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308 results for “habitat selection”
Migratory shorebird habitat use, diet, and prey selection on mudflats in the Virginia barrier island and lagoon system, 2023-2024
Migratory shorebirds require access to heterogenous resources during migration. Understanding how shorebirds utilize different foraging substrates and food resources across the coastal landscape is important for informing conservation. We compared shorebird habitat use and invertebrate prey communities between barrier island and mudflat foraging substrates. We counted shorebirds and collected prey samples at random points on sand, peat, and mudflat substrates during spring migration (May 14 - June 2), 2023 - 2024. We opportunistically collected fecal samples on mudflats in our study area and used fecal DNA metabarcoding with 18S (invertebrates) and 23S (biofilm) primers to describe the diets of dunlin (Calidris alpina), red knots (Calidris canutus rufa) and semipalmated sandpipers (Calidris pusilla). We then used network null modeling to determine if our focal species were selectively consuming invertebrates on mudflats. Peat banks were the most heavily used intertidal substrate and mudflats supported similar shorebird abundances and species richness to sand. Dunlin and semipalmated sandpipers were more abundant on peat and mudflats, while red knots were more abundant on sand and peat. Invertebrate density was highest on peat banks and similar between mudflat and sand substrate, though mudflats supported a more diverse prey community. Amphipod crustaceans, blue mussels (Mytilus edulis), and polychaete worms were main prey consumed by all species on mudflats. Dunlin and semipalmated sandpipers fed primarily on crustaceans whereas red knots mainly fed on bivalves. All species consumed biofilm and a high proportion of diatoms were observed in fecal samples collected from semipalmated sandpipers. Red knots and dunlin selectively consumed bivalves on mudflats while semipalmated sandpipers showed no dietary preferences. Managing staging sites to preserve a diversity of intertidal habitats is critical for meeting the variable foraging requirements of migratory shorebirds.
Common Raven (Corvus corax) Occupancy Survey and Habitat Selection Data in Cliff Habitat of the Central Appalachian Region, USA, 2009-2010
We identified 24 cliff sites across four states of the Central Appalachian Region of the eastern USA (Kentucky, North Carolina, Virginia, and West Virginia) with known raven occupancy at which to perform occupancy surveys for estimating detection probability and the effects of covariates. We surveyed each cliff site 2-4 times in either 2009 or 2010 and recorded time-to-first detection and time to confirmed cliff occupancy during a two-hour survey. Daily surveys were completed between 06:00 and local solar noon. During each survey, we recorded covariates, including air temperature at survey start time, cloud cover, wind speed, and day of year. We also calculated the distance of the observation point from the cliff being surveyed and the forest cover around the cliff. We also collected data thought to be pertinent for habitat selection by ravens on 26 cliffs occupied by ravens and 26 cliffs deemed unoccupied by ravens in 2010. For each cliff, we measured cliff physiographic characteristics, such as cliff length, cliff height, and occlusion by vegetation, and landscape characteristics, including percent forest and urban cover around the cliff and distances from the cliff to the nearest road and human habitation.
Phrynus habitat selection
This data set comprises a single data file, which contains data on the abundance and distribution of the whipspider Phrynus longipes on the Luquillo Forest Dynamics Plot in July 2001. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Data from: "Imprinted habitat selection varies across dispersal phases in a raptor species"
<p><span><span>Natal Habitat Preference Induction (NHPI) plays a significant role in shaping settlement decisions in dispersive animals. Despite its importance, limited research has explored how NHPI varies during natal dispersal phases and across different types of natal habitats. In this study, we examined NHPI in 77 GPS-tagged juvenile red kites <em>(Milvus milvus</em>) originating from different natal habitats along an elevational gradient in Switzerland. We applied individual-based step selection analysis to investigate habitat selection from independence to settlement. We found that during the prospecting phase, individuals predominantly selected habitats similar to their natal environments. However, this pattern changed in the settlement phase: individuals fledged from habitats at higher elevations or closer to urban areas mostly avoided similar habitats (negative NHPI), while those from areas with more farmlands or pastures (combined with forests) showed a preference for similar habitats (positive NHPI). Moreover, the magnitude and individual variation in NHPI differed depending on the natal habitat types from which individuals originated. These findings highlight that strength, direction, and individual variation in NHPI differ between natal habitat types and dispersal phases. Natal habitats therefore can have pervasive legacy effects on subsequent habitat selection, likely affecting population and range dynamics.</span></span></p>
Supplementary data for "Influence of prey availability on habitat selection during the non-breeding period in a resident bird of prey"
