Selection on the timing of migration and breeding: A neglected aspect of fishing-induced evolution and trait change

2.1 Direct temporal management

Many fishes undertake spawning migrations or form large groups during reproduction (Harden Jones, 1981; Neuenfeldt et al., 2013; van Overzee & Rijnsdorp, 2014; Sadovy de Mitcheson, 2016), aggregating a fisheries resource in time and space. Indeed, the majority of global fisheries catch is comprised of species that display seasonal movement patterns (Harden Jones, 1981). Fishermen have long exploited these movements and aggregations, and management measures such as spatial and seasonal closures—restricting fishing in certain areas, during certain times of the year or a combination of the two—are common for protecting fish during these vulnerable periods (Erisman et al., 2012; Loher, 2011; Sadovy de Mitcheson, 2016). Because they are explicitly temporal in nature, typically consistent across multiple years and commonly have some basis in the reproductive biology of the targeted species, seasonal closures are a likely cause of temporal selection in fisheries; almost inevitably some fish migrating or breeding outside the closed period are vulnerable to harvest. When migratory or reproductive behaviour is distributed across several weeks or months, it is often technically or politically difficult to enforce a seasonal closure that protects all breeders equally. This is the case in many river fisheries for Pacific salmon (Oncorhynchus spp., Salmonidae), where efforts to balance the conservation of depleted stocks with full exploitation of more abundant stocks have produced a complex system of seasonal closures that can lead to differential exploitation between early and late migrating fish (Larson & Ward, 1955; Washington Department of Fish and Wildlife, 2016). A similar type of selection occurs in the Canadian Pacific halibut (Hippoglossus stenolepis, Pleuronectidae) fishery, which utilizes a winter closure (typically mid-November through mid-March) to protect fish during their offshore migration and spawning. However, telemetry studies have revealed that the traditional closure does not completely protect migrants in either the spring or fall, and the fishery can therefore exert either directional or stabilizing selection (Loher & Seitz, 2008).

Non-migratory species can also be subjected to temporal selection because spawning date often varies by weeks or months within populations (Martell, Walters, & Wallace, 2000). For example, lingcod (Ophiodon elongatus, Hexagrammidae) typically spawn between January and April, and fisheries in Washington, British Columbia and Alaska all observe seasonal closures intended to protect nest-guarding males. Guarding males are sedentary, aggressive and highly susceptible to both hook and line and spearfishing mortality (Martell et al., 2000; Stahl, Green, & Vaughn, 2014; Withler et al., 2004). However, in each of these regions at least some males have been observed guarding after the spring opening dates (Smith, McFarlane, & Cass, 1990). Nest-guarding species in fresh water including important recreational species such as largemouth bass could also be susceptible to similar temporal selection (Gwinn & Allen, 2010). This type of incomplete spawning closure selects strongly against late reproduction because such guardian males would be vulnerable, and their death also exposes the clutch to egg predators (Withler et al., 2004).

2.2 Indirect temporal management

In addition to the fixed-date seasonal closures described above, flexible closures also occur (Melnychuk, Banobi, & Hilborn, 2014). In such cases, fishery openings vary from year to year, depending on in-season monitoring of abundance, environmental conditions, physiological state (e.g., proportion ripe, spawned or moulted) or presence of non-target species. For example, in some Pacific herring (Clupea pallasii, Clupeinae) fisheries, harvest is delayed until the majority of females have fully developed (and therefore marketable) roe (Thynes, Gordon, Harris, & Walker, 2016). This effectively reduces the harvest rate on early spawning fish and may impose directional selection on spawning date (Ware & Tanasichuk, 1989). Fisheries that target anadromous species often are managed to allow a fixed number of individuals—“the escapement”—to pass upstream for spawning (Walters, 1981). Even when managers endeavour to distribute the escapement evenly throughout a salmon run, several temporally selective mortality patterns can result from limited harvest capacity or management uncertainty (Sethi, Costello, Fisher, Hanemann, & Karp, 2005). If the capacity of a fishing fleet is limited, then a “predator swamping” effect may occur during the period of peak abundance. This results in stabilizing selection by lowering harvest rates during the middle of the migration relative to the beginning and end (Figure 2b; Ims, 1990). Alternatively, precautionary management can limit fishing during the early portion of the migration because of uncertainty in overall abundance, shifting to higher exploitation rates once the management targets have been met (i.e., directional selection as in Figure 2c). Quinn et al. (2007) demonstrated both patterns of selective mortality in the Egegik fishing district of the Bristol Bay sockeye salmon (Oncorhynchus nerka, Salmonidae) fishery. During the early 1970s, harvest rates were lower during peak abundance (as in the generalized example in Figure 2b), but in recent decades the managers have been reluctant to allow fishing early in the season, resulting in strongly directional selection on migration date (as in Figure 2c with data shown in Figure 3).

