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How and Why is the Timing and Occurrence of Seasonal Migrants in the Gulf of Maine Changing Due to Climate?

A Northeast CSC Directed Projects FY 2016 Project
Principal Investigator
Michelle Staudinger

Dates

Start Date
2016-09-12
End Date
2020-03-11
Release Date
2016

Summary

Plants and animals undergo certain recurring life-cycle events, such as migrations between summer and winter habitats or the annual blooming of plants. Known as phenology, the timing of these events is very sensitive to changes in climate (and changes in one species’ phenology can impact entire food webs and ecosystems). Shifts in phenology have been described as a “fingerprint” of the temporal and spatial responses of wildlife to climate change impacts. Thus, phenology provides one of the strongest indicators of the adaptive capacity of organisms (or the ability of organisms to cope with future environmental conditions). In this study, researchers are exploring how the timing and occurrence of a number of highly migratory marine [...]

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Contacts

Attached Files

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puffin_foraging_bigfish_MichelleStaudingerUSGS.JPG
“Puffin foraging for fish - Credit: Michelle Staudinger, USGS”
thumbnail 1.99 MB
FundyPark_MichelleStaudingerUSGS.JPG
“Fundy Park - Credit: Michelle Staudinger, USGS”
thumbnail 2.93 MB
GulfofMaine_MichelleStaudingerUSGS_crp.jpg
“Gulf of Maine - Credit: Michelle Staudinger, USGS”
thumbnail 3 MB
Grey_Seal_MichelleStaudingerUSGS.JPG
“Grey Seal; Credit: Michelle Staudinger, USGS”
thumbnail 1.35 MB
Grey_Seal_Swimming_MichelleStaudingerUSGS.JPG
“Grey Seal; Credit: Michelle Staudinger, USGS”
thumbnail 1.84 MB

Project Extension

projectStatusIn Progress

Budget Extension

annualBudgets
year2018
totalFunds53277.71
parts
typeAward Type
valueCooperative Agreement
typeAward Number
valueG16AC00237
totalFunds53277.71

Additional Information

Identifiers

Type Scheme Key
RegistrationUUID NCCWSC 65705c3f-5708-406d-8bdd-2fc9327b8bff
StampID NCCWSC NE16-VE0607

