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Fig. 9 in Centrohelid Heliozoans (Centroplasthelida Febvre-Chevalier et Febvre, 1984) from Different Types of Freshwater Bodies in the Middle Russian Forest-steppe
Fig. 9. Dendrogram showing the Bray-Curtis similarity (%) of studied water bodies by species diversity of centrohelids.
Рис. 1. Географическое поΛожение Норского заповеΑника (А) и картосхема распоΛожения на его территории (Б) учетных пΛощаΑок с фитоценозами (L_1–L_7) на Αвух мониторинговых станциях (I–II). I — МаΛьцевская: L_1 — березняк с участием осины и Λиственницы рябинниковый вейниково-разнотравный; L_2 — осиново-беΛоберезовый рябинниковый вейниково-разнотравный Λес; L_3 — Λиственничник с участием березы пΛоскоΛистной осоково-вейниковый с разнотравьем; L_4 — беΛоберезово-Λиственничный с примесью осины роΑоΑенΑроновый бруснично-осоковый Λес; L_5 — закустаренный, преимущественно тавоΛгой ивоΛистной, разнотравно-вейниковый Λуг. II — Антоновская: L_6 — Λиственничник роΑоΑенΑроново-брусничный; L_7 — Λиственнично-беΛоберезовый с примесью пихты и еΛи закустаренный разнотравно-вейниковый Λес (коΑ типа местообитания соответствуют таковому в табΛ. 1 и 3 и на рис. 2) Fig. 1. Geographical location of the Norsky Nature Reserve (A) and the map (B) of registration sites with phytocenoses (L_1–L_7) at two monitoring stations (I–II). I — Maltsevskaya: L_1 — birch forest with aspen and larch, fieldfare reed-forb; L_2 — aspen-white-birch, fieldfare reed-forb forest; L_3 — larch forest with flat-leaved sedge-reed birch with forbs; L_4 — white-birch-larch with an admixture of aspen rhododendron lingonberry-sedge forest; L_5 — bushy, mostly meadowsweet, forb-reed grass meadow. II — Antonovskaya: L_6 — rhododendron-cowberry larch forest; L_7 — larch-white-birch with fir and spruce, shrubby forb-reed grass forest (the code of the habitat type corresponds to that in Tables 1 and 3 and in Fig. 2) in Structure and dynamics of the taxocenes of shrews in different habitats of the Norsky nature reserve
Рис. 1. Географическое поΛожение Норского заповеΑника (А) и картосхема распоΛожения на его территории (Б) учетных пΛощаΑок с фитоценозами (L_1–L_7) на Αвух мониторинговых станциях (I–II). I — МаΛьцевская: L_1 — березняк с участием осины и Λиственницы рябинниковый вейниково-разнотравный; L_2 — осиново-беΛоберезовый рябинниковый вейниково-разнотравный Λес; L_3 — Λиственничник с участием березы пΛоскоΛистной осоково-вейниковый с разнотравьем; L_4 — беΛоберезово-Λиственничный с примесью осины роΑоΑенΑроновый бруснично-осоковый Λес; L_5 — закустаренный, преимущественно тавоΛгой ивоΛистной, разнотравно-вейниковый Λуг. II — Антоновская: L_6 — Λиственничник роΑоΑенΑроново-брусничный; L_7 — Λиственнично-беΛоберезовый с примесью пихты и еΛи закустаренный разнотравно-вейниковый Λес (коΑ типа местообитания соответствуют таковому в табΛ. 1 и 3 и на рис. 2) Fig. 1. Geographical location of the Norsky Nature Reserve (A) and the map (B) of registration sites with phytocenoses (L_1–L_7) at two monitoring stations (I–II). I — Maltsevskaya: L_1 — birch forest with aspen and larch, fieldfare reed-forb; L_2 — aspen-white-birch, fieldfare reed-forb forest; L_3 — larch forest with flat-leaved sedge-reed birch with forbs; L_4 — white-birch-larch with an admixture of aspen rhododendron lingonberry-sedge forest; L_5 — bushy, mostly meadowsweet, forb-reed grass meadow. II — Antonovskaya: L_6 — rhododendron-cowberry larch forest; L_7 — larch-white-birch with fir and spruce, shrubby forb-reed grass forest (the code of the habitat type corresponds to that in Tables 1 and 3 and in Fig. 2)
Fig. 2. Fresh specimen photos for West Indian Ocean II Group type A in Fig. 4 in Responses of Phyllostomid Bats to Traditional Agriculture in Neotropical Montane Forests of Southern Mexico.
Fig. 2. Fresh specimen photos for West Indian Ocean II Group type A (WIO IIA) and West Indian Ocean II Group type B (WIO IIB), and western Arabian type (WA), and the posterior part of the soft dorsal fin. Scale bar = 5 cm.
Figure 5 in Diversity of bats in three selected forest types in Peninsular Malaysia
Figure 5. Species accumulation curves indicating the cumulative number of species encountered relative to sampling time.
