Reintroducing Environmental Change Drivers in Biodiversity–Ecosystem Functioning Research. (December 2016)

• Record Type: Journal Article
• Authors: De Laender, Frederik; Rohr, Jason R.; Ashauer, Roman; Baird, Donald J.; Berger, Uta; Eisenhauer, Nico; Grimm, Volker; Hommen, Udo; Maltby, Lorraine; Meliàn, Carlos J.; Pomati, Francesco; Roessink, Ivo; Radchuk, Viktoriia; Van den Brink, Paul J.
• Is Part Of: Trends in ecology & evolution. Volume 31:Number 12(2016)
• Page Start: 905
• Page End: 915
• Publication Date: 2016-12
• Subjects: biodiversity -- richness -- environmental change -- traits -- modeling -- food webs; Ecology -- Periodicals; Evolution (Biology) -- Periodicals; 576.8
• DOI: 10.1016/j.tree.2016.09.007
• Languages: English
• ISSNs: 0169-5347

Abstract

Abstract : For the past 20 years, research on biodiversity and ecosystem functioning (B-EF) has only implicitly considered the underlying role of environmental change. We illustrate that explicitly reintroducing environmental change drivers in B-EF research is needed to predict the functioning of ecosystems facing changes in biodiversity. Next we show how this reintroduction improves experimental control over community composition and structure, which helps to provide mechanistic insight on how multiple aspects of biodiversity relate to function and how biodiversity and function relate in food webs. We also highlight challenges for the proposed reintroduction and suggest analyses and experiments to better understand how random biodiversity changes, as studied by classic approaches in B-EF research, contribute to the shifts in function that follow environmental change. Trends: In the 1990s critiques on early biodiversity–ecosystem function (B-EF) research pushed the field towards direct and random biodiversity manipulations. This evolution allowed the establishment of causal relationships between ecosystem functioning and biodiversity, a main research gap at that time. A main research gap today is to predict and mechanistically understand shifts of ecosystem functioning following real-world biodiversity shifts caused by different types of environmental change. Data from direct and random biodiversity manipulations do not predict the functioning of ecosystems that experience biodiversity shifts as these shifts are often nonrandom and combine with a series of other effects such as changes in per capita functioning and density. Environmental change drivers are useful as they offer experimental control over: (i) the relative magnitude of the different facets of biodiversity change; and (ii) food web composition. These two features facilitate inference of the mechanisms connecting environmental change with ecosystem functioning.