Eco-Evolutionary Spatial Dynamics. Rapid Evolution and Isolation Explain Food Web Persistence

One of the current challenges in evolutionary ecology is understanding the long-term persistence of contemporary-evolving predator–prey interactions across space and time. To address this, we developed an extension of a multi-locus, multi-trait eco-evolutionary individual-based model that incorporates several interacting species in explicit landscapes. We simulated eco-evolutionary dynamics of multiple species food webs with different degrees of connectance across soil-moisture islands. A broad set of parameter combinations led to the local extinction of species, but some species persisted, and this was associated with (1) high connectance and omnivory and (2) ongoing evolution, due to multi-trait genetic variability of the embedded species. Furthermore, persistence was highest at intermediate island distances, likely because of a balance between predation-induced extinction (strongest at short island distances) and the coupling of island diversity by top predators, which by travelling among islands exert global top-down control of biodiversity. In the simulations with high genetic variation, we also found widespread trait evolutionary changes indicative of eco-evolutionary dynamics. We discuss how the ever-increasing computing power and high-resolution data availability will soon allow researchers to start bridging the in vivo–in silico gap.

Eco-evolutionary Dynamics of Individual-Based Food Webs

The past decade has seen the rise of high resolution datasets. One of the main surprises of analysing such data has been the discovery of a large genetic, phenotypic and behavioural variation and heterogeneous metabolic rates among individuals within natural populations. A parallel discovery from theory and experiments has shown a strong temporal convergence between evolutionary and ecological dynamics, but a general framework to analyse from individual-level processes the convergence between ecological and evolutionary dynamics and its implications for patterns of biodiversity in food webs has been particularly lacking. Here, as a first approximation to take into account intraspecific variability and the convergence between the ecological and evolutionary dynamics in large food webs, we develop a model from population genomics and microevolutionary processes that uses sexual reproduction, genetic-distance-based speciation and trophic interactions. We confront the model with the prey consumption per individual predator, species-level connectance and prey–predator diversity in several environmental situations using a large food web with approximately 25,000 sampled prey and predator individuals. We show higher than expected diversity of abundant species in heterogeneous environmental conditions and strong deviations from the observed distribution of individual prey consumption (i.e. individual connectivity per predator) in all the environmental conditions. The observed large variance in individual prey consumption regardless of the environmental variability collapsed species-level connectance after small increases in sampling effort. These results suggest (1) intraspecific variance in prey–predator interactions has a strong effect on the macroscopic properties of food webs and (2) intraspecific variance is a potential driver regulating the speed of the convergence between ecological and evolutionary dynamics in species-rich food webs. These results also suggest that genetic–ecological drift driven by sexual reproduction, equal feeding rate among predator individuals, mutations and genetic-distance-based speciation can be used as a neutral food web dynamics test to detect the ecological and microevolutionary processes underlying the observed patterns of individual and species-based food webs at local and macroecological scales.

Chapter Six – Individual Trait Variation and Diversity in Food Webs

In recent years, there has been a renewed interest in the ecological consequences of individual trait variation within populations. Given that individual variability arises from evolutionary dynamics, to fully understand eco-evolutionary feedback loops, we need to pay special attention to how standing trait variability affects ecological dynamics. There is mounting empirical evidence that intra-specific phenotypic variation can exceed species-level means, but theoretical models of multi-trophic species coexistence typically neglect individual-level trait variability. What is needed are multispecies datasets that are resolved at the individual level that can be used to discriminate among alternative models of resource selection and species coexistence in food webs. Here, using one the largest individual-based datasets of a food web compiled to date, along with an individual trait-based stochastic model that incorporates Approximate Bayesian computation methods, we document intra-population variation in the strength of prey selection by different classes or predator phenotypes which could potentially alter the diversity and coexistence patterns of food webs. In particular, we found that strongly connected individual predators preferentially consumed common prey, whereas weakly connected predators preferentially selected rare prey. Such patterns suggest that food web diversity may be governed by the distribution of predator connectivity and individual trait variation in prey selection. We discuss the consequences of intra-specific variation in prey selection to assess fitness differences among predator classes (or phenotypes) and track longer term food web patterns of coexistence accounting for several phenotypes within each prey and predator species.