Figure 1 in Diversity of bats in three selected forest types in Peninsular Malaysia
Figure 1. Map showing three sampling localities: the primary forest, secondary forest of Ulu Gombak Forest Reserve, Selangor, and urban forest at Universiti Malaya Rimba Ilmu Botanical Garden, Kuala Lumpur.
Fig. 1. Location and vegetation types where small mammals were sampled between November 2012 and September 2013 in Small mammals from the lasting fragments of Araucaria Forest in southern Brazil: a study about richness and diversity
Fig. 1. Location and vegetation types where small mammals were sampled between November 2012 and September 2013, at Piraí do Sul National Forest, ParanÁ state, Brazil (A, Pine Plantation; B, Riparian Forest; C, Araucaria Plantation; D, Natural Regeneration forest; E, High Altitude forest). Original distribution of Atlantic Forest biome (light gray) and Araucaria forest (dark gray).
Figure 1 in Seasonality and bait type driving the diversity of dung beetle (Scarabaeidae: Scarabaeinae) communities in urban remnants of the Atlantic Forest
Figure 1. Partial map of the state of Pernambuco, with emphasis on the remnants of the Atlantic Forest (Green) and the urban area (Pink) located on the outskirts of FURB Jaguarana in the municipality of Paulista and APA Aldeia-Beberibe in the municipality of Camaragibe, PE, Brazil.
Figure 3 in Seasonality and bait type driving the diversity of dung beetle (Scarabaeidae: Scarabaeinae) communities in urban remnants of the Atlantic Forest
Figure 3. Canonical Correspondence Analysis (CCA) with group formations related to separation and types of baits used in the collection of dung beetles at FURB Jaguarana (A) and APA Aldeia-Beberibe (B).
Figure 2 in Seasonality and bait type driving the diversity of dung beetle (Scarabaeidae: Scarabaeinae) communities in urban remnants of the Atlantic Forest
Figure 2. Differences between diversity index values (q0, q1, q2) for different types of baits (feces, carrion, millipedes) in the rainy and dry season at FURB Jaguarana (A) and APA Aldeia-Beberibe (B). Meaningfulness: <0.001'***'; <0.01'**'; <0.05'*'.
Text-fig. 6. The riparian/swamp forest structure of the village of Sakarcaören in the late Miocene, location within the east part of GVP, and comparison with the other forest types from early Miocene of GVP (Akkemik et al. 2009, 2016, 2017, Bayam et al. 2018). in The First Glyptostroboxylon And Taxodioxylon Descriptions From The Late Miocene Of Turkey And Palaeoclimatological Evaluation
Text-fig. 6. The riparian/swamp forest structure of the village of Sakarcaören in the late Miocene, location within the east part of GVP, and comparison with the other forest types from early Miocene of GVP (Akkemik et al. 2009, 2016, 2017, Bayam et al. 2018).
Floristic composition in three different forest types in western Amazonia
<p><span><span>Aim</span></span><span>: The latitudinal gradient is considered a first-order biogeographical pattern for most taxonomic groups. Yet, latitudinal changes in plant ecological communities are not always consistent, and this could be related to the physical and biological characteristics of different forest types. In this study, we compare latitudinal changes in floristic diversity (alpha diversity), composition (beta diversity), and dominance across different tropical forest types: floodplain, <em>terra</em> <em>firme</em>, and submontane forests. </span></p> <p><span><span>Location</span></span><span>: Western Amazonia (Ecuador, Peru, and Bolivia).</span></p> <p><span><span>Taxon</span>: Woody plants. </span></p> <p><span><span>Methods</span></span><span>: We inventoried 1,978 species and 31,203 individuals of vascular plants with a diameter at breast height ≥ 2.5 cm in 118 0.1-ha plots over a 1,800-km latitudinal gradient in three different forest types. The relationships between alpha diversity, latitude, and forest type were analysed using generalised linear mixed models (GLMMs). Semi-parametric permutational multivariate analysis of variance was used to investigate the effects of latitude and forest type on beta diversity. Dominant species abundances were correlated with non-metric multidimensional scaling ordination axes to reflect their contributions in shaping changes in beta diversity. </span></p> <p><span><span>Results</span></span><span>: Alpha diversity increased towards equatorial latitudes in <em>terra</em> <em>firme</em> and submontane forests but remained relatively constant in floodplains. Beta diversity of all forest types changed with latitude, although less clearly in floodplains. Overall, the abundances of dominant species decreased towards the Equator, though in floodplains they were more homogeneous along the gradient.</span></p> <p><span><span>Main conclusions</span></span><span>: Alpha diversity, beta diversity and dominance patterns differed across forest types. In floodplain forests, the flooding regime is a strong predictor of floristic composition, which maintains alpha diversity constant along the latitudinal gradient. However, alpha and beta diversity in unflooded forests increase steadily towards equatorial latitudes. Furthermore, we found fewer dominant species contributing to changes beta diversity in floodplain forests. Shifts in abundance of dominant species over gradients can explain how beta diversity is driven differently per forest type.</span></p>
