Fish represent vast economic and cultural endowments cooperatively owned by citizens and managed by experts. Accordingly, fishery managers have a responsibility to ensure that publicly-owned resources are not degraded, and that the vitality of wild populations or the stability of ecosystem interactions are not infringed upon by social, cultural, and economic demands. Balancing these competing interests requires robust scientific monitoring methods informing predictive mathematical models that accurately represent stock structure and abundance estimates, independent of fishing activity.

Scientific surveys account for shifting distributions of fish populations in response to environmental variation, changes in fishing pressure, and fluctuations in forage opportunities. Also factored into the analyses are demographic processes such as recruitment dynamics, age and growth, and mortality rates that together provide the necessary data to create accurate estimates of stock structure, spawning stock biomass, and reproductive potential over a broad geographic range.

Managing fisheries is more complex than managing terrestrial species simply because fish flourish in a murky medium that inhibits visual collection of statistical data or movement patterns. Adding to the difficulty, managed fish species tend to incorporate far-ranging, habitat shifts into their life-history patterns to exploit seasonal forage opportunities or to accommodate reproductive demands. Strategies for managing recreational fisheries must therefore account for an array of possibilities occurring in a spatially structured fishery compounded by variability of angler skill and harvest behaviors. To overcome the difficulty of managing multiple species under their purview, fishery scientists often employ stratified-random sampling techniques, which reduces variability in the data by distributing the sampling effort across habitat types and directing greater sampling effort into habitats with higher variability in catch rates.

To understand fisheries, one must also understand that all wild animal populations struggle to exist within an often tempestuous environment that ultimately shapes a population of individuals. Environmental rigor acting on a rich pool of genetic information within a breeding population ultimately shapes both the organism and their life-history patterns, and provides adaptive resiliency to accommodate changing conditions. Nevertheless, within a range of habitat possibilities, species become unevenly distributed into temporal and spatial distribution patterns that reflect both a fundamental range and a realized range. The fundamental range includes all possibilities where a species interacts with their environment, with themselves or with other species. The realized range includes the set of conditions that occur after interactions with other species have been taken into account, and thus are nested as a subset of habitat within the fundamental range. In other words, there are optimal zones within a broader range of habitat in which species choose that provide enhanced forage benefit and/or reproductive potential. However, habitat and forage are most often limited in nature causing competition for position and opportunities, whereby the strongest, largest, most physically fit, or the luckiest specimens obtain tenure in the prime habitat locations.

Hypothetically, individuals with less biological fitness may be relegated to suboptimal locations. As individuals are removed or receive their fill of prey items, a successional replacement process allows other individuals to obtain prime positions for as long as the forage or reproductive window remains open or conditions allow. Adding to the predicament, each year a proportion of fish will die naturally whether they are harvested or not. The rate at which fish die of natural causes is called natural mortality and the rate at which fish die from fishing is called fishing mortality.

Striped bass are the East Coast’s premier game fish that spawn in freshwater, and after spawning activities will venture back to estuarine and marine waters ravenously seeking forage opportunities. Stripers generally seek rips, eddies, structure, or bottom contours  where they can ambush smaller prey struggling in turbulent waters. Discrete contingents of striped bass will harass schools of menhaden in coastal waters, and others will settle around rips or current edges, waiting in ambush for the time and tide to deliver preferred prey. Spatial limitations often restrict advantageous positions at prime locations which then conceivably facilitates cycles of successional replacement. Perennial conditions or migration patterns cause prey to occur in specific locations which then leads to striped bass or other predators aggregating in the most productive habitats. Anglers knowing that same tendency focus their efforts at these same locations year after year. As fish are removed by anglers, other individuals fill the vacant niche allowing catch rates to remain consistent even as metapopulation may be contracting and recruitment declines. However, at some point, replacement rates and CPUE will catch up with each other and suddenly slow as the population falters.

