Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) project - Yuri Y. Shprits; Tony Arber; Michael Liemohn; Ondřej Santolík; Keith Bennett; Stefano Bianco; Melanie Burns; Angelica Castillo; Marina García Peñaranda; Bernhard Haas; Julia Himmelsbach; Artem Smirnov; et al. (Advances in Space Research, 2026)

A heuristic approach to attenuation of non-relevant metabolites in groundwater and drinking water in Germany - Robin Sur; Marco Herrmann; Namjil Ganbaatar; Alexander Singer (Journal of Consumer Protection and Food Safety, 2024)
A simple and effective heuristic approach was developed and validated to predict the concentration of non-relevant metabolites (nrM) of pesticides in groundwater and drinking water resources based on the simulated concentrations in leachate as used in product authorizations. The evaluation of extensive monitoring data for 50 nrM has demonstrated that the heuristic has a high predictive performance, i.e., concentrations of < 10 µg/l in shallow leachate in the unsaturated zone of the soil in 1 m depth are protective of 1 µg/l in groundwater and raw water in 98 % of cases (49/50 nrM). The reason for the excellent predictive power of the heuristic approach is the large concentration attenuation from leachate to groundwater and to raw water, which was determined to be, on average, 25- and 45-fold, respectively.

Urinary metabolite concentrations of phthalate and plasticizers in infancy and childhood in the UNC baby connectome project - Jake E. Thistle; Chih-Wei Liu; Julia E. Rager; Alison B. Singer; Dazhe Chen; Cherrel K. Manley; Joseph Piven; John H. Gilmore; Alexander P. Keil; Anne P. Starling; Hongtu Zhu; Weili Lin; et al. (Environmental Research, 2024)

Melt inclusions in zircon: a window to understanding the structure and evolution of the magmatic system beneath the Laguna del Maule volcanic field - Kei Shimizu; Tyler B. Blum; Chloe E. Bonamici; John H. Fournelle; Christine E. Jilly-Rehak; Noriko T. Kita; Kouki Kitajima; Jacob D. Klug; Will O. Nachlas; Brad S. Singer; Michael J. Spicuzza; Alexander V. Sobolev; et al. (Contributions to Mineralogy and Petrology, 2024)

Emotions and transformative learning for sustainability: a systematic review - Julius Grund; Mandy Singer-Brodowski; Alexander Georg Büssing (Sustainability Science, 2024)
As multiple global sustainability crises are getting more severe and existential, a better understanding of how people undergo deep personal transformations related to sustainability is needed. In the educational debate on sustainability learning, transformative learning theories are widely used. To analyze specific phases of transformative learning, we derived five meta-phases from the literature (novel experience, reflection, social exchange, shift of action, shift of meaning). Although human emotions often arise during the confrontation with sustainability issues and are central to moral action, no substantial, theorized understanding of the role of emotions within sustainability-related transformative learning exists to date. We conducted a systematic review (following the PRISMA guidelines) and screened 355 publications to close this research gap. After applying the exclusion criteria, the in-depth analysis of 20 studies showed that sound theoretical references to theories of emotion and transformative learning are rare. The review shows clearly that diverse emotions permeate sustainability-related transformative learning processes. Among these are both negative emotions to novel learning experiences concerning sustainability (e.g., sadness, shame, disgust, guilt) as well as positive emotions in the context of social exchange (e.g., awe, gratitude, fun) and associated with newly formed actions (e.g., fulfillment, pride). Accordingly, to enable emotionally positive learning experiences, relationship and action orientation are particularly important within sustainability learning. The analyzed studies call for an educational practice where emotions can be experienced, expressed, and understood in a safe atmosphere. Future research in this area should use more stable theoretical foundations for emotions and transformative learning theory and apply methods that can capture deeper levels of subjective experience.

Blood transcriptomics mirror regulatory mechanisms during hibernation—a comparative analysis of the Djungarian hamster with other mammalian species - Valeria Rojas Cuyutupa; Dominique Moser; Victoria Diedrich; Yiming Cheng; Jean-Noël Billaud; Elena Haugg; Dominique Singer; Jürgen Bereiter-Hahn; Annika Herwig; Alexander Choukér (Pflügers Archiv - European Journal of Physiology, 2023)
Hibernation enables many species of the mammalian kingdom to overcome periods of harsh environmental conditions. During this physically inactive state metabolic rate and body temperature are drastically downregulated, thereby reducing energy requirements (torpor) also over shorter time periods. Since blood cells reflect the organism´s current condition, it was suggested that transcriptomic alterations in blood cells mirror the torpor-associated physiological state. Transcriptomics on blood cells of torpid and non-torpid Djungarian hamsters and QIAGEN Ingenuity Pathway Analysis (IPA) revealed key target molecules (TM IPA ), which were subjected to a comparative literature analysis on transcriptomic alterations during torpor/hibernation in other mammals. Gene expression similarities were identified in 148 TM IPA during torpor nadir among various organs and phylogenetically different mammalian species. Based on TM IPA , IPA network analyses corresponded with described inhibitions of basic cellular mechanisms and immune system-associated processes in torpid mammals. Moreover, protection against damage to the heart, kidney, and liver was deduced from this gene expression pattern in blood cells. This study shows that blood cell transcriptomics can reflect the general physiological state during torpor nadir. Furthermore, the understanding of molecular processes for torpor initiation and organ preservation may have beneficial implications for humans in extremely challenging environments, such as in medical intensive care units and in space.