<p><strong>Abstract</strong></p> <p>Background: For resident birds of prey in the temperate zone, the cold non-breeding period can have strong impacts on survival and reproduction with implications for population dynamics. Therefore, the non-breeding period should receive the same attention as other parts of the annual life cycle. Birds of prey in intensively managed agricultural areas are repeatedly confronted with unpredictable, rapid changes in their habitat due to agricultural practices such as mowing, harvesting, and ploughing. Such a dynamic landscape likely affects prey distribution and availability and may even result in changes in habitat selection of the predator throughout the annual cycle.</p> <p>Methods: In the present study, we 1) quantified barn owl prey availability in different habitats across the annual cycle, 2) quantified the size and location of barn owl breeding and non-breeding home ranges using GPS-data, 3) assessed habitat selection in relation to prey availability during the non-breeding period, and 4) discussed differences in habitat selection during the non-breeding period to habitat selection during the breeding period.</p> <p>Results: The patchier prey distribution during the non-breeding period compared to the breeding period led to habitat selection towards grassland during the non-breeding period. The size of barn owl home ranges during breeding and non-breeding were similar, but there was a small shift in home range location which was more pronounced in females than males. The changes in prey availability led to a mainly grassland-oriented habitat selection during the non-breeding period. Further, our results showed the importance of biodiversity promotion areas and undisturbed field margins within the intensively managed agricultural landscape. </p> <p>Conclusions: We showed that different prey availability in habitat categories can lead to changes in habitat preference between the breeding and the non-breeding period. Given these results we show how important it is to maintain and enhance structural diversity in intensive agricultural landscapes, to effectively protect birds of prey specialised on small mammals. Hereafter we provide the datasets and R script to reproduce the resource selection functions.</p>
Fig. 2 in Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape
Fig. 2. Map representing the study area and the different habitat types present in it. The Caricteum acutiformis patch in the North is the main tall sedge meadow, where most of the study was conducted. The transects (red lines) shown on this map were the ones used for trapping (i.e., for the Capture, Mark and Release event).
Fig. 7 in Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape
Fig. 7. Relocations of the four male individuals M1, M2, M3 and M4. M1 was tracked from the 19th to the 21th of September 2017. M2 was tracked from the 06th to the 10th of October 2017. M3 was tracked from the 15th to the 19th of October 2017. M4 was tracked from the 15th to the 17th of October 2017.
Figure 1 in Home range and foraging habitat selection by breeding lesser kestrels (Falco naumanni) in Greece
Figure 1. Minimum convex polygon home ranges (outer: 100%, interior: 95% of locations) of male (A) and female (B) lesser kestrels during the breeding season in central Greece, 2008.
Code and data for: Is habitat selection in the wild shaped by individual-level cognitive biases in orientation strategy?
<p>This repository is a companion to the manuscript "<em>Is habitat selection in the wild shaped by individual-level cognitive biases in orientation strategy?</em>" and is linked to <a href="https://github.com/CBeardsworth/Pheasant_OrientStrat_Habitat">Github</a>.</p> <p>For any questions about the code please contact Christine at <a href="mailto:c.e.beardsworth@gmail.com">c.e.beardsworth@gmail.com</a></p> <p>To use any data contained in this repository contact Joah at <a href="mailto:j.r.madden@exeter.ac.uk">j.r.madden@exeter.ac.uk</a> for permission.</p> <p>In this repository, we have included a run-through of the R analysis <a href="https://cbeardsworth.github.io/Pheasant_OrientStrat_Habitat/">here</a> to show the outputs of the analysis without the need to run the code. For those that might want to run the code themselves, we have included three R scripts (<a href="https://github.com/CBeardsworth/NavigationHabitat/blob/master/R">/R</a>) and their accompanying datasets (<a href="https://github.com/CBeardsworth/NavigationHabitat/blob/master/Data">/Data</a>). A description of the code and the data needed to run them is below:</p> <p><em>Cognition analysis and figs.R</em> = Run the cognition analysis for the first section of the manuscript and create the figures. For this, the datasets mazeData.csv (the learning trials) and mazeRotationResults.csv (the probe trial) are required. </p> <p><em>iSSA analysis and bootstrapping.R</em> = Run iSSA models and bootstrapping. This produces the datasets required for the next stage of analysis. For this code, the datasets habitat.grd (habitat information), atlas2018-strategy.csv (atlas data + id and strategy data for each bird) and FeederCoords2017_27700.csv (coordinates of feeder locations from 2017-2018) are required. The produced datasets are included in <a href="https://github.com/CBeardsworth/NavigationHabitat/blob/master/Data">/Data</a> therefore to run subsequent analyses, this code does not need to be run. To develop this code we relied heavily on the code included in the supplementary material of <a href="https://doi.org/10.1002/ece3.4823">Signer et al. (2019)</a> as well as an <a href="https://bsmity13.github.io/log_rss">online tutorial</a> from Brian J. Smith for calculating log-RSS.</p> <p><em>Habitat analysis and Figs.R</em> = Run the statistical models for the final section of the manuscript and create the figures. For this code, the datasets produced in the previous R script are required (habitatOrientation_coefs.csv and habitatOrientation_avail.csv). We have included <a href="https://github.com/CBeardsworth/NavigationHabitat/blob/master/Data">these datasets</a> so users do not need to run the iSSA analysis and bootstrapping.R script themselves. </p>