Coastal management of striped bass occurs across state boundaries through a cooperative charter of states under the aegis of the Atlantic States Marine Fisheries Commission. New York along with other representative states within the ASMFC compact are mandated to monitor and manage prized fish species within respective state waters. In accordance with this mandate, scientists utilize a variety of scientific techniques to monitor and assess fish populations. Consistency is a fundamental component of effective monitoring efforts that are repeated along a wide range of habitat locations and performed over extended periods of time. From these surveys, effectiveness of their gear in relation to the census population can be determined as can an understanding of localized stock structure and abundance estimates.

With regard to striped bass monitoring, New York State Department of Environmental Conservation (NYSDEC) implemented Beach Seine Surveys in 1979, followed by Spawning Stock Surveys and fall juvenile surveys in 1985. Those surveys provide continuous, ongoing data sets while generating an expanding database that details all aspects of capture including date, numbers, sex, weight, length, and age-class. Scale samples are also taken and fish are tagged and subsequently released. Tag returns, the Hudson River Cooperative Angler Program, and angler creel surveys add to the volume of data collection. Bolstering those long-term monitoring studies, academic researchers provide further research into striped bass. On top of all that, a mandatory Marine Registry provides a coast-wide estimate of anglers. Each state within the ASMFC collective is mandated to conduct their own state-supported monitoring programs. Combining that trove of data allows the ASMFC to paint an accurate representation of the overall stock structure and population status for each managed species under their authority. A periodic, comprehensive benchmark stock assessment is then conducted and published for each managed species. Thus, with each state conducting their own respective monitoring and submitting their data analyses to the ASMFC, we obtain clear and reliable diagnostics to assess stock health of the coastal populations of striped bass.

A question often asked is how a fish species could be caught in robust numbers and yet the population is simultaneously declining. This phenomenon is not uncommon, and ample scientific research performed under a variety of conditions with various species reveals that catch rates are often misleading. Catch per unit effort (CPUE) can remain sufficiently high and stable long enough to forge a false narrative until fish populations suddenly crash and stocks collapse. At times CPUE can be incorrectly perceived as a proxy for stock status which causes angler optimism, and negative information may be stubbornly resisted by anglers. In situations where CPUE remains consistently high during population instability or downturns, a condition known as stock hyperstability occurs. Under hyperstability situations, catch rates remain sufficiently stable because fish such as striped bass perennially prefer particular habitats and replacement of individuals continually occurs despite broadscale declines, until sudden upset in the system is detected. Hyperstability at prime fishing locations attracts anglers for the same reason their quarry are attracted to prey. Continued fishing success and high catch rates ultimately lead to deceptive perceptions of population status. Danger lies in utilizing CPUE as a proxy for abundance. Consequently, without full range conditions and broadscale status trends, angler perceptions can be understandably distorted into believing robust stock conditions that contravenes data assessments of fishery managers. This situation often leads to a disconnect between fishery scientists and anglers who may perceive that the data are wrong or the experts are misguided. Another way to perceive the phenomenon is to consider an hourglass, where the thin waist of the hourglass represents the restricted perspective of the anglers and the CPUE represents the grains of sand. The CPUE will remain constant as do the grains of sand passing through the bottleneck, until the sand is depleted and time has run out.

Most importantly, the striped bass stock is currently below mandated thresholds. Increasingly strict regulations are necessary to not only ensure survival of the spawning stock biomass but rebuilding of the stock. As I wrote in my last blog, data from the ASMFC reveals that recreational mortality increased by 32 percent in 2022 from the previous year. The increased mortality rates on declining populations of striped bass restricts stock rebuilding goals and reduces the likelihood of achieving threshold levels of the spawning stock biomass as mandated by ASMFC. In 2023, Hudson River striped bass experienced their worst spawning season since 1995. News from Chesapeake Bay has been grim as well, with data showing below average recruitment of juvenile striped bass for the past five years. So while anecdotal fishing reports certainly have value for managing an exploited population, accurate stock assessment and fisheries management must be based upon scientific methodology using probability-based sampling methods from which mathematical estimates of sampling bias, statistical error, sampling error, and confidence intervals can be determined. Surveys not utilizing probability-based statistical methods will fail to accurately capture the true stock structure and health of a managed fish population. The absolute worst outcome for the striped bass and recreational anglers is for stocks to collapse, which is precisely why highly trained experts must manage our fisheries.