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214 results for “suitable habitat”
Mid-winter habitat suitability indices for centrarchids in contiguous lentic areas of the Upper Mississippi River System: 1994-2018
This dataset includes raw measurements and calculated bluegill winter habitat suitability indices for depth (HSID), dissolved oxygen (HSIDO), temperature (HSIT), and flow (HSIF), as well as an overall bluegill winter habitat suitability index (HSIO), for 2915 mid-winter, lentic sampling locations across 208 contiguous lentic areas throughout the Upper Mississippi River System (Upper Mississippi and Illinois Rivers) from 1994-2018. This dataset also includes several spatial and temporal climatic and hydrogeomorphic parameters that were used to assess potential drivers of winter habitat suitability.
Relative predation rates on juvenile Chinook Salmon in the lower Stanislaus River, California, 2012-2024 by habitat suitability informed by juvenile Chinook Salmon and black bass observations in the lower Stanislaus and Merced rivers, California, 2012-2017
Overview The purpose of this work was to estimate relative predation on juvenile Chinook Salmon rearing in tributaries of the San Joaquin River, California in relation to meso- and microhabitat factors. Predation rates were estimated using predation bioassays. Ranges of depth and velocity targeted by the bioassays were informed by habitat suitability indices developed prior to field efforts. Juvenile Chinook and Bass Habitat Suitability Indices The purpose of this dataset is to develop habitat suitability indices for juvenile Chinook Salmon (<120mm) on the lower Stanislaus River and nonnative black bass ( Micropterus spp.). on the lower Merced River, both tributaries of the San Joaquin. This data was used to identify target ranges of depth and velocity during predation fieldwork. Occupancy data was collected via snorkel surveys on the lower Stanislaus River in 2018 and 2019 and on the Merced River in 2012 and 2014-2017. Predation Tethering Bioassay Study The purpose of this field study was to estimate relative rates of predation of juvenile Chinook Salmon. Predation rates were estimated using assays of tethered hatchery Chinook Salmon deployed across a range of mesohabitats on the lower Stanislaus River. Habitat suitability was expected to vary across mesohabitats and across depths and velocities sampled within habitats. Cameras were deployed with tethers to identify predators for a subset of predation events happening within the first 1-2 hours of deployment. Assays were deployed monthly March-May in 2022 and 2024. A supplemental set of assays were deployed in May 2023 under wet water year conditions that varied strongly from conditions sampled in 2022 and 2024.
Distribution and habitat suitability maps for Central European steppe plants
<p>This dataset contains distribution maps for Central European steppe plants and coordinates of species occurrence points used by Divíšek et al. (2022) to calibrate habitat suitability models. These models were projected onto past climates and the resulting habitat suitability maps for 10 periods since the Last Glacial Maximum (LGM) are also included. These maps were further used as input data for simulations of species migration from climatically suitable areas in the LGM to identify those that may have served as a source for colonisation of the species' current ranges. For each species, we present maps of climatically suitable areas during the LGM and mid-Holocene (for the latter period, only areas accessible from the LGM are shown), as well as maps of the "source areas" from which the species may have colonised the regions occupied today.</p>
Habitat suitability predictions for a boreal forest indicator species, the northern goshawk (Accipiter gentilis), in Central Finland
<p>This repository contains files that show optimal sites in Central Finland for the northern goshawk (<em>Accipiter gentilis</em>, hereafter goshawk), an indicator species of boreal forests with conservation values. The optimal sites were derived from the habitat suitability model outputs included in the following publication:</p> <p> </p> <p><strong>Björklund Heidi<sup>a</sup>, Parkkinen Anssi<sup>b</sup>, Hakkari Tomi<sup>c</sup>, Heikkinen Risto K.<sup>d</sup>, Virkkala Raimo<sup>d</sup>, Lensu Anssi<sup>b</sup> (2020): Predicting valuable forest habitats using an indicator species for biodiversity. Biological Conservation, </strong><a href="https://doi.org/10.1016/j.biocon.2020.108682">https://doi.org/10.1016/j.biocon.2020.108682</a> . </p> <p> </p> <p><sup>a</sup> Finnish Museum of Natural History Luomus, P.O. Box 17, FI-00014 University of Helsinki, Finland</p> <p><sup>b</sup> University of Jyvaskyla, Department of Biological and Environmental Science, P.O. Box 35, FI-40014 University of Jyvaskyla, Finland</p> <p><sup>c</sup> Centre for Economic Development, Transport and the Environment Central Finland, P.O. Box 250, FI-40101 Jyväskylä, Finland</p> <p><sup>d</sup> Finnish Environment Institute, Biodiversity Centre, Latokartanonkaari 11, FI-00790 Helsinki, Finland</p> <p> </p> <p>The files are ArcGIS compatible shape files which indicate