Body size in ecological networks

Body size determines a host of species traits that can affect the structure and dynamics of food webs, and other ecological networks, across multiple scales of organization. Measuring body size provides a relatively simple means of encapsulating and condensing a large amount of the biological information embedded within an ecological network. Recently, important advances have been made by incorporating body size into theoretical models that explore food web stability, the patterning of energy fluxes, and responses to perturbations. Because metabolic constraints underpin bodysize scaling relationships, metabolic theory offers a potentially useful new framework within which to develop novel models to describe the structure and functioning of ecological networks and to assess the probable consequences of biodiversity change.

Scaling of Food-Web Properties with Diversity and Complexity Across Ecosystems

Trophic scaling models describe how topological food-web properties such as the number of predator prey links scale with species richness of the community. Early models predicted that either the link density (i.e. the number of links per species) or the connectance (i.e. the linkage probability between any pair of species) is constant across communities. More recent analyses, however, suggest that both these scaling models have to be rejected, and we discuss several hypotheses that aim to explain the scale dependence of these complexity parameters. Based on a recent, highly resolved food-web compilation, we analysed the scaling behaviour of 16 topological parameters and found significant power law scaling relationships with diversity (i.e. species richness) and complexity (i.e. connectance) for most of them. These results illustrate the lack of universal constants in food-web ecology as a function of diversity or complexity. Nonetheless, our power law scaling relationships suggest that fundamental processes determine food-web topology, and subsequent analyses demonstrated that ecosystem-specific differences in these relationships were of minor importance. As such, these newly described scaling relationships provide robust and testable cornerstones for future structural food-web models.

Temporal Variability in Predator-Prey Relationships of a Forest Floor Food Web

Connectance webs represent the standard data description in food web ecology, but their usefulness is often limited in understanding the patterns and processes within ecosystems. Increasingly, efforts have been made to incorporate additional, biologically meaningful, data into food web descriptions, including the construction of food webs using data describing the body size and abundance of each species. Here, data from a terrestrial forest floor food web, sampled seasonally over a 1-year period, were analysed to investigate (i) how stable the body size abundance and predator prey relationships of an ecosystem are through time and (ii) whether there are system-specific differences in body size abundance and predator prey relationships between ecosystem types.

Manipulating Interaction Strengths and the Consequences for Trivariate Patterns in a Marine Food Web

We are experiencing a global extinction crisis as a result of climate change and human-induced alteration of natural habitats, with large predators at high trophic levels in food webs being particularly vulnerable. Unfortunately, there is a scarcity of food web data that can be used to assess how species extinctions alter the structure and stability of temporally and spatially replicated networks. We established a series of large experimental mesocosms in a shallow subtidal benthic marine system and constructed food webs for each replicate. After 6 months of community assembly, we removed large predators from the core communities of 20 experimental food webs, based on the strength of their trophic interactions, and monitored the changes in the networks' structure and stability over an 8-month period. Our analyses revealed the importance of allometric relationships and size-structuring in natural communities as a means of preserving food web structure and sustainability, despite significant changes in the diversity, stability and productivity of the system.

Perturbations to trophic interactions and the stability of complex food webs

The pattern of predator-prey interactions is thought to be a key determinant of ecosystem processes and stability. Complex ecological networks are characterized by distributions of interaction strengths that are highly skewed, with many weak and few strong interactors present. Theory suggests that this pattern promotes stability as weak interactors dampen the destabilizing potential of strong interactors. Here, we present an experimental test of this hypothesis and provide empirical evidence that the loss of weak interactors can destabilize communities in nature. We ranked 10 marine consumer species by the strength of their trophic interactions. We removed the strongest and weakest of these interactors from experimental food webs containing >100 species. Extinction of strong interactors produced a dramatic trophic cascade and reduced the temporal stability of key ecosystem process rates, community diversity and resistance to changes in community composition. Loss of weak interactors also proved damaging for our experimental ecosystems, leading to reductions in the temporal and spatial stability of ecosystem process rates, community diversity, and resistance. These results highlight the importance of conserving species to maintain the stabilizing pattern of trophic interactions in nature, even if they are perceived to have weak effects in the system.

