Premium
Geographical bias in physiological data limits predictions of global change impacts
Author(s) -
White Craig R.,
Marshall Dustin J.,
Chown Steven L.,
ClusellaTrullas Susana,
Portugal Steven J.,
Franklin Craig E.,
Seebacher Frank
Publication year - 2021
Publication title -
functional ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.272
H-Index - 154
eISSN - 1365-2435
pISSN - 0269-8463
DOI - 10.1111/1365-2435.13807
Subject(s) - climate change , biology , ecology , global change , adaptation (eye) , range (aeronautics) , niche , global warming , extinction (optical mineralogy) , local adaptation , environmental change , phenotypic plasticity , ecological niche , organism , environmental resource management , habitat , environmental science , paleontology , population , materials science , demography , neuroscience , sociology , composite material
Climate affects all aspects of biology. Physiological traits play a key role in mediating these effects, because they define the fundamental niche of each organism. Climate change is likely to shift environmental conditions away from physiological optima. The consequences for species are significant: they must alter their physiology through plasticity or adaptation, move, or decline to extinction. The ability to understand and predict such organismal responses to global change is, however, only as good as the geographical coverage of the data on which these predictions are based. Geographical biases in the state of physiological knowledge have been identified, but it has not been determined if these geographical biases are likely to limit our capacity to predict the outcomes of global change. We show that current knowledge of physiological traits is representative of only a limited range of the climates in which terrestrial animals will be required to operate, because data for animals from only a limited range of global climates have been incorporated in existing compilations. We conclude that geographical bias in existing datasets limits our capacity to predict organismal responses in the vast areas of the planet that are unstudied, and that this geographical bias is a much greater source of uncertainty than the difference between the current climate and the projected future climate. Addressing this bias is urgent to understand where impacts will be most profound, and where the need for intervention is most pressing. A free Plain Language Summary can be found within the Supporting Information of this article.