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379 results for “environmental change”
Observed phenological indicators and environmental drivers at global change experiments at the Jornada Basin LTER site, 2014-2020
This dataset contains plant phenological data extracted from phenocams installed at a global exchange experiment involving Chihuahuan desert plant communities at the Jornada Basin LTER site in southern New Mexico, U.S.A. Cycles of plant growth, termed phenology, are tightly linked to environmental controls, and our overarching objective in this study is to determine if temperature or precipitation are relatively more important for determining shrub and grass greenup date (start of season) and senescence date (end of season). At these camera locations, we experimentally manipulated incoming precipitation at the Jornada Basin LTER for over a decade and recorded plant leaf phenology at the daily scale for seven years using phenocams. The data here are derived from raw "phenocam" camera data collected at two ongoing studies at the Jornada Basin LTER site, one studying ecosystem responses to long term changes in water and nitrogen availability, and one studying plant productivity and partitioning responses to water availability and herbivory (studies 349 and 456, respectively). Phenocams at the sites have collected images since 2014, and basic color and greenness data extracted from those images are available in a companion dataset on EDI (knb-lter-jrn.210574001). This dataset includes the derived annual and quarterly phenological indices and greenness indices for each plot monitored by phenocams, and temperature and precipitation variables aggregated to the same frequency. The dataset also includes R code and input files used to generate these derived data. See Currier and Sala 2022 for more details. This study is ongoing.
PALEODEM/Late Glacial and Early Holocene human demographic responses to climatic and environmental change in Atlantic Iberia
<p>This data files and R markdown scripts have been used in the meta-analysis of chronological and subsistence patterns of Atlantic hunter-gatherer groups between Late Glacial and Early Holocene in Atlantic Iberia.</p> <p>They correspond to the following reference: </p> <p>McLaughlin, T.R., Gómez-Puche, M., Cascalheira, J., Bicho, N.F., Fernández-López de Pablo, J. 2020. Late Glacial and Early Holocene human demographic responses to climatic and environmental change in Atlantic Iberia. <em>Phil. Trans. R. Soc. B. </em>(revised submitted version 29/04/2020)</p> <p>We specify the content of each file further down:</p> <ol> <li>Analysis_markdown.Rmd – R markdown file with the scripts to reproduce the analyses.</li> <li>Analysis_markdown.pdf – R markdown file in pdf format to reproduce the analyses.</li> <li>database_references.docx –A separate text file that comprises the extended bibliographic references used as source of the archaeological radiocarbon archaeological and isotopic data sets analyzed.</li> <li>Datelist.csv – spreadsheet that contains the 371 radiocarbon dates used as raw data to run the scripts. The last column of the table includes the bibliographical reference of the archaeological data compiled.</li> <li>ngrip.csv – NGRIP GICC05 paleotemperature record based on oxygen isotope series from Rasmussen SO <em>et al.</em>2006 A new Greenland ice core chronology for the last glacial termination. <em>J. Geophys. Res. Atmos.</em><strong>111</strong>. (doi:10.1029/2005JD006079) and Andersen KK <em>et al.</em>2006 The Greenland Ice Core Chronology 2005, 15–42ka. Part 1: constructing the time scale. <em>Quat. Sci. Rev.</em>25, 3246–3257. </li> <li>Pailler_and_Bard_42.csv­­ – Sea surface temperature data of the Atlantic margin of Iberia based on the paper: Pailler D, Bard E. 2002 High frequency palaeoceanographic changes during the past 140 000 yr recorded by the organic matter in sediments of the Iberian Margin. <em>Palaeogeogr. Palaeoclimatol. Palaeoecol.</em>181, 431–452. (doi:https://doi.org/10.1016/S0031-0182(01)00444-8)</li> <li>Paleodiet.csv – spreadsheet containing the published palaeodietary isotopic information of the human remains considered in this study.</li> <li>src.r – source r code of custom functions called upon this analysis by the R.markdown files. </li> </ol> <p>To reproduce analyses reported in the McLaughlin et al Phil Trans paper, donwload R_scripts and csv_files into the same folder. Open the *.rmd scripts in RStudio (https://www.rstudio.com), and run the scripts. </p> <p>The csv files can also be imported into R and used by the scripts. </p> <p> </p> <p> </p> <p> </p>
Replication material for paper "Freihardt (2025): Trapped by climate change? (In)voluntary immobility in Bangladesh. Regional Environmental Change. DOI 10.1007/s10113-025-02452-3."