Data from: Habitat selection in transformed landscapes and the role of forest remnants and shade coffee in the conservation of resident birds
1. Biodiversity conservation in transformed landscapes is becoming increasingly important. However, most assessments of the value of modified habitats rely heavily on species presence and/or abundance, masking ecological processes such as habitat selection and phenomena like ecological traps, which may render species persistence uncertain. High species richness has been documented in tropical agroforestry systems but comparisons with native habitat remnants generally lack detailed information on species demography and habitat use. 2. We generated a multi-species, multi-measure framework to evaluate the role of habitat selection in the adaptation of species to transformed landscapes, and demonstrate that its use could affect how we value the contribution different land uses make to biodiversity conservation. 3. We analyzed seven years of capture-mark-recapture and observation data for twelve species of resident birds present in native forest remnants and shade coffee plantations in a mega-diverse region. We assessed whether species behaved adaptively by evaluating the correlation between measures of habitat preference (occurrence, abundance, fidelity, inter-seasonal variance and age) and performance (body condition, muscle, primary molt, breeding and juveniles) in forest and coffee, and generated hypotheses about their role in species persistence. 4. We documented adaptive habitat selection for seven species, non-ideal selection for four, and maladaptive selection for one. While many species showed equal-preference and/or equal performance in many traits, in general we found more evidence for birds preferring and/or performing better in forest than coffee, although relationships between our indicators and population adaptation need to be studied further before our proposed framework can be applied to more species and landscapes. 5. While shade coffee can act as a biodiversity-friendly matrix providing complementary or supplementary habitat to a wide range of resident bird species, protecting remnants of native vegetation is still of paramount importance for biodiversity conservation in agricultural landscapes. 28-Aug-2019
Data for: Pollinator and habitat-mediated selection as potential contributors to ecological speciation in two closely related species
<p>In ecological speciation, incipient species diverge due to natural selection that is ecologically based. In flowering plants, different pollinators could mediate that selection (pollinator-mediated divergent selection) or other features of the environment that differ between habitats of two species could do so (environment-mediated divergent selection). Although these mechanisms are well understood, they have received little rigorous testing, as few studies of divergent selection across sites of closely related species include both floral traits that influence pollination and vegetative traits that influence survival. This study employed common gardens in sites of the two parental species and a hybrid site, each containing advanced generation hybrids along with the parental species, to test these forms of ecological speciation in plants of the genus <em>Ipomopsis</em>. Three vegetative traits (specific leaf area, leaf trichomes, and photosynthetic water-use efficiency) and five floral traits (corolla length and width, anther insertion, petal color, nectar production) were analyzed for impacts on fitness components (survival to flowering and seeds per flower, respectively). These traits exhibited strong clines across the elevational gradient in the hybrid zone, with narrower clines in theory reflecting stronger selection or higher genetic variance. Plants with long corollas and inserted anthers had higher seeds per flower at the <em>I. tenuituba </em>site, whereas selection favored the reverse condition at the <em>I. aggregata</em> site, a signature of divergent selection. In contrast, no divergent selection due to variation in survival was detected on any vegetative trait. Selection within the hybrid zone most closely resembled selection within the <em>I. aggregata</em> site. Across traits, the strength of divergent selection was not significantly correlated with width of the cline, which was better predicted by evolvability (standardized genetic variance). These results support the role of pollinator-mediated divergent selection in ecological speciation and illustrate the importance of genetic variance in determining divergence across hybrid zones.</p>
Data for: Hunting mode and habitat selection mediate the success of human hunters
