A multitrophic perspective on biodiversity-ecosystem functioning research

Abstract

Concern about the functional consequences of unprecedented loss in biodiversity has prompted biodiversity-ecosystem functioning (BEF) research to become one of the most active fields of ecological research in the past 25 years. Hundreds of experiments have manipulated biodiversity as an independent variable and found compelling support that the functioning of ecosystems increases with the diversity of their ecological communities. This research has also identified some of the mechanisms underlying BEF relationships, some context-dependencies of the strength of relationships, as well as implications for various ecosystem services that mankind depends upon. In this paper, we argue that a multitrophic perspective of biotic interactions in random and non-random biodiversity change scenarios is key to advance future BEF research and to address some of its most important remaining challenges. We discuss that the study and the quantification of multitrophic interactions in space and time facilitates scaling up from small-scale biodiversity manipulations and ecosystem function assessments to management-relevant spatial scales across ecosystem boundaries. We specifically consider multitrophic conceptual frameworks to understand and predict the context-dependency of BEF relationships. Moreover, we highlight the importance of the eco-evolutionary underpinnings of multitrophic BEF relationships. We outline that FAIR data (meeting the standards of findability, accessibility, interoperability, and reusability) and reproducible processing will be key to advance this field of research by making it more integrative. Finally, we show how these BEF insights may be implemented for ecosystem management, society, and policy. Given that human well-being critically depends on the multiple services provided by diverse, multitrophic communities, integrating the approaches of evolutionary ecology, community ecology, and ecosystem ecology in future BEF research will be key to refine conservation targets and develop sustainable management strategies.

Figure 1

The evolution of biodiversity research. Main foci of biodiversity–ecosystem functioning research over time (Chapin et al., 2000; De Laender et al., 2016; Eisenhauer et al., 2016; Isbell et al., 2013a; van der Plas, 2019). While studying example environmental drivers of different facets of biodiversity and ecosystem functioning has been an important subdiscipline in ecological research for many decades (i.e., community ecology) (a), in the mid-1990s, researchers started to manipulate biodiversity (mostly at the producer level; mostly random biodiversity loss scenarios) as an independent variable (functional biodiversity research or BEF research) (b). More recently, ecologists started focusing on the complex interplay between anthropogenically driven environmental gradients, non-random biodiversity change across trophic levels in food webs (c) (see also Figure 2), and the consequences for ecosystem function (e.g., Barnes et al., 2018; De Laender et al., 2016; Hines et al., 2019 this issue; Mori et al., 2013; Sobral et al., 2017; Soliveres et al., 2016a) (c). Figure modified after van der Plas (2019).

Figure 2

A multitrophic perspective on biodiversity-ecosystem functioning research. Mobility tends to increase with increasing trophic position in ecological networks, and some work suggests that the vulnerability to environmental change does too (Hines et al., 2015a; Voigt et al., 2003), although species at all trophic levels may be vulnerable to changing environments based on their specific life-history traits. This means that the previous focus of BEF experiments on the primary producer level does not necessarily reflect that this is the most vulnerable trophic level to environmental change. This simple aboveground food web serves as the basis for other figures in this paper. It illustrates that species within complex communities are connected by feeding links that can represent ecosystem functions and services (see also Figure 3); although not shown here, the same concept applies to belowground food webs and ecosystem functions.

Figure 3

Multitrophic communities drive ecosystem multifunctionality. This scheme depicts relationships between the diversity of species in aboveground-belowground networks and the management of multiple ecosystem services across adjacent agricultural ecosystems. Management decisions, such as intensifying agricultural practices (right part of the figure), that focus on locally maximizing one ecosystem service, such as crop yield, can limit the other ecosystem services provided in complex food webs in a given area (e.g., pest control is reduced, indicated by higher biomass of aphid and vole). Note that the stability of delivering the focal service decreases in this example (larger error bar in crop yield) at high land-use intensity (Isbell et al., 2017b). Socio-political context related to human population density and stakeholder interests can influence feedbacks between ecosystem services and the management of complex ecosystems. Importantly, ecosystem services are not solely provided by single nodes in the food web and at a single location, but by the interaction among multiple nodes (colors of example links between nodes in upper part, correspond to ecosystem service bar colors in lower part) across adjacent ecosystems. Redrawn after Hines et al. (2015b).

Figure 4

Context-dependent biodiversity-ecosystem functioning (BEF) relationships; examples include (a) environmental heterogeneity, (b) environmental stress, (c) trophic level, (d) spatial and temporal scale, and (e) resource availability. Although the proposed relationships are supported by some studies (examples given, no comprehensive list of studies), a thorough understanding of the context-dependency of BEF and the underlying mechanisms is elusive. Thus, the depicted relationships should be regarded as working hypotheses for future research. See also Bardgett and Wardle (2010) (Fig. 5.3 and references therein) for a similar conceptualization of the context-dependency of BEF relationships that are mostly based on observational studies and removal experiments, rather than on random biodiversity manipulation experiments, as done here. For panel (b), we followed the definition by Chase and Leibold (2003), stating that “stressful niche factors limit the per capita population growth rate of the focal population, but are not influenced by changes in the population size.” 1: Stachowicz et al. (2008b), 2: Griffin et al. (2009), 3: Cardinale (2011), 4: Jousset et al. (2011), 5: Baert et al. (2018), 6: Lefcheck et al. (2015), 7: Cardinale et al. (2007), 8: Eisenhauer et al. (2010), 9: Cardinale et al. (2011), 10: Isbell et al. (2011), 11: Reich et al. (2012), 12: Thakur et al. (2015), 13: Meyer et al. (2016), 14: Guerrero-Ramírez et al. (2017), 15: Kardol et al. (2018), 16: Reich et al. (2001), 17: Fridley (2002), 18: Craven et al. (2016), 19: Zhang and Zhang (2006).

Figure 5

Complex communities link different habitats, a consideration that may facilitate the upscaling of BEF. Conceptual illustration of how multitrophic interactions across ecosystem boundaries can link different ecosystem types and compartments, including above- and belowground compartments, forests and grasslands, as well as terrestrial and aquatic ecosystems. Links between different network modules in these subsystems provide stability of trophic dynamics, matter and energy flow across system boundaries and provide stability of ecosystem function and service delivery (Barnes et al., 2018).