Ecological dynamics of extinct species in empty habitat networks. 1. The role of habitat pattern and quantity, stochasticity and dispersal

We examined a remnant host plant (Primula veris L.) habitat network that was last inhabited by the rare butterfly Hamearis lucina L. in north Wales in 1943, to assess the relative contribution of several spatial parameters to its regional extinction. We first examined relationships between P. veris characteristics and H. lucina eggs in surviving H. lucina populations, and used these to predict the suitability and potential carrying capacity of the habitat network in north Wales. This resulted in an estimate of roughly 4500 eggs (ca 227 adults). We developed a discrete space, discrete time metapopulation model to evaluate the relative contribution of dispersal distance, habitat and environmental stochasticity as possible causes of extinction. We simulated the potential persistence of the butterfly in the current network as well as in three artificial (historical and present) habitat networks that differed in the quantity (current and X3) and fragmentation of the habitat (current and aggregated). We identified that reduced habitat quantity and increased isolation would have increased the probability of regional extinction, in conjunction with environmental stochasticity and H. lucina's dispersal distance. This general trend did not change in a qualitative manner when we modified the ability of dispersing females to stay in, and find suitable habitats (by changing the size of the grid cells used in the model). Contrary to most metapopulation model predictions, system persistence declined with increasing migration rate, suggesting that the mortality of migrating individuals in fragmented landscapes may pose significant risks to system-wide persistence. Based on model predictions for the present landscape we argue that a major programme of habitat restoration would be required for a re-established metapopulation to persist for > 100 years.

Ecological dynamics of extinct species in empty habitat networks. 2. The role of host plant dynamics

This paper explores the relative effects of host plant dynamics and butterfly-related parameters on butterfly persistence. It considers an empty habitat network where a rare butterfly (Cupido minimus) became extinct in 1939 in part of its historical range in north Wales, UK. Surviving populations of the butterfly in southern Britain were visited to assess use of its host plant (Anthyllis vulneraria) in order to calibrate habitat suitability and carrying capacity in the empty network in north Wales. These data were used to deduce that only a portion ( similar to 19%) of the host plant network from north Wales was likely to be highly suitable for oviposition. Nonetheless, roughly 65,460 eggs (3273 adult equivalents) could be expected to be laid in north Wales, were the empty network to be populated at the same levels as observed on comparable plants in surviving populations elsewhere. Simulated metapopulations of C. minimus in the empty network revealed that time to extinction and patch occupancy were significantly influenced by carrying capacity, butterfly mean dispersal distance and environmental stochasticity, although for most reasonable parameter values, the model system persisted. Simulation outputs differed greatly when host plant dynamics was incorporated into the modelled butterfly dynamics. Cupido minimus usually went extinct when host plant were at low densities. In these simulations host plant dynamics appeared to be the most important determinant of the butterfly's regional extirpation. Modelling the outcome of a reintroduction programme to C. minimus variation at high quality locations, revealed that 65% of systems survived at least 100 years. Given the current amount of resources of the north Wales landscape, the persistence of C. minimus under a realistic reintroduction programme has a good chance of being successful, if carried out in conjunction with a host plant management programme.

Ecological coherence in marine reserve network design: an empirical evaluation of sequential site selection using genetic structure

Ecological coherence is a multifaceted conservation objective that includes some potentially conflicting concepts. These concepts include the extent to which the network maximises diversity (including genetic diversity) and the extent to which protected areas interact with non-reserve locations. To examine the consequences of different selection criteria, the preferred location to complement protected sites was examined using samples taken from four locations around each of two marine protected areas: Strangford Lough and Lough Hyne, Ireland. Three different measures of genetic distance were used: FST, Dest and a measure of allelic dissimilarity, along with a direct assessment of the total number of alleles in different candidate networks. Standardized site scores were used for comparisons across methods and selection criteria. The average score for Castlehaven, a site relatively close to Lough Hyne, was highest, implying that this site would capture the most genetic diversity while ensuring highest degree of interaction between protected and unprotected sites. Patterns around Strangford Lough were more ambiguous, potentially reflecting the weaker genetic structure around this protected area in comparison to Lough Hyne. Similar patterns were found across species with different dispersal capacities, indicating that methods based on genetic distance could be used to help maximise ecological coherence in reserve networks. ⺠Ecological coherence is a key component of marine protected area network design. ⺠Coherence contains a number of competing concepts. ⺠Genetic information from field populations can help guide assessments of coherence. ⺠Average choice across different concepts of coherence was consistent among species. ⺠Measures can be combined to compare the coherence of different network designs.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.