Joint survival modelling for multiple species exposed to toxicants - Alexander Singer; Dirk Nickisch; André Gergs (Science of The Total Environment, 2023)

Small-scale distribution modeling of benthic species in a protected natural hard ground area in the German North Sea (Helgoländer Steingrund) - Lydia R. Becker; Alexander Bartholomä; Anja Singer; Kai Bischof; Susanne Coers; Ingrid Kröncke (Geo-Marine Letters, 2020)

ATLANTIC EPIPHYTES : a data set of vascular and non‐vascular epiphyte plants and lichens from the Atlantic Forest - Flavio Nunes Ramos; Sara Ribeiro Mortara; Nathalia Monalisa‐Francisco; João Pedro Costa Elias; Luiz Menini Neto; Leandro Freitas; Rodrigo Kersten; André Márcio Amorim; Fernando Bittencourt Matos; André Felippe Nunes‐Freitas; Suzana Alcantara; Marcia Helena Nagahama Alexandre; et al. (Ecology, 2019)
Epiphytes are hyper‐diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non‐vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer‐reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non‐vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non‐vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events.

Structural bias in aggregated species‐level variables driven by repeated species co‐occurrences: a pervasive problem in community and assemblage data - Bradford A. Hawkins; Boris Leroy; Miguel Á. Rodríguez; Alexander Singer; Bruno Vilela; Fabricio Villalobos; Xiangping Wang; David Zelený (Journal of Biogeography, 2017)
Aim Species attributes are often used to explain diversity patterns across assemblages/communities. However, repeated species co‐occurrences can generate spatial pattern and strong statistical relationships between aggregated attributes and richness in the absence of biological information. Our aim is to increase awareness of this problem. Location North America. Methods We generated empirical species richness patterns using two data structures: (1) birds gridded from range maps and (2) tree communities from the US Forest Service's Forest Inventory and Analysis. We analysed richness using linear regression, regression trees, generalized additive models, geographically weighted regression and simultaneous autoregression, with ‘random intrinsic variables’ as predictors generated by assigning random numbers to species and calculating averages in assemblages. We then generated simulations in which species with cohesive or patchy distributions are placed with respect to the North American temperature gradient with or without a broad‐scale richness gradient. Random intrinsic variables are again used as predictors of richness. Finally, we analysed one simulated scenario with random intrinsic variables as both response and predictor variables. Results The models of bird and tree richness often explained moderate to large proportions of the variance. Regression trees, geographically weighted regression and simultaneous autoregression were very sensitive to the problem; generalized additive models were moderately affected, as was multiple regression to a lesser extent. In the virtual data, the variance explained increased with increasing species co‐occurrences, but neither range cohesion, a richness gradient nor spatial autocorrelation in predictors had major impacts on the variance explained. The problem persisted when the response variable was also a random intrinsic variable. Main conclusions Repeated species co‐occurrences can generate strong spurious relationships between richness and aggregated species attributes. It is important to realize that models utilizing assemblage variables aggregated from species‐level values, as well as maps illustrating their spatial patterns, cannot be taken at face value.

Viability of cyclic populations - Alexander Singer; Karin Frank (Ecology, 2016)
Theory on viability of small populations is well developed and has led to the standard methodology of population viability analysis ( PVA ) to assess vulnerability of single species. However, more complex situations involving community dynamics or environmental change violate theoretical assumptions. Synthesizing concepts from population, community, and conservation ecology, we develop a generic theory on the viability of cyclic populations. The interplay of periodic population decline and demography causes varying risk patterns that aggregate during cycles and modify the temporal structure of viability. This variability is visualized and quantitatively assessed. For two standard viability metrics that summarize immediate extinction risk and the general long‐term conditions of populations, we mathematically describe the impact of population cycles. Finally, we suggest and demonstrate PVA for cyclic populations that respond to, e.g., seasonality, interannual variation, or trophic interactions. Our theoretical and methodological advancement opens a route to viability analysis in food webs and trophic meta‐communities and equips biodiversity conservation with a long‐missing tool.

