Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Count data

Evento de amostragem
Versão 1.3 published by SCAR - AntOBIS on jan 24, 2020 SCAR - AntOBIS
Início:
Link
Publication date:
24 de Janeiro de 2020
Published by:
SCAR - AntOBIS
Licença:
CC-BY 4.0

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Dados como um arquivo DwC-A download 3.630 registros em English (147 KB)  - Frequência de atualização: atualmente
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Descrição

MAPPPD ((Mapping Application for Penguin Populations and Projected Dynamics) is a project funded by the National Aeronautics and Space Administration (NASA) in partnership with Oceanites and the Lab of Dr. Heather Lynch at Stony Brook University. Penguins are some of the most charismatic animals in the world and have captured the imaginations of news-makers, scientists, film producers and the general public. Beyond their general intrinsic value, they are considered important ecosystem indicators. That is to say, monitoring these beautiful species can tell us a lot about the general health of the Antarctic. This is because penguins are top predators, and changes (natural or anthropogenic) which influence the oceanography of the region or prey abundance, will ultimately be detected through changes in distribution or population size. The Antarctic is currently governed by nations which make up the Antarctic Treaty System (ATS). Management strategies designed by the ATS rely on accurate and citable penguin population data in order to mitigate any anthropogenic impacts in the region. However, data on penguin populations are limited primarily due to the fact that most monitored colonies are nearby permanent research stations. This means that any remote populations are essentially ignored during planning processes. Due to advances in remote sensing, modeling and aerial imagery, it is now possible to obtain population estimates for these hard-to-reach sites. MAPPPD aims to deliver population data from four species of penguin to any interested party with the goal of helping support conservation decisions in the Antarctic. We use a combination of highly advanced remote sensing technologies, aerial imagery and field counts to estimate penguin abundance across the entire continent. All of the data in MAPPPD are open access to the general public, and the process is well documented in our white paper report. (http://www.penguinmap.com)

Registros de Dados

Os dados deste recurso de evento de amostragem foram publicados como um Darwin Core Archive (DwC-A), que é o formato padronizado para compartilhamento de dados de biodiversidade como um conjunto de uma ou mais tabelas de dados. A tabela de dados do núcleo contém 3.630 registros.

This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.

Versões

A tabela abaixo mostra apenas versões de recursos que são publicamente acessíveis.

Como citar

Lembre-se, esta é uma versão antiga do dataset.  Pesquisadores deveriam citar esta obra da seguinte maneira:

Humphries G R, Naveen R, Schwaller M, Che-Castaldo C, McDowall P, Schrimpf M, Lynch H J (2020): Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Count data. v1.3. SCAR - AntOBIS. Dataset/Occurrence. https://ipt.biodiversity.aq/resource?r=mapppd_count_data&v=1.3

Direitos

Pesquisadores devem respeitar a seguinte declaração de direitos:

O editor e o detentor dos direitos deste trabalho é SCAR - AntOBIS. This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.

GBIF Registration

Este recurso foi registrado no GBIF e atribuído ao seguinte GBIF UUID: f7c30fac-cf80-471f-8343-4ec5d8594661.  SCAR - AntOBIS publica este recurso, e está registrado no GBIF como um publicador de dados aprovado por Ocean Biodiversity Information System.

Palavras-chave

Occurrence; Ocean; SOUTHERN OCEAN; Continent; Antarctica; Animals/Vertebrates; Birds; Penguins

Contatos

Grant R.W. Humphries
  • Provedor Dos Metadados
  • Originador
  • Ponto De Contato
Director
Black Bawks Data Science
PH32 4DR Fort Augustus
GB
R Naveen
  • Originador
Founder
Oceanites
PO Box 15259,
MD 20825 Chevy Chase
US
M. Schwaller
  • Originador
Retired
Mesoscale Atmospheric Processes Laboratory
Mail Code 612
MD 20771 Greenbelt
Maryland
US
C. Che-Castaldo
  • Originador
Post Doctoral Researcher
Department of Ecology and Evolution, Stony Brook University
113 Life Sciences Building
NY 11794 Stony Brook
US
P. McDowall
  • Originador
PhD student (former)
Department of Ecology and Evolution, Stony Brook University
113 Life Sciences Building
NY 11794 Stony Brook
US
M. Schrimpf
  • Originador
PhD student
Department of Ecology and Evolution, Stony Brook University
113 Life Sciences Building
NY 11794 Stony Brook
US
Heather J. Lynch
  • Originador
Principle Investigator
Department of Ecology and Evolution, Stony Brook University
113 Life Sciences Building
NY 11794 Stony Brook
US
Maialen Van de Putte
  • Distribuidor
Science Officer
Royal Belgian Institute for Natural Sciences
vautierstraat 29
B-1000 Brussels
BE

Cobertura Geográfica

Southern Ocean

Coordenadas delimitadoras Sul Oeste [-90, -180], Norte Leste [-60, 180]

Cobertura Taxonômica

Data are only collected on the four species of penguin that breed on the Antarctic continent - Macaroni penguin, although breeding on some of the outlying islands, are not included here.

