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The field of eco‐evolutionary dynamics is developing rapidly, with a growing number of well‐designed experiments quantifying the impact of evolution on ecological processes and patterns, ranging from population demography to community composition and ecosystem functioning. The key challenge remains to transfer the insights of these proof‐of‐principle experiments to natural settings, where multiple species interact and the dynamics are far more complex than those studied in most experiments. Here, we discuss potential pitfalls of building a framework on eco‐evolutionary dynamics that is based on data on single species studied in isolation from interspecific interactions, which can lead to both under‐ and overestimation of the impact of evolution on ecological processes. Underestimation of evolution‐driven ecological changes could occur in a single‐species approach when the focal species is involved in co‐evolutionary dynamics, whereas overestimation might occur due to increased rates of evolution following ecological release of the focal species. In order to develop a multi‐species perspective on eco‐evolutionary dynamics, we discuss the need for a broad‐sense definition of “eco‐evolutionary feedbacks” that includes any reciprocal interaction between ecological and evolutionary processes, next to a narrow‐sense definition that refers to interactions that directly feed back on the interactor that evolves. We discuss the challenges and opportunities of using more natural settings in eco‐evolutionary studies by gradually adding complexity: (a) multiple interacting species within a guild, (b) food web interactions and (c) evolving metacommunities in multiple habitat patches in a landscape. A literature survey indicated that only a few studies on microbial systems so far developed a truly multi‐species approach in their analysis of eco‐evolutionary dynamics, and mostly so in artificially constructed communities. Finally, we provide a road map of methods to study eco‐evolutionary dynamics in more natural settings. Eco‐evolutionary studies involving multiple species are necessarily demanding and might require intensive collaboration among research teams, but are highly needed. A plain language summary is available for this article. Plain Language Summary

1. The study of plant-pollinator interactions in a network context is receiving increasing attention. This approach has helped to identify several emerging network patterns such as nestedness and modularity. However, most studies are based only on qualitative information, and some ecosystems, such as deserts and tropical forests, are underrepresented in these data sets. 2. We present an exhaustive analysis of the structure of a 4-year plant-pollinator network from the Monte desert in Argentina using qualitative and quantitative tools. We describe the structure of this network and evaluate sampling completeness using asymptotic species richness estimators. Our goal is to assess the extent to which the realized sampling effort allows for an accurate description of species interactions and to estimate the minimum number of additional censuses required to detect 90% of the interactions. We evaluated completeness of detection of the community-wide pollinator fauna, of the pollinator fauna associated with each plant species and of the plant-pollinator interactions. We also evaluated whether sampling completeness was influenced by plant characteristics, such as flower abundance, flower life span, number of interspecific links (degree) and selectiveness in the identity of their flower visitors, as well as sampling effort. 3. We found that this desert plant-pollinator network has a nested structure and that it exhibits modularity and high network-level generalization. 4. In spite of our high sampling effort, and although we sampled 80% of the pollinator fauna, we recorded only 55% of the interactions. Furthermore, although a 64% increase in sampling effort would suffice to detect 90% of the pollinator species, a fivefold increase in sampling effort would be necessary to detect 90% of the interactions. 5. Detection of interactions was incomplete for most plant species, particularly specialists with a long flowering season and high flower abundance, or generalists with short flowering span and scant flowers. Our results suggest that sampling of a network with the same effort for all plant species is inadequate to sample interactions. 6. Sampling the diversity of interactions is labour intensive, and most plant-pollinator networks published to date are likely to be undersampled. Our analysis allowed estimating the completeness of our sampling, the additional effort needed to detect most interactions and the plant traits that influence the detection of their interactions.

How well do you really know your users? With properly conducted user research, you can discover what really makes your audience tick. This practical guide will show you, step-by-step decisions on solid evidence. You'll not only learn the different methodologies that you can employ in user research, but also gain insight into important set-up activities, such as recruiting and make the most of the data you've gathered. And finally, you'll learn how to communicate findings and deploy evidence, to boost your design rationale and persuade skeptical colleagues.