the spatial location of the 160 m × 160 m grid cells which include forest stands projected to be either highly suitable or suitable as a nesting site for the goshawk in Central Finland. The habitat suitability models and values were developed across the study area using Maxent software. The files show those 160-m grid cells from the study area which were included in one of the following two categories: (i) cells deemed as the most optimal (with high probability of suitable conditions) for goshawk nesting with suitability index values in Maxent outputs varying between 0.92–1.00 (‘best’ goshawk squares), and (ii) cells deemed as ‘good’ goshawk squares (with Maxent suitability index values of ≥ 0.69 and < 0.92). The coordinate system for the data files is: ETRS-TM35FIN (EPSG: 3067) (or YKJ Finland/Finnish Uniform Coordinate System (EPSG: 2393)). </p> <p>Summarization of the key settings and elements of the study are provided below. A detailed treatment can now be found in the article published in Biological Conservation (Björklund et al.) for which the link is the following: <a href="https://doi.org/10.1016/j.biocon.2020.108682">https://doi.org/10.1016/j.biocon.2020.108682</a> .</p> <p> </p> <p><strong>Summary of the study</strong></p> <p>Intensive commercial use of boreal forests is an accelerating threat to forest biodiversity, highlighting the development of cost-effective tools to detect the locations valuable for conservation. We applied species distribution models (SDMs) in our study area, Central Finland, to locate the optimal nesting sites for the goshawk, an indicator bird species for biodiversity hotspots in mature boreal forests. The optimal sites (here, 160 x 160 m grid squares) for the goshawk were determined using the Maxent software. Optimal squares for the goshawk had forests with considerably high volumes of Norway spruce (<em>Picea abies</em>, hereafter spruce) covering only 3.4% of the boreal landscape, and they were located mostly outside protected areas. Many of the squares with optimal nesting forests appeared to be under threat due to recently intensified logging operations. Half of the squares were logged to some extent and 10% were already lost or notably deteriorated due to logging after 2015 for which our models were calibrated. Threats to biodiversity of mature boreal spruce forests are likely to accelerate with increasing logging pressures. Thus, there is an urgent need to secure the continuous supply of mature spruce forests in the landscape by developing a denser network of protected areas and applying measures that aid in sparing large entities of mature forest on privately-owned land. Our modelled optimal squares can be used for selection of potential areas with biodiversity values in conservation prioritization.</p> <p><strong>The study species</strong></p> <p>The goshawk is a raptor species which prefers mature forests for nesting in Europe. Old forests dominated by spruce are considered as important for the breeding success of the species particularly in northern latitudes. Thus, intensive forest management can impair the breeding possibilities of the goshawk, and changes in forest landscapes are likely to contribute to the decline of the species. For example, in Finland, the goshawk is classified as nearly threatened species. In our study, we used the goshawk as an indicator species to model the spatial locations of boreal forest with much potential for including biodiversity values. The indicator species status of the goshawk is based on earlier studies showing the close association of the goshawk with various taxa of mature spruce forest, as well as the reported declines of both the goshawk and associated species due to loggings.</p> <p><strong>Developing Maxent models for the goshawk</strong></p> <p>The location data on occupied nests of the goshawk gathered in spring and summer 2015 and 2016 in Central Finland – as a part of the Finnish Common Birds of Prey Monitoring – were related to a set of environmental predictor variables using a maximum entropy method, Maxent software, which is considered particularly useful for modelling presence-only data (such as our goshawk nest site data). In our case, the data on forest stand and tree characteristics were related using Maxent to the known nesting sites to predict suitable conditions for the species across the Central Finland. The forest data used in the modelling were extracted from the multi-source national forest inventory (MS-NFI) data sources governed by the Natural Resources Institute Finland. The MS-NFI data used in our modelling are based on field data of the 11th and 12th NFIs from 2009 to 2016 and satellite images from 2015 and 2016.</p> <p>Prior modelling, Pearson correlations were calculated between the continuous environmental variables at the nest sites. Of the highly (|r| ≥ 0.7) correlated variables, we chose those variables which are known to be important for the goshawk, which are useful for generalization in other areas, or whose impact was of specific interest. Our final selected set of predictor variables included one class variable, site fertility class, and nine continuous variables: growing stock volume of the spruce, pine, birches and other hardwood, canopy cover, canopy cover of broad-leaved trees, saw timber of other broad-leaved trees than birches, pulpwood volume of the birches, and the biomass of the stem residual of the spruce. The original MS-NFI data recorded at the resolution of 16 × 16 m were resampled to the resolution of 160 × 160 m for the Maxent models, to represent one potential nesting forest stand.