Espécie Aptenodytes forsteri (Emperor penguin), Pygoscelis adéliae (Pygoscelis Adéliae), Gentoo penguin (Pygoscelis Papua), Chinstrap penguin (Pygoscelis Antarctica)

Cobertura Temporal

Data Inicial / Data final 1895-01-01 / 2018-01-01

Dados Sobre o Projeto

The ASI is the only non-governmental science project working in Antarctica and the only project monitoring both penguin and seabird population changes throughout the entirety of the vastly warming Antarctic Peninsula. Over 22 seasons, Oceanites’ Antarctic Site Inventory has made over 1700 site visits and collected data at 223 locations. The changes we’ve been tracking are significant — gentoo penguins increasing their numbers and extending their range southward, while Adélie and chinstrap numbers are in decline across the region. The 2016-17 field season, just concluded, was the ASI's 23rd consecutive season tracking these trends.

Título Antarctic Site Inventory
Identificador Oceanites_ASI
Financiamento Various
Descrição da Área de Estudo Generally the Western Antarctic Peninsula during tourist season, however the ASI collects data, housed at www.penguinmap.com for all of Antarctica from peer-reviewed articles and reports.
Descrição do Design The ASI uses ships of opportunity where penguin counters are berthed aboard tourist vessels visiting the Antarctic Peninsula. During site visits, penguin counters visit colonies and count nests, chicks, or in rare cases, adults.

O pessoal envolvido no projeto:

Ron Naveen
  • Pesquisador Principal
Heather J. Lynch
  • Pesquisador Principal
Grant R.W. Humphries
  • Programador

Métodos de Amostragem

Data on penguin abundance (number of breeding pairs or chicks) and occupancy (presence/absence) form the largest component of MAPPPD’s database. We classify the sources of abundance and occupancy data for MAPPPD into four categories. By far the largest source of abundance and occupancy data currently in theMAPPPD database is the publicly available published literature, which includes both peer-reviewed scientific literature as well as reports, management plans and other ‘grey’ literature. Data contributed through the literature may derive from direct ground surveys, aerial counts, satellite counts or counts from photographs, and the methods associated with each record are included with the data’s metadata. The Antarctic Site Inventory project and publications stemming from it (for example, Lynch and others 2013; Casanovas and others 2015) contribute 41.1% of all the population data in the MAPPPD database; the second biggest contributor is the Landcare Research dataset (http://www.landcareresearch.co.nz/resources/data/adelie-census-data)with 12.3%.All other contributors combined make up the other 46.6% of surveys in MAPPPD for all species. The second category of data are those that are contributed directly to MAPPPD, which may include prepublished survey data or census data collected on an ad hoc or opportunistic basis by professional or citizen scientists in the region. While this is currently a minor component of MAPPPD, we expect this data stream to grow in future iterations of the web application. To ensure consistent quality and metadata for users, data contributed to MAPPPD will be vetted by MAPPPD collaborators before integration. This is a twofold process wherein we first ensure that data being submitted are representative of site-wide counts for the four penguin species in our database and, second, precision estimates are consistent with those already existing in the database. In this way, MAPPPD will serve as a data ‘clearinghouse’ for ad hoc data that may otherwise go unpublished and allows for proper credit to be established for data contributors. The third category of data are those derived from historical sources (for example, aerial photographs) that have not been included in previous census data compilations. Finally, when fully developed, MAPPPD will automatically ingest satellite data from NASA and other imagery providers, extract pixels classified as guano and incorporate those data into the MAPPPD database and, when appropriate, into models for current abundance and forecasts of future abundance. The distribution of survey data by species per year varies greatly and is primarily dominated by the Pygoscelis spp. penguins (Adélie, chinstrap and gentoo).While the number of surveys with chinstrap penguin data have remained roughly consistent over time, the number of surveys with Adélie and gentoo penguin data have decreased and increased, respectively, since the 1980s. This is probably due to an increase in visitation to gentoo penguin colonies on the Antarctic Peninsula, which represent a large and growing proportion of sites visited by passenger vessels (Bender and others 2016). Except for a large effort in 2009, emperor penguins represent the smallest component, reflecting both their smaller population size and the remoteness of their colonies (Fig. 1). However, we expect that as satellites are more frequently being used to estimate colony size for emperor penguins, the number of abundance estimates available for this species will increase in the next decade.

