Incidence, or compositional, matrices are generated for a broad range of research applications in biology. Zeta diversity provides a common currency and conceptual framework that links incidence‐based metrics with multiple patterns of interest in biology, ecology, and biodiversity science. It quantifies the variation in species (or OTU) composition of multiple assemblages (or cases) in space or time, to capture the contribution of the full suite of narrow, intermediate, and wide‐ranging species to biotic heterogeneity. Here we provide a conceptual framework for the application and interpretation of patterns of continuous change in compositional diversity using zeta diversity. This includes consideration of the survey design context, and the multiple ways in which zeta diversity decline and decay can be used to examine and test turnover in the identity of elements across space and time. We introduce the zeta ratio–based retention rate curve to quantify rates of compositional change. We illustrate these applications using 11 empirical data sets from a broad range of taxa, scales, and levels of biological organization—from DNA molecules and microbes to communities and interaction networks—including one of the original data sets used to express compositional change and distance decay in ecology. We show (1) how different sample selection schemes used during the calculation of compositional change are appropriate for different data types and questions, (2) how higher orders of zeta may in some cases better detect shifts and transitions, and (3) the relative roles of rare vs. common species in driving patterns of compositional change. By exploring the application of zeta diversity decline and decay, including the retention rate, across this broad range of contexts, we demonstrate its application for understanding continuous turnover in biological systems.

The influence of space on the structure (e.g. modularity) of complex ecological networks remains largely unknown. Here, we sampled an individual‐based plant–pollinator network by following the movements and flower visits of marked bumblebee individuals within a population of thistle plants for which the identities and spatial locations of stems were mapped in a 50 × 50 m study plot. The plant–pollinator network was dominated by parasitic male bumblebees and had a significantly modular structure, with four identified modules being clearly separated in space. This indicated that individual flower visitors opted for the fine‐scale division of resources, even within a local site. However, spatial mapping of network modules and movements of bumblebee individuals also showed an overlap in the dense center of the plant patch. Model selection based on Akaike information criterion with traits as predictor variables revealed that thistle stems with high numbers of flower heads and many close neighbours were particularly important for connecting individuals within the modules. In contrast, tall plants and those near the patch center were crucial for connecting the different modules to each other. This demonstrated that individual‐based plant–pollinator networks are influenced by both the spatial structure of plant populations and individual‐specific plant traits. Additionally, bumblebee individuals with long observation times were important for both the connectivity between and within modules. The latter suggests that bumblebee individuals will still show locally restricted movements within sub‐patches of plant populations even if they are observed over a prolonged time period. Our individual‐based and animal‐centered approach of sampling ecological networks opens up new avenues for incorporating foraging behaviour and intra‐specific trait variation into analyses of plant–animal interactions across space.

The accurate estimation of interaction network structure is essential for understanding network stability and function. A growing number of studies evaluate under‐sampling as the degree of sampling completeness (proportional richness observed). How the relationship between network structural metrics and sampling completeness varies across networks of different sizes remains unclear, but this relationship has implications for the within‐ and between‐system comparability of network structure. Here, we test the combined effects of network size and sampling completeness on the structure of spatially distinct networks (i.e., subwebs) in a host–parasitoid model system to better understand the within‐system variability in metric bias. Richness estimates were used to quantify a gradient of sampling completeness of species and interactions across randomly subsampled subwebs. The combined impacts of network size and sampling completeness on the estimated values of twelve unweighted and weighted network metrics were tested. The robustness of network metrics to under‐sampling was strongly related to network size, and sampling completeness of interactions were generally a better predictor of metric bias than sampling completeness of species. Weighted metrics often performed better than unweighted metrics at low sampling completeness; however, this was mainly evident at large rather than small subweb size. These outcomes highlight the significance of under‐sampling for the comparability of both unweighted and weighted network metrics when networks are small and vary in size. This has implications for within‐system comparability of species‐poor networks and, more generally, reveals problems with under‐sampling ecological networks that may otherwise be difficult to detect in species‐rich networks. To mitigate the impacts of under‐sampling, more careful considerations of system‐specific variation in metric bias are needed.

