Kelly S. Andrews

Kelly S. Andrews

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Kelly S. Andrews

Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, Washington, United States of America

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2017 in Ecosystem Health and Sustainability
Verified
Journal Article
Open access
KHKirstin Holsman
Kirstin Holsman
JSJameal Samhouri
Jameal Samhouri
GCGeoffrey Cook
Geoffrey Cook
EHElliott Hazen
Elliott Hazen
EOErik Olsen
Erik Olsen
KAKelly Andrews
Kelly Andrews
Risk assessments quantify the probability of undesirable events along with their consequences. They are used to prioritize management interventions and assess tradeoffs, serving as an essential component of ecosystem‐based management (). A central objective of most risk assessments for conservation and management is to characterize uncertainty and impacts associated with one or more pressures of interest. Risk assessments have been used in marine resource management to help evaluate the risk of environmental, ecological, and anthropogenic pressures on species or habitats including for data‐poor fisheries management (e.g., toxicity, probability of extinction, habitat alteration impacts). Traditionally, marine risk assessments focused on singular pressure‐response relationships, but recent advancements have included use of risk assessments in an context, providing a method for evaluating the cumulative impacts of multiple pressures on multiple ecosystem components. Here, we describe a conceptual framework for ecosystem risk assessment (), highlighting its role in operationalizing , with specific attention to ocean management considerations. This framework builds on the ecotoxicological and conservation literature on risk assessment and includes recent advances that focus on risks posed by fishing to marine ecosystems. We review how examples of s from the United States fit into this framework, explore the variety of analytical approaches that have been used to conduct s, and assess the challenges and data gaps that remain. This review discusses future prospects for s as decision‐support tools, their expanded role in integrated ecosystem assessments, and the development of next‐generation risk assessments for coupled natural–human systems.

17 August 2022 in Global Change Biology
Verified
Journal Article
Open access
SBStephanie Brodie
Stephanie Brodie
JSJames A. Smith
James A. Smith
BMBarbara A. Muhling
Barbara A. Muhling
LBLewis A. K. Barnett
Lewis A. K. Barnett
GCGemma Carroll
Gemma Carroll
IKIsaac C. Kaplan
Isaac C. Kaplan
Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change—rather than accurately predict specific outcomes—it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.

1 August 2009 in Animal Behaviour
Verified
Journal Article
Closed access
KAKelly S. Andrews
Kelly S. Andrews
GWGreg D. Williams
Greg D. Williams
DFDebbie Farrer
Debbie Farrer
NTNick Tolimieri
Nick Tolimieri
CHChris J. Harvey
Chris J. Harvey
PLPhillip S. Levin
Phillip S. Levin

26 May 2011 in Marine Biology
Verified
Journal Article
Closed access
PDF file
KAKelly S. Andrews
Kelly S. Andrews
NTNick Tolimieri
Nick Tolimieri
GWGreg D. Williams
Greg D. Williams
JSJameal F. Samhouri
Jameal F. Samhouri
CHChris J. Harvey
Chris J. Harvey
PLPhillip S. Levin
Phillip S. Levin

7 April 2009 in Marine Ecology Progress Series
Verified
Journal Article
Closed access
NTN Tolimieri
N Tolimieri
KAK Andrews
K Andrews
GWG Williams
G Williams
SKS Katz
S Katz
PLPs Levin
Ps Levin

8 September 2010 in PLOS ONE
Verified
Journal Article
Open access
PDF file
KAKelly S. Andrews
Kelly S. Andrews
GWGreg D. Williams
Greg D. Williams
PLPhillip S. Levin
Phillip S. Levin
Understanding movement patterns is fundamental to population and conservation biology. The way an animal moves through its environment influences the dynamics of local populations and will determine how susceptible it is to natural or anthropogenic perturbations. It is of particular interest to understand the patterns of movement for species which are susceptible to human activities (e.g. fishing), or that exert a large influence on community structure, such as sharks. We monitored the patterns of movement of 34 sixgill sharks Hexanchus griseus using two large-scale acoustic arrays inside and outside Puget Sound, Washington, USA. Sixgill sharks were residents in Puget Sound for up to at least four years before making large movements out of the estuary. Within Puget Sound, sixgills inhabited sites for several weeks at a time and returned to the same sites annually. Across four years, sixgills had consistent seasonal movements in which they moved to the north from winter to spring and moved to the south from summer to fall. Just prior to leaving Puget Sound, sixgills altered their behavior and moved twice as fast among sites. Nineteen of the thirty-four sixgills were detected leaving Puget Sound for the outer coast. Three of these sharks returned to Puget Sound. For most large marine predators, we have a limited understanding of how they move through their environment, and this clouds our ability to successfully manage their populations and their communities. With detailed movement information, such as that being uncovered with acoustic monitoring, we can begin to quantify the spatial and temporal impacts of large predators within the framework of their ecosystems.