<p>This is the data and replication code underlying the paper:</p> <p>Freihardt, J. Trapped by climate change? (In)voluntary immobility in Bangladesh. <em>Reg Environ Change</em> <strong>25</strong>, 117 (2025). https://doi.org/10.1007/s10113-025-02452-3</p>
Temnothorax rugatulus ants do not change their nest walls in response to environmental humidity
<p><strong>Overview</strong></p> <p>Data used for manuscript: <em>Temnothorax rugatulus</em> ants do not change their nest walls in response to environmental humidity</p> <p> </p> <p><strong>Structure of the data</strong></p> <p>SupplementalHygrometerDatabase.csv</p> <p>Raw hygrometer data that is used to calculate the average environmental humidity and temperature for each Trial:Salt combination</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>TrialNumber: Sequential trial number (1-4) that is NOT unique for each colony - see "Trial"</li> <li>Salt: Saturated salt solution used</li> <li>"Date Time, GMT-07:00": Date and time of each observation</li> <li>Temp: Temperature in celcius</li> <li>RH: Relative humidity (%)</li> <li>Trial: The trial number for each individual colony, each colony underwent two trials</li> </ul> <p>HumidityExperimentalDatabase.csv</p> <p>Raw experimental data with nest features and colony size</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Trial: The trial number for each individual colony, each colony underwent two trials</li> <li>TrialNumber: Sequential trial number (1-4) that is NOT unique for each colony - see "Trial"</li> <li>Day: The day in the experimental timeline (always 10, but days 1 and 5 were captured and not considered)</li> <li>Area: Area of the built nest wall (mm<sup>2</sup>)</li> <li>Length: Length of the built nest wall (mm)</li> <li>Nest.Area: Area of the internal nest space (mm<sup>2</sup>)</li> <li>HumLevel: Whether the colony started with a higher or lower relative humidity (High/Low)</li> <li>Number.Ant: The number of workers in the colony</li> <li>Number.Brood: The number of brood in the colony</li> <li>Number.Queens: The number of brood in the colony</li> <li>Salt: Saturated salt solution used</li> <li>SubstrateISide: Substrate I placement in the container from the perspective of looking out from the nest entrance</li> <li>StartWtI: The initial weight (g) of the available substrate I building nest wall material</li> <li>UsedWtI: The weight (g) of the available substrate I building nest wall material following the experimental building phase</li> <li>StartWtII: The initial weight (g) of the available substrate II building nest wall material</li> <li>UsedWtII: The weight (g) of the available substrate II building nest wall material following the experimental building phase</li> <li>CollWallWt: The weight (g) of the experimental nest wall that each colony built</li> </ul> <p>HumidMortalityRaw.csv</p> <p>Raw experimental data with proportion of workers and brood dead after each colony underwent Trial 1</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>WorkerDeath: Proportion of workers that died</li> <li>BroodDeath: Proportion of brood that died</li> <li>TrialNumber: Sequential trial number (1-4) that is NOT unique for each colony</li> </ul> <p>PorosityComparisonRaw.csv</p> <p>Data used for comparing the porosities of each experimental substrate, experimentally built walls, and collected <em>Temnothorax rugatulus</em> walls</p> <p>Porosity is the percentage of void space in compact substrate - PoreVolume/TotalVolume</p> <ul> <li>SubstrateID: A unique identifier for each substrate replicate</li> <li>Trial: The trial number for each individual colony, each colony underwent two trials (only applicable for experimentally built walls)</li> <li>SubCategory: The type of substrate (Sub I, Sub II, Built, Natural)</li> <li>TotalVolume: The combined pore (void space in compact substrate grains) and soil volume (ml) of a substrate</li> <li>PoreVolume: The void space in between compact substrate grains (ml)</li> </ul>
Site environmental, climate, water levels and temperatures, vegetation cover, and GIS change detection for assessing permafrost change in fens on the Tanana Flats, central Alaska
