Estimating Shifts in Phenology and Habitat Use of Cobia in Chesapeake Bay Under Climate Change

Crear, Daniel P.; Watkins, Brian; Friedrichs, Marjorie A. M.; St‐Laurent, Pierre; Weng, Kevin C.

doi:10.3389/fmars.2020.579135

Cited by 17 publications

(6 citation statements)

References 39 publications

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“…2). This trend of earlier arrival times is consistent with temperature data (from buoys of the Chesapeake Bay Interpretive Buoy System) that indicate that the warming of Chesapeake Bay begins earlier each year, affecting migratory timing and species distributions in the bay and other areas along the Atlantic coast of the United States (Richardson et al, 2018;Crear et al, 2020;Pinsky et al, 2020). Our observations support the conclusion of Ingram et al (2019) that use of offshore habitat was influenced primarily by inshore drivers.…”

Section: Yearsupporting

confidence: 88%

Arrival and departure windows of Atlantic sturgeon in Chesapeake Bay in Virginia

Kahn,

Hager,

Breault

et al. 2023

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Section: Yearsupporting

confidence: 88%

Arrival and departure windows of Atlantic sturgeon in Chesapeake Bay in Virginia

Kahn,

Hager,

Breault

et al. 2023

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“…For example, cobia ( Rachycentron canadum ), a coastal pelagic fish that makes an inshore and northern migration into Chesapeake Bay where they spawn, feed, and are targeted by recreational fishermen, was estimated to migrate into the bay earlier and leave the bay later due to climate change. This shift would increase the duration cobia would spend in Chesapeake Bay by an additional 30 days by 2050 compared to today (Crear, Watkins, Friedrichs, et al, 2020). Phenology shifts of large HMS, in addition to being driven by their physiology, are also likely influenced by prey shifts.…”

Section: Discussionmentioning

confidence: 99%

“…tional fishermen, was estimated to migrate into the bay earlier and leave the bay later due to climate change. This shift would increase the duration cobia would spend in Chesapeake Bay by an additional 30 days by 2050 compared to today(Crear, Watkins, Friedrichs, et al, 2020). Phenology shifts of large HMS, in addition to being driven by their physiology, are also likely influenced by prey shifts.…”

mentioning

confidence: 99%

Climate‐influenced shifts in a highly migratory species recreational fishery

Crear

Curtis

Hutt

et al. 2023

Fisheries Oceanography

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Funding for the study was provided by the NOAA NMFS. The authors declare no conflicts of interest. Ethics approval Not applicable Data availability statementThe Large Pelagics Survey data used in this study are publicly available. The sea surface temperature dataset is publicly available from the sources identified in the manuscript as well as the other explanatory variables. R statistical code from this study can be available upon request to the corresponding author.

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“…Numerous studies that have focused on climate change impacts on the phenology of specific species. These include tree species (Chamberlain & Wolkovich, 2021), grassland songbirds (McGowan et al, 2021), avian migration (Horton et al, 2020) and fish (Crear et al, 2020). While climate influences all these various species, the exact ways can be quite different.…”

Section: Methodsmentioning

confidence: 99%

False springs and spring phenology: Propagating effects of downscaling technique and training data

Wootten,

Dixon,

Adams‐Smith

et al. 2024

Intl Journal of Climatology

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Projected changes to spring phenological indicators (such as first leaf and first bloom) are of importance to assessing the impacts of climate change on ecosystems and species. The risk of false springs (when a killing freeze occurs after plants of interest bloom), which can cause ecological and economic damage, is also projected to change across much of the United States. Given the coarse nature of global climate models, downscaled climate projections have commonly been used to assess local changes in spring phenological indices. Few studies that examine the influence of the sources of uncertainty sources in the downscaling approach on projections of phenological changes. This study examines the influence of sources of uncertainty on projections of spring phenological indicators and false spring risk using the South Central United States. The downscaled climate projections were created using three statistical downscaling techniques applied with three gridded observation datasets as training data and three global climate models. This study finds that projections of spring phenological indicators and false spring risk are primarily sensitive to the choice of global climate models. However, this study also finds that the formulation of the downscaling approach can cause errors representing the daily low‐temperature distribution, which can cause errors in false spring risk by failing to capture the timing between the last spring freeze and the first bloom. One should carefully consider the downscaling approach used when using downscaled climate projections to assess changes to spring phenology and false spring risk.

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Estimating Shifts in Phenology and Habitat Use of Cobia in Chesapeake Bay Under Climate Change

Cited by 17 publications

References 39 publications

Arrival and departure windows of Atlantic sturgeon in Chesapeake Bay in Virginia

Arrival and departure windows of Atlantic sturgeon in Chesapeake Bay in Virginia

Climate‐influenced shifts in a highly migratory species recreational fishery

False springs and spring phenology: Propagating effects of downscaling technique and training data

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