Data Management Plan Extension

customSoftware
descriptionDynamic occupancy models in unmarked
sourcehttps://cran.r-project.org/web/packages/unmarked/vignettes/colext.pdf
webToolMaintenanceAndSupportNone, although significant support available on the UMass campus.
languagesR statistical language
restrictionsNone
environmentWindows
name[R package Unmarked]
dataProduct
metadataTBDIdentify the metadata standard that will be used to describe the data and products (FGDC, ISO, EML, etc.)
exclusiveUseNo request at this time.Project data and associated products should be available publicly at the end of the project. If a request to limit access for a period of time after project completion is needed, please identify the length of time and the reason for the extension. (Request cannot be more than one year.)
descriptionOutput from these models will provide us with species-specific phenological trends and estimates of species occurrence relationships with environmental covariates. Bulk estimates will be produced of occupancy at monthly or quarterly timescales as appropriate for each habitat. Viewed over multiple years, this will allow us to estimate a phenological time series for each species, and help us answer questions regarding species-specific changes in migration and habitat use.Describe the information that will be produced, including its characteristics, temporal scope and scale, and geographic scope and scale, when available.
repositoryn/aIn addition to the NCCWSC repository (ScienceBase), identify any other repositories where you plan to share your data.
dataLifespan50+ yearsAt some point, datasets may be archived. Choose one of the following options to indicate how long you anticipate this data will be of value to other researchers. Less than 5 years, 5-10 years, 10-20 years, 20-50 years, 50+ years.
qualityChecksData used in models will have already undergone QA/QC. We have asked Dr. Chris Sutherland (UMass Amherst)to be a collaborator on the project and to review and verify code and outputs.Identify the procedural steps for ensuring data quality during the project.
citationPendleton, Staudinger, and Jordaan.Specify how the project’s data should be cited.
formatMaps and data plots will be created in ArcGIS and R, respectively to visualize where and over what time scales phenological shifts have been observed for individual species. Results will be presented in peer reviewed scientific papers.Identify the formats in which the data will be generated, maintained, and made available.
restrictionsDatasets will require data-sharing agreements with state and federal agencies that collect and maintain them. These datasets may be restricted for reuse without permission from the original collection agency.Identify any limitations on access or reuse (e.g., sensitive data, restricted data, software with license restrictions, etc.) and provide justification for restriction. Provide citation or documentation describing limitations if due to policies or legal reasons.
backupAndStorageData, databases, and references will be accumulated and stored on a project laptop. We will have an external hard drive to regularly back up our data and files.Describe the approach for backup and storage of the information associated with the research project during the project.
dataManagementResourcesPI Pendleton will be supported to organize and conduct primary modeling activities on this project. About 50% of the project costs are for PI Pendleton to work on modeling activities.Describe the proposal resources allocated for data management activities for the data products as a level of effort, total dollars allocated, or as a percentage of the total project’s cost. Resources could include people’s time or proposal funding.
volumeEstimate1 TBEstimate the volume of information generated: megabyte (MB), GB, TB, or PB.
dataProcessingTBDDescribe data processing steps or provide a scientific workflow you plan to use to manipulate the data, as appropriate.
nameOccupancy models
doin/aProvide a digital object identifier (DOI)/link to the project when available publicly.
existingInput
feesNo fees are associated with acquiring the data.
descriptionBiological data: We will be using existing long-term datasets provided by the North Atlantic Right Whale Consortium and the National Stranding Database managed by NOAA. These data are occurrences of sightings of cetaceans, pinnipeds, sea turtles, and basking sharks (list of all species can be found in our proposal) with data on day, time, year, lat/long, survey effort, and number of individuals. Some records may also contain body size and individual-specific identifiers (mark recapture or visual identification characteristics). Data extend for the NARWC dataset from 1979 – 2016 and will encompass the greater Gulf of Maine region. Stranding data will extend from 1980 to 2016, will cover the Atlantic coast from Cape Hatteras to Maine, and include all level A data for live and dead stranded animals. A description of level A data is attached to this DMP.Environmental data: We will be using existing data on sea surface temperature, Chlorophyll a, sea surface temperature fronts, Chlorophyll a fronts from the NASA MODIS oceancolorweb database. Data span 1993-present. Bathymetry data will be obtained from USGS; sea ice data will be obtained from the National Snow and Ice Data Center and information on NAO trends will be obtained from the NOAA Climate Prediction Center.Describe the information that will be used, including its characteristics, temporal scope and scale, and geographic scope and scale, when available.
sourceNorth Atlantic Right Whale Consortium; NOAA National Stranding Databases; NASA MODIS, USGS; National Snow and Ice Data Center; NOAA Climate Prediction CenterIdentify the source for the data; include a link and digital object identifier (DOI) if available.
