@article{SchittkoOnandiaBernardVerdieretal.2022, author = {Schittko, Conrad and Onandia, Gabriela and Bernard-Verdier, Maud and Heger, Tina and Jeschke, Jonathan M. and Kowarik, Ingo and Maaß, Stefanie and Joshi, Jasmin}, title = {Biodiversity maintains soil multifunctionality and soil organic carbon in novel urban ecosystems}, series = {Journal of ecology}, volume = {110}, journal = {Journal of ecology}, number = {4}, publisher = {Wiley}, address = {Hoboken}, issn = {0022-0477}, doi = {10.1111/1365-2745.13852}, pages = {916 -- 934}, year = {2022}, abstract = {Biodiversity in urban ecosystems has the potential to increase ecosystem functions and support a suite of services valued by society, including services provided by soils. Specifically, the sequestration of carbon in soils has often been advocated as a solution to mitigate the steady increase in CO2 concentration in the atmosphere as a key driver of climate change. However, urban ecosystems are also characterized by an often high level of ecological novelty due to profound human-mediated changes, such as the presence of high numbers of non-native species, impervious surfaces or other disturbances. Yet it is poorly understood whether and how biodiversity affects ecosystem functioning and services of urban soils under these novel conditions. In this study, we assessed the influence of above- and below-ground diversity, as well as urbanization and plant invasions, on multifunctionality and organic carbon stocks of soils in non-manipulated grasslands along an urbanization gradient in Berlin, Germany. We focused on plant diversity (measured as species richness and functional trait diversity) and, in addition, on soil organism diversity as a potential mediator for the relationship of plant species diversity and ecosystem functioning. Our results showed positive effects of plant diversity on soil multifunctionality and soil organic carbon stocks along the entire gradient. Structural equation models revealed that plant diversity enhanced soil multifunctionality and soil organic carbon by increasing the diversity of below-ground organisms. These positive effects of plant diversity on soil multifunctionality and soil fauna were not restricted to native plant species only, but were also exerted by non-native species, although to a lesser degree. Synthesis. We conclude that enhancing diversity in plants and soil fauna of urban grasslands can increase the multifunctionality of urban soils and also add to their often underestimated but very valuable role in mitigating effects of climate change.}, language = {en} } @article{HegerNiklesJacobs2018, author = {Heger, Tina and Nikles, Gabriele and Jacobs, Brooke S.}, title = {Differentiation in native as well as introduced ranges}, series = {AoB PLANTS}, volume = {10}, journal = {AoB PLANTS}, number = {1}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {2041-2851}, doi = {10.1093/aobpla/ply009}, pages = {12}, year = {2018}, abstract = {Germination, a crucial phase in the life cycle of a plant, can be significantly influenced by competition and facilitation. The aim of this study was to test whether differences in cover of surrounding vegetation can lead to population differentiation in germination behaviour of an annual grassland species, and if so, whether such a differentiation can be found in the native as well as in the introduced range. We used maternal progeny of Erodium cicutarium previously propagated under uniform conditions that had been collected in multiple populations in the native and two introduced ranges, in populations representing extremes in terms of mean and variability of the cover of surrounding vegetation. In the first experiment, we tested the effect of germination temperature and mean cover at the source site on germination, and found interlinked effects of these factors. In seeds from one of the introduced ranges (California), we found indication for a 2-fold dormancy, hindering germination at high temperatures even if physical dormancy was broken and water was available. This behaviour was less strong in high cover populations, indicating cross-generational facilitating effects of dense vegetation. In the second experiment, we tested whether spatial variation in cover of surrounding vegetation has an effect on the proportion of dormant seeds. Contrary to our expectations, we found that across source regions, high variance in cover was associated with higher proportions of seeds germinating directly after storage. In all three regions, germination seemed to match the local environment in terms of climate and vegetation cover. We suggest that this is due to a combined effect of introduction of preadapted genotypes and local evolutionary processes.}, language = {en} } @misc{HiggsHarrisHegeretal.2018, author = {Higgs, Eric S. and Harris, Jim A. and Heger, Tina and Hobbs, Richard J. and Murphy, Stephen D. and Suding, Katharine N.}, title = {Keep ecological restoration open and flexible}, series = {Nature Ecology \& Evolution}, volume = {2}, journal = {Nature Ecology \& Evolution}, number = {4}, publisher = {Nature Publ. Group}, address = {London}, issn = {2397-334X}, doi = {10.1038/s41559-018-0483-9}, pages = {580 -- 580}, year = {2018}, language = {en} } @article{BragaGomezAparicioHegeretal.2018, author = {Braga, Raul Renno and Gomez-Aparicio, Lorena and Heger, Tina and Simoes Vitule, Jean Ricardo and Jeschke, Jonathan M.