</p> <p>The accuracy of Maxent models were assessed with cross-validation and associated averaged AUC-values. The relative importance of the variables was measured by variable contribution and model deterioration measures provided by Maxent. The cloglog-transformed output index values ranging from 0 to 1 described the relative suitability of the 160-m squares to goshawk nesting. Based on the index values, the squares were classified as ‘optimal’ (with index values of 0.69–1.00), ‘typical’ (0.46– <0.69) and ‘poor’ (<0.46). In addition, we divided optimal squares into ‘best’ goshawk squares (index values of 0.92–1.00 corresponding to a high probability of suitable conditions), and ‘good’ goshawk squares (index values ≥ 0.69 and < 0.92).</p> <p><strong>Maxent model outputs</strong></p> <p>Spruce volume was the most important variable in defining habitat suitability for goshawk nesting, but hardwood cover, other hardwood logs and site fertility class contributed also to some extent to habitat suitability. In Maxent outputs, the set of 160-m squares deemed as optimal for goshawk nesting included 6 895 (cover 0.9% of the study area) best goshawk squares and 19 421 (cover 2.5%) good goshawk squares. The projected best and good goshawk squares were mostly located in unprotected areas: 95.0% of the best and 96.0% of the good goshawk squares occurred completely outside protected areas. For further details concerning the data and the model outputs, see the referred article Björklund et al. (2020).</p> <p><strong>State of the optimal goshawk squares</strong></p> <p>In total, 11% of best and over 9% of good goshawk squares were severely altered due to recent harvesting, typically clear-cutting, of the forests during the time period between 2015 and 2019. Altogether, some level of logging occurred in 3 062 (44%) of best goshawk and 9 846 (51%) of good goshawk squares during the recent years. However, many of the squares still included enough unlogged area for the goshawk in 2019.</p> <p>In our article, we conclude that while most of the optimal squares for the goshawk were still preserved in 2019, they are under risk as they are mainly situated outside protected area network. This stresses the importance of conserving biodiversity with complementary measures in privately-owned managed forests. In conclusion, a denser network with more PAs for forest-dwelling species should be secured in areas with intensive forestry, e.g. in southern Finland where PAs currently cover a smaller proportion of land compared to northern Finland.</p>
Data from: Understanding the Influence of Check Dam and Season on Habitat Use to Develop Habitat Suitability Criteria for Overwintering Tadpoles of Nanorana spp.
<p>Dataset for the article: Understanding the Influence of Check Dam and Season on Habitat Use to Develop Habitat Suitability Criteria for Overwintering Tadpoles of <em>Nanorana</em> spp.</p> <p>See readme.txt for details.</p>
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>
Random sample of habitat suitability for wolves in Scotland
<p>A rule-based habitat suitability model was created for wolves (<em>Canis lupus</em>) in mainland Scotland. Six variations of the model were run, in order to test sensitivity to changes in input values. In order to test for difference in the outputs of the six models, 500 random points were sampled from all six models, and then a test for statistical difference performed. This dataset constitutes the values of the 500 random points, where 1 indicates complete suitability and 0 indicates complete unsuitability.</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 2 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 2. Maxent predictions of suitable zebra mussel (Dreissena polymorpha) habitat in Texas. Shading indicates the logistic output of the Maxent model. Polygons represent state and national borders as well as major river basins within Texas.
Figure 1 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 1. Physicochemical data survey lakes. Sites categorized by TPWD (at the time of this study in 2016) as "infested" (the water body has an established, reproducing population) or "positive" (zebra mussels or their larvae have been detected on more than one occasion despite lack of evidence of a fully established, reproducing population) are indicated by red triangles and included: Lakes Austin, Belton, Bridgeport, Dean Gilbert, Lavon, Lewisville, Ray Roberts, Stillhouse Hollow, Texoma, Travis, and Waco. Sites categorized by TPWD as zebra mussel "negative" are indicated by green circles and included: Lakes Aquilla, Buchanan, Georgetown, Granbury, Granger, Hubbard Creek, Inks, Lady Bird, LBJ, Limestone, Marble Falls, Palo Pinto, Pflugerville, Possum Kingdom, Proctor, and Whitney.