The case of Bristol Bay sockeye salmon demonstrates that even when management is “conservation minded” and not explicitly temporal in nature, selective harvest may nevertheless occur. Efforts to control overfishing have led to the introduction of strict harvest quotas in many fisheries, and in some cases, there is a “race for fish” as fishermen strive to fulfil these quotas over very short time periods (Chu, 2009). Annual quotas that lead to early closure of fisheries result in the same temporal pattern of fisheries mortality as seasonal closures (Figure 2a), whereas daily quotas or trip limits impose stabilizing selection by reducing harvest rates during periods of peak abundance (Figure 2b). While comprehensive statistics on the prevalence of fisheries management strategies are not available, fixed or variable temporal closures are very common management practices (Melnychuk, Banobi, & Hilborn, 2013). The increasing focus on preventing overfishing around the world is likely to bring more fisheries under seasonal or quota management systems capable of producing temporally selective fishing mortality (Anderson et al., 2012).

2.3 Fishermen's behaviour

In addition to management actions, the behaviour of fishermen is likely to result in temporally selective fishing effort because people tend to fish when it is most economical, safe or productive. In many areas of the world, seasonally bad weather or other environmental conditions (e.g., ice, high river flows) limit fishing at certain times of the year (Smith & Wilen, 2005). Because migration and breeding commonly coincide with seasonal changes in environmental conditions (ice, storms, high river flows, etc.), selection can occur if part of the population has already reproduced or migrated by the time fishing becomes safe or practical (Figure 2a). Fishermen are also sensitive to economic forces, and fishing effort commonly changes throughout the year in response to seasonal variability in the absolute or relative profitability of targeting different species or stocks (Katsukawa & Matsuda, 2003). Fishing that targets periods of abundance (such as spawning aggregations or migrations) can increase profitability, but might also impose disruptive selection if less abundant early and late migrants or breeders experience lower fishing mortality (Figure 2d). Thus, various forms of temporal selection can result from intentional management actions, or as unintended consequences of management and the behaviour of fishermen. Furthermore, the phenomenon is likely widespread in both commercial and recreational fisheries, freshwater and marine environments, and across a range of taxa.

3.1 Evolutionary impacts

Following evolutionary theory, spawning should be timed to maximize reproductive success by optimizing the balance between survival of parents and their progeny; reproductive phenology should reflect the prevailing environmental and ecological conditions experienced throughout the period of maturation, spawning and hatching (Cushing, 1969; Sinclair & Tremblay, 1984; Wright & Trippel, 2009). In some cases, reproductive phenology can be very plastic, responding to environmental changes such as water temperature (e.g., American shad [Alosa sapidissima, Clupeinae] Leggett & Whitney, 1972; striped bass [Morone saxatilis, Moronidae] Peer & Miller, 2014). However, in other cases, especially in salmonids, the genetic control over timing of upstream migration and reproduction is much stronger, as inferred from (i) population-specific differences in timing (Hodgson & Quinn, 2002; Webb & McLay, 1996), (ii) selective breeding experiments (Neira et al., 2006; Siitonen & Gall, 1989), (iii) evolution of timing in hatchery populations (Hard, 2004; Quinn, Peterson, Gallucci, Hershberger, & Brannon, 2002; Tipping & Busack, 2004), (iv) estimates of heritability in wild populations (Dickerson, Willson, Bentzen, & Quinn, 2005; Lin et al., 2016), (v) changes in response to fishery selection (Quinn et al., 2007), and (vi) the rapid evolution of timing outside the native range of the species (Quinn, Unwin, & Kinnison, 2000). Indeed, there is often substantial variation in reproductive phenology—both migration and spawning timing—among and within salmon populations (Quinn et al., 2016), and heritability in these traits appears quite high (Carlson & Seamons, 2008; Dickerson et al., 2005; Lin et al., 2016). In some populations, more than half the variability of spawn timing in progeny can be predicted by spawn timing in adults (Quinn et al., 2000; Thériault, Garant, Bernatchez, & Dodson, 2007). Thus, at least in salmonids the key ingredients for adaptive evolution of reproductive phenology are both present; variability on which selection can act and heritability of timing traits.