Dispersal dynamics in food webs

Studies of food webs suggest that limited nonrandom dispersal can play an important role in structuring food webs. It is not clear, however, whether density-dependent dispersal fits empirical patterns of food webs better than density-independent dispersal. Here, we study a spatially distributed food web, using a series of population-dispersal models that contrast density-independent and density-dependent dispersal in landscapes where sampled sites are either homogeneously or heterogeneously distributed. These models are fitted to empirical data, allowing us to infer mechanisms that are consistent with the data. Our results show that models with density-dependent dispersal fit the α, β, and γ tritrophic richness observed in empirical data best. Our results also show that density-dependent dispersal leads to a critical distance threshold beyond which site similarity (i.e., β tritrophic richness) starts to decrease much faster. Such a threshold can also be detected in the empirical data. In contrast, models with density-independent dispersal do not predict such a threshold. Moreover, preferential dispersal from more centrally located sites to peripheral sites does not provide a better fit to empirical data when compared with symmetric dispersal between sites. Our results suggest that nonrandom dispersal in heterogeneous landscapes is an important driver that shapes local and regional richness (i.e., α and γ tritrophic richness, respectively) as well as the distance-decay relationship (i.e., β tritrophic richness) in food webs.

Patterns of morphological changes and hybridization between sympatric whitefish morphs (Coregonus spp.) in a Swiss lake: a role for eutrophication?

Whitefish, genus Coregonus, show exceptional levels of phenotypic diversity with sympatric morphs occurring in numerous postglacial lakes in the northern hemisphere. Here, we studied the effects of human-induced eutrophication on sympatric whitefish morphs in the Swiss lake, Lake Thun. In particular, we addressed the questions whether eutrophication (i) induced hybridization between two ecologically divergent summer-spawning morphs through a loss of environmental heterogeneity, and (ii) induced rapid adaptive morphological changes through changes in the food web structure. Genetic analysis based on 11 microsatellite loci of 282 spawners revealed that the pelagic and the benthic morph represent highly distinct gene pools occurring at different relative proportions on all seven known spawning sites. Gill raker counts, a highly heritable trait, showed nearly discrete distributions for the two morphs. Multilocus genotypes characteristic of the pelagic morph had more gill rakers than genotypes characteristic of benthic morph. Using Bayesian methods, we found indications of recent but limited introgressive hybridization. Comparisons with historical gill raker data yielded median evolutionary rates of 0.24 haldanes and median selection intensities of 0.27 for this trait in both morphs for 1948-2004 suggesting rapid evolution through directional selection at this trait. However, phenotypic plasticity as an alternative explanation for this phenotypic change cannot be discarded. We hypothesize that both the temporal shifts in mean gill raker counts and the recent hybridization reflect responses to changes in the trophic state of the lake induced by pollution in the 1960s, which created novel selection pressures with respect to feeding niches and spawning site preferences.

Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment

Biodiversity is rapidly declining, and this may negatively affect ecosystem processes, including economically important ecosystem services. Previous studies have shown that biodiversity has positive effects on organisms and processes across trophic levels. However, only a few studies have so far incorporated an explicit food-web perspective. In an eight-year biodiversity experiment, we studied an unprecedented range of above- and below-ground organisms and multitrophic interactions. A multitrophic data set originating from a single long-term experiment allows mechanistic insights that would not be gained from meta-analysis of different experiments. Here we show that plant diversity effects dampen with increasing trophic level and degree of omnivory. This was true both for abundance and species richness of organisms. Furthermore, we present comprehensive above-ground/below-ground biodiversity food webs. Both above ground and below ground, herbivores responded more strongly to changes in plant diversity than did carnivores or omnivores. Density and richness of carnivorous taxa was independent of vegetation structure. Below-ground responses to plant diversity were consistently weaker than above-ground responses. Responses to increasing plant diversity were generally positive, but were negative for biological invasion, pathogen infestation and hyperparasitism. Our results suggest that plant diversity has strong bottom-up effects on multitrophic interaction networks, with particularly strong effects on lower trophic levels. Effects on higher trophic levels are indirectly mediated through bottom-up trophic cascades.

Temperature and Resource Availability May Interactively Affect Over-Wintering Success of Juvenile Fish in a Changing Climate

The predicted global warming may affect freshwater systems at several organizational levels, from organism to ecosystem. Specifically, in temperate regions, the projected increase of winter temperatures may have important effects on the over-winter biology of a range of organisms and especially for fish and other ectothermic animals. However, temperature effects on organisms may be directed strongly by resource availability. Here, we investigated whether over-winter loss of biomass and lipid content of juvenile roach (Rutilus rutilus) was affected by the physiologically relatively small (2-5°C) changes of winter temperatures predicted by the Intergovernmental Panel on Climate Change (IPCC), under both natural and experimental conditions. This was investigated in combination with the effects of food availability. Finally, we explored the potential for a correlation between lake temperature and resource levels for planktivorous fish, i.e., zooplankton biomass, during five consecutive winters in a south Swedish lake. We show that small increases in temperature (+2°C) affected fish biomass loss in both presence and absence of food, but negatively and positively respectively. Temperature alone explained only a minor part of the variation when food availability was not taken into account. In contrast to other studies, lipid analyses of experimental fish suggest that critical somatic condition rather than critical lipid content determined starvation induced mortality. Our results illustrate the importance of considering not only changes in temperature when predicting organism response to climate change but also food-web interactions, such as resource availability and predation. However, as exemplified by our finding that zooplankton over-winter biomass in the lake was not related to over-winter temperature, this may not be a straightforward task.

