Spatio-temporal species distribution models reveal dynamic indicators for ecosystem-based fisheries management

Author:

Badger J J1ORCID,Large S I2ORCID,Thorson J T3ORCID

Affiliation:

1. Cetacean Research Program, Pacific Islands Fisheries Science Center , NMFS, NOAA, Honolulu, HI 96818 , USA

2. Ecosystem Dynamics & Assessment Branch, Northeast Fisheries Science Center , NMFS, NOAA, Woods Hole, MA 02543 , USA

3. Resource Ecology and Fisheries Management, Alaska Fisheries Science Center , NMFS, NOAA, Seattle, WA 98112 , USA

Abstract

Abstract Many economic sectors rely on marine ecosystem services, and holistic management is necessary to evaluate trade-offs between sectors and facilitate sustainable use. Integrated ecosystem assessments (IEA) integrate system components so that managers can evaluate pathways to achieve desired goals. Indicators are a central element of IEAs and capture the status and trend of individual components and should be sensitive to changes in the system; however, most indicators are aggregated over space and time as annual values, potentially leading to incomplete or inaccurate inferences about system change. Here, we demonstrate the utility of spatially and temporally explicit ecological indicators by fitting multivariate spatio-temporal models to survey data from the northeast US Shelf Ecosystem, encompassing three distinct ecoregions: Georges Bank, Gulf of Maine, and mid-Atlantic Bight. We evaluate three case studies to explore how these models can help assess ecosystem performance relative to management objectives, such as to: (1) identify dominant modes of variation in zooplankton communities; (2) quantify components of system stability; and (3) assess the density-dependent condition of groundfish over time. Collectively, these three examples demonstrate multiple interesting processes, but particularly highlight the rapid zooplankton changes and associated changes in benthivore condition and stability in the Gulf of Maine. Attributing changes in ecosystem indicators to localized processes is difficult using conventional “regionally aggregated” indicators, so this example highlights the benefits of spatio-temporal methods for integrated ecosystem analysis in this and other regions.

Funder

NSF

Publisher

Oxford University Press (OUP)

Subject

Ecology,Aquatic Science,Ecology, Evolution, Behavior and Systematics,Oceanography

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