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Fig. 5 in Long-term changes in avian relative abundances in relation to human disturbance in a tropical dry forest in central Myanmar
Fig. 5. Human detections along five, two-kilometre transects, one each in five habitats/subtypes (young dipterocarp forest, flooded dipterocarp forest, mixed deciduous forest, mature dipterocarp forest, and wetlands) per month in Chatthin Wildlife Sanctuary. Effort = number of habitat subtypes * total months sampled per year * 2 km, X-axis= year, Y-axis= human disturbance index (number of human detections per one unit of effort).
Fig. 1 in Long-term changes in avian relative abundances in relation to human disturbance in a tropical dry forest in central Myanmar
Fig. 1. Map of Chatthin Wildlife Sanctuary with land-cover changes; flooded dipterocarp forest (FL), mixed deciduous forest (MD) and young dipterocarp forest (YI) in Chatthin Wildlife Sanctuary between 1999 and 2020 and locations of bird survey points.
Fig 4 in Long-term changes in avian relative abundances in relation to human disturbance in a tropical dry forest in central Myanmar
Fig 4. Seasonal (y-axis) and long-term trends of abundances of six avian guilds in Chatthin Wildlife Sanctuary from 1999 to 2020. Redder = higher abundances, white/paler = lower abundances, and grey = no data.
Data from: Tree functional traits across Caribbean island dry forests are remarkably similar
<p>Delineation of potential dry forest and estimated actual dry forest on Caribbean islands. Potential dry forest is delineated based on CHELSA climate data (<a href="http://www.chelsa-climate.org/">www.chelsa-climate.org</a>) and the FAO definition of dry forest. Estimated actual dry forest is corrected for land cover using data from Hansen et al. (2022) <a href="https://doi.org/10.1088/1748-9326/ac46ec">https://doi.org/10.1088/1748-9326/ac46ec</a>. Areas of potential dry forest, estimated actual dry forest, and area of built-up land covers are summarized by islands and joined to CHELSA bioclimatic variables for selected islands where data on functional traits are available. Trait values by sites are also included. The package consists of data outputs and R scripts to reproduce the data outputs from identified publicly available data sources.</p>
Mapping canopy cover in African dry forests from combined use of Sentinel-1 and Sentinel-2 data: 2018 maps for Tanzania
<p>The monitoring of tropical forests has benefited from the increased availability of high-resolution earth observation data. However, the seasonality and openness of the canopy of dry tropical forests remains a challenge for optical sensors. The availability of time series of remote sensing images at 10-meters is changing this paradigm.</p> <p>In the context of REDD+ national reporting requirements, we investigated a methodology that is reproducible and adaptable in order to ensure user appropriation. The overall methodology consists of three main steps: (i) the generation of Sentinel-1 (S1) and Sentinel-2 (S2) layers, (ii) the collection of an ad-hoc training/validation dataset and (iii) the classification of the satellite data. Three different classification workflows are compared in terms of their capability to capture the canopy cover of forests in East Africa. Two types of maps are derived from these mapping approaches: i) binary tree cover/no tree cover (TC/NTC) maps, and ii) maps of canopy cover classes. The method is applied at scale, over Tanzania and one final map for each workflow is shared. Two big data computing platforms are combined to exploit the important volume of satellite data available over a yearly period.</p> <p>The reference dataset (training and validation), the three best maps and the codes to produce the S1 and S2 composites on Google Earth Engine are shared here.</p> <p>The folder “reference_dataset.zip” contains the expert based training and validation dataset. The point shapefile corresponding to the center of the plot as well as the 3x3 and 5x5 polygon shapefile are shared together with qml layer file for each type of shapefile.</p> <p>Three maps (binary TC-NTC “pixel” RF, forest type “pixel” RF and “window” ETC) are shared. A 40 km buffer from national boundaries is kept in order to let users refine their area of interest. The qml style file are also shared.</p> <p>In the “script.zip” folder, the javascript codes to generate the S1 and S2 mosaics are shared.</p>
Fig. 2 in A new species of Operculicarya H. Perrier (Anacardiaceae) from western dry forests of Madagascar
Fig. 2. – Geographic distribution of Operculicarya calcicola Randrian. & Lowry; darker areas indicate remaining natural vegetation (insert map shows the bioclimatic zones of Madagascar (after CORNET, 1974; see SCHATZ, 2000).
