Increasing the resolution of global change gradients along which
traits are measured
Species traits are often measured along major environmental gradients
(i.e. elevation or latitude), with measurements focused on capturing
intraspecific variation (Chalmandrier et al. 2017), interspecific
variation (Balasubramaniam & Rottenberry, 2016), or both (Classen et
al. 2017). Such gradients usually encompass a broad range of
environmental factors that can be static or dynamic across space and
time (i.e. water temperature, acidity, soil quality, wind, etc.).
Constructing trait-based predictions requires ecologists to identify at
what scale specific traits metrics change in response to particular
aspects of the gradient of interest, yet trait variation is often not
explicitly linked to measures of important aspect of the gradient at the
same resolution (e.g. environmental data collected at the region or site
level, while trait data collected at the individual level). Designing
field data collection with trait and environmental data sets gathered at
equal resolutions allows ecologists to quantify the scale at which
variation in both response and explanatory variables matters for the
environmental filtering process(s) under investigation (i.e. Figure 1).
Advanced multivariate techniques (e.g. fourth corner an RQL analysis)
can be used to parse out relationships between traits and different
aspects of environmental gradients, as well as the spatial and temporal
scale at which these relationships hold, subsequently allowing for the
identification of potential ecological mechanisms driving trait and
phylogenetic patterns across land and seascapes (Anderson et al. 2019).
Without explicit links between directional trait variation and the
aspect(s) of the environment driving that change, ecologists may
continue to miss likely causal relationships that are useful for
prediction.