TY - JOUR
T1 - Detección de tendencias temporales en muestreo de pesquerías continentales
T2 - Poder estadístico y las relaciones entre temas de manejo y objetivos de monitoreo
AU - Wagner, Tyler
AU - Irwin, Brian J.
AU - Bence, James R.
AU - Hayes, Daniel B.
N1 - Funding Information:
We thank the U.S. Fish and Wildlife Service Great Lakes Restoration Act for supporting this work and the Michigan Department of Natural Resources and the Pennsylvania Fish and Boat Commission for additional support. We also thank Mike Seider (WI DNR), Lars Rudstam (Cornell University), and Jim Hoyle (Ontario Ministry of Natural Resources) for providing the gillnet data and Weihai Liu for assistance in developing the estimation and simulation programs. We thank Lars Rudstam, Dan Dauwalter, Phil Bettoli and one anonymous reviewer for comments on this article. This article is contribution number 2013-03 of the Quantitative Fisheries Center at Michigan State University. Use of trade names does not imply endorsement by the federal government.
PY - 2013
Y1 - 2013
N2 - Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant "temporal trend." It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.
AB - Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant "temporal trend." It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.
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U2 - 10.1080/03632415.2013.799466
DO - 10.1080/03632415.2013.799466
M3 - Review article
AN - SCOPUS:84880111547
VL - 38
SP - 309
EP - 319
JO - Fisheries
JF - Fisheries
SN - 0363-2415
IS - 7
ER -