The biggest losers: habitat isolation deconstructs complex food webs from top to bottom

Abstract

Habitat fragmentation threatens global biodiversity. To date, there is only limited understanding of how the different aspects of habitat fragmentation (habitat loss, number of fragments and isolation) affect species diversity within complex ecological networks such as food webs. Here, we present a dynamic and spatially explicit food web model which integrates complex food web dynamics at the local scale and species-specific dispersal dynamics at the landscape scale, allowing us to study the interplay of local and spatial processes in metacommunities. We here explore how the number of habitat patches, i.e. the number of fragments, and an increase of habitat isolation affect the species diversity patterns of complex food webs ( α -, β -, γ -diversities). We specifically test whether there is a trophic dependency in the effect of these two factors on species diversity. In our model, habitat isolation is the main driver causing species loss and diversity decline. Our results emphasize that large-bodied consumer species at high trophic positions go extinct faster than smaller species at lower trophic levels, despite being superior dispersers that connect fragmented landscapes better. We attribute the loss of top species to a combined effect of higher biomass loss during dispersal with increasing habitat isolation in general, and the associated energy limitation in highly fragmented landscapes, preventing higher trophic levels to persist. To maintain trophic-complex and species-rich communities calls for effective conservation planning which considers the interdependence of trophic and spatial dynamics as well as the spatial context of a landscape and its energy availability.

A Bayesian network approach to trophic metacommunities shows that habitat loss accelerates top species extinctions

“…In the literature, an increased risk of extinction has been related to various indicators such as high trophic level, large body size, and low abundance (Gaston and Blackburn, 1995;Purvis et al, 2000;Cardillo et al, 2005;Davidson et al, 2009;Lee and Jetz, 2011). In agreement with several previous studies (Kondoh, 2003;van Nouhuys, 2005;Eklöf and Ebenman, 2006;Curtsdotter et al, 2011;Liao et al, 2017b;Ryser et al, 2019), we found that species at higher trophic levels indeed tend to suffer elevated extinction risks. Differences in other indicators can be accounted for through their effects on the species-level parameters π k i and ξ i .…”

“…Here we have studied the effect of habitat loss on food webs by developing a novel approach to trophic metacommunities, combining the methods of classic metapopulation models on fragmented landscapes (Hanski andOvaskainen, 2000, 2003;Ovaskainen and Hanski, 2001;Grilli et al, 2015) with a Bayesian network representation of trophic interactions (Eklöf et al, 2013) for calculating local extinction rates. The approach has much of the flexibility of explicit dynamical models (Ryser et al, 2019), but is close in tractability and computational efficiency to simple topological methods (Dunne and Williams, 2009). This allows one to apply it to much larger food webs and landscapes than would be feasible with fully fledged dynamical models, while still retaining the ability to make predator extinction a smooth function of prey absence (as in Cazelles et al, 2015).…”

“…For example, Liao et al (2016Liao et al ( , 2017aLiao et al ( ,2016 studied how the loss of habitat patches and landscape fragmentation affect food chains and simple food web motifs. An explicit population dynamical approach was taken by Ryser et al (2019), who theoretically studied complex food webs in fragmented landscapes and found that habitat isolation drives top species extinctions due to bottom-up energy limitation. Using a system of differential equations, Ryser et al (2019) explicitly simulate feeding and dispersal dynamics which allows for greater biological realism but also restricts the network sizes that are computationally feasible (Box 1).…”

Interaction of habitat isolation and seasonality: impact of fragmentation in dynamic landscapes on local and regional population variability in meta-food chains

“…In contrast to the prediction of Rip and McCann (2011), low dispersal mortality does not generally result in higher α - or even γ -variability in our model. We attribute this counter-intuitive trend to an indirect effect of dispersal mortality: Despite their superior dispersal abilities, top predators often suffer most from landscape fragmentation because they are energetically more limited than the species on lower trophic levels (Ryser et al, 2019). In fact, we also find that the lower the landscape connectance, the lower the mean biomass of the predator (see Online Resource, Fig.…”

The role of habitat configuration in shaping animal population processes: a framework to generate quantitative predictions

“…Animals rarely move unrestrictedly, as the physical habitat environments they depend on are often heterogeneous and uneven (Fahrig, 2007;Lovett et al, 2007;Kovalenko et al, 2012). By shaping individual movements, the physical configuration of habitats can have implications for population and community dynamics, including ecological interactions (Plitzko and Drossel, 2015;Jordano, 2016;Ryser et al, 2019), community structure (Altermatt and Holyoak, 2012;Henriques-Silva et al, 2013;Wilson et al, 2016), and speciation (Naka and Brumfield, 2018). Habitat configuration can also determine the rates of social interactions among conspecifics, thus shaping the social structure of populations (Emlen and Oring 1977;Gosling 1991;Leu et al, 2016;Farine and Sheldon, 2019;.…”