Global change effects on plant communities are magnified by time and the number of global change factors imposed

Abstract

Global change drivers (GCDs) are expected to alter community structure and consequently, the services that ecosystems provide. Yet, few experimental investigations have examined effects of GCDs on plant community structure across multiple ecosystem types, and those that do exist present conflicting patterns. In an unprecedented global synthesis of over 100 experiments that manipulated factors linked to GCDs, we show that herbaceous plant community responses depend on experimental manipulation length and number of factors manipulated. We found that plant communities are fairly resistant to experimentally manipulated GCDs in the short term (<10 y). In contrast, long-term (≥10 y) experiments show increasing community divergence of treatments from control conditions. Surprisingly, these community responses occurred with similar frequency across the GCD types manipulated in our database. However, community responses were more common when 3 or more GCDs were simultaneously manipulated, suggesting the emergence of additive or synergistic effects of multiple drivers, particularly over long time periods. In half of the cases, GCD manipulations caused a difference in community composition without a corresponding species richness difference, indicating that species reordering or replacement is an important mechanism of community responses to GCDs and should be given greater consideration when examining consequences of GCDs for the biodiversity–ecosystem function relationship. Human activities are currently driving unparalleled global changes worldwide. Our analyses provide the most comprehensive evidence to date that these human activities may have widespread impacts on plant community composition globally, which will increase in frequency over time and be greater in areas where communities face multiple GCDs simultaneously.

Interactive effects of global change factors on terrestrial net primary productivity are treatment length and intensity dependent

“…Therefore, changing plant community composition over long timescales may also lead to the alteration of interactive effects among multiple factors (Komatsu et al, 2019). For example, N addition can reduce plant species richness (Harpole et al, 2016), which may consequently limit the response of NPP to elevated [CO 2 ] (Niklaus et al, 2001).…”

“…In contrast, recent meta-analyses suggest that additive, rather than synergistic or antagonistic, effects of two global change factors on terrestrial carbon/nutrient cycling are more common (Song et al, 2019;Yuan & Chen, 2015;Yue et al, 2017;Zhou et al, 2016). These divergent findings may be attributable to the selection of analytical methods, but more likely due to the potential change of interactive effects with experimental duration, for example, through changes in community composition (Komatsu et al, 2019), and treatment intensity (i.e. the level of the treatment applied).…”

Changes in multiple environmental factors additively enhance the dominance of an exotic plant with a novel trade‐off pattern

“…Thus, the dominance of a species in the global change era may owe little to its origin (Dawson et al, 2012;Thompson & Davis, 2011). Previous studies of native-native and native-exotic species interactions have typically focused on single environmental factors (Dawson et al, 2012;Kimball et al, 2014), even though ecosystems are often influenced by multiple environmental factors (Komatsu et al, 2019;Langley, Mozdzer, Shepard, Hagerty, & Patrick Megonigal, 2013;Rillig et al, 2019). Whether the combined effects of multiple environmental factors on native-exotic species interactions differ from those on native-native species interactions is largely unclear.…”

Progress Towards Plant Community Transcriptomics: Pilot RNA-Seq Data from 24 Species of Vascular Plants at Harvard Forest

“…Trancriptome profiling or genome sequencing of multiple species and individuals within a community will open new, integrative avenues of analyses and allow us to address existing questions that require sampling of floras and communities (Bragg et al, 2015;Fitzpatrick and Keller, 2015;Bowsher et al, 2017;Han et al, 2017;Swenson and Jones, 2017;Zambrano et al, 2017;Matthews et al, 2018;Subrahmaniam et al, 2018;Breed et al, 2019) . This is especially true for understanding responses to climate change where community level analyses are needed to capture the interacting dynamics of different species responses (Liu et al, 2018;Komatsu et al, 2019;Snell et al, 2019) . The integration of community level genomic data from non-model species with ecological and trait data will improve our understanding of plant responses to climate change.…”