Who Is Where in Marine Food Webs? A Trait-Based Analysis of Network Positions

Networks of trophic interactions provide a lot of information on the functioning of marine ecosystems. Beyond feeding habits, three additional traits (mobility, size, and habitat) of various organisms can complement this trophic view. The combination of traits and food web positions are studied here on a large food web database. The aim is a better description and understanding of ecological roles of organisms and the identification of the most important keystone species. This may contribute to develop better ecological indicators (e.g., keystoneness) and help in the interpretation of food web models. We use food web data from the Ecopath with Ecosim (EwE) database for 92 aquatic ecosystems. We quantify the network position of organisms by 18 topological indices (measuring centrality, hierarchy, and redundancy) and consider their three, categorical traits (e.g., for mobility: sessile, drifter, limited mobility, and mobile). Relationships are revealed by multivariate analysis. We found that topological indices belong to six different categories and some of them nicely separate various trait categories. For example, benthic organisms are richly connected and mobile organisms occupy higher food web positions

Spatial insurance against a heatwave differs between trophic levels in experimental aquatic communities

Climate change-related heatwaves are major threats to biodiversity and ecosystem functioning. However, our current understanding of the mechanisms governing community resistance to and recovery from extreme temperature events is still rudimentary. The spatial insurance hypothesis postulates that diverse regional species pools can buffer ecosystem functioning against local disturbances through the immigration of better-adapted taxa. Yet, experimental evidence for such predictions from multi-trophic communities and pulse-type disturbances, like heatwaves, is largely missing. We performed an experimental mesocosm study to test whether species dispersal from natural lakes prior to a simulated heatwave could increase the resistance and recovery of plankton communities. As the buffering effect of dispersal may differ among trophic groups, we independently manipulated the dispersal of organisms from lower (phytoplankton) and higher (zooplankton) trophic levels. The experimental heatwave suppressed total community biomass by having a strong negative effect on zooplankton biomass, probably due to a heat-induced increase in metabolic costs, resulting in weaker top-down control on phytoplankton. While zooplankton dispersal did not alleviate the negative heatwave effects on zooplankton biomass, phytoplankton dispersal enhanced biomass recovery at the level of primary producers, providing partial evidence for spatial insurance. The differential responses to dispersal may be linked to the much larger regional species pool of phytoplankton than of zooplankton. Our results suggest high recovery capacity of community biomass independent of dispersal. However, community composition and trophic structure remained altered due to the heatwave, implying longer-lasting changes in ecosystem functioning

Additivity of pairwise perturbations in food webs: Topological effects

Food webs dynamically react to perturbations and it is an open question how additive are the effects of single-species perturbations. Network structure may have topological constraints on additivity and this influences community response. Better understanding the relationships between single-species and multi-species perturbations can be useful for systems-based conservation management. Here we study a single model food web by (1) characterising the positional importance of its nodes, (2) building a dynamical network simulation model and performing sensitivity analysis on it, (3) determining community response to each possible single-species perturbation, (4) determining community response to each possible pairwise species perturbation and (5) quantifying the additivity of effects for particular types of species pairs. We found that perturbing pairs of species that are either competitors or have high net status values in the network is less additive: their combined effect is dampened

Topology of additive pairwise effects in food webs

Contrasting reductionistic versus holistic views, it is a general question whether adding the parts equals the sum. In the time of multiple drivers of anthropogenic change, it is a crucial issue, and better understanding additivity is critical for strategy and management. More particular research questions ask what are the community effects of the extinction of a single species and whether multiple local effects on different species will generate additive community responses. Here we perform food web simulations and study the community response to perturbing each species, one by one, and perturbing each possible pairwise combination of species. By comparing the two, we quantify additivity and analyze how does it depend on the topological positions of perturbed species pairs. Results increase the predictability of food web research, supporting systems-based conservation management and, possibly, multi-species maximum sustainable yield assessment in fisheries

Aggregating a plankton food web: Mathematical versus biological approaches

Species are embedded in a web of intricate trophic interactions. Understanding the functional role of species in food webs is of fundamental interests. This is related to food web position, so positional similarity may provide information about functional overlap. Defining and quantifying similar trophic functioning can be addressed in different ways. We consider two approaches. One is of mathematical nature involving network analysis where unique species can be defined as those whose topological position is very different to others in the same food web. A species is unique if it has very different connection pattern compared to others. The second approach is of biological nature, based on trait-based aggregations. Unique species are not easy to aggregate with others because their traits are not in common with the ones of most others. Our goal here is to illustrate how mathematics can provide an alternative perspective on species aggregation, and how this is related to its biological counterpart. We illustrate these approaches using a toy food web and a real food web and demonstrate the sensitive relationships between those approaches. The trait-based aggregation focusing on the trait values of size (sv) can be best predicted by the mathematical aggregation algorithms

The vulnerability of plant-pollinator communities to honeybee decline: A comparative network analysis in different habitat types

The populations of most pollinators, including honeybees, are declining that heavily affects both crop and wild plant pollination. Wild bee diversity and habitat type may modulate these effects. We addressed the question how the structure of plant-pollinator networks in different habitat types may influence the vulnerability of pollinator communities to the hypothetical loss of honeybees. We performed network analysis based on plant-visitation data in a traditional agricultural landscape and quantified the structural vulnerability (i.e. the effect of the loss of honeybee) of the plant-pollinator networks by a topological index (distance-based fragmentation). We found that very different plant-pollinator communities inhabited the studied different agricultural habitat types. The early summer arable fields had the most, pastures in mid-summer had the less vulnerable structure and, in general, an intermediate plant/pollinator ratio was associated with high vulnerability in the absence of honeybees. We suggest that increased plant species richness can ensure higher wild bee diversity and more stable plant-pollinator networks without honeybee, where flower-visitation can rely more on wild bees. Decreased management intensity in agricultural landscapes can therefore contribute to the maintenance of diverse plant-pollinator communities in agricultural landscapes and to sustainable farming