Forest Site Types 2070-2099
<p>The shapefiles show two scenarios of forest site type suitability for 2070-2099 in the Canton of Bern, Switzerland, based on the altitudinal vegetation belt scenarios for the concentration pathways RCP4.5 and RCP8.5 (Zischg et al. 2021). </p>
Meta-analysis shows forest soil CO2 effluxes are dependent on the disturbance regime and biome type
<p class="MsoNormal"><span>F</span><span>orest </span><span>s</span><span>oil CO<sub>2</sub> efflux (F</span><span>CO<sub>2</sub></span><span>)</span><span> is a crucial process in global carbon cycling; however, how F</span><span>CO<sub>2</sub></span><span> responds to disturbance regimes in different forest biomes is poorly understood. </span><span>W</span><span>e quantif</span><span>ied</span><span> the effects of disturbance regimes on F</span><span>CO<sub>2</sub></span><span> </span><span>across boreal, temperate, tropical, and</span><span> Mediterranean</span><span> forests</span><span> based on 1240 observations from 380 studies. Globally, climatic perturbations such as elevated CO<sub>2</sub> concentration, warming, and increased precipitation increase F</span><span>CO<sub>2</sub></span><span> </span><span>by 13 to 25%. F</span><span>CO<sub>2</sub></span><span> is increased by forest conversion to grassland and elevated carbon input by forest management practices but reduced by decreased carbon input, fire, and acid rain. Disturbance also changes soil temperature and water content, which in turn affect the direction and magnitude of disturbance influences on F</span><span>CO<sub>2</sub></span><span>. F</span><span>CO<sub>2</sub></span><span> is disturbance- and biome-type dependent, and such effects should be incorporated into earth system models to improve the projection of the feedback between the terrestrial C cycle and climate change.</span></p>
Fig. 8. Peruvian vegetation types. A. Amazonian forest, Pasco Region. B. Northwest Peruvian montane forest, Piura Region. C. Dry forest, Piura Region. D in The genus Begonia (Begoniaceae) in Peru
Fig. 8. Peruvian vegetation types. A. Amazonian forest, Pasco Region. B. Northwest Peruvian montane forest, Piura Region. C. Dry forest, Piura Region. D. Lomas, Lima Region. All photographs taken by P.W. Moonlight.
Carbon storage and carbon-equivalent albedo impact for US forests, by age and forest type
<p>These tables document estimates of carbon storage (Mg/ha +/- Standard Error) and carbon-equivalent albedo impacts (same units) of US forests by age and forest type (Healey et al., in review). Carbon estimates are derived from field measurements made by the USDA Forest Service on approximately 125,000 forested field plots (Domke et al., 2022). Soil organic carbon is omitted from these estimates, but all other above- and below-ground pools are included. Albedo impacts (time-dependent emissions equivalent, TDEE; Bright et al., 2016) were developed by applying atmospheric kernels (Bright and O'Halloran) to a new Landsat blue sky albedo product for the Landsat archive (Erb et al., 2022), as described by Healey et al. (in review). Standard error is supplied for each age/forest type bin for carbon storage, but upper and lower standard error bounds are specified for TDEE because log transformation creates an asymmetrical uncertainty envelope. </p> <p> </p> <p>Bright, Bogren, Bernier, Astrup, (2016). Carbon-equivalent metrics for albedo changes in land management contexts: Relevance of the time dimension. <em>Ecol. Appl.</em> 26, 1868–1880</p> <p>Bright, R. M., & O'Halloran, T. L. (2019). Developing a monthly radiative kernel for surface albedo change from satellite climatologies of Earth's shortwave radiation budget: CACK v1. 0. <em>Geoscientific Model Development, </em>12(9), 3975-3990.</p> <p>Domke, Walters, Nowak, Greenfield, Smith, Nichols, Ogle, Coulston, Wirth (2022). Greenhouse Gas Emissions and Removals From Forest Land, Woodlands, Urban Trees, and Harvested Wood Products in the United States, 1990–2020. (US Dept. Ag. For. Service, Madison, WI; <a href="https://doi.org/10.2737/FS-RU-382">https://doi.org/10.2737/FS-RU-382</a>).</p> <p>Erb, Li, Sun, Paynter, Wang, & Schaaf, (2022). Evaluation of the Landsat-8 Albedo Product across the Circumpolar Domain. <em>Remote Sensing</em>, <em>14</em>(21), 5320.</p> <p>Healey, Yang, Erb, Bright, Domke, Frescino, Schaaf, (in review) New satellite observations expose albedo dynamics offsetting half of carbon storage benefits in US forests.</p>
Data from: Fungal energy channeling sustains soil animal communities across forest types and regions
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Data from: Temporal variation of soil microarthropods in different forest types and regions of Central Europe
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Meta-analysis shows forest soil CO2 effluxes are dependent on the disturbance regime and biome type
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Floristic composition in three different forest types in western Amazonia
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Data from: Historical reindeer corrals in northern boreal forests reveal divergent post-disturbance reorganization by forest type
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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.