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FIGURE 3 in Land-use changes affect the functional structure of stream fish assemblages in the Brazilian Savanna
FIGURE 3 | Predictions tested using structural equation modeling, indicating the expected pathways (arrows) for the effects of catchment degradation (CDI) on stream physical habitat and, consequently, on the functional structure of the fish assemblages. Land use is expected to influence the functional diversity mediated by alterations in habitat heterogeneity and stability (A), and to influence functional identity, mediated by changes in habitat type (B). Arrows indicate expected effects between predictive and response variables, which can be positive (black continuous line), negative (gray continuous line) or non-directional (dashed lines). For physical-habitat codes, calculation and ecological meaning, see Tab. 1.
FIGURE 1 in Land-use changes affect the functional structure of stream fish assemblages in the Brazilian Savanna
FIGURE 1 | Headwater streams (N = 40; black dots) sampled for fish and local physical habitat. All sites drain to Nova Ponte Reservoir in the Araguari River basin, Upper Paraná River, Minas Gerais, Brazil.
Data for: Widespread forest-savanna coexistence but limited bistability at a landscape scale in Central Africa
<p>This directory contains the data used in the article **Zwaan et al. (2024) Widespread forest-savanna coexistence but limited bistability at a landscape scale in Central Africa** (DOI: <span><a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1088%2F1748-9326%2Fad8cef&data=05%7C02%7Ca.zwaan%40uu.nl%7C66d868876ad44e69715608dcf9c1c197%7Cd72758a0a4464e0fa0aa4bf95a4a10e7%7C0%7C0%7C638659857776731023%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=3Bk8nBksr5ZBWJF4nfBvx3yp1tbyZiy%2FLlnfwDCZwfE%3D&reserved=0">https://doi.org/10.1088/1748-9326/ad8cef</a></span>).</p> <p>This repository provides the datasets used for the figures and statistics in our research article. We hope that this data can be useful for other researchers. Feel free to explore and analyze the data as needed. If you use this data in your own research, please cite our article.</p> <p><br>**Contact**: For any questions or further information, please contact:<br>* Aart Zwaan<br>* Email: a.zwaan@uu.nl</p>
FIG. 2 in Distribution and conservation of Paepalanthus Mart. sect. Diphyomene Ruhland (Eriocaulaceae) in Neotropical savannas
FIG. 2. — Geographic distributions of: A, P. koernickei (Ruhland) Trovó (●), P. linearis Trovó (■), and P. longiciliatus Trovó (�); B, P. arcua- tus Trovó (●), P. cordatus Ruhland (■), and P. decussus Koern. (�); C, P. macer Trovó (●), P. brevis (■), and P. polycladus Silveira (�); D, P. sericiscapus Trovó (●), P. flexuosus Trovó (■), and P. urbanianus Ruhland (�).
FIG. 1 in Distribution and conservation of Paepalanthus Mart. sect. Diphyomene Ruhland (Eriocaulaceae) in Neotropical savannas
FIG. 1. — Geographic distribution of: A, Paepalanthus sect. Diphyomene (�); B, P. chiquitensis Herzog (�); C, P. erectifolius Silveira (�) and P. stellatus Trovó (�); D, P. acanthophyllus Ruhland (�) and P. amoenus (Bong.) Koern. (�).
Fig. 6 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 6. Proportion of autochthonous feeding items (black) and allochthonous (gray) with respect to the rainy (C) and dry (S) seasons for the fish species that presented this significant variation. Species abbreviations: Aspidoras fuscoguttatus (aspfus), Astyanax sp. (astsp), Characidium xanthopterum (chaxan), Hasemania sp. (hassp), Hyphessobrycon balbus (hypbal), Heptapterus sp. (hepsp), Knodus moenkhausii (knomoe), Kolpotocheirodon theloura (kolthe), Moenkhausia sp. (moesp), Phalloceros harpagos (phahar), Planaltina myersi (plamye), Rhamdia quelen (rhaque) and Rivulus pictus (rivpic)..
Fig. 1 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 1. Localization of the Brasília National Park in the Distrito Federal and distribution of sampling sites in the Bananal stream subbasin, Paranoá Lake basin, DF.
Fig. 5 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 5. Feeding items distributed according to the frequency of fish species occurrence (axis X) and relative abundance (axis Y), based upon the method proposed by Amundsen et al (1996): Moenkhausia sp., Phalloceros harpagos, Planaltina myersi, Rhamdia quelen and Rivulus pictus. The number of analyzed stomachs is shown in parentheses.
