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56 results for “habitat suitability model”
Data from: Habitat suitability models reveal extensive distribution of deep warm water coral frameworks in the Red Sea
<p>Deep-sea coral frameworks are understudied in the Red Sea, where conditions in the deep are conspicuously warm and saline compared to other basins. Habitat suitability models can be used to predict the distribution pattern of species or assemblages where direct observation is difficult. Here we show how coral frameworks, built by species within the families Caryophylliidae and Dendrophylliidae, are distributed between water depths of 150 m and 700 m in the northern Red Sea and Gulf of Aqaba. To extrapolate the known (ground-truthed) positions of these deep frameworks, we use environmental and geomorphometric variables to inform well-performing maximum entropy models. Over 250 km2 of seafloor in our study area are identified as suitable for such frameworks, equivalent to at least 35% of the area of photic-zone coral reefs in the same region. We hence contend that deep-water coral frameworks are an important and underappreciated repository of Red Sea biodiversity.</p>
Dataset for: African manatee (Trichechus senegalensis) habitat suitability at Lake Ossa, Cameroon using trophic state models and predictions of submerged aquatic vegetation
<p>See research article here: https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.8202</p> <p>Aim: The present study aims at investigating the past and current trophic status of Lake Ossa and evaluating its potential impact on African manatee health.</p> <p>Location: Lake Ossa is known as a refuge for the threatened African manatees in Cameroon. Little information exists on the water quality and health of the ecosystem as reflected by its chemical and biological characteristics.</p> <p>Methods: Aquatic biotic and abiotic parameters including water clarity, nitrogen, phosphorous and chlorophyll concentrations were measured monthly during four months at each of 18 water sampling stations evenly distributed across the lake. These parameters were then compared with historical values obtained from the literature to examine the dynamic trophic state of Lake Ossa.</p> <p>Results: Results indicate that Lake Ossa’s trophic state parameters doubled in only three decades (from 1985 to 2016), moving from a mesotrophic to a eutrophic state. The decreasing nutrient gradient moving from the mouth of the lake (in the south) to the north indicates that the flow of the adjacent Sanaga River is the primary source of nutrient input. Further analysis suggests that the poor transparency of the lake is not associated with chlorophyll concentrations but rather with the suspended sediments brought-in by the Sanaga River. Consequently, our model demonstrated that despite nutrient enrichment, less than 5% of the lake bottom surface sustained submerged aquatic vegetation. Thus, shoreline emergent vegetation is the primary food available for the local manatee population. During the dry season, water recedes drastically and disconnects from the dominant shoreline emergent vegetation, decreasing accessibility for manatees.</p> <p>Main conclusions: The current study revealed major environmental concerns (eutrophication and sedimentation) that may negatively impact habitat quality for manatees. Efficient land use and water management across the entire watershed may be necessary to mitigate such issues.</p>
Fig. 6 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 6. Abundance (mean number of burrows/100 × 5 m transect) of S. citellus in 4 colonies in the study area in summer (for the period 2017–2021) N = Luda Yana; –– l –– = Belotrup; ---- l ---- = Panagyurski kolonii; u = Beli Manastiri
Fig. 5 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 5. Changes in the habitat suitability in the study area (white – not suitable, black – high suitability) of European souslik assessed by maxent modelling based on data from 2006–2018 (B) and extrapolated for the period 1985–2005 (A). The results are presented in
Fig. 3 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 3. Negative and positive anomalies (white and black bars) of the Mean Annual Temperature time series for the period of 1985–2018 (data from the meteorological station Sofia)
Fig. 2 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 2. Changes in the number of grazing livestock in the southern central Bulgarian planning region for the period 2001–2018
Figure 4 in Modeling habitat suitability and current distribution of the Maghreb magpie (Pica mauritanica)
Figure 4. (A) Current distribution of the Maghreb magpie in North Africa, (B) binary map of habitat suitability with a threshold> 0.6.
Figure 6 in Modeling habitat suitability and current distribution of the Maghreb magpie (Pica mauritanica)
Figure 6. Response curves of the explanatory variables included in the species distribution model (SDM) for Pica mauritanica. (MTWQ: mean temperature of wettest quarter).
Figure 5 in Modeling habitat suitability and current distribution of the Maghreb magpie (Pica mauritanica)
Figure 5. Two-dimensional plots of Pica mauritanica niche hypervolume with the most influential variables.
Environmental DNA data of aquatic insects for habitat suitability models
Open the record for dataset details and reuse information.