Figure 4 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 4. Biplot of components 1 and 2 (top) and 1 and 3 (bottom) from Principal Component Analysis of water quality variables in 27 study lakes. Variables that predominated in each component (|factor loading| ≥ 0.50) are shown on the appropriate axes. Individual lake data are represented by symbols, with open circles representing lakes without previously reported incidences of zebra mussels (absent, 16 lakes), and solid circles those known to harbor the invasive species (present, 11 lakes) at the time of sampling (October 2016). No separation between the two lake groups is evident in either of the biplots. Ca, calcium, N, nitrogen; P, phosphorous.
Figure 3 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 3. Maxent predictions of suitable quagga mussel (Dreissena bugensis) habitat in Texas. Shading indicates the logistic output of the Maxent model. Polygons represent state and national borders as well as major river basins within Texas.
Fig. 1 in Development of habitat suitability criteria for Neotropical stream fishes and an assessment of their transferability to streams with different conservation status
Fig. 1. Location of the study sites in the São José dos Dourados River basin, São Paulo State, Brazil (a and b). Forested sites (dark circles) are located within the greatest forest fragments and deforested (gray circles) streams lack arboreal vegetation in their riparian zone and are located in areas dominated by pasture (c).
Fig. 2 in Development of habitat suitability criteria for Neotropical stream fishes and an assessment of their transferability to streams with different conservation status
Fig. 2. Habitat suitability criteria for depth and velocity of 10 species (codes in Table 1) developed for forested streams, considering five classes of depth (D1 = 0 to 0.2 m; D2 = 0.21 to 0.30 m; D3 = 0.31 to 0.40 m; D4 = 0.41 to 0.50 m; D5> 0.51 m) and four classes of velocity (V1 => 0.0 to 0.2 m/s; V2 = 0.21 to 0.40 m/s; V3 = 0.41 to 0.60 m/s; V4> 0.61 m/s). The dotted lines indicate SI = 0.7, above which conditions were considered optimal.
Fig. 4 in Ticks on the move-climate change-induced range shifts of three tick species in Europe: current and future habitat suitability for Ixodes ricinus in comparison with Dermacentor reticulatus and Dermacentor marginatus
Fig. 4 Area projected as suitable or unsutable under current and future (2081–2100) climatic conditions (km2) for the three tick species in comparison. a Ixodes ricinus. b Dermacentor reticulatus. c D. marginatus. The corresponding maps are shown in Figs. 1–3 in the main document. Future suitable conditions refers to the area (km2) projected as unsuitable under current climatic conditions but suitable under future climatic conditions (i.e., potential new range). Continuing suitable conditions refers to area (km2) projected as suitable under current climatic conditions as well as under future climatic conditions (i.e., stable presence). Continuing unsuitable conditions refers to area (km 2) projected as unsuitable under current climatic conditions as well as under future climatic conditions (i.e. stable absence). Future unsuitable conditions refers to the area (km.2) projected as suitable under current climatic conditions but unsuitable under future climatic conditions (i.e., potential extinction)
Fig. 2 Projected future changes for Dermacentor reticulatus until 2080–2100. a SSP 126. b SSP 245. c SSP 370. d SSP 585 in Ticks on the move-climate change-induced range shifts of three tick species in Europe: current and future habitat suitability for Ixodes ricinus in comparison with Dermacentor reticulatus and Dermacentor marginatus
Fig. 2 Projected future changes for Dermacentor reticulatus until 2080–2100. a SSP 126. b SSP 245. c SSP 370. d SSP 585. In dark blue: area projected as suitable under current climatic conditions but unsuitable under future climatic conditions (i.e., potential extinction). In light blue: area projected as unsuitable under current climatic conditions as well as under future climatic conditions (i.e., stable absence). In orange: area projected as suitable under current climatic conditions as well as under future climatic conditions (i.e., stable range). In red: area projected as unsuitable under current climatic conditions but suitable under future climatic conditions (i.e., potential new range). AUC = 0.8333 (average over 10 replicates using cross-validation, standard deviation = 0.001113603). Threshold to transform the logistic model output: 0.3816 (10% omission rate threshold). Maps were built using ESRI ArcGIS (Release 10.7, www.esri.com). Projection: Europe Albers Equal Area Conic
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.