Fig. 4 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 4. Feeding items distributed according to the frequency of fish species occurrence (axis X) and relative abundance (axis Y), based upon the method proposed by Amundsen et al (1996): Aspidoras fuscoguttatus, Astyanax sp., Characidium xanthopterum, Hasemania sp., Hyphessobrycon balbus, Heptapterus sp., Knodus moenkhausii and Kolpotocheirodon theloura. The number of analyzed stomachs is shown in parentheses.
Fig. 2 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 2. General view of sites 1 to 7 sampled at the Bananal stream subbasin, Paranoá Lake basin, DF.
Fig. 3. Non-metric multidimensional scaling analysis for the 13 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF
Fig. 3. Non-metric multidimensional scaling analysis for the 13 more abundant fish species' diet found in the Bananal stream subbasin, Paranoá Lake basin, DF. Indication of four groups A, B, C and D. Species abbreviations: Aspidoras fuscoguttatus (aspfus), Astyanax sp. (astsp), Characidium xanthopterum (chaxan), Hasemania sp. (hassp), Hyphessobrycon balbus (hypbal), Heptapterus sp. (hepsp), Knodus moenkhausii (knomoe), Kolpotocheirodon theloura (kolthe), Moenkhausia sp. (moesp), Phalloceros harpagos (phahar), Planaltina myersi (plamye), Rhamdia quelen (rhaque) and Rivulus pictus (rivpic).
Fig. 2 in Influence of the riparian zone phytophysiognomies on the longitudinal distribution of fishes: evidence from a Brazilian savanna stream
Fig. 2. Two-dimension ordinations based on Jaccard similarity coefficient (a) and on Bray-Curtis (b), considering the ten samples from the wet and dry seasons from the Correntes stream, central west Brazil.
Fig. 1 in Influence of the riparian zone phytophysiognomies on the longitudinal distribution of fishes: evidence from a Brazilian savanna stream
Fig. 1. Map showing localization of the sampled reaches of Correntes stream in the plateau region of the Paraguay basin, Mato Grosso do Sul State, Brazil.
Variation in biomass allocation and root functional parameters in response to fire history in Brazilian savannas
<p>Dataset associated with the manuscript "<strong>Variation in biomass allocation and root functional parameters in response to fire history in Brazilian savannas" </strong> (Le Stradic et al.). It includes 5 different datasets and for each one we provided metadata.</p> <p>above_below_b_SBI: it includes data related to aboveground and belowground biomass. Aboveground data were collected in circular plots of 0.5m2 and belowground biomass was collected using an auger of 5cm of diameter, every 10cm up to 40cm and every 20cm up to 1m depth. See the method section in the manuscript for full details.</p> <p>below_b_wet_all_SBII: it includes data related to belowground biomass (collected in the first 1m of soil, during the wet season, January-February 2018), including values for each soil depth.</p> <p>root_trait_SBI: it includes all root functional parameters for samples collected in the first 10 cm of soil.</p> <p>Sampling_data: it includes information associated with sampling areas (localization, GPS point, fire history).</p> <p>soil.expand.SBI: it includes all soil data.</p> <p> </p> <p><strong>Abstract</strong></p> <ol> <li>Fire is a fundamental ecological factor in savannas because it affects vegetation dynamics and ecosystem functioning. However, the effects of fire on belowground compartments, including biomass and root traits, and their regeneration remain poorly understood. In this study, we assess the variation of above- and belowground plant components along fire-history gradients in Brazilian open savannas and investigate whether vegetation and soil composition changes are associated with the responses of belowground biomass and root traits.</li> <li>The study was conducted in eight sampling areas of open savanna (<em>campo sujo</em>) the Cerrado (Brazilian savannas), located along a gradient of time since the last fire (1–34 years); the number of fires that occurred within the past 34 years (0–9 fires) varied by sampling area. In each sampling area, we measured above- and belowground biomass, root depth distribution, root functional parameters, and nutrient levels in the upper soil layers (0–10 cm).</li> <li>Rapid recovery of aboveground live biomass after a fire was primarily due to resprouting of graminoids. This recovery was associated with an increase in absorptive root biomass in the upper soil layer in the most recently burnt sites, whereas root biomass was unaffected in deeper layers. Root parameters remained constant regardless of fire history but responded to variations in vegetation structure and soil resources. Specific root length (SRL) decreased with K, Mg<sup>2+</sup>, Al<sup>3+</sup>, N, and C and increased with P concentration. In contrast, root tissue density (RTD) and absorptive root proportion were negatively correlated with soil P. RTD was strongly associated with the aboveground biomass of graminoids. Soil texture impacted the root system: the proportion of absorptive root increased with fine sand content in the soil, inversely to transport root biomass. The relationship between fire and soil composition was insignificant.</li> <li><em>Synthesis</em>. In savannas, fire stimulates absorptive root biomass in response to the higher demand for belowground resources. This response is correlated with shoot regrowth after a fire. Variations in morphological root parameters are not directly associated with fire history; instead, they reflect differences in soil chemistry, especially soil P and graminoid biomass changes.</li> </ol>
Worldwide savanna monkey (Chlorocebus spp.) body measures