Fig. 1 in A new species of Operculicarya H. Perrier (Anacardiaceae) from western dry forests of Madagascar
Fig. 1. – Operculicarya calcicola Randrian. & Lowry. A. Fruiting branch; B. Detail of indument on lower surface of leaflet; C. Fruit on pedicel (lateral view); D. Fruit on pedicel (dorsal view).
Simulated treatment effects on bird communities inform landscape‐scale dry conifer forest management
<p>Human land use and climate change have increased forest density and wildfire risk in dry conifer forests of western North America, threatening various ecosystem services, including habitat for wildlife. Government policy supports active management to restore historical structure and ecological function. Information on potential contributions of restoration to wildlife habitat can allow assessment of tradeoffs with other ecological benefits when prioritizing treatments. We predicted avian responses to simulated treatments representing alternative scenarios to inform landscape‐scale forest management planning along the Colorado Front Range. We used data from the Integrated Monitoring in Bird Conservation Regions program to inform a hierarchical multispecies occupancy model relating species occupancy and richness with canopy cover at two spatial scales. We then simulated changes in canopy cover (remotely sensed in 2018) under three alternative scenarios, (1) a "fuels reduction" scenario representing landscape‐wide 30% reduction in canopy cover, (2) a "restoration" scenario representing more nuanced, spatially variable treatments targeting historical conditions, and (3) a reference, no‐change scenario. Model predictions showed areas of potential gains and losses for species richness, richness of ponderosa pine forest habitat specialists, and the ratio of specialists to generalists at two (1 km<sup>2</sup> and 250 m<sup>2</sup>) spatial scales. Under both fuels reduction and restoration scenarios, we projected greater gains than losses for species richness. Surprisingly, despite restoration more explicitly targeting ecologically relevant historical conditions, fuels reduction benefited bird species richness over a greater spatial extent than restoration, particularly in the lower montane life zone. These benefits reflected generally positive species associations with moderate canopy cover promoted more consistently under the fuels reduction scenario. In practice, contemporary forest management is likely to lie somewhere between the fuels reduction and restoration scenarios represented here. Therefore, our results inform where and how active forest management can best support avian diversity. Although our study raises questions regarding the value of including landscape‐scale heterogeneity as a management objective, we do not question the value of targeting finer-scale heterogeneity (i.e., stand and treatment level). Rather, our results combined with those from previous work clarify the scale at which targeting structural heterogeneity and historical reference conditions can promote particular ecosystem services.</p>
Fig. 2 in Croton sertanejus, a new species from Seasonally Dry Tropical Forest in Brazil, and redescription of C. echioides (Euphorbiaceae)
Fig. 2. Croton sertanejus Sodré & M.J.Silva sp. nov. A–B. Habit. C. Flowering branch showing ramifying in alternate branches. D. Inflorescence showing pistillate flowers and staminate buds. E. Pistillate flowers. F. Unisexual staminate inflorescence. G. Fruit. H–I. Fruit columella. J. Apex of columella with irregular and plane tips. K. Seed, dorsal side. L. Seed, ventral surface. A–F = Population from Oliveira dos Brejinhos, Bahia (R.C. Sodré et al. 3350, holotype; BOTU); G–L = K.N.C. Castro & J.B.A. Souza 471 (CEN). Photographs: R.C. Sodré.
