Standardized Broad‐Scale Management and Monitoring of Inland Lake Recreational Fisheries: An Overview of the Ontario Experience

Abstract

There are ~250,000 lakes in Ontario that support important cultural, recreational, and economic fisheries. In 2005, the Ontario Ministry of Natural Resources and Forestry adopted the Ecological Framework for Recreational Fisheries Management to tackle the heterogeneity of lake resources and angler mobility across the landscape, increase public participation in fisheries management, and streamline an ever‐growing list of regulations. The Broad‐Scale Monitoring Program for Inland Lakes began in 2008 to meet these goals. Essential elements of the program are: clear objectives, standardized sampling methods, operational implementation, diagnostic indicators, standardized reporting, a multidisciplinary team, and adaptive monitoring. Fishes, zooplankton, habitat, and angling activity are measured at each lake and provide the data needed to make evidence‐based fisheries management decisions. The data have benefited other provincial initiatives and provided significant contributions to the science of freshwater ecology. Recommendations are provided for other jurisdictions considering the implementation of a standardized broad‐scale monitoring program.

Size spectrum model reveals importance of considering species interactions in a freshwater fisheries management context

“…The BsM program uses a random, depth‐stratified design with both large‐mesh (varying from 38 to 127 mm) and small‐mesh (varying from 13 to 38 mm) gillnets. We chose to use BsM data as opposed to FWIN to estimate spatial overlap because the BsM data for Lake Nipissing sample a greater range of depth strata (Lester et al, 2020). We used the Morisita index (Morisita, 1959), a measure of niche overlap based on counts of individuals, to calculate interaction scores.…”

“…Overlap in space or habitat use is one of the main components determining the occurrence of feeding interactions in food webs, apart from body size (Morales-Castilla et al, 2015). Spatial co-occurrence was determined using catch data from the OMNDMNRF Broad-scale Monitoring (BsM) Program for Inland Lakes (Lester et al, 2020). The BsM program uses a random, depth-stratified design with both large-mesh (varying from 38 to 127 mm) and small-mesh (varying from 13 to 38 mm) gillnets.…”

It’s Complicated and It Depends: A Review of the Effects of Ecosystem Changes on Walleye and Yellow Perch Populations in North America

“…Still, even passive adaptive management can facilitate learning when systems are monitored following standardized protocols to facilitate comparisons among systems. Particularly in regions where multiple stocks are managed and cannot be monitored annually, standardized data collection and stratified sampling can allow for robust inference that would be impossible when relying on single systems (Lester et al 2003(Lester et al , 2021Fayram et al 2009) and enable more robust understanding of Walleye and Yellow Perch responses to ecosystem change.…”

Unveiling the recovery dynamics of walleye after the invisible collapse

“…In doing so these approaches ignore the wealth of knowledge and experience gained from assessing data-rich fisheries throughout the world (Hilborn and Liermann 1998;Myers et al 1999). Furthermore, assessing fishery status across landscapes using age-structured models is more attainable now than ever before as several agencies coordinate monitoring programs similar to the Alberta FWIN program (e.g., see Lester et al 2020). While stock assessment models were mathematically explicit, none of our findings required methodological advances for fisheries science more generally (see similar methods used in Beverton and Holt 1957;Fournier and Archibald 1982;Punt and Hilborn 1997;Millar 2015;Monnahan et al 2019).…”