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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