Fig. 7 in Croton sertanejus, a new species from Seasonally Dry Tropical Forest in Brazil, and redescription of C. echioides (Euphorbiaceae)
Fig. 7. Cross sections of the petiole of Croton echioides Baill. and C. sertanejus Sodré & M.J.Silva sp. nov. A–E. Croton echioides. A. Median portion of the petiole. B. Detail of accessory vascular bundles. C. Detail of the epidermis, cortex and vascular cylinder. D–E. Detail of vascular cylinder, laticifers, gelatinous fibers and druses. – F–J. C. sertanejus sp. nov. F. Median portion of the petiole. G. Detail of accessory vascular bundles. H. Detail of the epidermis and cortex. I–J. Detail of vascular cylinder, gelatinous fibers and druses. Asterisks indicate laticifers. Abbreviations: av = accessory vascular bundles; cl = collenchyma; co = cortex; d = druses; ep = epidermis; f = gelatinous fibers; p = pericycle; pa = ground parenchyma; ph = phloem; pi = pith; stt = stellate trichome; vc = vascular cylinder; xy = xylem. A–E = R.C. Sodré et al. 3284 (BOTU); F–J = R.C. Sodré et al. 3350, holotype (BOTU). Scale bars: A, F = 300 µm; B–D, G–H, J = 50 µm; C = 200 µm; E, I = 20 µm.
Fig. 3 in Croton sertanejus, a new species from Seasonally Dry Tropical Forest in Brazil, and redescription of C. echioides (Euphorbiaceae)
Fig. 3. Geographical distribution of Croton echioides Baill. and C. sertanejus Sodré & M.J.Silva sp. nov. Ecoregions classified according to Dinerstein et al. (2017) (avaliable athttps://ecoregions2017.appspot.com). Abbreviations for Brazilian States: AL = Alagoas; BA = Bahia; CE = Ceará; ES = Espirito Santo; DF = Federal District; GO = Goiás; MA = Maranhão; MG = Minas Gerais; PB = Paraíba; PE = Pernambuco; PI = Piauí; RJ = Rio de Janeiro; RN = Rio Grande do Norte; SE = Sergipe; SP = São Paulo; TO = Tocantins.
Fig. 5. Croton echioides Baill. A–B. Habit. C. Flowering branch. D in Croton sertanejus, a new species from Seasonally Dry Tropical Forest in Brazil, and redescription of C. echioides (Euphorbiaceae)
Fig. 5. Croton echioides Baill. A–B. Habit. C. Flowering branch. D. Inflorescence showing pistillate flowers and staminate buds, detail of the pistillate flowers in the insert. E. Pistillate flowers. F. Median portion of an inflorescence with bisexual cymules containing one pistillate flower and one staminate bud. G. Detail of the staminate inflorescence. H. Staminate flowers. I. Staminate flowers and buds. J. Fruit. K. Fruit columella. L. Apex of columella with three slightly ascending tips. M. Seed, dorsal side. N. Seed, ventral side. A, F–I. = Population from Igaporã, Bahia (R.C. Sodré et al. 3284; BOTU); B–E. = Population from Abaíra, Bahia (R.C. Sodré et al. 3314; BOTU); J–N. = V.C. Souza et al. 5495 (ESA). Photographs: R.C. Sodré.
Fig. 3 in Javan mongoose (Herpestes javanicus) abundance and spatial ecology in a degraded dry dipterocarp forest
Fig. 3. Map of Sakaerat Biosphere Reserve with radio tracked (December 2019 to January 2021) Javan mongoose (Herpestes javanicus) home ranges and prey grids (PG). 95% utilisation contours (U.C) for male (M6, M1) and female (F1) mongooses are labelled in the legend. 50% U.C are solid line circles within each individual's home range. Prey grids collected ground-dwelling invertebrate mass as well as rodent biomass within the DDF (October to December 2020). Stars indicate where only ground-dwelling invertebrates were collected. Triangles indicate areas where sweep netting for invertebrates occurred in addition to sampling for rodent biomass and ground-dwelling invertebrates.
Fig. 1 in Javan mongoose (Herpestes javanicus) abundance and spatial ecology in a degraded dry dipterocarp forest
Fig. 1. Map and location of Sakaerat Biosphere Reserve with camera trap stations used to estimate Javan mongoose (Herpestes javanicus) abundance in 2017. Prey grid stations were used to calculate yearly averaged rodent biomass from January 2017 to November 2017.