<p>Objectives: Direct comparative work in morphology and growth on widely dispersed wild primate taxa is rarely accomplished, yet critical to understanding ecogeographic variation, plastic local varia- tion in response to human impacts, and variation in patterns of growth and sexual dimorphism. We investigated population variation in morphology and growth in response to geographic variables (i.e., latitude, altitude), climatic variables (i.e., temperature and rainfall), and human impacts in the vervet monkey (<em>Chlorocebus</em> spp.).</p> <p>Methods: We trapped over 1,600 wild vervets from across Sub-Saharan Africa and the Caribbean, and compared measurements of body mass, body length, and relative thigh, leg, and foot length in four well-represented geographic samples: Ethiopia, Kenya, South Africa, and St. Kitts & Nevis.</p> <p>Results: We found significant variation in body mass and length consistent with Bergmann's Rule in adult females, and in adult males when excluding the St. Kitts & Nevis population, which was more sexually dimorphic. Contrary to Rensch's Rule, although the South African population had the largest average body size, it was the least dimorphic. There was significant, although very small, variation in all limb segments in support for Allen's Rule. Females in high human impact areas were heavier than those with moderate exposures, while those in low human impact areas were lighter; human impacts had no effect on males.</p> <p>Conclusions: Vervet monkeys appear to have adapted to local climate as predicted by Bergmann's and, less consistently, Allen's Rule, while also responding in predicted ways to human impacts. To better understand deviations from predicted patterns will require further comparative work in vervets.</p>
High-resolution large weighing lysimeter measurements with meteorological and soil-hydrological variables from a Mediterranean Savanna
<p>Raw and processed lysimeter weighing and flux data at the instrumental site ES-LMa of six large high-precision weighing lysimeters in a Mediterranean Savanna ecosystem for the period from 2019-06-01 to 2020-05-31. Additionally, meteorological and radiometric data are provided. Additionally, code for the lysimeter processing is provided.</p> <p>Reproducible workflow of the article <strong>Paulus et al. 2022: Resolving seasonal and diel dynamics of non-rainfall water inputs in a Mediterranean ecosystem using lysimeters. HESS, https://doi.org/10.5194/hess-2021-519</strong></p> <p>Variables, units and detailed description are found in the README.html file.</p>
Variation in herbivore space use: comparing two savanna ecosystems with different anthrax outbreak patterns in southern Africa
<p><span>Background</span></p> <p><span>The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen. </span></p> <p><span>Methods</span></p> <p><span>We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and</span><span> Kruger National Park, South Africa, where the main host species and outbreak sizes differ</span><span>. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species. </span></p> <p><span>Results</span></p> <p><span>Range size differences among species were not linearly related to anthrax case numbers. In Kruger t</span><span>he main host species </span><span>had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. </span><span>Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent.</span></p> <p><span>Conclusions</span></p> <p><span>Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens. </span></p>
Benthic macroinvertebrates in a protected area within the Brazilian savanna
<p><strong>This dataset is part of manuscript: <em>Vanishing springs and benthic macroinvertebrates as environmental quality indicators in a savanna protected area, Brazil</em></strong><br> <br> In the Neotropics, especially in southeastern Brazil, due to sugarcane and eucalypt monocultures, and the expansion of industries and the largely unplanned urban centers entire aquatic ecosystems are threatened. Nonetheless, benthic macroinvertebrates are important biomonitoring tools to assess the biotic and abiotic condition of endangered freshwater environments. In this study we address how benthic macroinvertebrate diversity respond to the combined effect of local environmental factors. We also aimed to evaluate how benthic macroinvertebrates diversity respond according to the habitat integrity. We expected to find higher diversity in the sampling sites with higher habitat integrity (i.e., low potential of hydrogen, electrical conductivity and water temperature, and high canopy coverage and concentration of dissolved oxygen). By using a multivariate approach (i.e., PCA) and a regression analysis (i.e., Linear Mixed-Effect Model) we were able to address the combined effect of local environmental variables on the benthic macroinvertebrate community. Our results show a negative effect of the environmental factors on the benthic macroinvertebrate diversity. As expected, sites with higher integrity and water quality values according to, respectively, the Habitat Integrity Index (i.e., HII) and the Biological Monitoring Working Party (i.e., BMWP’) tended to have higher benthic macroinvertebrates diversity. This is the first report that provides knowledge of the benthic macroinvertebrate community in the Paulicéia river, within the Cerrado Pé-de-Gigante, a conservation unity of full protection of a State Park in the Neotropics.In the Neotropics, especially in southeastern Brazil, due to sugarcane and eucalypt monocultures, and the expansion of industries and the largely unplanned urban centers entire aquatic ecosystems are threatened. Nonetheless, benthic macroinvertebrates are important biomonitoring tools to assess the biotic and abiotic condition of endangered freshwater