Quinn and Adams (1996) hypothesized that because the environments experienced by anadromous salmon during migration and spawning are temporally distant from the conditions experienced by their progeny, the optimal strategy is to track long-term mean conditions rather than short-term variation. In contrast, for other anadromous fish such as American shad and striped bass that have shorter incubation periods, environmental conditions at the time of migration or spawning better predict conditions at hatching, thus favouring plasticity in spawning date (Peer & Miller, 2014). The strength and rate of evolutionary responses to temporal selection is therefore expected to vary between taxa and salmonids may represent a somewhat extreme case. Nevertheless, even in species with more plastic reproductive phenology, evolution of timing traits is possible because trait variability commonly reflects an underlying, genetically controlled norm of reaction to external cues (Crozier & Hutchings, 2014). Reaction norms such as size at maturity evolve in response to size-selective fishing (Kendall, Dieckmann, Heino, Punt, & Quinn, 2014), and similar responses in both the mean and variability of timing traits seem probable responses to temporal selection. Fisheries-induced evolution of timing traits could have significant and long-lasting impacts on fisheries sustainability by disrupting the relationship between phenology and the ecological conditions that optimize reproductive success (Beaugrand, Brander, Alistair Lindley, Souissi, & Reid, 2003; Cushing, 1990; Sinclair & Tremblay, 1984). However, even in the absence of a genetic response, temporal selection can drive trait changes that influence the productivity of populations and stock complexes (Lowerre-Barbieri et al., 2011; Wright & Trippel, 2009).

3.2 Ecological and demographic impacts

Although reproduction follows predictable cycles in most fishes, there is often significant variation in timing between individuals from the same population (Scott, Marteinsdottir, Begg, Wright, & Kjesbu, 2006). This variation can buffer the population against an uncertain environment by ensuring that at least some offspring are likely to encounter favourable conditions. This variation in larval survival, commonly known as the match-mismatch hypothesis, is foundational in fisheries oceanography (Cushing, 1990) and has often been demonstrated in marine systems where fishes rely on secondary productivity of zooplankton and other small pelagic prey (Beaugrand et al., 2003; Cushing, 1990; Mertz & Myers, 1994; Sinclair & Tremblay, 1984). These fundamental principles apply to freshwater systems as well, so alteration of the normal phenology is likely to affect recruitment in lakes (e.g., Ludsin, Devanna, & Smith, 2014). Consistent with the match-mismatch hypothesis, empirical (Mertz & Myers, 1994) and simulation (James, Pitchford, & Brindley, 2003) studies have found that longer spawning seasons increase a population's productivity and reduce recruitment variability in uncertain environments.

Because mortality from fishing reduces the probability of fish growing old and large, exploited populations—even in the absence of any size or temporal selectivity—can nevertheless experience reductions in the duration and shifts in the peak of spawning activity as a result of altered demographics (Hixon, Johnson, & Sogard, 2014). Size and reproductive timing are commonly correlated; early migrating and spawning salmonids are commonly (though not universally) larger or older than those later in the run (Anderson & Beer, 2009; Bracis & Anderson, 2013; Doctor & Quinn, 2009; Quinn et al., 2016). Indeed, this pattern occurs in many fishes, although in some cases the reverse pattern is seen (Horrall, 1981). For example, in Atlantic cod the larger and older individuals tend to spawn later and over a longer period compared to younger ones (Hutchings & Myers, 1994). Thus, the loss of large, old individuals in heavily exploited populations is likely to reduce overall reproductive output, but also shorten the spawning season, potentially reducing the likelihood of a “match” of juveniles with abundant prey (Cushing, 1990; Mertz & Myers, 1994). Indeed, Wright and Trippel (2009) reviewed the potential impact of demographic-driven changes in spawn timing and duration on reproductive success in fishes and argued that this is likely a major component of reduced productivity in age-truncated populations. In similar fashion to this process of demography-driven contraction of spawning seasons in exploited populations, directional and stabilizing temporal selection both serve to reduce the number individuals spawning at the extremes of the temporal distribution. As such, temporal selection may result in the same negative outcomes for impacted populations including increased variability and reduced productivity.