Área de Estudo Southern Ocean

Descrição dos passos do método:

  1. The database was programmed using Structured Query Language (SQL) using the R programming language as the interface (v 3.2.0; R Core Team, 2015). It consists of 24 tables that are related via several primary key identifier fields. Once population data from the various data sources are processed, they are populated in a table that contains information on the type of count (chicks, nests, adults), quality of the count, date, species counted, and the associated citation. The table structure and procedures for version control we have adopted allows us to trace the analysis process in a transparent fashion. The population model framework then creates estimates of current populations with corresponding credible intervals, and generates forecasts for the abundance at any breeding population or in any user-defined collection of breeding locations. MAPPPD has been designed for ease of use by the management community and as a mechanism for open source development, testing, and benchmarking of population models to support Antarctic science and management. All sites in MAPPPD are intended to represent one biologically relevant population separated, except through occasional migration, to populations at other "sites". The delineation of geographic areas as a “site” is largely consistent with historical precedent (e.g., Croxall and Kirkwood 1979, Woehler 1993, Lynch and LaRue 2014), including in cases where several small islands have been combined to a single “site”. This was done so that historical survey data could be used for more complete population time series. We have used the names that have been historically associated with each site, though we have eliminated synonymous names and merged the associated time series where required. We have also renamed sites as needed to correct previous naming errors (based on, for example, an incorrectly identified geographic feature). Data on penguin abundance (number of breeding pairs or chicks) and occupancy (presence/absence) form the largest component of MAPPPD’s database. We classify the sources of abundance and occupancy data for MAPPPD into four categories. By far the largest source of abundance and occupancy data currently in the MAPPPD database is the publicly available published literature, which includes both peer reviewed scientific literature as well as reports, management plans, and other “gray” literature. Data contributed through the literature may derive from direct ground surveys, aerial counts, satellite counts, or counts from photographs, and the methods associated with each record are included with the data’s metadata. Quality flags, following the precedent set by Croxall and Kirkwood (1979) and other compilations of penguin census data, are included with all data records so end users can filter by count accuracy. Quality flags of 1 are those of the highest accuracy (e.g., recent ground counts that are site-wide), while flags of 5 are those of the lowest (e.g., estimates from satellite data or modeled output). The Antarctic Site Inventory project and publications stemming from it (e.g., Lynch et al. 2013, Casanovas et al. 2015) contribute 41.1% of all the population data in the MAPPPD database; the second biggest contributor is the Landcare Research dataset (http://www.landcareresearch.co.nz/resources/data/adelie-census-data) with 12.3%. All other contributors combined make up the other 46.6% of surveys in MAPPPD for all species. The second category of data are those that are contributed directly to MAPPPD, which may include pre-published survey data or census data collected on an ad hoc or opportunistic basis by professional or citizen scientists in the region. While this is currently a minor component of MAPPPD, we expect this data stream to grow in future iterations of the web application. To ensure consistent quality and metadata for users, data contributed to MAPPPD will be vetted by MAPPPD collaborators before integration. This is a two-fold process wherein we first ensure that data being submitted are representative of site-wide counts for the four penguin species in our database, and second, precision estimates are consistent with those already existing in the database. In this way, MAPPPD will serve as a data clearinghouse for ad hoc data that may otherwise go unpublished and allows for proper credit to be established for data contributors. The third category of data are those derived from historical sources (e.g., aerial photographs) that have not been included in previous census data compilations. Finally, when fully developed, MAPPPD will automatically ingest satellite data from NASA and other imagery providers, extract pixels classified as guano (Fretwell et al. 2012, Larue et al. 2014, Lynch and Larue 2014, Lynch and Schwaller 2014, Witharana and Lynch 2016), and incorporate those data into the MAPPPD database and, when appropriate, into models for current abundance and forecasts of future abundance. The distribution of survey data by species per year varies greatly and is primarily dominated by the Pygoscelis spp. penguins (Adélie, Chinstrap and Gentoo). While the number of surveys with Chinstrap penguin data have remained roughly consistent over time, the number of surveys with Adélie and Gentoo penguin data have decreased and increased, respectively, since the 1980s. This is likely due to an increase in visitation to Gentoo penguin colonies on the Antarctic Peninsula, which represent a large and growing proportion of sites visited by passenger