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The effects of temperature and food availability on feeding and egg production of the Arctic copepod Calanus hyperboreus were investigated in Disko Bay, western Greenland, from winter to spring 2009. The abundance of females in the near bottom layer and the egg production of C. hyperboreus prior to the spring bloom document that reproduction relies on lipid stores. The maximum in situ egg production (± SE) of 54 ± 8 eggs female −1 d −1 was recorded in mid-February at chlorophyll a concentrations below 0.1 μg l −1 , whereas no egg production was observed in midApril when the spring bloom developed. After reproduction, the females migrated to the surface layer to exploit the bloom and refill their lipid stores. In 2 laboratory experiments, initiated before and during the spring bloom, mature females were kept with and without food at 5 different temperatures ranging from 0 to 10°C and the fecal pellet and egg production were monitored. Food had a clear effect on fecal pellet production but no effect on egg production, while temperature did not have an effect on egg or fecal pellet production in any of the experiments. Analyses of carbon and lipid content of the females before and after the experiments did not reflect any effect of food or temperature in the pre-bloom experiment, whereas in the bloom experiment a clear positive effect of food was detected in female biochemical profiles. The lack of a temperature response suggests a future warmer ocean could be unfavorable for C. hyperboreus compared to smaller Calanus spp. which are reported to exploit minor temperature elevations for increased egg production. KEY WORDS: Calanus hyperboreus · Egg production · Fecal pellet production · Effect of temperatureResale or republication not permitted without written consent of the publisher

This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Abstract. The population dynamics of insect herbivore biocontrol agents is central to the successful control of invasive weeds. Although the importance of agent population dynamics is recognized, it is rarely considered in assessments of the biocontrol potential of herbivore agents. Herbivore insect population dynamics are influenced by a combination of top-down effects from natural enemies, bottom-up effects from plant resource availability (resource quality and quantity), and potential interactions between these effects. To better understand the tri-trophic interactions that are likely to determine biocontrol success in a host plant-gall wasp-parasitoid system, the relative importance of top-down and bottom-up effects for the survival of a herbivore biocontrol agent (Trichilogaster acaciaelongifoliae), on two Acacia host plants in their native range, was estimated using path analysis. On both host plants, there was a strong positive relationship between gall mass per chamber and gall wasp survival and a strong negative relationship between gall mass per chamber and gall parasitism, with parasitoids being less common in large than small galls. There was, however, no significant correlation between parasitism and gall wasp survival and, therefore, no evidence for top-down effects in this system. Strong bottom-up effects of host plant resources on both gall wasp survival and gall parasitism have implications for the spatio-temporal variability of biocontrol success. Such variation should be considered in pre-release assessments and post-release monitoring of gall wasps used as herbivore biocontrol agents.

Invasive alien species are repeatedly shown to be amongst the top threats to biodiversity globally. Robust indicators for measuring the status and trends of biological invasions are lacking, but essential for monitoring biological invasions and the effectiveness of interventions. Here, we formulate and demonstrate three such indicators that capture the key dimensions of species invasions, each a significant and necessary advance to inform invasive alien species policy targets: 1) Rate of Invasive Alien Species Spread, which provides modelled rates of ongoing introductions of species based on invasion discovery and reporting. 2) Impact Risk, that estimates invasive alien species impacts on the environment in space and time and provides a basis for nationally targeted prioritization of where best to invest in management efforts. 3) Status Information on invasive alien species, that tracks improvement in the essential dimensions of information needed to guide relevant policy and data collection and in support of assessing invasive alien species spread and impact. We show how proximal, model-informed status and trend indicators on invasive alien species can provide more effective global (and national) reporting on biological invasions, and how countries can contribute to supporting these indicators.