Size selectivity, especially the common pattern of increased exploitation of large individuals, only serves to exacerbate the issue of spawning season contraction as it further reduces the abundance of large individuals with particularly early or late spawn timing (Hixon et al., 2014). Additionally, because timing often covaries with size and age, there is the potential for complex interactions between multiple forms of selection and demographic impacts of fishing (Anderson et al., 2008; Wright & Trippel, 2009); just as size-selective fishing may influence timing, temporally selective fishing may in turn influence size. Depending on the temporal pattern of fisheries mortality, the direction of size selectivity and the relationship between size and timing, various outcomes seem plausible in the case of dual selectivity including counteracting and reinforcing effects on correlated traits. To further complicate matters, size and phenology may also be associated with other behavioural traits such as boldness or aggression (Biro & Post, 2008; McPhee & Quinn, 1998). These interactions highlight the fact that both the process of, and biological responses to, all forms of fisheries selection do not happen in a vacuum and trait changes in exploited fish populations may result from selection on ostensibly unrelated traits.

3.3 Impacts on stock complexes

Advances in population genetics have revealed that many commercially exploited fish populations once thought to be relatively homogeneous have complex stock structure (Stephenson, 1999; Waples & Naish, 2009). Subpopulations with unique morphology, phenology, population dynamics and ecological interactions commonly comingle despite reproductive isolation, and can therefore be harvested by a single fishery (Hilborn, 1985a). When populations vary in their productivity or are differentially vulnerable to harvest, management as a single stock can lead to population-specific depletion or extirpation (Hilborn, 1976). Populations exploiting even subtly different ecological niches commonly vary in productivity; thus, applying a single harvest rate to a stock complex will often deplete the less productive populations (Hilborn, 1985a; Ricker, 1958). In salmon, differences in migratory timing between populations returning to the same river system have been exploited by managers through temporal closures to protect the weaker stocks while harvesting the more abundant (Collie et al., 1990). However, in cases where populations overlap significantly in migration timing, or timing differences are not appreciated, temporally selective fishing can shift the overall run-timing by altering the relative abundances of the substocks (Figure 4). For example, the sockeye salmon run to Bear Lake, Alaska, is characteristically bimodal, with distinct early and late peaks, and management was based on the idea that there were distinct early and late populations. However, Boatright, Quinn, and Hilborn (2004) revealed a series of populations with a continuum of migration timing. The higher exploitation rate in the middle of the season had created the appearance of bimodality by suppressing the populations migrating at that time.

Long-term monitoring of stock complexes with fine-scale population structure has demonstrated that the relative productivity of individual stocks fluctuates significantly over time, and increased diversity therefore stabilizes overall variability in abundance, a phenomenon now commonly referred to in ecology as the portfolio effect (Schindler et al., 2010). Thus, reduced genetic and phenotypic diversity resulting from over-exploitation of individual stocks serve to erode the portfolio effect and can therefore increase overall variability (Hilborn, Quinn, Schindler, & Rogers, 2003) and reduce the long-term resilience of stock complexes to environmental change (Moore, McClure, Rogers, & Schindler, 2010). The importance of maintaining population structure and intraspecific diversity has been appreciated for decades in Pacific salmon management (Thompson, 1959) but has been less widely known in marine fishes until more recently (Stephenson, 1999). Reproductive timing in Pacific herring varies significantly between populations spawning in discrete locations (Haegele & Schweigert, 1985; Hay, 1985). However, many populations comingle in the winter and during pre-spawn staging periods in coastal areas where they are fished (Ware & Tanasichuk, 1989). Variability between populations in spawning date or the duration of staging is likely to influence susceptibility to fisheries, and population-specific over-exploitation might occur. Such losses of genetic and phenotypic diversity may also impede the recovery of depleted stocks. For example, Ames (2004) reported that prior to intensive fishing, the Atlantic cod stock complex in the Gulf of Maine was composed of many smaller subpopulations with unique spatial and temporal migration patterns. Many of these subpopulations were extirpated during decades of intensive harvest, and even after years of drastically reduced fishing, the historic diversity in migratory routes and spawning areas has not recovered (Ames & Lichter, 2013).