<p class="MsoNormal"><span>As a globally widespread apex predator, humans have unprecedented lethal and non-lethal effects on prey populations and ecosystems<span>. </span>Yet compared to non-human predators<span>, little is known about the </span>drivers and consequences of<span> </span>human<span> hunt</span>ing behavior<span>.<strong> </strong>Here, we characterized the hunting modes, habi</span>tat selection,<span> and harvest success of 483 rifle hunters in California</span> using<span> high-resolu</span>tion <span>GPS </span>data<span>. We used Hidden Markov Models to characterize fine-scale behavior, and k-means clustering to group hunters by hunting mode, on the basis of their time spent in each behavioral state. Hunters exhibited three distinct and successful hunting modes ("coursing", "stalking", and "sit-and-wait"), with stalking as the most successful strategy. Across hunting modes, there was variation in patterns of selection for roads, topography, and habitat cover, with </span>important<span> differences in habitat use of successful and unsuccessful hunters across modes. Our study indicates that hunters can successfully employ a diversity of harvest strategies, and </span>that<span> hunting success </span>is <span>mediated by the </span>interacting effects of<span> hunting mod</span>e and <span>landscape features. Such results high</span>light the breadth of human hunting modes, even within a single hunting technique, and lend insight into the varied ways that humans exert predation pressure on wildlife.</span></p>
Application of LiDAR to assess the habitat selection of an endangered small mammal in an estuarine wetland environment
<p>Light detection and ranging (lidar) has emerged as a valuable tool for examining the fine-scale characteristics of vegetation. However, lidar is rarely used to examine coastal wetland vegetation or the habitat selection of small mammals. Extensive anthropogenic modification has threatened the endemic species in the estuarine wetlands of the California coast, such as the endangered salt marsh harvest mouse (<em>Reithrodontomys raviventris</em>; SMHM). A better understanding of SMHM habitat selection could help managers better protect this species. We assessed the ability of airborne topographic lidar imagery in measuring the vegetation structure of SMHM habitats in a coastal wetland with a narrow range of vegetation heights. We also aimed to better understand the role of vegetation structure in habitat selection at different spatial scales. Habitat selection was modeled from data compiled from 15 small mammal trapping grids collected in the highly urbanized San Francisco Estuary in California, USA. Analyses were conducted at three spatial scales: microhabitat (25 m<sup>2</sup>), mesohabitat (2,025 m<sup>2</sup>), and macrohabitat (10,000 m<sup>2</sup>). A suite of structural covariates was derived from raw lidar data to examine vegetation complexity. We found that adding structural covariates to conventional habitat selection variables significantly improved our models. At the microhabitat scale in managed wetlands, SMHM preferred areas with denser and shorter vegetation, and selected for proximity to levees and taller vegetation in tidal wetlands. At the mesohabitat scale, SMHM were associated with a lower percentage of bare ground and with pickleweed (<em>Salicornia pacifica</em>) presence. All covariates were insignificant at the macrohabitat scale.<em> </em>Our results suggest that SMHM preferentially selected microhabitats with access to tidal refugia and mesohabitats with consistent food sources. Our findings showed that lidar can contribute to improving our understanding of habitat selection of wildlife in coastal wetlands and help to guide future conservation of an endangered species.</p>
Data from: Digging deeper: habitat selection within the home ranges of a threatened marsupial
<p>While resource selection varies according to the scale and context of study, gathering data representative of multiple scales and contexts can be challenging especially when a species is small, elusive, and threatened. We explore resource selection in a small, nocturnal, threatened species—the greater bilby (<em>Macrotis lagotis</em>)—to test <strong>(a)</strong> which resources best predict bilby occupancy, and <strong>(b) </strong>whether responses are sex-specific and/or vary over time. We tracked a total of 20 bilbies and examined within home range resource selection over multiple seasons in a large (110ha) fenced sanctuary in temperate Australia. We tested a set of plausible models for bilby resource selection, showing that food biomass (terrestrial and subterranean invertebrates, and subterranean plants) and soil textures (% sand, clay and silt) best predicted bilby resource selection for all sampling periods. Selection was also sex-specific; female resource use, relative to males, was more closely linked to the location of high-quality resources (sandier soils, and terrestrial invertebrate biomass). Bilby selection for roads was independent of season but varied over time with females selecting for areas closer to roads when plants increased in density off roads. Our findings demonstrate the importance of considering resource selection over multiple contexts and highlight a method to collect such data on a difficult to study, threatened species. Collecting such data is critical to understanding the habitat required by species.</p>
Fig. 2 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance
Fig. 2. Linear relationship (solid line) and 95 % confidence interval (gray area) between habitat quality predicted by the BART model (x-axis) and shell height (H in millimeters, y-axis), derived from the linear mixed model.