From Broadstone to Zackenberg

Ecological networks are typically complex constructions of species and their interactions. During the last decade, the study of networks has moved from static to dynamic analyses, and has attained a deeper insight into their internal structure, heterogeneity, and temporal and spatial resolution. Here, we review, discuss and suggest research lines in the study of the spatio-temporal heterogeneity of networks and their hierarchical nature. We use case study data from two well-characterized model systems (the food web in Broadstone Stream in England and the pollination network at Zackenberg in Greenland), which are complemented with additional information from other studies. We focus upon eight topics: temporal dynamic space-for-time substitutions linkage constraints habitat borders network modularity individual-based networks invasions of networks and super networks that integrate different network types. Few studies have explicitly examined temporal change in networks, and we present examples that span from daily to decadal change: a common pattern that we see is a stable core surrounded by a group of dynamic, peripheral species, which, in pollinator networks enter the web via preferential linkage to the most generalist species. To some extent, temporal and spatial scales are interchangeable (i.e. networks exhibit ‘ergodicity’) and we explore how space-for-time substitutions can be used in the study of networks. Network structure is commonly constrained by phenological uncoupling (a temporal phenomenon), abundance, body size and population structure. Some potential links are never observed, that is they are ‘forbidden’ (fully constrained) or ‘missing’ (a sampling effect), and their absence can be just as ecologically significant as their presence. Spatial habitat borders can add heterogeneity to network structure, but their importance has rarely been studied: we explore how habitat generalization can be related to other resource dimensions. Many networks are hierarchically structured, with modules forming the basic building blocks, which can result in self-similarity. Scaling down from networks of species reveals another, finer-grained level of individual-based organization, the ecological consequences of which have yet to be fully explored. The few studies of individual-based ecological networks that are available suggest the potential for large intraspecific variance and, in the case of food webs, strong size-structuring. However, such data are still scarce and more studies are required to link individual-level and species-level networks. Invasions by alien species can be tracked by following the topological ‘career’ of the invader as it establishes itself within a network, with potentially important implications for conservation biology. Finally, by scaling up to a higher level of organization, it is possible to combine different network types (e.g. food webs and mutualistic networks) to form super networks, and this new approach has yet to be integrated into mainstream ecological research. We conclude by listing a set of research topics that we see as emerging candidates for ecological network studies in the near future.

A glimpse into the future composition of marine phytoplankton communities

It is expected that climate change will have significant impacts on ecosystems. Most model projections agree that the ocean will experience stronger stratification and less nutrient supply from deep waters. These changes will likely affect marine phytoplankton communities and will thus impact on the higher trophic levels of the oceanic food web. The potential consequences of future climate change on marine microbial communities can be investigated and predicted only with the help of mathematical models. Here we present the application of a model that describes aggregate properties of marine phytoplankton communities and captures the effects of a changing environment on their composition and adaptive capacity. Specifically, the model describes the phytoplankton community in terms of total biomass, mean cell size, and functional diversity. The model is applied to two contrasting regions of the Atlantic Ocean (tropical and temperate) and is tested under two emission scenarios: SRES A2 or “business as usual” and SRES B1 or “local utopia.” We find that all three macroecological properties will decline during the next century in both regions, although this effect will be more pronounced in the temperate region. Being consistent with previous model predictions, our results show that a simple trait-based modeling framework represents a valuable tool for investigating how phytoplankton communities may reorganize under a changing climate.

Sequestration of plant secondary metabolites by insect herbivores: molecular mechanisms and ecological consequences

Numerous insect herbivores can take up and store plant toxins as self-defense against their own natural enemies. Plant toxin sequestration is tightly linked with tolerance strategies that keep the toxins functional. Specific transporters have been identified that likely allow the herbivore to control the spatiotemporal dynamics of toxin accumulation. Certain herbivores furthermore possess specific enzymes to boost the bioactivity of the sequestered toxins. Ecologists have studied plant toxin sequestration for decades. The recently uncovered molecular mechanisms in combination with transient, non-transgenic systems to manipulate insect gene expression will help to understand the importance of toxin sequestration for food-web dynamics in nature.