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Conducting robust ecological analyses with climate data
Author(s) -
Suggitt Andrew J.,
Platts Philip J.,
Barata Izabela M.,
Bennie Jonathan J.,
Burgess Malcolm D.,
Bystriakova Nadia,
Duffield Simon,
Ewing Steven R.,
Gillingham Phillipa K.,
Harper Anna B.,
Hartley Andrew J.,
Hemming Deborah L.,
Maclean Ilya M. D.,
Maltby Katherine,
Marshall Harry H.,
Morecroft Mike D.,
PearceHiggins James W.,
PearceKelly Paul,
Phillimore Albert B.,
Price Jeff T.,
Pyke Ayesha,
Stewart James E.,
Warren Rachel,
Hill Jane K.
Publication year - 2017
Publication title -
oikos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.672
H-Index - 179
eISSN - 1600-0706
pISSN - 0030-1299
DOI - 10.1111/oik.04203
Subject(s) - climate change , ecology , climate science , climate model , data science , computer science , representation (politics) , data sharing , environmental resource management , environmental science , political science , biology , medicine , alternative medicine , pathology , politics , law
Although the number of studies discerning the impact of climate change on ecological systems continues to increase, there has been relatively little sharing of the lessons learnt when accumulating this evidence. At a recent workshop entitled ‘Using climate data in ecological research’ held at the UK Met Office, ecologists and climate scientists came together to discuss the robust analysis of climate data in ecology. The discussions identified three common pitfalls encountered by ecologists: 1) selection of inappropriate spatial resolutions for analysis; 2) improper use of publically available data or code; and 3) insufficient representation of the uncertainties behind the adopted approach. Here, we discuss how these pitfalls can be avoided, before suggesting ways that both ecology and climate science can move forward. Our main recommendation is that ecologists and climate scientists collaborate more closely, on grant proposals and scientific publications, and informally through online media and workshops. More sharing of data and code (e.g. via online repositories), lessons and guidance would help to reconcile differing approaches to the robust handling of data. We call on ecologists to think critically about which aspects of the climate are relevant to their study system, and to acknowledge and actively explore uncertainty in all types of climate data. And we call on climate scientists to make simple estimates of uncertainty available to the wider research community. Through steps such as these, we will improve our ability to robustly attribute observed ecological changes to climate or other factors, while providing the sort of influential, comprehensive analyses that efforts to mitigate and adapt to climate change so urgently require.