Anna Eklöf

Trophically Unique Species Are Vulnerable to Cascading Extinction

Understanding which species might become extinct and the consequences of such loss is critical. One consequence is a cascade of further, secondary extinctions. While a significant amount is known about the types of communities and species that suffer secondary extinctions, little is known about the consequences of secondary extinctions for biodiversity. Here we examine the effect of these secondary extinctions on trophic diversity, the range of trophic roles played by the species in a community. Our analyses of natural and model food webs show that secondary extinctions cause loss of trophic diversity greater than that expected from chance, a result that is robust to variation in food web structure, distribution of interactions strengths, functional response, and adaptive foraging. Greater than expected loss of trophic diversity occurs because more trophically unique species are more vulnerable to secondary extinction. This is not a straightforward consequence of these species having few links with others but is a complex function of how direct and indirect interactions affect species persistence. A positive correlation between a species’ extinction probability and the importance of its loss defines high‐risk species and should make their conservation a priority.

Relevance of evolutionary history for food web structure

Explaining the structure of ecosystems is one of the great challenges of ecology. Simple models for food web structure aim at disentangling the complexity of ecological interaction networks and detect the main forces that are responsible for their shape. Trophic interactions are influenced by species traits, which in turn are largely determined by evolutionary history. Closely related species are more likely to share similar traits, such as body size, feeding mode and habitat preference than distant ones. Here, we present a theoretical framework for analysing whether evolutionary history—represented by taxonomic classification—provides valuable information on food web structure. In doing so, we measure which taxonomic ranks better explain species interactions. Our analysis is based on partitioning of the species into taxonomic units. For each partition, we compute the likelihood that a probabilistic model for food web structure reproduces the data using this information. We find that taxonomic partitions produce significantly higher likelihoods than expected at random. Marginal likelihoods (Bayes factors) are used to perform model selection among taxonomic ranks. We show that food webs are best explained by the coarser taxonomic ranks (kingdom to class). Our methods provide a way to explicitly include evolutionary history in models for food web structure.

Coexpression patterns indicate that GPI-anchored non-specific lipid transfer proteins are involved in accumulation of cuticular wax, suberin and sporopollenin

The non-specific lipid transfer proteins (nsLTP) are unique to land plants. The nsLTPs are characterized by a compact structure with a central hydrophobic cavity and can be classified to different types based on sequence similarity, intron position or spacing between the cysteine residues. The type G nsLTPs (LTPGs) have a GPI-anchor in the C-terminal region which attaches the protein to the exterior side of the plasma membrane. The function of these proteins, which are encoded by large gene families, has not been systematically investigated so far. In this study we have explored microarray data to investigate the expression pattern of the LTPGs in Arabidopsis and rice. We identified that the LTPG genes in each plant can be arranged in three expression modules with significant coexpression within the modules. According to expression patterns and module sizes, the Arabidopsis module AtI is functionally equivalent to the rice module OsI, AtII corresponds to OsII and AtIII is functionally comparable to OsIII. Starting from modules AtI, AtII and AtIII we generated extended networks with Arabidopsis genes coexpressed with the modules. Gene ontology analyses of the obtained networks suggest roles for LTPGs in the synthesis or deposition of cuticular waxes, suberin and sporopollenin. The AtI-module is primarily involved with cuticular wax, the AtII-module with suberin and the AtIII-module with sporopollenin. Further transcript analysis revealed that several transcript forms exist for several of the LTPG genes in both Arabidopsis and rice. The data suggests that the GPI-anchor attachment and localization of LTPGs may be controlled to some extent by alternative splicing.

Spatial aspects of food webs

Spatial distributions of trophic interactions define the spatial heterogeneity of food webs and differences between local and macroecological food webs. The concept of co-occurrence has to be given up when larger spatial scales are considered that integrate different local community food webs into a metacommunity food web. This chapter provides two examples. First, some large-bodied predators are too low in numerical abundance to invade all local community food webs simultaneously. Second, not all potential resource species in a metacommunity can persist under strong top-down pressure by their consumer species and thus avoid coexistence in the same local communities. Food webs consist of organisms that vary in their taxonomic identity, body size, trophic interactions, and trophic position and thus might have very different spatial scales of interactions. Recognition of the importance of spatial scale in food web studies has several implications for food web theory. In particular, the potential food webs that are frequently described by ecologists will often differ from how food webs are realized in actual space and time. Clearly, choosing the right spatio-temporal scale for a food web study depends on the species studied and the study objective. Integrating spatial processes such as extinction and colonization by dispersal in food web models is an important step towards understanding population dynamics in complex communities, and understanding the consequences of habitat loss for the community structure and food web dynamics.

Species-rich ecosystems are vulnerable to cascading extinctions in an increasingly variable world

Global warming leads to increased intensity and frequency of weather extremes. Such increased environmental variability might in turn result in increased variation in the demographic rates of interacting species with potentially important consequences for the dynamics of food webs. Using a theoretical approach, we here explore the response of food webs to a highly variable environment. We investigate how species richness and correlation in the responses of species to environmental fluctuations affect the risk of extinction cascades. We find that the risk of extinction cascades increases with increasing species richness, especially when correlation among species is low. Initial extinctions of primary producer species unleash bottom-up extinction cascades, especially in webs with specialist consumers. In this sense, species-rich ecosystems are less robust to increasing levels of environmental variability than species-poor ones. Our study thus suggests that highly species-rich ecosystems such as coral reefs and tropical rainforests might be particularly vulnerable to increased climate variability.