Orthophotos and 2D hydraulic modelling results used for habitat suitability modelling of the River Inn section (river km 35.3-48) in SE Germany
<p>The aerial RGB picture acquisition was performed on October 7 (bypass channel) and 11 (side channel) 2022 using a DJI-Matrice 210 V2 RTK drone. For the image acquisition, the drone mounted the DJI Zenmuse X5S RGB camera. The flight was realized at an altitude of about 120 m, ensuring a lateral and longitudinal overlap of the images of about 80%. Gound Control Points (GCPs) have been disposed along the study site, and their position georeferenced using a Emlid Reach RS2 RTK GPS system. After data collection, an RGB orthomosaic with a spatial resolution of 25 cm was generated, using PIX4Dmapper v4.7.5 (www.pix4d.com).</p><p>The hydrodynamic simulations were performed with the freeware software BASEMENT v3.2 (https://basement.ethz.ch), which solves the 2D shallow-water equations using a finite volume approach over two-dimensional unstructured meshes. Computational meshes were created using the QGIS plugin BASEmesh 2, with spatially varying element sizes, which were set to be finer in areas expected to be suitable for spawning and as nursery grounds, or when needed to more accurately represent the local morphological complexity.</p>
Modelling the potential global distribution of suitable habitat for the biological control agent Heterorhabditis indica
<p class="MsoNoSpacing">Entomopathogenic nematode (EPN) <em>Heterorhabditis indica</em> is a promising biocontrol candidate. Despite the acknowledged importance of EPN in pest control, no extensive data sets or maps have been developed on their distribution at global level. This study is the first attempt to generate Ecological Niche Models (ENM) for <em>H. indica</em> and its global Habitat Suitability Map (HSM) to generate biogeographical information and predicts its global geographical range of prospective areas for its exploration and to help identify the suitable release areas for biocontrol purpose. The aim of the modelling exercise was to access the influence of temperature and soil moisture on the biogeographical patterns of <em>H. indica</em> at the global level. CLIMEX software was used to model the distribution of <em>H. indica</em> and access to the influence of environmental variable on its global distribution. In total, 162 records of <em>H. indica</em> occurrence from 27 countries over 25 years was combined to generate the known distribution data. The model was further fine-tuned using the direct experimental observations of the <em>H. indica</em>'s growth response to temperature and soil moisture. Model predicts much of the tropics and subtropics has suitable climatic conditions for <em>H. indica</em>. It further predicts that <em>H. indica</em> distribution can extends into warmer temperate climates. Examination of the model output, predictions maps at a global level indicate that <em>H. indica</em> distribution may be limited by cold stress, heat stress and dry stresses in different areas. However, cold stress appears to be the major limiting factor. This study, highlighted an efficient way to construct HSM for EPN potentially useful in the search/release of target species in new locations. The study showed that <em>H. indica</em> which is known as warm adapted EPN generally found in tropics and subtropics can potentially establish itself in warmer temperate climates as well. The model can also be used to decide the release timing of EPN by adjusting with season for maximum growth. The model developed in the current study clearly identified the value and potential of Habitat Suitability Map (HSM) in planning of future surveys and application of <em>H. indica.</em></p>
Climate change effects on deep-water corals – habitat suitability model input data
<p>Deep-water corals are protected in the seas around New Zealand by legislation that prohibits intentional damage and removal, and by marine protected areas where bottom trawling is prohibited. However, these measures do not protect them from the impacts of a changing climate and ocean acidification. To enable adequate future protection from these threats we require knowledge of the present distribution of corals and the environmental conditions that determine their preferred habitat, as well as the likely future changes in these conditions, so that we can identify areas for potential refugia.</p> <p>In this study, we built habitat suitability models for 12 taxa of deep-water corals using a comprehensive set of sample data and predicted present and future seafloor environmental conditions from an earth system model specifically tailored for the South Pacific. These models predicted that for most taxa there will be substantial shifts in the location of the most suitable habitat and decreases in the area of such habitat by the end of the 21st century, driven primarily by decreases in seafloor oxygen concentrations, shoaling of aragonite and calcite saturation horizons, and increases in nitrogen concentrations. The current network of protected areas in the region appear to provide little protection for most coral taxa, as there is little overlap with areas of highest habitat suitability, either in the present or the future. We recommend an urgent re-examination of the spatial distribution of protected areas for deep-water corals in the region, utilising spatial planning software that can balance protection requirements against value from fishing and mineral resources, take into account the current status of the coral habitats after decades of bottom trawling, and consider connectivity pathways for colonisation of corals into potential refugia.</p>
Fig. 4 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 4. Response curves, representing the dependence of predicted suitability both on the
Fig. 1 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 1. Satellite view of the study area. White circles represent the location of the colonies
Dataset: Habitat suitability models to make conservation decisions based on areas of high species richness and endemism
<p>This repository contains the files associated with the following article:</p> <p>Hernández-Quiroz NS, EI Badano, F Barragán-Torres, J Flores & C Pinedo-Álvarez. Habitat suitability models to make conservation decisions based on areas of high species richness and endemism. Biodiversity and Conservation, 27, pp. 3185-3200. <a href="https://doi.org/10.1007/s10531-018-1596-9">https://doi.org/10.1007/s10531-018-1596-9</a></p> <p>The Microsoft Excel file (SM 01-Oak occurrences.xlsx) contains the occurrence points used to calibrate the habitat suitability model of each oak species (59 species in total). This file indicates the name of the species (column A), latitude and longitude of each occurrence point (columns B and C; in geographic coordinates) and the full set of bioclimatic variables (columns D-V) and topographic variables (columns W-Z) associated to each point. These later data are provided as they were gathered from the bioclimatic layers of WorldClim and the topographic layers of the Mexican National Institute of Statistics and Geography. The repository also contains interactive maps indicating the predicted and observed distributions of the 59 Mexican oak species (SM 02-Estimated oak distribution ranges.kmz), and the probability-based and occurrence-based map of oak richness and endemic species (SM 03-Oak richness maps.kmz). These geographic projections are provided in KMZ format to make them easy to visualize in Google Earth (freely available at www.google.com/earth). Details about these KMZ files can be consulted by accessing the file properties after opening them in Google Earth.</p>
Figure 1 in Modeling habitat suitability and current distribution of the Maghreb magpie (Pica mauritanica)
Figure 1. The distribution of Pica mauritanica throughout North Africa.