qualityChecksDatasets are reviewed and checked for QA/QC prior to being made available for requests by the original data owners.Identify the procedural steps used to evaluate the existing data, including verification, validation, and an assessment of usability.
citationA general acknowledgement of the North Atlantic Right Whale Consortium should be included in any publications. http://www.narwc.orgWe are waiting for specific instructions from NOAA on how to cite the National Stranding database as well as other data sources as we request them.Provide citation for data product. If the data product can be found online, provide a URL.
formatData are provided by original owners and will be maintained as csv or Excel files.Identify the formats in which the data are maintained and made available.
restrictionsDatasets should be requested directly from the curators and not released publically or reused without permission from the original agency. We have obtained permission from NARWC for use of the data outlined in our proposal and are in the process of obtaining permission from NOAA (as of September 2016). NARWC conditions of use are attached to DMP.Identify any limitations on access or reuse (e.g., sensitive data, restricted data, software with license restrictions, etc.) and provide justification for restriction. Provide citation or documentation describing limitations if due to policies or legal reasons.
backupAndStorageData, databases, and references will be accumulated and stored on a project laptop. We will have an external hard drive to regularly back up our data and files.Describe the approach for backup and storage of the information associated with the research project during the project.
volumeEstimate1 TB
dataProcessingDatasets will be evaluated in models by common fields that are consistent across all datasets. A test species and habitats for developing occupancy models will likely be the North Atlantic Right Whale. Other species will be evaluated based upon the distribution and availability of seasonal records of observations. Likely candidate habitats are Cape Cod Bay, the Bay of Fundy, and the Nantucket Shoals.Describe any data processing steps or provide a scientific workflow you plan to use to manipulate the data, as appropriate.
name[North Atlantic Right Whale Consortium, National Stranding Database, NASA MODIS, USGS, National Snow and Ice Data Center, NOAA Climate Prediction Center]
history2016-10-19 09:08:39 MDT: phase Draft DMP
model
modelVersionDynamic occupancy models will be executed in R Statistical Programming Language. Any novel scripts, data QA/QC or algorithms, and the full code used, will be published as supplementary online material with the publication(s) resulting from this work.Identify the version of model used.
descriptionWe plan to apply dynamic occupancy models to marine mammal sightings and effort data from the NARWC and National Stranding databases. A retrospective analysis of marine animal phenology will be executed in which we will estimate probability of occupancy, colonization and extinction for three habitats in and around the Gulf of Maine. Test habitats will be selected based upon available data spatial and temporal extent. Likely candidate habitats are Cape Cod Bay, the Bay of Fundy, and the Nantucket Shoals, or divisions of Inner Gulf of Maine, offshore Gulf of Maine and Georges Bank.Provide a brief description of the model and its purpose.
sourceMacKenzie, D.I., J.D. Nichols, J.E. Hines, M.G. Knutson, A.B. Franklin. 2003. Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly. Ecology 84:2200–2207.Royle, J.A., and M. Kéry. 2007. A Bayesian state-space formulation of dynamic occupancy models. Ecology 88:1813–1823.The model used will be based on the R package Unmarked, details can be found:https://cran.r-project.org/web/packages/unmarked/vignettes/colext.pdf
modelInputsAll data sources listed under “data inputs” will be included in models.Data will be species at a site (occurrence, distribution), or of an individual in a territory. Parameters will be modeled as functions of covariates to generate colonization and survival with site- and yearly-site-covariates and detection with site-, yearly-site- and sample-occasion-covariates. Covariates will be generated from satellite derived products (sea surface temperature, bloom dynamics) or buoy data that describe patterns in chlorophyll and timing of temperature changes and bloom initiation.Enter the types of input data required for driving, calibrating, or validating the model. For proposals, summary information is all that is needed. For funded projects, these should be described in detail in the existing or new collection, data inputs section.
calibrationDetailsTBDBriefly describe the calibration/validation approach being taken.
modelOutputsOutput from these models will provide us with species-specific phenological trends and estimates of species occurrence relationships with environmental covariates. Bulk estimates will be produced of occupancy at monthly or quarterly timescales as appropriate for each habitat. Viewed over multiple years, this will allow us to estimate a phenological time series for each species, and help us answer questions regarding species-specific changes in migration and habitat use.Enter the types of output data the model will produce. For proposals, summary information is all that is needed. For funded projects, provide more details as known. If the model output is a generated dataset that is a project deliverable, describe it in detail in the data product section.
name[Dynamic occupancy models]
newInput
metadatan/a
exclusiveUsen/a
descriptionNo new data will be collected in this project.
repositoryn/a
dataLifespann/a
qualityChecksn/a
protocolsn/a
citationn/a
formatn/a
restrictionsn/a
backupAndStoragen/a
dataManagementResourcesn/a
volumeEstimaten/a
dataProcessingn/a
name[Provide a brief name to describe new data collection]
doin/a
phaseDraft DMP
templateNameNCCWSC DMP v3

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