Hidden diversity: how genetic richness affects species diversity and ecosystem processes in freshwater ponds
Intraspecific diversity loss in a predator species alters prey community structure and ecosystem functions
Recommendation: posted 05 November 2020, validated 16 November 2020
De Laender, F. (2020) Hidden diversity: how genetic richness affects species diversity and ecosystem processes in freshwater ponds. Peer Community in Ecology, 100064. 10.24072/pci.ecology.100064
Biodiversity loss can have important consequences for ecosystem functions, as exemplified by a large body of literature spanning at least three decades [1–3]. While connections between species diversity and ecosystem functions are now well-defined and understood, the importance of diversity within species is more elusive. Despite a surge in theoretical work on how intraspecific diversity can affect coexistence in simple community types [4,5], not much is known about how intraspecific diversity drives ecosystem processes in more complex community types. One particular challenge is that intraspecific diversity can be expressed as observable variation of functional traits, or instead subsist as genetic variation of which the consequences for ecosystem processes are harder to grasp.
Raffard et al.  examined how intraspecific biodiversity loss in a consumer fish changes species diversity at lower trophic levels and ecosystem processes in pond mesocosms. An interesting feature of this experiment is that it crosses functional and genetic intraspecific diversity. To do so, Raffard and colleagues measured and genotyped European minnow (P. phoxinus) individuals sampled from streams across southern France. Combining these collected specimens into experimental ponds allowed them to control functional (population variance of body size) and genetic intraspecific richness (number of genotypes).
Effects on minnow biomass production were mostly small; biomass was significantly reduced only when lowering both functional and genetic richness. However, the consequences for lower trophic levels (zooplankton and macroinvertebrates) were more pronounced and – importantly – not intuitive. For instance, the macroinvertebrate community was less species-diverse at higher minnow functional richness. If minnows with different body sizes would be the main regulator factors  explaining macroinvertebrate interactions, one would expect a more diverse set of minnow body sizes (i.e. higher functional minnow richness) to permit higher instead of lower macroinvertebrate richness. At the same time, the macroinvertebrate community was more species-diverse at higher minnow genotype richness, which could indicate unobserved minnow traits determining macroinvertebrate diversity more than the usual suspects (functional consumer richness). Such unobserved traits could be behavioral traits, allowing for resource partitioning among fish.
The consequences of functional minnow diversity loss on zooplankton diversity were negative, as expected in case body size differences among fish would facilitate coexistence of their zooplankton prey, as explained above. However, this was only the case when genetic diversity was high, suggesting nonstraightforward interactive effects of observed and non-observed traits on prey diversity.
The effects of functional and genetic minnow diversity loss on invertebrate (macroinvertebrates and zooplankton) abundance were more consistent than for invertebrate diversity. This suggests again nonstraightforward relationships in this experimental ecosystem, but now between invertebrate diversity and abundance. When using abundance as a proxy for an ecosystem process (which the authors did not), this result illustrates that biodiversity loss in multitrophic communities can have consequences that are challenging to interpret, let alone predict [8,9]. Path analyses showed how the observed changes of invertebrate diversity and abundance co-determined decomposition, a key ecosystem function. These path analyses had highest explanatory power show when including both kinds of intraspecific diversity.
Taken together, the results by Raffard and colleagues suggest that genetic consumer richness can drive species diversity of connected trophic levels and ecosystem processes with similar magnitude as functional diversity. Indeed, the effects of genetic consumer richness were shown to be so strong as to compensate or exacerbate the loss of observed functional richness. The exact mechanisms explaining these effects remain to be identified, however. The possibility that fish grazing by fish with different (observed or not observed) traits regulates coexistence among invertebrate prey, for instance, would depend on how strong fish consumption feeds back on prey growth during a 30-week experiment. As the authors indicate, detailed studies on resource partitioning among consumers (e.g. using stable isotope labelling) can shed light on these matters. Doing so may address a more fundamental question, which is if the mechanisms linking intraspecific diversity to function are different from those linking interspecific diversity to function, and at what time scales.
 Tilman D, Downing JA (1994) Biodiversity and stability in grasslands. Nature, 367, 363–365. https://doi.org/10.1038/367363a0
 Cardinale BJ, Duffy JE, Gonzalez A, Hooper DU, Perrings C, Venail P, Narwani A, Mace GM, Tilman D, Wardle DA, Kinzig AP, Daily GC, Loreau M, Grace JB, Larigauderie A, Srivastava DS, Naeem S (2012) Biodiversity loss and its impact on humanity. Nature, 486, 59–67. https://doi.org/10.1038/nature11148
 De Laender F, Rohr JR, Ashauer R, Baird DJ, Berger U, Eisenhauer N, Grimm V, Hommen U, Maltby L, Meliàn CJ, Pomati F, Roessink I, Radchuk V, Brink PJV den (2016) Reintroducing Environmental Change Drivers in Biodiversity–Ecosystem Functioning Research. Trends in Ecology & Evolution, 31, 905–915. https://doi.org/10.1016/j.tree.2016.09.007
 Hart SP, Schreiber SJ, Levine JM (2016) How variation between individuals affects species coexistence. Ecology Letters, 19, 825–838. https://doi.org/10.1111/ele.12618
 Barabás G, D’Andrea R (2016) The effect of intraspecific variation and heritability on community pattern and robustness. Ecology Letters, 19, 977–986. https://doi.org/10.1111/ele.12636
 Raffard A, Cucherousset J, Montoya JM, Richard M, Acoca-Pidolle S, Poésy C, Garreau A, Santoul F, Blanchet S (2020) Intraspecific diversity loss in a predator species alters prey community structure and ecosystem functions. bioRxiv, 2020.06.10.144337, ver. 3 peer-reviewed and recommended by PCI Ecology. https://doi.org/10.1101/2020.06.10.144337
 Pásztor L, Botta-Dukát Z, Magyar G, Czárán T, Meszéna G. Theory-Based Ecology: A Darwinian approach. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199577859.001.0001
 Binzer A, Guill C, Rall BC, Brose U (2016) Interactive effects of warming, eutrophication and size structure: impacts on biodiversity and food-web structure. Global Change Biology, 22, 220–227. https://doi.org/10.1111/gcb.13086
 Schwarz B, Barnes AD, Thakur MP, Brose U, Ciobanu M, Reich PB, Rich RL, Rosenbaum B, Stefanski A, Eisenhauer N (2017) Warming alters energetic structure and function but not resilience of soil food webs. Nature Climate Change, 7, 895–900. https://doi.org/10.1038/s41558-017-0002-z
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article. The authors declared that they comply with the PCI rule of having no financial conflicts of interest in relation to the content of the article.
Reviewed by Andrew Barnes, 03 Nov 2020
Evaluation round #1
DOI or URL of the preprint: 10.1101/2020.06.10.144337
Version of the preprint: 1
Author's Reply, 09 Oct 2020
Decision by Frederik De Laender, posted 12 Aug 2020
Both reviewers acknowledge that the contribution is novel and potentially of interest to a broad range of ecologists. One reviewer suggests adding reflections on other traits than body size. The other reviewer is more critical and lists a number of methodological concerns.
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