Figure 3 in Modeling habitat suitability and current distribution of the Maghreb magpie (Pica mauritanica)
Figure 3. Variable importance (based on correlation metric) of the ensemble model.
Data from: Assessing the usefulness of Citizen Science Data for habitat suitability modelling: opportunistic reporting versus sampling based on a systematic protocol
<p><strong>Aim:</strong> To evaluate the potential of models based on opportunistic reporting (OR) compared to models based on data from a systematic protocol (SP) for modelling species distributions. We compared model performance for eight forest bird species with contrasting spatial distributions, habitat requirements, and rarity. Differences in the reporting of species were also assessed. Finally, we tested potential improvement of models when inferring high quality absences from OR based on questionnaires sent to observers.</p> <p><strong>Location:</strong> Both datasets cover the same large area (Sweden) and time period (2000 -2013).</p> <p><strong>Methods:</strong> Species distributions were modelled using logistic regression. Predictive performance of OR models to predict SP data were assessed based on AUC. We quantified the congruence in spatial predictions using Spearman's rank correlation coefficient. We related these results to species characteristics and reporting behaviour of observers. We also assessed the gain in predictive performance of OR models by adding inferred absences. Finally, we investigated the potential impact of sampling bias in OR.</p> <p><strong>Results:</strong> For all species, and despite the sampling biases, results from OR overall agreed well with those of SP, for the nationwide spatial congruence of habitat suitability maps and the selection and directions of species-environment relationships. The OR models also performed well in predicting the SP data. The predictive performance of the OR models increased with species rarity and even outperformed the SP model for the rarest species. No significant impact of observer behaviour was found.</p> <p><strong>Main Conclusions:</strong> Relatively simple analyses with inferred absences could produce reliable spatial predictions of habitat suitability. This was especially true for rare species. OR data should be seen as a complement to SP, as the weakness of one is the strength of the other, and OR may be especially useful at large spatial scales or where no systematic data collection protocols exist.</p>
Data from: One model to rule them all: Identifying priority bat habitats from multi‐species habitat suitability models
<p>Bats are important components of global ecosystems, providing essential ecosystem services with substantial economic benefit. Yet North American bat populations have been negatively affected by numerous factors (e.g., disease, habitat loss, and wind energy development) with compounding effects. Bats use habitats at a variety of scales, from small, isolated patches to large, contiguous corridors. Landscape‐level research is necessary to identify important habitats, patches, and corridors to strategically target management interventions. We created habitat suitability models (HSMs) for hoary bats (<em>Lasiurus cinereus</em>), eastern red bats (<em>L. borealis</em>), and tri‐colored bats (<em>Perimyotis subflavus</em>) across Illinois, USA using species-specific landscape and climate variables. With the 3 models from this study and a previously published HSM for Indiana bats (<em>Myotis sodalis</em>), we stacked binary HSMs, thereby identifying priority conservation areas across Illinois. Species exhibited different distributional patterns and habitat preferences across Illinois. Multi‐species HSMs highlight high quality habitat (i.e., ecologically important habitat that provides preferred resources for roosting, foraging, and raising young) in southern Illinois and along river riparian areas. This approach identified priority conservation areas mainly following hydrologic zones, which allows managers to strategically target restoration and conservation measures, invest funds in habitat likely to have high return‐on‐investment, and assist with decisions that affect bats (e.g., siting wind turbines and purchasing mitigation lands). </p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.