Aim Species distribution models (SDMs) are common tools in biogeography and conservation ecology. It has been repeatedly claimed that aggregated (stacked) SDMs (S‐SDMs) will overestimate species richness. One recently suggested solution to this problem is to use macroecological models of species richness to constrain S‐SDMs. Here, we examine current practice in the development of S‐SDMs to identify methodological problems, provide tools to overcome these issues, and quantify the performance of correctly stacked S‐SDMs alongside macroecological models. Locations Barents Sea, Europe and Dutch Wadden Sea. Methods We present formal mathematical arguments demonstrating how S‐SDMs should and should not be stacked. We then compare the performance of macroecological models and correctly stacked S‐SDMs on the same data to determine if the former can be used to constrain the latter. Next, we develop a maximum‐likelihood approach to adjusting S‐SDMs and discuss how it could potentially be used in combination with macroecological models. Finally, we use this tool to quantify how S‐SDMs deviate from observed richness in four very different case studies. Results We demonstrate that stacking methods based on thresholding site‐level occurrence probabilities will almost always be biased, and that these biases will tend toward systematic overprediction of richness. Next, we show that correctly stacked S‐SDMs perform very similarly to macroecological models in that they both have a tendency to overpredict richness in species‐poor sites and underpredict it in species‐rich sites. Main conclusions Our results suggest that the perception that S‐SDMs consistently overpredict richness is driven largely by incorrect stacking methods. With these biases removed, S‐SDMs perform similarly to macroecological models, suggesting that combining the two model classes will not offer much improvement. However, if situations where coupling S‐SDMs and macroecological models would be beneficial are subsequently identified, the tools we develop would facilitate such a synthesis.

International audienceThe Bay of Biscay (North-East Atlantic) has long been subjected to intense direct and indirect human activities that lead to the excessive degradation and sometimes overexploitation of natural resources. Fisheries management is gradually moving away from single-species assessments to more holistic, multi-species approaches that better respond to the reality of ecosystem processes. Quantitative modelling methods such as Ecopath with Ecosim can be useful tools for planning, implementing and evaluating ecosystem-based fisheries management strategies. The aim of this study was therefore to model the energy fluxes within the food web of this highly pressured ecosystem and to extract practical information required in the diagnosis of ecosystem state/health. A well-described model comprising 30 living and two non-living compartments was successfully constructed with data of local origin, for the Bay of Biscay continental shelf. The same level of aggregation was applied to primary producers, mid-trophic-levels and top-predators boxes. The model was even more general as it encompassed the entire continuum of marine habitats, from benthic to pelagic domains. Output values for most ecosystem attributes indicated a relatively mature and stable ecosystem, with a large proportion of its energy flow originating from detritus. Ecological network analysis also provided evidence that bottom-up processes play a significant role in the population dynamics of upper-trophic-levels and in the global structuring of this marine ecosystem. Finally, a novel metric based on ecosystem production depicted an ecosystem not far from being overexploited. This finding being not entirely consistent over indicators, further analyses based on dynamic simulations are required