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38
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ShareScore release 0.9.0
Dataset results
38 results for “phenology models”
Data from: Limited alpine climatic warming and modeled phenology advancement for three alpine species in the Northeast United States
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Data from: Estimating phenology and phenological shifts with hierarchical modeling
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Data from: An empirical comparison of models for the phenology of bird migration
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Data from: Modeling winter moth Operophtera brumata egg phenology: nonlinear effects of temperature and developmental stage on developmental rate
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Data from: Estimating the phenology of elk brucellosis transmission with hierarchical models of cause-specific and baseline hazards
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Data from: Integrating reproductive phenology in Ecological Niche Models changed the predicted future ranges of a marine invader
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Data from: Modeling the effects of climate-change induced shifts in reproductive phenology on temperature-dependent traits
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Modeling phenological reaction norms over an elevational gradient reveals contrasting strategies of Dusky Flycatchers and Mountain Chickadees in response to early season temperatures
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Data from: The response of migratory populations to phenological change: a Migratory Flow Network modelling approach
1. Declines in migratory species have been linked to anthropogenic climate change through phenological mismatch, which arises due to asynchronies between the timing of life-history events (such as migration) and the phenology of available resources. Long-distance migratory species may be particularly vulnerable to phenological change in their breeding ranges, since the timing of migration departure is based on environmental cues at distant non-breeding sites. 2. Migrants may, however, be able to adjust migration speed en route to the breeding grounds and thus ability of migrants to update their timing of migration may depend critically on stopover frequency during migration; however, understanding how migratory strategy influences population dynamics is hindered by a lack of predictive models explicitly linking habitat quality to demography and movement patterns throughout the migratory cycle. 3. Here, we present a novel modelling framework, the Migratory Flow Network (MFN), in which the seasonally varying attractiveness of breeding, winter, and stopover regions drives the direction and timing of migration based on a simple general flux law. 4. We use the MFN to investigate how populations respond to shifts in breeding site phenology based on their frequency of stopover and ability to detect and adapt to these changes. 5. With perfect knowledge of advancing phenology, 'jump' migrants (low frequency stopover) require more adaptation for populations to recover than 'hop' and 'skip' (high or medium frequency stopover) migrants. If adaptation depends on proximity, hop and skip migrants' populations can recover but jump migrants cannot adjust and decline severely. 6. These results highlight the importance of understanding migratory strategies and maintaining high-quality stopover habitat to buffer migratory populations from climate-induced mismatch. 7. We discuss how MFNs could be applied to diverse migratory taxa, and highlight the potential of MFNs as a tool for exploring how migrants respond to other environmental changes such as habitat loss.
An empirical model for predicting insects diapause termination and phenology: an application to Cydia pomonella
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Novel representation of leaf phenology improves simulation of Amazonian evergreen forest photosynthesis in a land surface model
<p>This dataset contains the LAI, Litterfall and GPP etc. of the four Amazon FLUX sites (BR-Sa1, BR-Sa3, BR-Ma2 and GF-Guy) simulated using the improved ORCHIDEE model and the corresponding FLUXNET eddy-covariance or ground-measured data. The more detial please the ReadMe.pdf in the zip.</p> <p>Data is organized with netCDF4(.nc).</p> <p><br> If you want to know more detail please contact: chenxzh73@mail.sysu.edu.cn</p>
Processed Data, Code, & Supplementary Material for de la Torre Cerro et al. (2024) Modelling asynchrony in phenology using a dynamic representation of meteorological variables
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Temperature-based phenology model of African citrus triozid (Trioza erytreae Del Guercio): Vector of citrus greening disease.
<p>The data in this dataset show the developmental stages of the African citrus psyllid, vector of citrus greening disease. The data consist of egg development time and survival and, development time and survival of the 1st 2nd, 3rd, 4th and 5th nymphal instar stages of the African citrus triozid. </p>
Data from: Model-data assimilation of multiple phenological observations to constrain and predict leaf area index
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Data from: The response of migratory populations to phenological change: a Migratory Flow Network modelling approach
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Data from: Studying phenology by flexible modeling of seasonal detectability peaks
1.Many animals and plant species have advanced spring phenology in response to climate warming. The majority of avian phenological studies are based on arrival dates. Consequently knowledge on bird phenology is mainly based on migratory species. In addition, arrival dates of migratory birds may be substantially affected by en-route climate conditions; thus failing to provide good indicators for spring phenology on the breeding grounds. Correlating arrival dates with other phenological data or with environmental covariates may be meaningless in these cases. 2.We propose the date of highest singing activity, quantified by detection probability, as a powerful proxy for breeding phenology that is applicable to migratory and sedentary bird species alike. In contrast to arrival dates, breeding phenology is mainly (non-migrants) or at least partially (migrants) influenced by conditions experienced within the breeding area. 3.We developed a new method for flexible estimation of peak detectability date in spring by combining multi-season site-occupancy with semi-parametric regression modeling (thin-plate splines). We applied our approach to opportunistic observations of 27 bird species (mostly passerines) in Switzerland. 4.We found substantial differences among species in the date of spring peak detectability: late February to mid-April in sedentary and short-distance migratory species and mid-April to late May in long-distance migrants. Among 10 species with data for >9 years, five showed a trend in detectability peaks towards an earlier spring phenology by nine to 17 days within 10 years. The mean shift over all species was ~3.5 days per 10 years. 5.Our approach is widely applicable, especially for temporally and spatially large-scale data from monitoring or citizen-science programs. Besides using the detectability peak as measure of phenology, the estimated seasonal pattern in detectability can help designing monitoring programs for improved efficiency. Our approach may be applied to any species with pronounced acoustic displays or other behavioral traits strongly influencing detectability during the breeding period. We believe that it can contribute substantially to unraveling how species and communities respond to environmental change.
Dastaset for: "Rodriguez-Galiano, V.F., Sanchez-Castillo, M., Dash, J., Atkinson, P. and Ojeda-Zujar, J. (2016). Modelling interannual variation in the spring and autumn land surface phenology of the European forest, Biogeosciences, 13
<p>Dastaset for: "Rodriguez-Galiano, V.F., Sanchez-Castillo, M., Dash, J., Atkinson, P. and Ojeda-Zujar, J. (2016). Modelling interannual variation in the spring and autumn land surface phenology of the European forest, Biogeosciences, 13</p>
Data from: Studying phenology by flexible modeling of seasonal detectability peaks
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.