cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/bda717b1074ed48dc11a8289d95024bc
title: Adelie penguin diet composition, secondary prey items, 1991-2020

description: The fundamental long-term objective of the seabird component of the Palmer LTER (PAL) has been to identify and understand the mechanistic processes that regulate the mean fitness (population growth rate) of regional penguin populations. Since the inception of PAL, Adélie penguin populations have effectively collapsed, gentoo penguin populations have increased dramatically and chinstrap penguin populations have remained relatively stable. These trends are spatially and temporally coherent with regional warming and decreasing sea ice duration. Adélie penguins are an ice-obligate polar species whose life history is intimately linked to the presence of sea ice, while chinstrap and gentoo penguins are ice-intolerant species whose life histories evolved in the sub-Antarctic, where sea ice is a less permanent feature of the marine ecosystem. The PAL study region includes five main islands on which Adélie penguin colonies have historically occurred, with each island containing a different number of spatially segregated sub-colonies. These colonies are censused to determine the total number of nests and chicks produced each year, and breeding success. Diet samples are acquired to understand diet composition (e.g., krill, fish) and krill length-frequencies. In general, krill constitute the most important component of the summer diets by mass of these three penguin species, but changes in PAL krill abundances have exhibited no long-term trends and thus far, have failed to explain the divergent patterns in penguin populations evident in our time series. Chick fledging masses are recorded as a cumulative measure of climate, weather, diet, and parental influences on chick health at the end of the breeding season. These data have provided valuable insights into the marine and terrestrial factors that influence Adélie penguin population fitness.
 No data were collected during the 2021-2022 season due to the Palmer Station pier rebuild.
DOI: 10.15468/dl.km7puk
title: Occurrence Download

description: A dataset containing 5094 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acrocercops brongniardella (Fabricius, 1798)",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "not" : {
 "Country" : [
 "is one of (United States of America, Canada)"
 ]
 }
 }
 ]
}

 The dataset includes 5094 records from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039734-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p3f8yq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudocercospora paraexosporioides C.Nakash. & U.Braun",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "not" : {
 "Country" : [
 "is one of (United States of America, Canada)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039736-240906103802322/datasets/export for details.
DOI: 10.34740/kaggle/dsv/9542047
title: Balochi Language to English Translation Dataset
DOI: 10.15468/dl.tcckm8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyalophora cecropia Linnaeus, 1758",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "not" : {
 "Country" : [
 "is one of (United States of America, Canada)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039737-240906103802322/datasets/export for details.
DOI: 10.71578/bjspgj
title: Modelo de exposición de Chile por Yepes-Estrada et al. (2017)

description: El proyecto de evaluación de riesgo sísmico para Sudamérica SARA (*South America Risk Assessment*) de la iniciativa *Global Earthquake Model* GEM desarrolló un modelo de exposición para varios países de Sudamérica, entre los que se incluye Chile. Este modelo fue construido a través de una colaboración entre distintas instituciones y su metodología publicada en el artículo Modeling the Residential Building Inventory in South America for Seismic Risk Assessment de Yepes-Estrada et al. (2017). El inventario disponible en este conjunto de datos es un listado de más de un millón de activos, de los cuales se recopila la siguiente información: - Ubicación del activo (Longitud, latitud, número de región y nombre de la región) - Uso del activo (Residencial, comercial o industria) - Taxonomía (Materialidad, tipología, número de pisos. El detalle está disponible en el Glosario de Taxonomías GEM - Número de edificios (calculado como la razón entre el número de viviendas por piso y pisos por edificio) - Costo de reposición estructural (en dólares) - Población permanente o nocturna El número de edificios se calcula en base a la expresión $\displaystyle N_{edificios} = \frac{N_{viviendas}}{N_{\frac{viviendas}{piso}} \times N_{\frac{pisos}{edificio}}}$
DOI: 10.15468/dl.ps4vrx
title: Occurrence Download

description: A dataset containing 903095 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2024-08-08",
 "EventDate is less than or equal to 2024-09-07",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 903095 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039663-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.71578/hnijx9
title: Índice de vulnerabilidad SoVI del Censo 2017 por Bronfman et al. (2021)

