Manipulation of Non-random Species Loss in Natural Phytoplankton: Qualitative and Quantitative Evaluation of Different Approaches

Abstract

Ecological research in recent decades revealed that species loss has a predominantly negative effect on ecosystem functioning and stability. Most of these studies were based on random species loss scenarios, but extinctions in nature are not random. Recent experimental studies using macroscopic communities largely advanced knowledge about the effects of non-random species loss. However, in microscopic communities like the phytoplankton, implementing realistic species loss scenarios is challenging and experimental data are scarce. Creating more realistic experiments to study the role of phytoplankton diversity for ecosystem functioning is particularly important, as they provide up to 50% of global primary productivity, form the basis of all pelagic food webs, and are important for biogeochemical cycling. In this study, we experimentally tested and evaluated three methods for non-random species loss in a natural marine phytoplankton community. Dilution, filtration, and heat stress removed the targeted rare, large, and sensitive species, respectively. All these species groups are extremely vulnerable to extinction in future climate scenarios and play important roles in the communities. Dilution and filtration with a fine mesh additionally decreased initial biomass, which increased the variability of species left in the respective replicates. The methods tested in this study can be used to non-randomly manipulate phytoplankton species diversity in communities used for experiments. However, in studies where species identities are more important than species richness, the dilution and filtration methods should be modified to eliminate the effect of decreasing initial biomass.

A higher taxonomic richness does not ensure the functional resilience of saproxylic beetle communities in evergreenQuercusforests

“…This may be because functional richness is associated with a high number of redundant species, ensuring communities against species loss by exercising buffer functions (Winfree et al, 2015). However, this may also imply that functional redundancy will be strongly affected by species loss, causing a considerable decrease in the communities' functional resilience (Mouillot et al, 2013;Carmona et al, 2016;Engel et al, 2017;Stotz et al, 2021). Conversely, when a community is dominated by functionally rare species with low functional redundancy, as in the case of Sierra Espadán, despite the fact that the communities may be generally more vulnerable, those rare species might be sustaining the functional diversity (Figures S2-S4; Mouillot et al, 2013;Kissick et al, 2018).…”

“…That is, the stability and resilience of ecosystem services in the face of loss or changes of species may be more influenced by the species' function than their numbers (Tilman et al, 1997;Oliver et al, 2015). Moreover, species loss in natural communities is not random; it can depend on a range of factors such as population size or sensitivity to environmental stress (Mouillot et al, 2013;Engel et al, 2017). All this makes it necessary first to analyse the relationship between different biodiversity metrics, such as taxonomic and functional measurements, so as to help calibrate the extent to which a large number of species may ensure ecosystem functions or a small number may jeopardise them.…”

“…All this makes it necessary first to analyse the relationship between different biodiversity metrics, such as taxonomic and functional measurements, so as to help calibrate the extent to which a large number of species may ensure ecosystem functions or a small number may jeopardise them. And second, we need to understand how species loss (both random or directed) can affect functional metrics, in order to determine how ecosystem functioning may react to future perturbations or changes (Engel et al, 2017;Leclerc et al, 2020).…”

Nonrandom species loss in phytoplankton communities and its effect on ecosystem functioning

“…The lake water was filtered through a 53 μ m mesh to remove the zooplankton grazers. The diversity treatments were generated by applying a dilution method to simulate nonrandom species loss resulting in a rare‐species gradient (Engel et al 2017; Hammerstein et al 2017) (Supplementary Information Appendix 1 Figs. A1–A4).…”

Environmental stoichiometry mediates phytoplankton diversity effects on communities' resource use efficiency and biomass

“…After sampling, grazers were excluded by filtering the water through a 53 μm mesh. The diversity gradient (six levels, increasing in diversity from the lowest diversity at D1 to the highest at D6) was generated by dilution of the natural community (dilution factors ranged from 1:1 × 10 5 to 1:1) and thus removal of rare species (Engel et al, 2017;Hammerstein et al, 2017). Each diversity level was incubated in flasks for 26 days to increase biomass prior to the start of the experiments (for methodological details, see Gerhard et al, 2020).…”