Operationalizing Network Theory for Ecosystem Service Assessments

Managing ecosystems to provide ecosystem services in the face of global change is a pressing challenge for policy and science. Predicting how alternative management actions and changing future conditions will alter services is complicated by interactions among components in ecological and socioeconomic systems. Failure to understand those interactions can lead to detrimental outcomes from management decisions. Network theory that integrates ecological and socioeconomic systems may provide a path to meeting this challenge. While network theory offers promising approaches to examine ecosystem services, few studies have identified how to operationalize networks for managing and assessing diverse ecosystem services. We propose a framework for how to use networks to assess how drivers and management actions will directly and indirectly alter ecosystem services.

Climate change in metacommunities: dispersal gives double-sided effects on persistence

Climate change is increasingly affecting the structure and dynamics of ecological communities both at local and at regional scales, and this can be expected to have important consequences for their robustness and long-term persistence. The aim of the present work is to analyse how the spatial structure of the landscape and dispersal patterns of species (dispersal rate and average dispersal distance) affects metacommunity response to two disturbances: (i) increased mortality during dispersal and (ii) local species extinction. We analyse the disturbances both in isolation and in combination. Using a spatially and dynamically explicit metacommunity model, we find that the effect of dispersal on metacommunity persistence is two-sided: on the one hand, high dispersal significantly reduces the risk of bottom-up extinction cascades following the local removal of a species; on the other hand, when dispersal imposes a risk to the dispersing individuals, high dispersal increases extinction risks, especially when dispersal is global. Large-bodied species with long generation times at the highest trophic level are particularly vulnerable to extinction when dispersal involves a risk. This suggests that decreasing the mortality risk of dispersing individuals by improving the quality of the habitat matrix may greatly increase the robustness of metacommunities.

Secondary extinctions in food webs: a Bayesian network approach

Summary Ecological communities are composed of populations connected in tangled networks of ecological interactions. Therefore, the extinction of a species can reverberate through the network and cause other (possibly distantly connected) species to go extinct as well. The study of these secondary extinctions is a fertile area of research in ecological network theory. However, to facilitate practical applications, several improvements to the current analytical approaches are needed. In particular, we need to consider that (i) species have different ‘a priori’ probabilities of extinction, (ii) disturbances can simultaneously affect several species, and (iii) extinction risk of consumers likely grows with resource loss. All these points can be included in dynamical models, which are, however, difficult to parameterize. Here we advance the study of secondary extinctions with Bayesian networks. We show how this approach can account for different extinction responses using binary – where each resource has the same importance – and quantitative data – where resources are weighted by their importance. We simulate ecological networks using a popular dynamical model (the Allometric Trophic Network model) and use it to test our method. We find that the Bayesian network model captures the majority of the secondary extinctions produced by the dynamical model and that consumers’ responses to species loss are best modelled using a nonlinear sigmoid function. We also show that an approach based exclusively on food web structure loses power when species at higher trophic levels are preferentially lost. Because the loss of apex predators is unfortunately widespread, the results highlight a serious limitation of studies on network robustness.

The phylogenetic component of food web structure and intervality

Despite the exceptional complexity formed by species and their interactions in ecological networks, such as food webs, regularities in the network structures are repeatedly demonstrated. The interactions are determined by the characteristics of a species. The characteristics are in turn determined by the species’ phylogenetic relationships, but also by factors not related to evolutionary history. Here, we test whether species’ phylogenetic relationships provides a significant proxy for food web intervality. We thereafter quantify the degree to which different species traits remain valuable predictors of food web structure after the baseline effect of species’ relatedness has been removed. We find that the phylogenetic relationships provide a significant background from which to estimate food web intervality and thereby structure. However, we also find that there is an important, non-negligible part of some traits, e.g., body size, in food webs that is not accounted for by the phylogenetic relationships. Additionally, both these relationships differ depending if a predator or a prey perspective is adopted. Clearly, species’ evolutionary history as well as traits not determined by phylogenetic relationships shapes predator-prey interactions in food webs, and the underlying evolutionary processes take place on slightly different time scales depending on the direction of predator-prey adaptations.

A quantitative framework for investigating the reliability of network construction

Descriptions of ecological networks typically assume that the same interspecific interactions occur each time a community is observed. This contrasts with the known stochasticity of ecological communities: community composition, species abundances, and link structure all vary in space and time. Moreover, finite sampling generates variation in the set of interactions actually observed. Here we develop the conceptual and analytical tools needed to capture uncertainty in the estimation of pairwise interactions. To define the problem, we identify the different contributions to the uncertainty of an interaction and its implications for the estimation of network properties. We then outline a framework to quantify the uncertainty around each interaction. We illustrate this framework using the most extensively sampled network to date. We found significant uncertainty in estimates for the probability of most pairwise interactions which we could, however, limit with informative priors. Through these efforts, we demonstrate the utility of our approach and the importance of acknowledging the uncertainty inherent in network studies. Most importantly, we stress that networks are best thought of as systems constructed from random variables, the stochastic nature of which must be acknowledged for an accurate representation. Doing so will fundamentally change networks analyses and yield greater realism. Statement of authorship DG designed the analytical approach. AC and DG wrote the code. AC performed statistical analyses. All authors contributed to writing and revising the manuscript. Data accessibility All data used in this study have been independently published and are accessible following the references provided in text. Details Running title: Quantitative network construction Article type: Ideas and Perspectives Number of references: 36 Number of figs, tables, & text boxes: 8 Text box 1 word count: 381 Text box 2 word count: 210 Abstract word count: 199 Main text word count: 6482