Endangered Quino checkerspot butterfly and climate change: Short-term success but long-term vulnerability? - Camille Parmesan; Alison Williams-Anderson; Matthew Moskwik; Alexander S. Mikheyev; Michael C. Singer (Journal of Insect Conservation, 2015)

Host‐associated genomic differentiation in congeneric butterflies: now you see it, now you do not - Alexander S. Mikheyev; Carolyn S. McBride; Ulrich G. Mueller; Camille Parmesan; Melanie R. Smee; Constanti Stefanescu; Brian Wee; Michael C. Singer (Molecular Ecology, 2013)
Ecotypic variation among populations may become associated with widespread genomic differentiation, but theory predicts that this should happen only under particular conditions of gene flow, selection and population size. In closely related species, we might expect the strength of host‐associated genomic differentiation ( HAD ) to be correlated with the degree of phenotypic differentiation in host‐adaptive traits. Using microsatellite and A mplified F ragment L ength P olymorphism ( AFLP ) markers, and controlling for isolation by distance between populations, we sought HAD in two congeneric species of butterflies with different degrees of host plant specialization. Prior work on E uphydryas editha had shown strong interpopulation differentiation in host‐adapted traits, resulting in incipient reproductive isolation among host‐associated ecotypes. We show here that E uphydryas aurinia had much weaker host‐associated phenotypic differentiation. Contrary to our expectations, we detected HAD in Euphydryas aurinia , but not in E. editha . Even within an E. aurinia population that fed on both hosts, we found weak but significant sympatric HAD that persisted in samples taken 9 years apart. The finding of significantly stronger HAD in the system with less phenotypic differentiation may seem paradoxical. Our findings can be explained by multiple factors, ranging from differences in dispersal or effective population size, to spatial variation in genomic or phenotypic traits and to structure induced by past histories of host‐adapted populations. Other infrequently measured factors, such as differences in recombination rates, may also play a role. Our result adds to recent work as a further caution against assumptions of simple relationships between genomic and adaptive phenotypic differentiation.

Determining Sensitive Parameters for the Population Viability of Reintroduced Sumatran Orangutans (Pongo abelii) - Doris Kelle; Dominik Fechter; Alexander Singer; Peter Pratje; Ilse Storch (International Journal of Primatology, 2013)

Process, correlation and parameter fitting in species distribution models: a response to Kriticos et al - Stanislaus J. Schymanski; Carsten F. Dormann; Juliano Cabral; Isabelle Chuine; Catherine H. Graham; Florian Hartig; Michael Kearney; Xavier Morin; Christine Römermann; Boris Schröder; Alexander Singer (Journal of Biogeography, 2013)
In a recent article (Dormann et al ., 2012, Journal of Biogeography , 39, 2119–2131), we compared different approaches to species distribution modelling and depicted modelling approaches along an axis from purely ‘correlative’ to ‘forward process‐based’ models. In their correspondence, Kriticos et al . (2013, Journal of Biogeography , doi: 10.1111/j.1365‐2699.2012.02791.x ) challenge this view, claiming that our continuum representation neglects differences among models and does not consider the ability of fitted process‐based models to combine the advantages of both process‐based and correlative modelling approaches. Here we clarify that the continuum view resulted from recognition of the manifold differences between models. We also reinforce the point that the current trend towards combining different modelling approaches may lead not only to the desired combination of the advantages but also to the accumulation of the disadvantages of those approaches. This point has not been made sufficiently clear previously.

Correlation and process in species distribution models: bridging a dichotomy - Carsten F. Dormann; Stanislaus J. Schymanski; Juliano Cabral; Isabelle Chuine; Catherine Graham; Florian Hartig; Michael Kearney; Xavier Morin; Christine Römermann; Boris Schröder; Alexander Singer (Journal of Biogeography, 2012)
Within the field of species distribution modelling an apparent dichotomy exists between process‐based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlative–process spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the process–correlation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process‐based approaches to species distribution modelling lags far behind more correlative (process‐implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process‐explicit species distribution models and how they may complement current approaches to study species distributions.

