Final thoughts
There are now many studies that support Bergmann’s Rule – across marine (Saunders & Tarling 2018; Wang et al. 2020) and terrestrial systems (Arnett & Gotelli 2003; Ho et al. 2010) – and across ectothermic (Olalla‐Tárraga & Rodríguez 2007; Wilson 2009) and endothermic taxa (Ashton et al. 2000; Brown et al. 2017). Despite this scientific support, there remains limited uptake of Bergmann’s Rule – and other macroecological ideas – in modelling studies. To project changes in biodiversity, ecosystems and fisheries under climate change, a host of modelling approaches are increasingly being coupled with Earth System Models (Everett et al. 2017), including nutrient-phytoplankton-zooplankton models (Stock et al.2014), population models (Feng et al. 2018), size-spectrum models (Carozza et al. 2019), end-to-end ecosystem models (Griffithet al. 2011; Griffith et al. 2012) and statistical models (Grieve et al. 2017). There is considerable opportunity to include well-tested macroecological principles such as Bergmann’s Rule in future modelling efforts focused on climate change. Our analysis shows that these principles could substantially influence future projections.
This study also highlights the utility of using large global datasets for testing macroecological theory. Datasets such as the CPR that have been collected consistently for decades have predominantly been used to understand ecosystem dynamics or describe global change (Edwardset al. 2010). There is great potential for comparative analyses with similar consistent, global datasets. Further, with the advent and increasing accessibility of powerful statistical techniques such as GLMMs – that make it possible to test multiple predictors whilst adjusting for spatial and temporal autocorrelation – there is increasing opportunity for providing robust and nuanced tests of macroecological relationships through spatial comparative analyses (Bolker et al. 2009). We recommend that future studies appropriately account for spatial and temporal autocorrelation, and consider simultaneously testing as multiple potential predictors to avoid spurious and confounded relationships, as was common in the past.
There is still much to learn about Bergmann’s Rule. Future research could be directed towards testing the rule across varied taxonomic levels, detailed investigations of regional differences, and testing nonlinear relationships between size and drivers of Bergmann’s Rule. With directed research in this area, we could get closer to understanding and resolving the many complexities of Bergmann’s Rule that have been debated for decades.
Acknowledgements
Pacific CPR data collection is supported by a consortium for the North Pacific CPR survey coordinated by the North Pacific Marine Science Organisation (PICES) and comprising the North Pacific Research Board (NPRB), Exxon Valdez Oil Spill Trustee Council (EVOS TC), Canadian Department of Fisheries and Oceans (DFO) and the Marine Biological Association, UK. AusCPR data were sourced from the Integrated Marine Observing System (IMOS). IMOS is a national collaborative research infrastructure, supported by the Australian Government. SO-CPR data were sourced from the Scientific Committee on Antarctic Research (SCAR) sponsored Southern Ocean CPR (SO-CPR) Survey Database, hosted by the Australian Antarctic Data Centre (AADC). The AADC is part of the Australian Antarctic Division (AAD, a division of the Department of Environment and Energy of the Australian Government). The SO-CPR Survey and database are also funded, supported and populated by the Australian Government through the Department of Environment-AAD approved AAS project 4107 and the Integrated Marine Observing System (IMOS) funded by the Australian Government National Collaborative Research Infrastructure Strategy and the Super Science Initiative, the Japanese National Institute of Polar Research (NIPR), the New Zealand National Institute of Water and Atmospheric Research (NIWA), the German Alfred Wegener Institute (AWI), the United States of America - Antarctic Marine Living Resources programme (NOAA US-AMLR), the Russian Arctic and Antarctic Research Institute (AARI), the Brazilian Programa Antártico Brasileiro (PROANTAR), the Chilean Instituto Antártico Chileno (INACH), the South African Department of Environment, Forestry and Fisheries (DEFF), the French Institut polaire francais Paul-Émile Victor (IPEV) and Université Pierre et Marie Curie (UPMC). Funding that supports the running of the North Atlantic CPR network used in this project includes DEFRA UK ME-5308, NSF USA OCE-1657887, DFO CA F5955-150026/001/HAL, NERC UK NC-R8/H12/100 and IMR Norway.
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