Fig. 6 in Croton sertanejus, a new species from Seasonally Dry Tropical Forest in Brazil, and redescription of C. echioides (Euphorbiaceae)
Fig. 6. Cross sections of the leaf blade of C. echioides Baill. (A, E–I, N–Q) and C. sertanejus Sodré & M.J.Silva sp. nov. (B–D, J–M, R–V). A. Median portion of the leaf blade of C. echioides, note the stipitate trichomes of abaxial surface in lateral view. B. Median portion of the leaf blade of C. sertanejus, note the sessile trichomes of abaxial surface in lateral view. C. Leaf margin of C. sertanejus, note simple trichomes of adaxial surface. D. Base of the trichome of adaxial surface of C. sertanejus. E. Vascular bundle of C. echioides. F–H. Median portion of the leaf blade of C. echioides. I. Leaf margin of C. echioides. J. Vascular bundle of C. sertanejus. K–L. Median portion of the leaf blade of C. sertanejus. M. Leaf margin of C. sertanejus. N. Primary vein of C. echioides. O. Detail of vascular cylinder of C. echioides primary vein. P. Collenchyma in adaxial surface of C. echioides primary vein. Q. Detail of the vascular bundle, note xylem, phloem, laticifer and druse. R. Primary vein of C. sertanejus. S. Detail of vascular cylinder of C. sertanejus primary vein. T. Collenchyma in adaxial surface of C. echioides primary vein. U. Detail of the epidermis and cortex of C. echioides primary vein. V. Detail of the vascular bundle, note xylem, phloem and druse. Arrowheads indicate stomata; asterisks indicate laticifers. Abbreviations: cl = collenchyma; co = cortex; d = druses; ep = epidermis; i = idioblasts; pa = ground parenchyma; ph = phloem; pp = palisade parenchyma; sp = spongy parenchyma; st = simple trichome; stt = stellate trichome; vb = vascular bundle; vc = vascular cylinder; xy = xylem. A, E–I, N–Q = R.C. Sodré et al. 3284 (BOTU); B–D, J–M, R–V = R.C. Sodré et al. 3350, holotype (BOTU). Scale bars: A–C, N, R = 200 µm; D–G, I–M, P–Q, T–V = 50 µm; H = 20 µm; O, S = 100 µm.
Fig. 1 in Croton sertanejus, a new species from Seasonally Dry Tropical Forest in Brazil, and redescription of C. echioides (Euphorbiaceae)
Fig. 1. Croton sertanejus Sodré & M.J.Silva sp. nov. A. Flowering branch. B. Detail of older portion of stem with leaf scars. C 1 –C 2. Indumentum of the stems. C 1. Tomentose indumentum. C 2. Hirsute indumentum. D 1 –D 3. Trichomes of the stems. D 1. Stellate trichome. D 2. Multiradiate-porrect trichome. D 3. Stellate-porrect trichome. E. Stipule, ventral surface. F 1 –F 2. Leaves. F 1. Elliptic leaf blade. F 2. Ovate leaf blade. G. Detail of the galls on the leaf blade. H. Extrafloral nectaries of leaf base in adaxial view. I. Colleters of leaf margin in adaxial view. J1–J3. Indumentum of leaf blades. J1. Tomentose indumentum of abaxial surface. J2. Sparse indumentum of simple, stellate-porrect or 2-radiate trichomes of adaxial surface. J 3. Sparse indumentum of stellate trichomes of adaxial surface. K. Inflorescence. L 1. Staminate flower bract, ventral surface. L 2. Staminate flower bracteole, ventral surface. M. Staminate flower. N 1 – N 3. Lobes of staminate flower calyx in dorsal view. N 1. Two lobes showing the union of the calyx. N 2. Dense indumentum of stellate-porrect trichomes. N3. Sparse indumentum of stellate-porrect trichomes. O 1 –O 2. Pistillate flower petals in dorsal view. O 1. Obovate petal. O 2. Oblanceolate petal. P. Stamen. Q 1. Pistillate flower bract, ventral surface. Q 2. Pistillate flower bracteole, ventral surface. R. Pistillate flower. S 1 –S 2. Pistillate flower sepal. S 1. Dorsal view. S 2. Ventral view. T. Gynoecium. U. Nectary disk and reduced petals of the pistillate flowers (cut out sepals and gynoecium removed). V. Fruit. W 1. Fruit columella. W2. Apex of columella with irregular and plane tips. W3. Apex of columella with three slightly ascending tips. X 1. Seed, dorsal side. X2. Seed, ventral side. Drawing by Renato Galhardo: A–U = R.C. Sodré et al. 3350, holotype (BOTU); V–X = K.N.C. Castro & J.B.A. Souza 471 (CEN).