vessels (Bender et al. 2016). Save for a large effort in 2009, Emperor penguins represent the smallest component, reflecting both their smaller population size and the remoteness of their colonies (Fig 1). However, we expect that as satellites are more frequently being used to estimate colony size for Emperor penguins, the number of abundance estimates available for this species will increase in the next decade. Population models On the front end, the user can query the database and models by individual colonies, groups of colonies, species, region, or user defined polygons (Fig 1). Estimates of population size are delivered as graphical outputs that can be downloaded in a variety of formats. MAPPPD's underlying population model generates Bayesian posterior distributions (i.e. the statistical distribution associated with predictions of the number of nests as a colony) for the number of breeding pairs (i.e. number of nests) in each colony (known to exist) in each year since 1982. An initial model has been developed to illustrate the functions available for display and download of results; the details of which will be distributed in a public Github repository. When complete, MAPPPD will include tools for community-contributed population models; the suite of models available within MAPPPD will facilitate the creation and display of ensemble model predictions and models will be compared each year in terms of their predictive performance as new data become available. Since the model development toolkit is still undergoing development, users are encouraged to interpret the displayed results with caution (i.e., although general trends will remain the same, be aware that results are likely to vary in the final version); downloaded results will be associated with metadata on the versions of each model included. Bayesian posteriors are summed across selected sites for each year to give a population estimate for the entire user query. Population model predictions within MAPPPD use the median, rather than the mean, of the posterior distribution for each year, because it provides a more sensible measure of central tendency for right skew distributions. Uncertainty is communicated through the display of 90th percentile highest posterior density credible intervals. For example, if the model output says that the Adélie penguin population at Petermann Island is 939 (416-1,482) breeding pairs, we would say that there is a 90% probability that the true abundance of Adélie penguins at Peterman Island was between 416 and 1,482 breeding pairs, and that there was an equal probability that the true count was greater than 939 and that it was less than 939. Occupancy models Occupancy, or the presence of species at a site, can be measured in different ways, such as whether a species is ever physically present at a site and whether a species uses a site as a breeding location. MAPPPD uses a series of Bayesian single-species multistate occupancy models to simultaneously calculate both an annual probability of presence and probability of breeding for 16 breeding bird species (Schrimpf et al., in review). These models currently use presence/absence data from ground surveys by the Antarctic Site Inventory at 181 sites throughout the Antarctic Peninsula, South Shetland Islands, and South Orkney Islands, from 1995 – 2015 (Naveen and Lynch 2011). Future research will allow other survey types, including citizen-science bird checklists such as those submitted to eBird (Sullivan et al. 2009), to inform these models. Modeling both presence and breeding as probabilities is necessary to account for uncertainty in the survey process. Multistate occupancy models incorporate probability of non-detection for each state, and accommodate the possibility that a survey missed evidence of breeding and/or presence during a visit. Probability of presence is useful for MAPPPD users who wish to create a list of species most likely to be seen at a site, while probability of breeding is most useful for assessing the chance that flying bird species with cryptic nesting habitats (e.g., storm petrels) may be using a site for reproduction. Though Bayesian occupancy modeling is still relatively new, similar models have been adapted to suit different needs (e.g. MacKenzie et al. 2009, Bailey et al. 2014). The models constructed for MAPPPD currently incorporate site-specific November sea-ice concentration averaged across all years as an environmental covariate, and previous-state (i.e., previous population estimate) as a biological covariate, which help to estimate occupancy for sites with very few data. On the front end, MAPPPD displays the probability of each species either being present, or present and breeding, which can be collapsed to a simpler checklist of birds likely to be present and/or breeding at a site. These probabilities are influenced by direct observation at the site in question, as well as by the statistically-estimated relationship between occupancy status and environmental conditions, the latter of which allows us to estimate the probability of occupancy for sites with known site characteristics even if no survey data has been collected.

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Propósito To provide open access penguin population census data to the general public.
Descrição da manutenção Maintenance on the website and database is ongoing with annual updates to numbers.
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http://www.penguinmap.com
https://ipt.biodiversity.aq/resource?r=mapppd_count_data