Responses of plant diversity to precipitation change are strongest at local spatial scales and in drylands

Human-caused climate change is altering global temperature and precipitation patterns, impacting ecosystems and biodiversity. Precipitation changes are particularly variable, with both increases and decreases observed across the globe. While models project ecosystem changes under altered precipitation, experimental manipulations provide crucial causal evidence. Previous meta-analyses of precipitation experiments yielded inconsistent results, often showing no overall effect on biodiversity. This inconsistency may stem from a failure to account for crucial factors like the magnitude and direction of precipitation manipulations, spatial scales of measurement, and background climate conditions. This study addresses these limitations by synthesizing data from a large number of precipitation manipulation experiments, explicitly considering these confounding variables to provide a more comprehensive understanding of how plant diversity responds to changes in precipitation.

Existing literature on the effects of precipitation change on plant biodiversity shows mixed results. Some studies found no overall effect, while others suggested context-dependent responses. The lack of consistent findings highlights the need for a synthesis that accounts for experimental variation in treatment magnitude, direction (increase vs. decrease), and spatial scale. Previous meta-analyses often lacked this level of detail, making it difficult to draw robust conclusions about the overall impact of precipitation change on biodiversity. This study builds upon previous work by explicitly incorporating these factors into a comprehensive analysis of a large dataset.

The authors conducted a systematic literature review, identifying 139 potentially relevant studies. They included studies that manipulated precipitation in field experiments of terrestrial ecosystems and measured plant species abundances. After screening for data availability and quality, the final dataset included 72 precipitation manipulation experiments from 23 studies, spanning diverse biogeographical regions and background precipitation levels. The authors extracted information on experimental location, duration, precipitation manipulation magnitude and direction, and background climate variables from the CHELSA database. Biodiversity was assessed using several metrics at multiple spatial scales (plot, site, and plot-to-plot turnover), including species richness (S), and the effective number of species (SpIE). Log response ratios (LRR) were calculated to quantify treatment effects. Linear mixed-effect models were used to analyze the data, accounting for the non-independence of experiments within studies. Model selection was based on AICc. The influence of background climate (mean annual precipitation, MAP, and potential evapotranspiration, PET) and life history strategies (monocarpic vs. polycarpic) on biodiversity responses was also investigated using appropriate statistical methods.

The analysis revealed that the effects of precipitation manipulation on plant diversity increased with the magnitude of the manipulation, irrespective of the direction (increase or decrease). The strongest effects were observed at the smallest spatial scale (plot scale) and in drier environments. Species richness decreased with experimental decreases in precipitation and increased with experimental increases in precipitation. Increases in species richness with precipitation were associated with higher evenness among common species. However, these effects were less pronounced at larger spatial scales. In drier communities, species richness showed a steeper positive relationship with precipitation manipulation than in wetter communities, at both local and site scales. This climate-dependent effect was primarily linked to stronger changes in total plant cover in drier environments. While aridity was linked to a higher probability of the dominant species being monocarpic, communities dominated by monocarpic species did not differ significantly in their responses to precipitation manipulation compared to communities dominated by polycarpic species. The study found limited evidence of a non-linear relationship between precipitation manipulation and biodiversity responses, indicating that the differences in artifacts and biological responses between treatments increasing or decreasing precipitation were not large enough to change the overall slope of the responses.

This study's findings highlight the importance of considering spatial scale and treatment magnitude when assessing ecosystem responses to climate change. The stronger responses of dryland ecosystems to precipitation change are likely due to the increased establishment probability of species in open patches with increased precipitation and the greater mortality in these already water-limited systems with decreased precipitation. These more pronounced effects of precipitation change on biodiversity in drylands represent a significant threat to these ecosystems, which cover a substantial portion of the earth’s surface, harbor unique biodiversity, and provide vital ecosystem services. The results contradict previous meta-analyses that did not find an overall effect of precipitation change on biodiversity; this difference is attributed to the current study's more thorough consideration of experimental variation.

This study demonstrates that the effects of precipitation change on plant diversity are context-dependent, being strongest at local scales and in dryland ecosystems. These findings emphasize the vulnerability of drylands to projected climate change and highlight the need for targeted conservation and management strategies. Future research should focus on standardizing experimental designs and measuring additional factors (soil conditions, biotic interactions) to enhance the accuracy and generalizability of future syntheses. Filling knowledge gaps in understudied ecosystems, such as tropical and tundra systems, is also crucial.

The study acknowledges limitations arising from the uneven geographic distribution of the included experiments, with a bias towards North America and Europe. The limited sample size in some climate zones may affect the generalizability of the findings. The synthesis relies on existing data, so potential biases stemming from variations in experimental design and data reporting practices may still influence results. Although the authors carefully accounted for several important variables, other unaccounted factors (soil conditions, biotic interactions) might also play a role in the observed responses.