This data package provides data used to assess the roles of climate extremes, ecological succession, and hydrology in repeated permafrost aggradation and degradation in fens on the Tanana Flats, central Alaska. The package provides data on site environmental information, Fairbanks climate, vegetation cover, water levels and temperatures, as well as GIS files for fen change detection. The Site data include information on observers, locations, geomorphology, hydrology, soils, vegetation, and disturbance. The table has numerous fields that uses coding for class characteristics and these codes are described in the metadata as well as compiled in the ELS_Arctic_Boreal_Site_Soil_Veg_Code_Sheet_2020.docx. Alaska Climate records for Fairbanks (UAF Experiment Station) from 1904 to 2019 were acquired from the National Oceanic and Atmospheric Administration (https://www.ncdc.noaa.gov/cdo-web/). Additional data were obtained for the Nenana station (about 70 km southwest of Fairbanks), to fill in small data gaps (particularly precipitation/snow depth ruler measurements) in the Fairbanks record. We attributed the data with fields for summer (May-September) and winter periods (November-March) and hydrologic year (October-September) and calculated mean air temperature, precipitation, and snow depth by seasonal period (average of daily values) and year. The broad summer and winter periods were of interest because warmer and wetter summers increase soil heat input and warmer and snowier winters reduce soil heat loss. Fen hydrology data include information on fen water level/pressure and temperatures collected every two hours at seven sites within fens from 2011 to 2014. Vegetation composition and cover of fens, scrub, and forests was sampled to assess effects of thermokarst on vegetation change. Plant cover was determined by point-sampling at 100 points (including repetitive “hits” for all layers) distributed along 5 equally spaced rows (4-m long, 20 points per row) across the 10-m l
Soil biogeochemical responses to multiple co-occurring forms of human-induced environmental change
Multiple forms of human-induced environmental change are impacting arid ecosystems. Climate change is increasing temperatures and altering precipitation patterns, and many rapidly-growing urban centers are in arid locations. Nitrogen deposition from air pollution accompanies urban activities in many of these locations. These forms of environmental stressors will certainly impact soil communities and the biogeochemical processes for which they are responsible. However, most studies investigate these multiple environmental change factors independently or sometimes in pairs, but rarely all together as co-occurring forms of change. We examined how the simultaneous manipulation of increasing temperatures, altered precipitation patterns (both pulse size and frequency), nitrogen deposition, and urbanization influenced soil respiration and mineral N pools in the Sonoran Desert. In a laboratory microcosm, we incubated soils collected from an urban vs. exurban site, from plots receiving ~20 yrs of experimental N fertilization vs. control plots. The microcosm soils were incubated at ambient vs. +2 degree C temperatures under a factorial precipitation treatment of decreased frequency and increased pulse size. We measured the response of soil respiration rates and inorganic N pools to these co-occurring forms of environmental change.
Figure 5. Changes from 1987 in Environmental influences on movements and distribution of a wild horse (Equus caballus) population in western Nevada, USA: a 25-year study
Figure 5. Changes from 1987 to 2007 in patterns of the geographic distribution of wild horses in the Montgomery Pass Wild Horse Territory (MPWHT). The central, lightly shaded area is the key summer range (KSR). The black mark within it is the highest elevation in the Territory (elevation decreases 360 degrees around it throughout). Dark shaded areas indicate regular horse use and represent> 90% of the population. Many wild horse populations in the intermountain west accommodate to seasonal conditions, spending winter at lower elevations and summer at higher elevations. The pattern across years in the MPWHT changed from summer horse concentration in the KSR to decreasing return to KSR from winter range. In addition to establishment of decreased KSR use and increased year-round use of historical winter-range areas, expansion of the geographic use areas occurred in the latter, including seasonal use beyond MPWHT map boundaries.
Figure 7 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 7. Box plots show the distribution of relative abundances of the associations across the six facies types.
Figure 3 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 3. Sampling locations of three expeditions in 2015–2017. The first (September–October 2015) and second expeditions (July 2016) were searching for living Pontocaspian molluscs in particular. The third expedition consisted of six transects sampled by GeoEcoMar in 2017 in search of any living mollusc. In the legend w/wo means with or without.
