Multiple environmental drivers structure plant traits at the community level in a pyrogenic ecosystem

Abstract

Summary Trait‐based approaches offer a way to predict changes in community structure along environmental gradients using measurable properties of individuals. Promoted as being generalizable across systems, trait‐based approaches benefit from information about the environmental drivers of trait variation, how they interact and how they change with scale. However, for most diverse, natural communities, it is largely unknown whether the relationships between leaf‐level traits and interacting environmental drivers (e.g. fire, water availability) are influenced by the scale of trait aggregation. We show that landscape‐level differences in community composition in a diverse, fire‐dependent pine savanna are explained by a small subset of species groups that are strongly correlated with soil moisture and elevation, but are insensitive to the time since the last fire. We used a trait‐based approach to show that significant variation in the community‐weighted mean (CWM) of specific leaf area (SLA) and leaf dry matter content (LDMC), two traits known to drive community structure and function, was explained by a small set of factors including the time since the last fire, soil moisture, precipitation and Shannon diversity. We show that statistical inference about the environmental drivers of community traits is radically altered when using CWMs computed with landscape‐level rather than plot‐level means, even over modest spatial scales. Synthesis: Environmental drivers of community composition across the landscape differed from those explaining trait composition. CWM traits were strongly influenced by interactions between drivers. Fire, in particular, strongly mediated the effect of other environmental variables on LDMC, showing that strong environmental gradients cannot be considered independently when assessing their effects on functional traits. The importance of environmental variables such as fire was lost when using landscape‐level trait means, highlighting the importance of local trait variation. This suggests caution when using traits from distant populations to make inferences about local processes, especially across strong gradients.

Revisiting the Holy Grail: using plant functional traits to understand ecological processes

“…These methods can still be somewhat limiting as focusing on the mean trait, even within subpopulations, neglects the effect of extreme values in the tails of the trait distributions, which may have a profound impact on community response to the environment (Bolnick et al, 2011). Ames, Anderson & Wright (2015) found that statistical inference regarding the environmental drivers of trait variation was greatly altered when using regional species means rather than locally measured trait values. There are several modelling approaches that are better suited for incorporating intraspecific variation into models of community dynamics and function.…”

Contributions of microbial activity and ash deposition to post-fire nitrogen availability in a pine savanna

“…Fort Bragg is composed of burn parcels (hereafter "sites") with independent burn histories. Permanent vegetation sampling transects spanning the topographic gradient have been maintained in 32 sites since 2011; the burn regime in the majority of these sites has been experimentally altered, with a subset of sites being maintained in 3-year burn intervals (Ames et al, 2015).…”

“…Thus, we were left with five study sites: B1, B2, and B3 experienced burns in 2014; C1 and C2 were control sites that remained unburned. Our study sites, renamed here for clarity, correspond to sites 3 and 11 (wildfire site), 15b (B1-3), and 9 and 32 (C1 and C2) described in Ames et al (2015). At each site, we established a 1 m 2 sampling area approximately 5 m upslope of the ecotone.…”

The more things change, the more they stay the same? When is trait variability important for stability of ecosystem function in a changing environment

“…We conducted a trait analysis of 11 plant traits measured on 107 species (63 685 measurements total) from a longleaf pine forest understory in North Carolina, USA (see [24] for trait collection methods and site description). We included a variety of common plant traits, such as SLA (cm 3 g 21 ),…”