description: El presente conjunto de datos representa los niveles de vulnerabilidad social frente a diversas amenazas naturales en Chile utilizando datos del Censo de Población de 2017. El modelo se basa en el Índice de Vulnerabilidad Social (SoVI) creado por Cutter et al., (2003). Este índice fue construido en base a variables demográficas, socioeconómicas y físicas de la población a nivel distrital, principalmente mediante el Censo de Población y vivienda de cada uno de los años involucrados en el estudio (1992, 2002 y 2017). En el mapa, se encuentran representados 5 niveles de vulnerabilidad, los cuales van desde “Muy bajo” a “Muy alto”. Cada uno de estos niveles, fueron definidos en valores de desviación estándar con respecto a la media y se representan con una escala de color rojo, donde el rojo más pálido indica los niveles más bajos de vulnerabilidad y el más fuerte los niveles más altos. | Rango SOVI | Concepto | |:--|:--| | $(-\infty , \mu - 1.5 \ \sigma ]$ | Muy bajo | | $(\mu - 1.5 \ \sigma , \mu - 0.5 \ \sigma]$ | Bajo | | $(\mu - 0.5 \ \sigma , \mu + 0.5 \ \sigma]$ | Medio | | $(\mu + 0.5 \ \sigma , \mu + 1.5 \ \sigma]$ | Alto | | $(\mu + 1.5 \ \sigma , + \infty)$ | Muy alto | Los niveles de vulnerabilidad obtenidos para cada año son explicados por diferentes factores. Sin embargo, se destaca que en general el estatus socioeconómico es el factor común para explicar la vulnerabilidad social para 1992, 2002 y 2017. Para más detalles referirse al artículo Temporal evolution in social vulnerability to natural hazards in Chile. Bronfman, N. C., Repetto, P. B., Guerrero, N., Castañeda, J. V., & Cisternas, P. C. (2021). Natural hazards, 107(2), 1757-1784.
DOI: 10.71578/j1tbli
title: Índice de vulnerabilidad SoVI del Censo 2002 por Bronfman et al. (2021)

description: El presente conjunto de datos representa los niveles de vulnerabilidad social frente a diversas amenazas naturales en Chile utilizando datos del Censo de Población de 2002. El modelo se basa en el Índice de Vulnerabilidad Social (SoVI) creado por Cutter et al., (2003). Este índice fue construido en base a variables demográficas, socioeconómicas y físicas de la población a nivel distrital, principalmente mediante el Censo de Población y vivienda de cada uno de los años involucrados en el estudio (1992, 2002 y 2017). En el mapa, se encuentran representados 5 niveles de vulnerabilidad, los cuales van desde “Muy bajo” a “Muy alto”. Cada uno de estos niveles, fueron definidos en valores de desviación estándar con respecto a la media y se representan con una escala de color rojo, donde el rojo más pálido indica los niveles más bajos de vulnerabilidad y el más fuerte los niveles más altos. | Rango SOVI | Concepto | |:--|:--| | $(-\infty , \mu - 1.5 \ \sigma ]$ | Muy bajo | | $(\mu - 1.5 \ \sigma , \mu - 0.5 \ \sigma]$ | Bajo | | $(\mu - 0.5 \ \sigma , \mu + 0.5 \ \sigma]$ | Medio | | $(\mu + 0.5 \ \sigma , \mu + 1.5 \ \sigma]$ | Alto | | $(\mu + 1.5 \ \sigma , + \infty)$ | Muy alto | Los niveles de vulnerabilidad obtenidos para cada año son explicados por diferentes factores. Sin embargo, se destaca que en general el estatus socioeconómico es el factor común para explicar la vulnerabilidad social para 1992, 2002 y 2017. Para más detalles referirse al artículo Temporal evolution in social vulnerability to natural hazards in Chile. Bronfman, N. C., Repetto, P. B., Guerrero, N., Castañeda, J. V., & Cisternas, P. C. (2021). Natural hazards, 107(2), 1757-1784.
DOI: 10.71578/sq62f5
title: Índice de vulnerabilidad SoVI del Censo 1992 por Bronfman et al. (2021)

description: El presente conjunto de datos representa los niveles de vulnerabilidad social frente a diversas amenazas naturales en Chile utilizando datos del Censo de Población de 1992. El modelo se basa en el Índice de Vulnerabilidad Social (SoVI) creado por Cutter et al., (2003). Este índice fue construido en base a variables demográficas, socioeconómicas y físicas de la población a nivel distrital, principalmente mediante el Censo de Población y vivienda de cada uno de los años involucrados en el estudio (1992, 2002 y 2017). En el mapa, se encuentran representados 5 niveles de vulnerabilidad, los cuales van desde "Muy bajo" a "Muy alto". Cada uno de estos niveles, fueron definidos en valores de desviación estándar ($\sigma$) con respecto a la media ($\mu$) y se representan con una escala de color rojo, donde el rojo más pálido indica los niveles más bajos de vulnerabilidad y el más fuerte los niveles más altos. | Rango SOVI | Concepto | |:--|:--| | $(-\infty , \mu - 1.5 \ \sigma ]$ | Muy bajo | | $(\mu - 1.5 \ \sigma , \mu - 0.5 \ \sigma]$ | Bajo | | $(\mu - 0.5 \ \sigma , \mu + 0.5 \ \sigma]$ | Medio | | $(\mu + 0.5 \ \sigma , \mu + 1.5 \ \sigma]$ | Alto | | $(\mu + 1.5 \ \sigma , + \infty)$ | Muy alto | Los niveles de vulnerabilidad obtenidos para cada año son explicados por diferentes factores. Sin embargo, se destaca que en general el estatus socioeconómico es el factor común para explicar la vulnerabilidad social para 1992, 2002 y 2017. Para más detalles referirse al artículo Temporal evolution in social vulnerability to natural hazards in Chile. Bronfman, N. C., Repetto, P. B., Guerrero, N., Castañeda, J. V., & Cisternas, P. C. (2021). Natural hazards, 107(2), 1757-1784.
DOI: 10.15468/dl.nj9f7d
title: Occurrence Download

description: A dataset containing 370017 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CollectionCode is kuh",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 370017 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039713-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ave8uh
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acrocercops insulariella Opler, 1971",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 "Country is one of (United States of America, Canada)"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039739-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ujpwqu
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudocercospora thujina (Dearn.) U.Braun & C.Nakash.",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 "Country is one of (United States of America, Canada)"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039740-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9g8ycd
title: Occurrence Download

description: A dataset containing 657 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyalophora columbia Smith, 1865",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 "Country is one of (United States of America, Canada)"
 ]
}