Figure 1 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 1. Location of study area along the Romanian Black Sea coast with core locations indicated by black stars. (a) Danube Delta and RSL (modified after Vespremeanu-Stroe et al., 2017). (b) RSL bathymetry with location of study cores (modified after Dimitriu et al., 2008). Two current marine outlets are indicated by white arrows; a third outlet (Gura Portiţa) was closed in the 1970s and is indicated by a dashed white arrow.
Figure 6 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 6. Overview of the 20 most abundant mollusc species grouped according to the results of Kendall's W coefficient of concordance (for k = 4). (a) Valvata piscinalis (RGM.1309841, Core C7, depth 6 cm). (b) Dreissena polymorpha (RGM.1309827, C7 – 6 cm). (c) Dreissena bugensis (RGM.1309846, C5 – 18 cm). (d) Adacna fragilis (RGM.1309835, C2 – 18 cm). (e) Monodacna colorata s.l. (RGM.1309823, C7 – 14 cm). (f) Rissoa membranacea (RGM.1309830, C3 – 48 cm). (g) Hypanis plicata (RGM.1309845, C9 – 3 cm). (h) Clathrocaspia knipowitschii (RGM.1309843, C11 – 102 cm). (i) Mytilaster minimus (RGM.1309838, C3 – 24 cm). (j) Ecrobia maritima (RGM.1309831, C3 – 48 cm). (k) Cerastoderma glaucum (RGM.1309844, C13 – 24 cm). (l) Abra segmentum (RGM.1309821, C1 – 48 cm). (m) Parthenia interstincta (RGM.1309832, C3 – 48 cm). (n) Lentidium mediterraneum (RGM.1309837, C4 – 12 cm). (o) Retusa truncatula (RGM.1309828, C2 – 42 cm). (p) Gyraulus crista (RGM.1309840, C5 – 54 cm). (q) Potamopyrgus antipodarum (RGM.1309836, C2 – 18 cm). (r) Lithoglyphus naticoides (RGM.1309842, C5 – 18 cm). (s) Theodoxus fluviatilis (RGM.1309826, C11 – 66 cm). (t) T. fluviatilis (RGM.1309824, C11 – 78 cm). (u) Theodoxus danubialis (RGM.1309839, C3 – 24 cm). (v) T. danubialis (RGM.1309834, C2 – 30 cm). Scale bars are 1 mm.
Figure 2 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 2. Overview of core data. From left to right each core: core photograph, lithology, facies, fauna relative abundance per species group based on origin, evolution and estimated palaeosalinities.
Figure 5 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 5. NMDS ordination plot of species compositions across samples grouped into lake regions (stress = 0.173). Optimum salinity and grain size were fitted as two-dimensional smooth surfaces to illustrate the associations with species composition. Species are marked with numbers: 1 – Planorbis planorbis, 2 – Clathrocaspia knipowitschii, 3 – Potamopyrgus antipodarum, 4 – Theodoxus danubialis, 5 – Planorbarius corneus, 6 – Abra segmentum, 7 – Rissoa membranacea, 8 – Valvata macrostoma, 9 – Hypanis plicata, 10 – Mytilaster minimus, 11 – Ecrobia maritima, 12 – Parthenia interstincta, 13 – Cerastoderma glaucum and 14 – Lentidium mediterraneum.
Figure 8 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 8. Snapshot reconstructions of the evolution of the RSL and their mollusc biota. The names of major sand barriers are indicated in yellow, while those of deltaic lobes are in black. The names in parentheses and italic font are currently inactive lobes. Pie charts indicate the relative abundance of the three associations in the time interval of ±50 years of the indicated snapshot: blue – Association I (freshwater); green – Association II (Pontocaspian), orange – Association III (marine), grey – rest of the group. Water colours indicate a salinity gradient: blue is Black Sea influence (18 psu); green is river influence (0 psu). Note the freshening of the system and according changes in species associations with the decreasing influence of mesohaline waters from the Black Sea.
