Introduction:
Considerable recent research has investigated how species’ ecological
niches evolve over time. Most of these studies have examined whether and
at what speed niches evolve in speciating lineages (e.g.,
Peterson et al. 1999;
Graham et al. 2004;
Knouft et al. 2006;
Losos 2008;
Pearman et al. 2008;
Evans et al. 2009;
Vieites et al. 2009;
Nyári and Reddy 2013;
Owens et al. 2017;
García-Navas and Rodríguez-Rey 2018).
Methods for estimating fundamental ecological niches
(Peterson et al. 2011;
Hijmans and Elith 2015) and inferring
macroevolutionary patterns from phylogenies
(Swofford and Maddison 1987;
Lanyon 1993;
Freckleton et al. 2002;
Pagel et al. 2004;
O’Meara 2012;
Revell 2012) have improved greatly in
recent decades. These developments have facilitated a paradigm shift
toward investigating biogeographic history in the context of
reconstructed ancestral ecological niche characteristics (e.g.,
Rice et al. 2003;
Graham et al. 2004;
Knouft et al. 2006;
Pearman et al. 2008;
Anciães and Peterson 2009;
Evans et al. 2009;
Vieites et al. 2009;
Smith and Donoghue 2010;
Nyári and Reddy 2013;
Ribeiro et al. 2016;
Owens et al. 2017).
Researchers have used several approaches to characterize ecological
niches when attempting to reconstruct the evolutionary history of
species’ niches. Some of the earliest studies used means and standard
errors of suitable abiotic niche characteristics in their
reconstructions (Rice et al. 2003;
Anciães and Peterson 2009). Soon, however,
researchers began characterizing niches using minimum and maximum
suitable abiotic niche values (Graham et
al. 2004; Yesson and Culham 2006),
central tendencies of suitable niche values (i.e. mean or median;
Ackerly et al. 2006;
Kozak and Wiens 2010;
Cooper et al. 2011), or distributions of
suitable niche values (Evans et al. 2009;
Smith and Donoghue 2010). These data were
derived either directly from the occurrence data (e.g.
Ackerly et al. 2006;
Kozak and Wiens 2010;
Cooper et al. 2011) or from ecological
niche model outputs (e.g. Rice et al.
2003; Smith and Donoghue 2010;
Nyári and Reddy 2013).
Fundamental ecological niches, however, are rarely characterized
completely and unambiguously, owing to pervasive partial representation
of fundamental ecological niches when assessed and characterized over
real-world landscapes (Fig. 1; Saupe et
al. 2012; Veloz et al. 2012;
Owens et al. 2013;
Guisan et al. 2014;
Warren et al. 2014; Saupe et al. 2017).
The fundamental ecological niche is defined as the set of conditions
under which the species is able to maintain populations without
immigrational input (Soberón 2007). The
ability of a species to occupy a particular fundamental ecological niche
is the result of phenotypic traits subject to natural selection
(Peterson et al. 2011). However, the full
suite of environmental conditions in a species’ fundamental niche is not
necessarily represented across Earth at any given time. Furthermore,
existing abiotic conditions are not necessarily accessible to a species
or coincident with suitable biotic conditions (Barve et al. 2011). A
species’ realized niche (i.e. where the species is found) is determined
by available resources, biotic factors such as competition, availability
of suitable environments, and/or dispersal barriers and dispersal
capabilities (Soberón 2007). As such, any characterization of
fundamental ecological niches that relies on inference from species’
geographic distributions (i.e. realized niche) will either be incomplete
or will have to be inferred via extrapolation
(Saupe et al. 2012;
Owens et al. 2013). Hence, while the
estimated niche of a lineage through time may show variation in response
to inherited adaptations that alters the lineage’s fundamental niche,
that variation may also derive from changes in the set of environments
accessible to that lineage, which do not represent a
genetically-inherited set of adaptations (Araújo et al. 2013).
Methodologies that use estimates based on species’ realized niches to
characterize ecological niches in phylogenetic analyses are known to
overestimate true amounts of niche change
(Saupe et al. 2017). Here, we present a
new framework to characterize species’ fundamental niches, which further
emphasizes and illustrates the importance of considering gaps in
knowledge as part of coding species’ fundamental niches as characters
for comparative phylogenetic analyses. The framework relies on
consideration of areas sampled by researchers and accessible to the
species over relevant time periods (M ; Phillips et al. 2009;
Barve et al. 2011; VanDerWal et al. 2009). Estimating and accounting for
this region has already been recognized as important in model excersises
that use background or pseudo-absence data for calibration of suitable
habitat (Phillips et al. 2009; Barve et al. 2011). If sampling effort
and regions accessible to a species are ignored when selecting the
geographic extent for model calibration, fitted models may be closer to
models of survey effort and/or erroneously omit suitable niche
conditions. However, even niche estimates derived from presence-only
data (i.e., without a modelling component) should consider M ,
as doing so provides one of the only ways of assessing whether estimates
are likely to be truncated. Specifically, unknown tolerance limits may
be highlighted when environments across M do not encompass
conditions in excess of those where the species in question is observed.
In these cases, it may be prudent to indicate potential suitability of
environments outside of the environmental bounds of M , whilst
noting uncertainty in these estimates. Thus, a broader suite of
environmental conditions must be considered, often derived from the
region occupied by a focal clade rather than the M of a single
species. The conceptual advance for our new approach is in assessment of
niche estimates in the context of available environments withinM , considering shared environmental space across all focal
species to account for potential cases of niche truncation.
Specifically, our new character coding method decomposes species’ niches
into discrete bins across the broader environmental background occupied
by a clade, and scores each bin as within, outside, or uncertain for
each species’ fundamental niche (Fig. 1). We illustrate the utility of
summarizing species’ niches this way by performing a simulation that
compares evolutionary rates estimated from characters coded using our
method to those estimated in a more traditional analysis. We detail how
to use our new coding scheme to infer ancestral ecological niches and
demonstrate the utility of our approach with an empirical
example—inferring patterns of ecological niche evolution in New
World orioles (Icterus spp.).