Fig. 4. Partial dependence plot for topographic Fig. 5 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance
Fig. 4. Partial dependence plot for topographic Fig. 5. Partial dependence plot for terrain roughness wetness index (TWI). index (tri).
Fig. 6 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance
Fig. 6. Partial dependence plot for pH water (phh2o). Fig. 7. Partial dependence plot for silt content (SLT).
Fig. 3. Partial dependence plot for BIO17 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance
Fig. 3. Partial dependence plot for BIO17 = Precipitation of Driest Quarter; gray area = 95 % confidence interval.
Data from: Stochastic character mapping, Bayesian model selection, and biosynthetic pathways shed new light on the evolution of habitat preference in cyanobacteria
<p>Cyanobacteria are the only prokaryotes to have evolved oxygenic photosynthesis paving the way for complex life. Studying the evolution and ecological niche of cyanobacteria and their ancestors is crucial for understanding the intricate dynamics of biosphere evolution. These organisms frequently deal with environmental stressors such as salinity and drought, and they employ compatible solutes as a mechanism to cope with these challenges. Compatible solutes are small molecules that help maintain cellular osmotic balance in high-salinity environments, such as marine waters. Their production plays a crucial role in salt tolerance, which, in turn, influences habitat preference. Among the five known compatible solutes produced by cyanobacteria (sucrose, trehalose, glucosylglycerol, glucosylglycerate, and glycine betaine), their synthesis varies between individual strains. In this study, we work in a Bayesian stochastic mapping framework, integrating multiple sources of information about compatible solute biosynthesis in order to predict the ancestral habitat preference of Cyanobacteria. Through extensive model selection analyses and statistical tests for correlation, we identify glucosylglycerol and glucosylglycerate as the most significantly correlated with habitat preference, while trehalose exhibits the weakest correlation. Additionally, glucosylglycerol, glucosylglycerate, and glycine betaine show high loss/gain rate ratios, indicating their potential role in adaptability, while sucrose and trehalose are less likely to be lost due to their additional cellular functions. Contrary to previous findings, our analyses predict that the last common ancestor of Cyanobacteria (living at around 3180 Ma) had a 97% probability of a high salinity habitat preference and was likely able to synthesize glucosylglycerol and glucosylglycerate. Nevertheless, cyanobacteria likely colonized low-salinity environments shortly after their origin, with an 89% probability of the first cyanobacterium with low-salinity habitat preference arising prior to the Great Oxygenation Event (2460 Ma). Stochastic mapping analyses provide evidence of cyanobacteria inhabiting early marine habitats, aiding in the interpretation of the geological record. Our age estimate of ~2590 Ma for the divergence of two major cyanobacterial clades (Macro- and Microcyanobacteria) suggests that these were likely significant contributors to primary productivity in marine habitats in the lead-up to the Great Oxygenation Event, and thus played a pivotal role in triggering the sudden increase in atmospheric oxygen.</p>
Data from: Home range and habitat selection of wolves recolonising Central European human-dominated landscapes
<p>Decades of persecution has resulted in the long-term absence of grey wolves (<em>Canis lupus</em>) from most European countries. However, recent changes in both legislation and public attitudes toward wolves has eased the pressure, allowing wolves to rapidly re-establish territories in their previous Central European habitats over the last 20 years. Unfortunately, these habitats are now heavily altered by humans. Understanding the spatial ecology of wolves in such highly modified environments is crucial, given the high potential for conflict and the need to reconcile their return with multiple human concerns. We equipped 20 wolves, originating from seven packs in six Central European regions, with GPS collars, allowing us to calculate monthly average home range sizes for 14 of the animals of 213.3 km2 using Autocorrelated Kernel Density Estimation. We then used ESA WorldCover data to assess the mosaic of available habitats used within each home range. Our data confirmed a general seasonal pattern for breeding individuals, with smaller apparent home ranges during the reproduction phase, and no specific pattern for non-breeders. Predictably, our wolves showed a general preference for remote areas, and especially forests, though some wolves within military training areas also showed a broader preference for grassland, possibly influenced by local land use and high availability of prey. Our results provide a comprehensive insight into the ecology of wolves during their re-colonisation of Central Europe. Though wolves are spreading relatively quickly across Central European landscapes, their permanent reoccupation remains uncertain due to conflicts with the human population. To secure the restoration of European wolf populations, further robust biological data, including data on spatial ecology, will be needed to clearly identify any management implications.</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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