Figure 4 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 4. Spatiotemporal salinity variations in the RSL. For each sample, the salinity was calculated by weighted averaging of the species' optimum salinities. Salinity categories adapted from Strydom et al. (2003). Snapshots referred to in the Discussion are indicated with letters A–F.
How does parasite environmental transmission stage concentration change before, during, and after disease outbreaks?
<p>Outbreaks of environmentally transmitted parasites require that susceptible hosts encounter transmission stages in the environment and become infected, but we also know that transmission stages can be in the environment without triggering disease outbreaks. One challenge for understanding the relationship between environmental transmission stages and disease outbreaks is that the distribution and abundance of transmission stages outside of their hosts have been difficult to quantify. Thus, we have limited data about how changes in transmission stage abundance influence disease dynamics; moreover, we do not know whether the relationship between transmission stages and outbreaks differs among parasite species. We used digital PCR to quantify environmental transmission stages of five parasites in six lakes in southeastern Michigan every two weeks from June to November 2021. At the same time, we quantified infection prevalence in hosts and host density. Our study focused on eight zooplankton host species (<em>Daphnia</em> spp. and <em>Ceriodaphnia</em> <em>dubia</em>) and five of their parasites from diverse taxonomic groups (bacteria, yeast, microsporidia, and oomycete) with different infection mechanisms. We found that parasite transmission stage concentration increased prior to disease outbreaks for all parasites. However, parasites differed significantly in the relative timing of peaks in transmission stage concentration and infection outbreaks. The 'continuous shedder' parasites had transmission stage peaks at the same time as or slightly after the outbreak peaks. In contrast, parasites relying on host death for transmission ('obligate killers') had transmission stage peaks before outbreak peaks. For most parasites, lakes with outbreaks had higher spore concentrations than those without outbreaks, especially once an outbreak began; the exception was for a parasite, <em>Pasteuria</em> <em>ramosa</em>, with very strong genotypic specificity of infection. Overall, our results show that disease outbreaks are tightly linked to transmission stage concentration; outbreaks were preceded by increases in transmission stage concentration in the environment and then were fueled by the production of more transmission stages during the outbreak itself, with concentrations decreasing to pre-outbreak levels as outbreaks waned. Thus, tracking transmission stages in the environment improves our understanding of the drivers of disease outbreaks and reveals how parasite traits may affect these dynamics.</p>
Data and code for: Nonlinear life table response analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers
<p>Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. In this study, we compare the relative efficacy of linear and second-order LTRE analyses in capturing changes in population growth rate caused by environmental driver changes. To explore this question, we analyze demographic data collected for three long-lived plant species: <em>Ardisia escallonioides</em> (Pascarella & Horvitz, 1998), <em>Silene acaulis</em>, and <em>Bistorta vivipara</em> (Doak & Morris, 2010). This repository includes data files containing vital rate (survival, growth, reproduction) observations or models for our three case studies, as well as an R script in which we use these demographic data to calculate linear and second-order LTRE approximations of changes in population growth rate for each system and generate the figures we present in our paper.</p>
Vegetation changes over the last centuries in the Lower Lake Constance region reconstructed from sediment-core environmental DNA
<p>Many European lake ecosystems, including their respective catchment areas, underwent anthropogenic environmental changes over the last centuries. This has resulted in changes in the aquatic and terrestrial vegetation, but historical records on the composition of the past vegetation on centennial scale are scarce. In this study, we examined changes in the terrestrial and aquatic plant communities in and around Lower Lake Constance using metabarcoding of sedimentary DNA (sedDNA) of three cores from different sub- basins covering the past, up to 300 years. We successfully identified an average of c. 3000 sequence variants (molecular operational taxonomic units - MOTUs) and obtained a taxonomically annotated dataset of 127 species, 104 genera and 72 families. We could detect major changes in the terrestrial and aquatic vegetation of the Lower Lake Constance region by examining the cores. For example, alpha diversity decreased in the last c. 100 years, and this decrease was more pronounced in the terrestrial than in the aquatic plant community. Unlike the terrestrial plant-community, the current aquatic plant- community composition partially resembles the community from before the 20th-century eutrophication phase of the lake. In addition to changes that can be attributed to anthropogenic impacts, we also captured the effect of DNA sedimentation on the terrestrial DNA diversity representation in sediments during periods of extensive flooding and potentially as a consequence of extremely cold winters. With 1sedDNA from Lower Lake Constance, we provide a new local dataset to investigate and extend the historical changes of different shoreline habitats and to identify characteristic and invasive plant species. Such highly-resolved datasets spanning the past centuries can provide detailed information on human environmental history in densely populated regions that have undergone severe changes in the recent past.</p>
