Comparing the steady state results of a range of multispecies models between and across geographical areas by the use of the jacobian matrix of yield on fishing mortality rate

Abstract

A B S T R A C TLike other fisheries models, multispecies models are subject to various sources of error. However, with regard to their use for ecosystem-based fisheries management (EBFM) between model errors are likely to be most important. As multispecies models are by definition many-dimensional, comparing them is potentially a complex task. The paper uses a simple approach. This is to calculate the Jacobian matrix of long term steady state catch by species with respect to the fishing mortality relative to status quo levels on all species. This enables the comparison of the relative strength of species interactions among models both within and between regions. This Jacobian matrix approach to comparing multispecies models is applied to available models for the North Sea, the Baltic Sea and from Icelandic waters. Moreover, this information is used to provide the basis for estimating a multidimensional quadratic yield surface for each model in the near field. Used this way it is possible to compare different model estimations of fishing mortality rate changes needed to approach yield-related management goals. The results suggest considerable variation between models in their detailed results but more coherence in suggesting directions for changing fishing mortality rate. Thus the approach is of considerable importance in specifying the confidence with which it is possible to make multispecies predictions for EBFM.

Spatio‐temporal models of intermediate complexity for ecosystem assessments: A new tool for spatial fisheries management

“…Livingston et al, 2017). We therefore support ongoing comparative research using multiple ecological models when evaluating climate or human-mediated changes on marine ecosystems (Kaplan et al, 2018;Olsen et al, 2016;Pope et al, 2019;Spence et al, 2018;Tittensor et al, 2018), and note that the MICE-in-space model could fill a useful niche in these model portfolios. Finally, nonconsumptive processes may cause diet analyses to misrepresent the cumulative impact of changing biomass for one species on per-capita productivity for other species.…”

“…Comparing results from multiple ecosystem models can help to evaluate the sensitivity of estimated ecosystem properties to structural assumptions and multiple data sources. We therefore support ongoing comparative research using multiple ecological models when evaluating climate or human-mediated changes on marine ecosystems (Kaplan et al, 2018;Olsen et al, 2016;Pope et al, 2019;Spence et al, 2018;Tittensor et al, 2018), and note that the MICE-in-space model could fill a useful niche in these model portfolios.…”

“…through predation or starvation) are often confounded in ecosystem models, and simultaneously addressing these two issues is a key goal in current ecosystem models in regions including the Bering Sea (e.g. multimodel inference) can be used to identify sensitivities in model specification and propagation of error (Kaplan et al, 2018;Pope et al, 2019;Spence et al, 2018). Underlying model structure and implicit versus explicit treatment of environmental or trophic changes to a population becomes extremely important when projecting models for management advice, especially on longer timescales (Lotze et al, 2019).…”

“…These comparisons are vital to identify the relative computational and human resource costs of these different models, as well as identify when models provide different advice (Kaplan et al, 2018;Pope et al, 2019). Comparison with alternative ecosystem models: Perhaps most importantly, we recommend detailed, side-by-side comparison of MICE-in-space and other ecosystem models.…”

What is multispecies MSY? A worked example from the North Sea

“…Whilst MSY is easy to determine for a single stock in isolation, however, it is much more problematic for a multispecies community (Guillen et al, 2013), where it is not in general possible to maximise the yield of all stocks simultaneously (FAO, 2001;Voss et al, 2014;Farcas & Rossberg, 2016;Ulrich et al, 2016;Norrstrom et al, 2017, Pope et al, 2019, whilst maximising the total yield may place the most vulnerable stocks at unacceptable risk (Matsuda & Abrams, 2006). This tension can be seen in Figure 1, which is adapted from Worm et al (2009) and represents the effect of progressively increasing a fixed pattern of fishing mortality across a fish community.…”