Biotic modifiers, environmental modulation and species distribution models - H. Peter Linder; Olga Bykova; James Dyke; Rampal S. Etienne; Thomas Hickler; Ingolf Kühn; Glenn Marion; Ralf Ohlemüller; Stanislaus J. Schymanski; Alexander Singer (Journal of Biogeography, 2012)
The ability of species to modulate environmental conditions and resources has long been of interest. In the past three decades the impacts of these biotic modifiers have been investigated as ‘ecosystem engineers’, ‘niche constructors’, ‘facilitators’ and ‘keystone species’. This environmental modulation can vary spatially from extremely local to global, temporally from days to geological time, and taxonomically from a few to a very large number of species. Modulation impacts are pervasive and affect, inter alia , the climate, structural environments, disturbance rates, soils and the atmospheric chemical composition. Biotic modifiers may profoundly transform the projected environmental conditions, and consequently have a significant impact on the predicted occurrence of the focal species in species distribution models (SDMs). This applies especially when these models are projected into different geographical regions or into the future or the past, where these biotic modifiers may be absent, or other biotic modifiers may be present. We show that environmental modulation can be represented in SDMs as additional variables. In some instances it is possible to use the species (e.g. biotic modifiers) in order to reflect the modulation. This would apply particularly to cases where the effect is the result of a single or a small number of species (e.g. elephants transforming woodland to grassland). Where numerous species generate an effect (such as tree species making a forest, or grasses facilitating fire) that modulates the abiotic environment, the effect itself might be a better descriptor for the aggregated action of the numerous species. We refer to this ‘effect’ as the modulator. Much of the information required to incorporate environmental modulation effects in SDMs is already available from remote‐sensing data and vegetation models.

How to understand species’ niches and range dynamics: a demographic research agenda for biogeography - Frank M. Schurr; Jörn Pagel; Juliano Sarmento Cabral; Jürgen Groeneveld; Olga Bykova; Robert B. O’Hara; Florian Hartig; W. Daniel Kissling; H. Peter Linder; Guy F. Midgley; Boris Schröder; Alexander Singer; et al. (Journal of Biogeography, 2012)
Range dynamics causes mismatches between a species’ geographical distribution and the set of suitable environments in which population growth is positive (the Hutchinsonian niche). This is because source–sink population dynamics cause species to occupy unsuitable environments, and because environmental change creates non‐equilibrium situations in which species may be absent from suitable environments (due to migration limitation) or present in unsuitable environments that were previously suitable (due to time‐delayed extinction). Because correlative species distribution models do not account for these processes, they are likely to produce biased niche estimates and biased forecasts of future range dynamics. Recently developed dynamic range models (DRMs) overcome this problem: they statistically estimate both range dynamics and the underlying environmental response of demographic rates from species distribution data. This process‐based statistical approach qualitatively advances biogeographical analyses. Yet, the application of DRMs to a broad range of species and study systems requires substantial research efforts in statistical modelling, empirical data collection and ecological theory. Here we review current and potential contributions of these fields to a demographic understanding of niches and range dynamics. Our review serves to formulate a demographic research agenda that entails: (1) advances in incorporating process‐based models of demographic responses and range dynamics into a statistical framework, (2) systematic collection of data on temporal changes in distribution and abundance and on the response of demographic rates to environmental variation, and (3) improved theoretical understanding of the scaling of demographic rates and the dynamics of spatially coupled populations. This demographic research agenda is challenging but necessary for improved comprehension and quantification of niches and range dynamics. It also forms the basis for understanding how niches and range dynamics are shaped by evolutionary dynamics and biotic interactions. Ultimately, the demographic research agenda should lead to deeper integration of biogeography with empirical and theoretical ecology.

Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents - W. D. Kissling; Carsten F. Dormann; Jürgen Groeneveld; Thomas Hickler; Ingolf Kühn; Greg J. McInerny; José M. Montoya; Christine Römermann; Katja Schiffers; Frank M. Schurr; Alexander Singer; Jens‐Christian Svenning; et al. (Journal of Biogeography, 2012)
Aim Biotic interactions – within guilds or across trophic levels – have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of ‘species interaction distribution models’ (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co‐occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non‐stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio‐temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species’ effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co‐occurrence datasets across large‐scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio‐temporal data on biotic interactions in multispecies communities.

META-X: Generic Software for Metapopulation Viability Analysis - Volker Grimm; Helmut Lorek; Jens Finke; Frank Koester; Michael Malachinski; Michael Sonnenschein; Atte Moilanen; Ilse Storch; Alexander Singer; Christian Wissel; Karin Frank (Biodiversity and Conservation, 2004)

Abstracts of presentations on plant protection issues at the fifth international Mango Symposium Abstracts of presentations on plant protection issues at the Xth international congress of Virology - J. E. Peña; M. Wysoki; Gajendra Singh; Nancy Boscán de M.; Freddy J. Godoy; A. Obligado; C. J. Rossetto; I. J. A. Ribeiro; P. B. Gallo; N. B. Soares; J. C. Sabino; A. L. M. Martins; et al. (Phytoparasitica, 1997)