Damaris Zurell

Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.

Correlative and dynamic species distribution modelling for ecological predictions in the Antarctic: a cross-disciplinary concept

Developments of future scenarios of Antarctic ecosystems are still in their infancy, whilst predictions of the physical environment are recognized as being of global relevance and corresponding models are under continuous development. However, in the context of environmental change simulations of the future of the Antarctic biosphere are increasingly demanded by decision makers and the public, and are of fundamental scientific interest. This paper briefly reviews existing predictive models applied to Antarctic ecosystems before providing a conceptual framework for the further development of spatially and temporally explicit ecosystem models. The concept suggests how to improve approaches to relating species’ habitat description to the physical environment, for which a case study on sea urchins is presented. In addition, the concept integrates existing and new ideas to consider dynamic components, particularly information on the natural history of key species, from physiological experiments and biomolecular analyses. Thereby, we identify and critically discuss gaps in knowledge and methodological limitations. These refer to process understanding of biological complexity, the need for high spatial resolution oceanographic data from the entire water column, and the use of data from biomolecular analyses in support of such ecological approaches. Our goal is to motivate the research community to contribute data and knowledge to a holistic, Antarctic-specific, macroecological framework. Such a framework will facilitate the integration of theoretical and empirical work in Antarctica, improving our mechanistic understanding of this globally influential ecoregion, and supporting actions to secure this biodiversity hotspot and its ecosystem services. To access the supplementary material to this article please see Supplementary Files under Article Tools online.

Frequency and intensity of facilitation reveal opposing patterns along a stress gradient

Abstract Disentangling the different processes structuring ecological communities is a long‐standing challenge. In species‐rich ecosystems, most emphasis has so far been given to environmental filtering and competition processes, while facilitative interactions between species remain insufficiently studied. Here, we propose an analysis framework that not only allows for identifying pairs of facilitating and facilitated species, but also estimates the strength of facilitation and its variation along environmental gradients. Our framework combines the analysis of both co‐occurrence and co‐abundance patterns using a moving window approach along environmental gradients to control for potentially confounding effects of environmental filtering in the co‐abundance analysis. We first validate our new approach against community assembly simulations, and exemplify its potential on a large 1,134 plant community plots dataset. Our results generally show that facilitation intensity was strongest under cold stress, whereas the proportion of facilitating and facilitated species was higher under drought stress. Moreover, the functional distance between individual facilitated species and their facilitating species significantly changed along the temperature–moisture gradient, and seemed to influence facilitation intensity, although no general positive or general negative trend was discernible among species. The main advantages of our robust framework are as follows: It enables detecting facilitating and facilitated species in species‐rich systems, and it allows identifying the directionality and intensity of facilitation in species pairs as well as its variation across long environmental gradients. It thus opens numerous opportunities for incorporating functional (and phylogenetic) information in the analysis of facilitation patterns. Our case study indicated high complexity in facilitative interactions across the stress gradient and revealed new evidence that facilitation, similarly to competition, can operate between functionally similar and dissimilar species. Extending the analyses to other taxa and ecosystems will foster our understanding how complex interspecific interactions promote biodiversity.

sOAR: A tool for modelling optimal animal life-history strategies in cyclic environments

Periodic environments determine the life cycle of many animals across the globe and the timing of important life history events, such as reproduction and migration. These adaptive behavioural strategies are complex and can only be fully understood (and predicted) within the framework of natural selection in which species adopt evolutionary stable strategies. We present sOAR, a powerful and user-friendly implementation of the well-established framework of optimal annual routine modelling. It allows determining optimal animal life history strategies under cyclic environmental conditions using stochastic dynamic programming. It further includes the simulation of population dynamics under the optimal strategy. sOAR provides an important tool for theoretical studies on the behavioural and evolutionary ecology of animals. It is especially suited for studying bird migration. In particular, we integrated options to differentiate between costs of active and passive flight into the optimal annual routine modelling framework, as well as options to consider periodic wind conditions affecting flight energetics. We provide an illustrative example of sOAR where food supply in the wintering habitat of migratory birds significantly alters the optimal timing of migration. sOAR helps improving our understanding of how complex behaviours evolve and how behavioural decisions are constrained by internal and external factors experienced by the animal. Such knowledge is crucial for anticipating potential species’ response to global environmental change. This article is protected by copyright. All rights reserved.