Functional organization of woody plant assemblages along precipitation and human disturbance gradients in a seasonally dry tropical forest

Abstract

Chronic anthropogenic disturbances (CAD) and rainfall are important drivers of plant community assembly, but little is known about the role played by inter‐ and intraspecific trait variation as communities respond to these pervasive forces. Here, we examined the hypothesis that lower precipitation and higher CAD reduce both intra‐ and interspecific trait variation in Caatinga dry forests. We sampled woody plants across 15 plots along precipitation and CAD gradients and measured resource‐use traits. The effects of precipitation and CAD on RaoQ functional diversity were decomposed into species turnover and intraspecific variability. We used “T‐statistics” to assess the trait sorting from the regional pool to local communities (i.e., external filtering), and within‐community forces leading to low trait overlap (i.e., internal filtering) at individual and species levels. Intraspecific variability explained at least one‐third of the total trait variation and 46% of variation in multitrait diversity across communities. Increasing disturbance reduced multitrait diversity, while precipitation affected some particular traits, such as wood density. Overall, precipitation determined species sorting across communities, while disturbance relaxed internal filters, leading to higher trait overlap within communities due to higher intraspecific variability. Our results suggest that the woody Caatinga flora contains a substantial amount of both inter‐ and intraspecific trait variation. This variation is not randomly distributed within and across communities, but varies according to rainfall conditions and disturbance intensity. These findings reinforce the emerging idea that human disturbances can reorganize plant communities at multiple scales and highlight trait variability as a key biological asset for the resilience of dry forests.

Intraspecific trait variability and community assembly in hawkmoths (Lepidoptera: Sphingidae) across an elevational gradient in the eastern Himalayas, India

“…Ironically, this variation of the internal filter across the environmental gradient, as with any other trait metric, is also evidence for the action of an external filter. Such a variation has only been reported previously by Zorger et al (2019). We suggest that this pattern was discernible in this study because the environmental range was large (spanning both tropical and temperate biomes), continuous, and closely sampled (every 200 m).…”

“…Such a variation has only been reported previously by Zorger et al. (2019). We suggest that this pattern was discernible in this study because the environmental range was large (spanning both tropical and temperate biomes), continuous, and closely sampled (every 200 m).…”

“…Conversely, even though the SES of T PC/PR of body mass and wing loading lay well within the null model envelopes, they exhibited a definite pattern (linear or otherwise) with elevation (Figure 4, bottom row). This has also been observed by Zorger et al (2019). Therefore, the action of an external filter can be discerned in two different ways: (i) the usual one of communities being nonrandom subsets of the regional pool, and (ii) a directional variation of any metric along the environmental gradient.…”

“…Identifying the most important environmental factor and its mechanistic role in community assembly is a difficult exercise. Of the previous studies using T‐statistics , three used nonparametric environmental classes (Danet et al., 2018; Khalil et al., 2019; Neyret et al., 2016), five used a surrogate (latitude: Hulshof et al., 2013; Outreman et al., 2018; elevation: Hulshof et al., 2013; Luo et al., 2016; Neyret et al., 2016; Wu et al., 2019), one used precipitation and anthropogenic disturbance (Zorger et al., 2019), two dealt with multiple variables (Le Bagousse‐Pinguet et al., 2014; Subedi et al., 2019), and two did not have an obvious gradient (Gusmão et al., 2020; Xavier‐Jordani et al., 2019). Even when the gradient is obvious, teasing apart the confounding factors can be difficult.…”

“…Additionally, one can test for deviation of the measured values of the metrics from those expected from randomness. Significant deviation from randomness is considered evidence of the impact of an ecological process on the trait distribution (Danet et al., 2018; Gusmão et al., 2020; Khalil et al., 2019; Luo et al., 2016; Neyret et al., 2016; Outreman et al., 2018; Subedi et al., 2019; Xavier‐Jordani et al., 2019; Zorger et al., 2019).…”