10.1126/sciadv.aar7806</p> <p>- Riris, P. and Arroyo-Kalin, M. 2019. Widespread population decline in South America correlates with mid-Holocene climate change. *Scientific Reports* 9: 6850. https://doi.org/10.1038/s41598-019-43086-w</p> <p>- Riris, P. and De Souza, J.G. 2021. Formal tests for resistance-resilience in archaeological time series. _Frontiers in Ecology and Evolution_, 9. https://doi.org/10.3389/fevo.2021.740629</p> <p> </p>
Fig. 10. A in Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest
Fig. 10. A more congenial relationship: the spider Pamphobeteus sp. (Theraphosidae) and Chiasmocleis royi. Photo by Emanuele Biggi.
Fig. 9 in Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest
Fig. 9. (A) Osteocephalus cf. leprieurii infected by several fly larvae; part of the skin of the infected area was removed to show cavity with degraded tissue and one fly larva (on right); (B) Dendropsophus leali and fly larvae (Diptera) that emerged through the frog's mouth; (C) Ranitomeya uakarii infected by a maggot that emerged from a small round lesion on its back. Photos by Rudolf von May (A), Daniel Rabosky (B), and Valia Herrera (C).
Fig. 7 in Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest
Fig. 7. (A) A wandering spider (Ctenidae) preying upon Hamptophryne boliviana; (B) the spider Ancylometes sp. (Ctenidae) preying upon an adult Dendropsophus sarayacuensis; (C) giant water bug (Belostomatidae) preying upon an adult Dendropsophus minutus; the belostomatid was guarding a clutch of eggs (likely its own clutch). Photos by Erin Westeen (A) and María Isabel Díaz (B–C).
Fig. 8 in Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest
Fig. 8. (A) Stingless bees in the genus Trigona (Apidae) preying upon a clutch of tree frog eggs (Hylidae) at a temporary pond located in terra firme forest; (B) the spider Phoneutria sp. (Ctenidae) preying upon an adult Dendropsophus kamagarini. Photos by Rudolf von May (A) and Roy Santa-Cruz (B).
Fig. 6 in Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest
Fig. 6. (A) Theraphosid spider Pamphobeteus sp. (Theraphosidae) preying upon the mouse opossum Marmosops cf. noctivagus; (B) The same individual of Pamphobeteus sp. dragging the mouse opossum on the leaf litter. Photos by Maggie Grundler (A–B).
Fig. 5 in Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest
Fig. 5. (A) Juvenile snake Dipsas catesbyi with lesion caused by scolopendrid centipede (red arrow); (B) juvenile snake Micrurus obscurus, missing head and soft tissues on most anterior part of body as a result of predation by scolopendrid centipede. Photos by Joanna Larson (A–B).
Fig. 1 in Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest
Fig. 1. (A) The spider Ancylometes sp. (Ctenidae) preying upon an adult Dendropsophus leali; (B) the spider Phoneutria sp. (Ctenidae) preying on a sub-adult Hamptophryne boliviana. Photos by Emanuele Biggi (A) and Francesco Tomasinelli (B).
Fig. 4 in Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest
Fig. 4. The spider Ctenus sp. (Ctenidae) preying upon a subadult Cercosaura eigenmani. Photo by Mark Cowan.
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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.