Fig. 4. Croton echioides Baill. A. Flowering branch. B in Croton sertanejus, a new species from Seasonally Dry Tropical Forest in Brazil, and redescription of C. echioides (Euphorbiaceae)
Fig. 4. Croton echioides Baill. A. Flowering branch. B. Detail of the indumentum of the stems and stipule. C 1 –C 2. Trichomes of the stems. C 1. Stellate-rotate trichome. C 2. Stellate-porrect trichome. D 1 –D 2. Stipules. D1. Surface. D 2. Ventral surface. E 1–E3. Leaves, note the variation in the shape of the leaf blades and in the length of the petioles. F1–F3. Extrafloral nectaries of leaf base in abaxial view. F1. Stipitatepatelliform. F 2. Obconic. F 3. Cylindric. G. Colleters of leaf margin in adaxial view. H 1. Leaf indumentum of the abaxial surface. H 2. Leaf indumentum of the adaxial surface. I. Inflorescence. J 1. Staminate flower bract, ventral surface. J 2. Staminate flower bracteole, ventral surface. K. Staminate flower. L 1 –L 2. Lobes of staminate flower calyces in dorsal view. L1. Dense indumentum. L2. Sparse indumentum. M1–M2. Staminate flower petals in dorsal view. M1. Obovate petal. M2. Oboval-oblanceolate petal. N. Stamen. O 1. Pistillate flower bract, ventral surface. O 2 –O 3. Pistillate flower bracteoles, ventral surface. P. Pistillate flower. Q. Pistillate flower in upper view showing ventral surface of the sepals, disk and reduced petals (gynoecium removed), note the unequal sepals. R 1 –R 2. Indumentum of ventral surface of the pistillate flower sepals. S. Pistillate flower in lower view showing dorsal surface of sepals. T. Indumentum of dorsal surface of the pistillate flower sepals. U. Gynoecium. V. Nectary disk and reduced petals of the pistillate flowers (cut out sepals and gynoecium removed). W. Fruit. X 1. Fruit columella. X 2. Apex of columella with plane tips. X 3. Apex of columella with three slightly ascending tips. Y 1. Seed, dorsal side. Y 2. Seed, ventral side. Drawing by Renato Galhardo: A, E2, F1 = E. Melo et al. 7571 (HUEFS); E1, F3, O1–V = R.C. Sodré et al. 3284 (BOTU); B–D2, G–N = R.C. Sodré et al. 3314 (BOTU); E3, F2, W–Y2 = V.C. Souza et al. 5495 (ESA).
Figure 3 in Woody species distribution across a savanna-dry forest soil gradient in the Brazilian Cerrado
Figure 3. Proportional occurrence of 51 woody species across 30 plots ordinated by the soil gradient of aluminum saturation and base saturation (RDA axis 1, see Figure 1) in a savanna-dry forest transition. Grey and black bars correspond to cerrado stricto sensu and dry forest plots, respectively.
Figure 2 in Woody species distribution across a savanna-dry forest soil gradient in the Brazilian Cerrado
Figure 2. Topography and the gradients of aluminum saturation, base saturation, and phosphorus across 30 plots (rectangles, 10×40 m) in a 4.5 ha area of contact between the cerrado stricto sensu (SA) and dry forest (DF) physiognomies.
Figure 1 in Woody species distribution across a savanna-dry forest soil gradient in the Brazilian Cerrado
Figure 1. Biplot of tb-RDA for woody species composition, and relationships with edaphic (P = phosphorous; A = aluminum saturation; B = base saturation) and spatial (M1 and M2) variables, among plots in cerrado stricto sensu (gray) or dry forest (black) physiognomies.
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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)
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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.