In PaulRegular/MSP: Multispecies production model incorporating covariance

Discussion {-}

Rather than assuming that populations are primarily regulated by species-specific carrying capacities, our multispecies production model assumes that both intra and interspecific competition stunts growth as total biomass approaches the environment's maximal load. This assumption is conceptually similar to aggregate production models [@mueter2006; @bundy2012; @fogarty2012] as it is rooted in the idea that total production, and consequently system-level MSY, is limited by the amount of resources available in a given ecosystem. In contrast to aggregate production models, we also attempt to capture the dynamics of species within a community. Fisheries landings, competitive interactions, predation, and prey availability all affect species-level production [@schaefer1954; @lotka1925; @volterra1926]. While our model explicitly accounts for landings, species interactions are implicitly accounted for by estimating species-to-species correlations [sensu @albertsen2018; see @gamble2009 for a more explicit approach]. Finally, by utilizing a state-space framework akin to single-species state-space production models [e.g., @millar2000; @winker2018], we attempt to differentiate population processes from noise and bias from surveys of fish populations. The overall structure of the model allows species-specific dynamics to be captured while avoiding the assumption that the dynamics of each species is isolated and independent from other species sharing the same space and potentially competing for the same resources.

Our case study focuses on the population dynamics of commercially important demersal fish stocks off the east coast of Canada. Stocks in the area collapsed in the early 1990s [@lear1998], and the relative contribution of fishing and environmental impacts has been highly debated [@pedersen2017]. We attempt to disentangle the impacts of fishing from environmental effects using our multispecies production model and, in doing so, we provide empirical evidence that environmental factors played a non-negligible role in the changes observed in the region. First, we found general support for models with a system-level carrying capacity, consistent with the expectation that species within the same ecosystem production unit are constrained by a finite amount of available energy [@pepin2014]. Second, we found evidence for synchronous changes in the demersal fish community, which implies that a common bottom-up driver is impacting the dynamics of these species [see also @bundy2012]. This is supported by species-specific studies on capelin (Mallotus villosus) and Atlantic cod in the region which highlight the influence of bottom-up drivers [e.g., @buren2014a; @buren2014b; @koen2021; @regular2022]. Taken together, evidence is mounting that fishing was not the sole cause of the collapses observed in the early 1990s.

Our inference that environmental factors were a key driver of stock collapses was unexpected given the compelling narrative that fishing activity was the primary driver [e.g., @gomes1995; @hutchings1996]. Since our model utilizes reported fisheries landings, a portion of these losses may be attributed to illegal fishing activity. However, it seems unlikely that the industry had the capacity to extract the amount needed to match the estimated losses. For instance, annual catches in the late 1980s across the Northeast NL Shelf and the Grand Bank totaled ~450 kt while residual losses estimated by the model in the early 1990s was ~1000 kt. The fishing industry would have had to covertly double its efforts to explain the declines. It follows that the decline must at least in part, if not primarily, be due to an unknown environmental driver. This contention is not new [see, for example, @morgan2002; @atkinson1994; @pedersen2017], however, it remains contentious and perplexing as we lack specific causal explanations. While increasingly cold conditions through the 1980s and early 1990s undoubtedly affected the distribution of multiple species [@montevecchi1997; @rose2000, @robertson2021], it is not yet clear whether shifting temperatures was the primary driver of the collapse and, if it was, the causal pathway has yet to be determined.

Regardless of the environmental driver behind the 1990s collapse, it is possible that increasingly industrialized and intense fishing activity through the 1960s and 1970s reduced population diversity and, consequently, hampered the ability of the species within the community to buffer subsequent environmental changes [sensu the portfolio effect, @schindler2010]. Yet, a recent study found no evidence of genetic diversity loss in heavily exploited species like Atlantic cod [@pinsky2021]. Another hypothesis is that fishing activity bounded the safe operating space of the system, triggering an alternate stable state [@scheffer2015]. While not a perfect test of chaotic dynamics, we did assess the possibility of a systematic shift in system-level carrying capacities and found little support for this hypothesis. That said, there were clear shifts in the communities in the region and these shifts may have emerged from the combined effects of interspecific competition and shifting energy pathways. It is well known that the dominant forage species in the area shifted from capelin to shrimp [@dawe2012] and this change was detrimental for cod [@regular2022; @link2019; @mullowney2014] and perhaps other piscivorous species that rely on capelin. Shrimp are an important prey item for redfish species [@brown2022], so it is possible that the increasing shrimp population helped support concurrent recruitment pulses of redfish. We admit that this conjecture is highly speculative; however, we add it as a simple example of how bottom-up forces may be driving the observed changes in the community. The reality is obviously more complex and the observed restructuring of the communities may be akin to the "paradox of plankton" where the continuous interaction of ecological and environmental factors give rise to "oscillations and chaos, with a continuous wax and wane of species within the community" [@scheffer2003].

Like all models, our multispecies production model is an imperfect abstraction of nature and while it may be useful in some contexts, it is important to consider its limitations when interpreting results. First, it is important to remember that there may be a spatial mismatch in the structure and function of the populations included in this study as some stock boundaries differ from the regions used in this study. For instance, Atlantic cod in NAFO divisions 2J3KL are considered a separate stock from cod in divisions 3NO [@templeman1962] and here we split 2J3K (Northeast NL Shelf) and 3LNO (Grand Bank) into distinct regions. Assuming that our results are comparable to previous results, it is peculiar that they indicate that total biomass in the Northeast NL Shelf production unit was above the carrying capacity of that region through the 1980s. This finding contradicts historic records that suggest populations such as Atlantic cod in 2J3KL were at substantially higher levels in the 1970s and earlier [@rose2004; @schijns2021], which implies that the carrying capacity should be higher than estimated by the model presented here. Still, it is possible that the 1970s represents a period of unusually high productivity, where the system may have exceeded the carrying capacity.

Results from the Grand Bank and Southern NL also indicate that the demersal fish community is currently dominated by redfish and, consequently, the system appears to be approaching its carrying capacity. Though redfish are currently rebounding in parts of eastern Canada [@cadigan2022], the implication that it dominates the benthic community seems unrealistic. This result may be an artifact of low estimates of survey catchability or the model’s inability to properly account for year effects. Observation errors are assumed to be lognormally distributed, however, extreme catch events / black swan events in space can introduce ‘year effects’ that may be better accounted for by assuming a distribution with heavier tails, such as the t-distribution [@anderson2019].

Conclusion {-}

Practitioners are becoming increasingly aware of the need to apply an ecosystem based fisheries management [EBFM\; @pikitch2004]. A robust understanding of the interactions of multiple species with each other and their environment is a critical prerequisite for advancing a EBFM. There are multiple analytical pathways to support such management, however, data requirements are often prohibitive [@latour2003]. Our study documents a production model that can estimate the population dynamics of multiple stocks using commonly available landings and survey data. This approach enables the estimation of multispecies trends and provides an avenue for producing species-specific projections conditioned on recent community dynamics. As such, it may serve as a relatively tractable method for informing management decisions for multiple species occupying the same region. While our model has limitations, it represents a step forward in understanding the complex interactions among species in marine ecosystems and provides a framework for supporting sustainable management decisions.

PaulRegular/MSP documentation built on Dec. 16, 2024, 1:59 p.m.