Species interactions drive continuous assembly of freshwater communities in stochastic environments

Abstract

Understanding the factors driving the maintenance of long-term biodiversity in changing environments is essential for improving restoration and sustainability strategies in the face of global environmental change. Biodiversity is shaped by both niche and stochastic processes, however the strength of deterministic processes in unpredictable environmental regimes is highly debated. Since communities continuously change over time and space-species persist, disappear or (re)appear-understanding the drivers of species gains and losses from communities should inform us about whether niche or stochastic processes dominate community dynamics. Applying a nonparametric causal discovery approach to a 30-year time series containing annual abundances of benthic invertebrates across 66 locations in New Zealand rivers, we found a strong negative causal relationship between species gains and losses directly driven by predation indicating that niche processes dominate community dynamics. Despite the unpredictable nature of these system, environmental noise was only indirectly related to species gains and losses through altering life history trait distribution. Using a stochastic birth-death framework, we demonstrate that the negative relationship between species gains and losses can not emerge without strong niche processes. Our results showed that even in systems that are dominated by unpredictable environmental variability, species interactions drive continuous community assembly.

Keywords: Biodiversity maintenance; Body size scaling; Causal inference; Community assembly; Stochastic modeling.

Fig 1

Sampling locations and river discharge in New Zealand. (a) Macroinvertebrate communities sampled annually across New Zealand rivers over 30 years at 66 sampling sites. (b) The signal-to-noise ratio (SNR) of river discharge time series indicate that New Zealand have rivers ranging from (c) aseasonal (left) to highly seasonal (right) discharge patterns.

Fig 2

Community metrics. Macroinvertebrate communities were sampled annually across New Zealand rivers over 30 years at 66 sampling sites. (a) Communities show overall a slight increase in richness through time. (b) Species evenness was also unchanged through time. (c) Species identity changes in communities were steady over time with relatively high turnover rates. (d) Species gains and losses were negatively correlated in each community (measured as the Spearman’s correlation) (e) with various levels of mutual dependence (dashed orange lines indicate the average value).

Fig 3

Causal graph. Causal relationships between species gains and losses, environmental noise (measured as the noise component of Fourier transform of river discharge) and community weighted mean (CWM) traits. Using causal discovery (PC algorithm) for time series data, results show that predation is the only variable that is directly linked to species gains and losses. Species gains and losses have a negative bidirectional relationship indicating the presence of cycles. Higher environmental noise slightly increases the mean generation time (voltinism) in the community. Higher predation leads to larger average body sizes and higher dispersal tend to lead to smaller body sizes. Larger average body sizes increases the average generation time.

Fig 4

Synthetic analysis of continuous community assembly. Communities assuming stochastic birth-death processes were generated with different levels of interaction strengths over 30 sampling events repeated 100 times for each parameter level. Interaction strengths refer to the average value of the non-diagonal elements of the interaction matrix. The purple dashed line indicates the empirical values. Panel (a) shows the Spearman’s correlation coefficient and panel (b) depicts the mutual information between species gains and losses time series. Stronger species interactions caused a more stronger negative association between gains and losses time series and higher mutual information. (c) Species richness is the highest when species do not interact and decreased with interaction strength. Similarly, interaction strength decreased (d) species evenness and increased (e) species turnover.