Biofilms, the complex communities of microbiota that live in association with aquatic interfaces, are considered to be hotspots of microbial life in many aquatic ecosystems. Although the importance of attached algae and bacteria is widely recognized, the role of the highly abundant biofilm-dwelling micrograzers (i.e., heterotrophic protists and small metazoans) is poorly understood. Studies often highlight the resistance of bacterial biofilms to grazing within the microbial food web and therefore argue that the micrograzers have a modulating role (i.e., have effects on biofilm phenotype) rather than a direct trophic role within biofilms. In the present review, we show that this view comes too short, and we establish a conceptual framework of biofilm food webs consisting of three major elements. (1) Energy pathways and subsidization from plankton. As inhabitants of interfaces, biofilm-dwelling grazers potentially access both planktonic organisms and surface-associated organisms. They can play an important role in importing planktonic production into the biofilm food web and thus in the coupling of the planktonic and benthic food webs. Nevertheless, specialized grazers are also able to utilize significant amounts of autochthonous biofilm production. (2) Horizontal complexity of the basal food web. While bacteria and algae within biofilms are edible in general, food quality and accessibility of both bacteria and algae can differ considerably between different prey phenotypes occurring during biofilm formation with respect to morphology, chemical defense, and nutrient stoichiometry. Instead of considering bacteria and algae within biofilms to be generally resistant to feeding by micrograzers, we suggest considering a horizontal food-quality axis to be at the base of biofilm food webs. This food quality gradient is probably associated with increasing costs for the micrograzers. (3) Vertical food web complexity and food chain length. In addition to the consumption of bacteria and algae, many predatory micrograzers exist within biofilm food webs. With the help of video microscopy, we were able to demonstrate the existence of a complex food web with several trophic levels within biofilms. Our conceptual framework should assist in integrating food web concepts and processes into whole-biofilm budgets and in understanding food-web-related interactions within biofilms.

Examines what social engineering is, the methods used by hackers to gather information, and ways to prevent social engineering threats.

Community interaction webs describe both direct and indirect interactions among species. Changes in direct interactions often become noticeable soon after a perturbation, but time lags in the responses of many species may delay the appearance of indirect effects and lead to temporal or spatial variation in interaction webs. Accurately identifying these shifts in the field requires time-specific, spatially differentiated interaction webs. We explore how variation in browsing affects interaction webs in a long-unburned chaparral shrubland near the central California coast. Most prior work in chaparral focused on rapid changes for <5 years after a wildfire that were assumed to determine community patterns until the next fire. Here, we report the results of the first 15 years of an ongoing experiment monitoring how interaction webs in long-unburned chaparral (at least 100 years postfire) respond to experimental variation in browsing by deer and rabbits on dominant shrubs (Arctostaphylos pumila, Ceanothus cuneatus var. rigidus, and Ericameria ericoides). We hypothesized that variation in browsing would directly affect foodplants, indirectly modify growth and survival of other shrubs, and impact habitat needed by herbaceous plants. We found a dynamic web of plant–herbivore and plant–plant interactions that responded rapidly to changes in deer browsing on Ceanothus followed by indirect interactions that continued developing over several years, affecting shrubs, open space, herbaceous plants, and small mammals. Experimental variation in the intensity of deer browsing led to temporal and spatial changes in interactions that produced three different community interaction webs. With deer, community webs were complex, having numerous direct and indirect interactions. Removing deer simplified the community web, changed outcomes of interactions, and reduced open space and herbaceous plant densities. Finally, changes in Ceanothus morphology without deer allowed woodrats to browse these shrubs, with negative impacts on Ceanothus growth and survival. General field observations also showed that all three alternative interaction webs occurred naturally at our fieldsite, varying across space and over time. Long-unburned chaparral communities browsed by deer maintain high biological diversity, but maintenance of this diversity involves many key direct and indirect biotic interactions.

1. In their natural environment, plants are faced with a multitude of attackers, of which insect herbivores and plant pathogens are an important component. In response to these attacks, plants release volatile organic compounds (VOCs), which play an important role in the communication between plants and the associated community members, such as other herbivores, phytopathogens and the natural enemies of herbivores. 2. While numerous studies have focused on either plant—pathogen or plant—insect interactions, less is known when these two sets of interactions co-occur. Depending on the mode of attack of the pathogen (necrotroph vs. biotroph) or herbivore (chewing vs. piercing-sucking) they will activate different defence pathways in the plant in which the phytohormones salicylic acid (SA), jasmonic acid (JA) and ethylene (ET) play key roles. As these pathways can crosstalk, a pathogen infection can interfere in a plant's defence response to herbivory, and vice versa. 3. Infestation of a plant with organisms inducing SA signalling prior to — or simultaneously with — attack by organisms that induce the JA pathway often suppresses JA signalling. However, the impact of this signalling pathway crosstalk on VOC induction is not clear cut, as there is high variability in the effects on volatile emissions, ranging from suppression to enhanced emission. The effects of the modified volatile blends on the foraging success of carnivorous natural enemies of herbivorous insects have started to be investigated. Foraging success of natural enemies generally withstands this modification of the host-induced VOC blend, but the presence or absence of key compounds is an important determinant of the response of certain carnivores. 4. Further studies incorporating plant—insect and plant—pathogen interactions at different levels of biological integration will provide valuable insight in how plants integrate signals from different suites of attacking organisms into an adaptive defence response.