environments. In this study we address how benthic macroinvertebrate diversity respond to the combined effect of local environmental factors. We also aimed to evaluate how benthic macroinvertebrates diversity respond according to the habitat integrity. We expected to find higher diversity in the sampling sites with higher habitat integrity (i.e., low potential of hydrogen, electrical conductivity and water temperature, and high canopy coverage and concentration of dissolved oxygen). By using a multivariate approach (i.e., PCA) and a regression analysis (i.e., Linear Mixed-Effect Model) we were able to address the combined effect of local environmental variables on the benthic macroinvertebrate community. Our results show a negative effect of the environmental factors on the benthic macroinvertebrate diversity. As expected, sites with higher integrity and water quality values according to, respectively, the Habitat Integrity Index (i.e., HII) and the Biological Monitoring Working Party (i.e., BMWP’) tended to have higher benthic macroinvertebrates diversity. This is the first report that provides knowledge of the benthic macroinvertebrate community in the Paulicéia river, within the Cerrado Pé-de-Gigante, a conservation unity of full protection of a State Park in the Neotropics.</p>
Data from: Flying high: Sampling savanna vegetation with UAV-lidar
<p>The flexibility of UAV-lidar remote sensing offers a myriad of new opportunities for savanna ecology, enabling researchers to measure vegetation structure at a variety of temporal and spatial scales. However, this flexibility also increases the number of customizable variables, such as flight altitude, pattern, and sensor parameters, that, when adjusted, can impact data quality as well as the applicability of a dataset to a specific research interest. <br>To better understand the impacts that UAV flight patterns and sensor parameters have on vegetation metrics, we compared 7 lidar point clouds collected with a Riegl VUX-1LR over a 300 x 300 m area in the Kruger National Park, South Africa. We varied the altitude (60 m above ground, 100 m, 180 m, and 300 m) and sampling pattern (slowing the flight speed, increasing the overlap between flightlines, and flying a crosshatch pattern), and compared a variety of vertical vegetation metrics related to height and fractional cover. <br>Comparing vegetation metrics from acquisitions with different flight patterns and sensor parameters, we found that both flight altitude and pattern had significant impacts on derived structure metrics, with variation in altitude causing the largest impacts. Flying higher resulted in lower point cloud heights, leading to a consistent downward trend in percentile height metrics and fractional cover. The magnitude and direction of these trends also varied depending on the vegetation type sampled (trees, shrubs, or grasses), showing that the structure and composition of savanna vegetation can interact with the lidar signal and alter derived metrics. While there were statistically significant differences in metrics among acquisitions, the average differences were often on the order of a few centimeters or less, which shows great promise for future comparison studies.<br>We discuss how these results apply in practice, explaining the potential trade-offs of flying at higher altitudes and alternating flight pattern. We highlight how flight and sensor parameters can be geared toward specific ecological applications and vegetation types, and we explore future opportunities for optimizing UAV-lidar sampling designs in savannas.</p>
Data from: Vegetation management shapes arthropod and bird communities in an African savanna
<p>Habitat heterogeneity is a key driver of the diversity and distribution of species. African savannas are experiencing changes to their vegetation structure causing shifts towards increased woody plant cover, which results in vegetation structure homogenization. Given the impact that increasing woody plant cover has on patterns of animal use, resource managers across Africa are implementing habitat management practices that are intended to reduce woody plant cover. To understand the ecological implications of various habitat management practices on arthropod and bird communities, we leveraged large-scale tree clearing and subsequent mowing in an African savanna to understand how changes to both the herbaceous layer and woody plant cover (i.e., structural heterogeneity) may shape arthropod and bird communities at the local scale. We focused on four replicated treatments: 1) annual summer mow, 2) annual winter mow, 3) >5 years since last mow (rest), and 4) an adjacent unmanipulated savanna to act as a control. We found that the mowing treatments significantly influenced vegetation structure both with respect to tree density and herbaceous layer. Both arthropod and bird community composition varied across treatments. Grass biomass was the best predictor of arthropod richness and abundance, with arthropods selecting for areas with high biomass. Insectivorous bird richness and abundance was driven by tree density (i.e., perching locations) and not arthropod abundance. Our results suggest that vegetation management practices contribute to habitat heterogeneity at the landscape scale and increase bird species richness through species turnover. However, we caution that if a single vegetation management practice dominates the landscape, it is plausible that it could lead to the simplification of the avian community.</p>
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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)
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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.