 The dataset includes 657 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039741-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tsjxrm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acrocercops insulariella Opler, 1971",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "not" : {
 "Country" : [
 "is one of (United States of America, Canada)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039743-240906103802322/datasets/export for details.
DOI: 10.15468/dl.jt64y9
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudocercospora thujina (Dearn.) U.Braun & C.Nakash.",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "not" : {
 "Country" : [
 "is one of (United States of America, Canada)"
 ]
 }
 }
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039744-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s8buup
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyalophora columbia Smith, 1865",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "not" : {
 "Country" : [
 "is one of (United States of America, Canada)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039745-240906103802322/datasets/export for details.
DOI: 10.6073/pasta/62ac8a56436072e00ca0830fef3fbbdf
title: Adelie penguin diet metadata, 1991-2024

description: The fundamental long-term objective of the seabird component of the Palmer LTER (PAL) has been to identify and understand the mechanistic processes that regulate the mean fitness (population growth rate) of regional penguin populations. Since the inception of PAL, Adélie penguin populations have effectively collapsed, gentoo penguin populations have increased dramatically and chinstrap penguin populations have remained relatively stable. These trends are spatially and temporally coherent with regional warming and decreasing sea ice duration. Adélie penguins are an ice-obligate polar species whose life history is intimately linked to the presence of sea ice, while chinstrap and gentoo penguins are ice-intolerant species whose life histories evolved in the sub-Antarctic, where sea ice is a less permanent feature of the marine ecosystem. The PAL study region includes five main islands on which Adélie penguin colonies have historically occurred, with each island containing a different number of spatially segregated sub-colonies. These colonies are censused to determine the total number of nests and chicks produced each year, and breeding success. Diet samples are acquired to understand diet composition (e.g., krill, fish) and krill length-frequencies. In general, krill constitute the most important component of the summer diets by mass of these three penguin species, but changes in PAL krill abundances have exhibited no long-term trends and thus far, have failed to explain the divergent patterns in penguin populations evident in our time series. Chick fledging masses are recorded as a cumulative measure of climate, weather, diet, and parental influences on chick health at the end of the breeding season. These data have provided valuable insights into the marine and terrestrial factors that influence Adélie penguin population fitness.
 No data were collected during the 2021-2022 season due to the Palmer Station pier rebuild.
DOI: 10.15468/dl.5tqfrk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acrocercops transecta Meyrick, 1931",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 "Country is one of (United States of America, Canada)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039746-240906103802322/datasets/export for details.
DOI: 10.15468/dl.js3dvq
title: Occurrence Download

description: A dataset containing 189 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudocercospora vitis (Lév.) Speg.",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 "Country is one of (United States of America, Canada)"
 ]
}

 The dataset includes 189 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039747-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kq7h3k
title: Occurrence Download

description: A dataset containing 3179 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyalophora euryalus Boisduval, 1855",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 "Country is one of (United States of America, Canada)"
 ]
}

 The dataset includes 3179 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039748-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/0e6521e65956177cc1f486b6977cba05
title: Adelie penguin chick fledging weights, 1991-2024

description: The fundamental long-term objective of the seabird component of the Palmer LTER (PAL) has been to identify and understand the mechanistic processes that regulate the mean fitness (population growth rate) of regional penguin populations. Since the inception of PAL, Adélie penguin populations have effectively collapsed, gentoo penguin populations have increased dramatically and chinstrap penguin populations have remained relatively stable. These trends are spatially and temporally coherent with regional warming and decreasing sea ice duration. Adélie penguins are an ice-obligate polar species whose life history is intimately linked to the presence of sea ice, while chinstrap and gentoo penguins are ice-intolerant species whose life histories evolved in the sub-Antarctic, where sea ice is a less permanent feature of the marine ecosystem. The PAL study region includes five main islands on which Adélie penguin colonies have historically occurred, with each island containing a different number of spatially segregated sub-colonies. These colonies are censused to determine the total number of nests and chicks produced each year, and breeding success. Diet samples are acquired to understand diet composition (e.g., krill, fish) and krill length-frequencies. In general, krill constitute the most important component of the summer diets by mass of these three penguin species, but changes in PAL krill abundances have exhibited no long-term trends and thus far, have failed to explain the divergent patterns in penguin populations evident in our time series. Chick fledging masses are recorded as a cumulative measure of climate, weather, diet, and parental influences on chick health at the end of the breeding season. These data have provided valuable insights into the marine and terrestrial factors that influence Adélie penguin population fitness.
 No data were collected during the 2021-2022 season due to the Palmer Station pier rebuild.