Demographic consequences of changes in environmental periodicity
<p>The fate of natural populations is mediated by complex interactions among vital rates, which can vary within and among years. While the effects of random, among-year variation in vital rates have been studied extensively, relatively little is known about how periodic, non-random variation in vital rates affects populations. This knowledge gap is potentially alarming as global environmental change is projected to alter common periodic variations, such as seasonality. We investigated the effects of changes in vital-rate periodicity on populations of three species representing different forms of adaptation to periodic environments: the yellow-bellied marmot (<em>Marmota flaviventer</em>), adapted to strong seasonality in snowfall; the meerkat (<em>Suricata suricatta</em>), adapted to inter-annual stochasticity as well as seasonal patterns in rainfall; and the dewy pine (<em>Drosophyllum lusitanicum</em>), adapted to fire regimes and periodic post-fire habitat succession. To assess how changes in periodicity affect population growth, we parameterized periodic matrix population models and projected population dynamics under different scenarios of perturbations in the strength of vital-rate periodicity. We assessed the effects of such perturbations on various metrics describing population dynamics, including the stochastic growth rate, log λ<sub>S</sub>. Overall, perturbing the strength of periodicity had strong effects on population dynamics in all three study species. For the marmots, log λ<sub>S</sub> decreased with increased seasonal differences in adult survival. For the meerkats, density dependence buffered the effects of perturbations of periodicity on log λ<sub>S</sub>. Finally, dewy pines were negatively affected by changes in natural post-fire succession under stochastic or periodic fire regimes with fires occurring every 30 years, but were buffered by density dependence from such changes under presumed more frequent fires or large-scale disturbances. We show that changes in the strength of vital-rate periodicity can have diverse but strong effects on population dynamics across different life histories. Populations buffered from inter-annual vital-rate variation can be affected substantially by changes in environmentally-driven vital-rate periodic patterns; however, the effects of such changes can be masked in analyses focusing on inter-annual variation. As most ecosystems are affected by periodic variations in the environment such as seasonality, assessing their contributions to population viability for future global-change research is crucial.</p>
Congruence among multiple indices of habitat preference for species facing human-induced rapid environmental change: A case study using the Brewer's sparrow
<p>Accurate evaluations of habitat preference are key to understanding optimal conditions for wildlife survival and reproduction. Habitat selection, however, usually is evaluated using a single index of preference, and congruence among multiple, relevant indices of preference is examined rarely.</p> <p>We assessed the concordance between patterns of habitat preference using three different indices of breeding site preference in a migratory songbird. Specifically, we compared the chronology of territorial establishment, pair formation, and reproductive initiation of the Brewer's sparrow (<em>Spizella breweri</em>) along a gradient of surface disturbance associated with natural gas development in Wyoming, USA during 2019.</p> <p>We expected all three indices to demonstrate a preference for breeding sites with less surface disturbance, where reproductive success typically is higher. By contrast, all indices suggested suboptimal preference with respect to surface disturbance, with some discrepancy among them. The chronology of settlement and pairing did not vary across the disturbance gradient, whereas nest initiation tended to occur earlier at sites with more disturbance.</p> <p>If the pattern of suboptimal selection of breeding sites that we identified is generalizable across other populations of migratory birds affected by energy development, the resultant lower fitness in those areas may exacerbate population declines.</p> <p>Our results suggest that traditional, single-index approaches to the study of habitat selection, if chosen carefully, may provide adequate inference on habitat preferences. Different metrics, however, can lead to at least subtle differences in patterns of habitat selection. The simultaneous examination of multiple indices of preference across a diversity of systems would help clarify the contexts under which preference metrics can become decoupled.</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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.