}, title = {Structuring evidence for invasional meltdown}, series = {Biological invasions : unique international journal uniting scientists in the broad field of biological invasions}, volume = {20}, journal = {Biological invasions : unique international journal uniting scientists in the broad field of biological invasions}, number = {4}, publisher = {Springer}, address = {Dordrecht}, issn = {1387-3547}, doi = {10.1007/s10530-017-1582-2}, pages = {923 -- 936}, year = {2018}, abstract = {Negative interactions have been suggested as a major barrier for species arriving in a new habitat. More recently, positive interactions drew attention from community assembly theory and invasion science. The invasional meltdown hypothesis (IMH) introduced the idea that positive interactions among non-native species could facilitate one another's invasion, even increasing their impact upon the native community. Many studies have addressed IMH, but with contrasting results, reflecting various types of evidence on a multitude of scales. Here we use the hierarchy-of-hypotheses (HoH) approach to differentiate key aspects of IMH, organizing and linking empirical studies to sub-hypotheses of IMH. We also assess the level of empirical support for each sub-hypothesis based on the evidence reported in the studies. We identified 150 studies addressing IMH. The majority of studies support IMH, but the evidence comes from studies with different aims and questions. Supporting studies at the community or ecosystem level are currently rare. Evidence is scarce for marine habitats and vertebrates. Few sub-hypotheses are questioned by more than 50\% of the evaluated studies, indicating that non-native species do not affect each other's survival, growth, reproduction, abundance, density or biomass in reciprocal A ↔ B interactions. With the HoH for IMH presented here, we can monitor progress in empirical tests and evidences of IMH. For instance, more tests at the community and ecosystem level are needed, as these are necessary to address the core of this hypothesis.}, language = {en} } @article{SchittkoBernardVerdierHegeretal.2020, author = {Schittko, Conrad and Bernard-Verdier, Maud and Heger, Tina and Buchholz, Sascha and Kowarik, Ingo and von der Lippe, Moritz and Seitz, Birgit and Joshi, Jasmin Radha and Jeschke, Jonathan M.}, title = {A multidimensional framework for measuring biotic novelty: How novel is a community?}, series = {Global Change Biology}, volume = {26}, journal = {Global Change Biology}, number = {8}, publisher = {John Wiley \& Sons, Inc.}, address = {New Jersey}, pages = {17}, year = {2020}, abstract = {Anthropogenic changes in climate, land use, and disturbance regimes, as well as introductions of non-native species can lead to the transformation of many ecosystems. The resulting novel ecosystems are usually characterized by species assemblages that have not occurred previously in a given area. Quantifying the ecological novelty of communities (i.e., biotic novelty) would enhance the understanding of environmental change. However, quantification remains challenging since current novelty metrics, such as the number and/or proportion of non-native species in a community, fall short of considering both functional and evolutionary aspects of biotic novelty. Here, we propose the Biotic Novelty Index (BNI), an intuitive and flexible multidimensional measure that combines (a) functional differences between native and non-native introduced species with (b) temporal dynamics of species introductions. We show that the BNI is an additive partition of Rao's quadratic entropy, capturing the novel interaction component of the community's functional diversity. Simulations show that the index varies predictably with the relative amount of functional novelty added by recently arrived species, and they illustrate the need to provide an additional standardized version of the index. We present a detailed R code and two applications of the BNI by (a) measuring changes of biotic novelty of dry grassland plant communities along an urbanization gradient in a metropolitan region and (b) determining the biotic novelty of plant species assemblages at a national scale. The results illustrate the applicability of the index across scales and its flexibility in the use of data of different quality. Both case studies revealed strong connections between biotic novelty and increasing urbanization, a measure of abiotic novelty. We conclude that the BNI framework may help building a basis for better understanding the ecological and evolutionary consequences of global change.}, language = {en} } @misc{SchittkoBernardVerdierHegeretal.2020, author = {Schittko, Conrad and Bernard-Verdier, Maud and Heger, Tina and Buchholz, Sascha and Kowarik, Ingo and von der Lippe, Moritz and Seitz, Birgit and Joshi, Jasmin Radha and Jeschke, Jonathan M.}, title = {A multidimensional framework for measuring biotic novelty: How novel is a community?}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {8}, issn = {1866-8372}, doi = {10.25932/publishup-52565}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-525657}, pages = {19}, year = {2020}, abstract = {Anthropogenic changes in climate, land use, and disturbance regimes, as well as introductions of non-native species can lead to the transformation of many ecosystems. The resulting novel ecosystems are usually characterized by species assemblages that have not occurred previously in a given area. Quantifying the ecological novelty of communities (i.e., biotic novelty) would enhance the understanding of environmental change. However, quantification remains challenging since current novelty metrics, such as the number and/or proportion of non-native species in a community, fall short of considering both functional and evolutionary aspects of biotic novelty. Here, we propose the Biotic Novelty Index (BNI), an intuitive and flexible multidimensional measure that combines (a) functional differences between native and non-native introduced species with (b) temporal dynamics of species introductions. We show that the BNI is an additive partition of Rao's quadratic entropy, capturing the novel interaction component of the community's functional diversity. Simulations show that the index varies predictably with the relative amount of functional novelty added by recently arrived species, and they illustrate the need to provide an additional standardized version of the index. We present a detailed R code and two applications of the BNI by (a) measuring changes of biotic novelty of dry grassland plant communities along an urbanization gradient in a metropolitan region and (b) determining the biotic novelty of plant species assemblages at a national scale. The results illustrate the applicability of the index across scales and its flexibility in the use of data of different quality. Both case studies revealed strong connections between biotic novelty and increasing urbanization, a measure of abiotic novelty. We conclude that the BNI framework may help building a basis for better understanding the ecological and evolutionary consequences of global change.}, language = {en} } @article{YannelliKarrerHalletal.2018, author = {Yannelli, Florencia A. and Karrer, Gerhard and Hall, Rea and Kollmann, Johannes and Heger, Tina}, title = {Seed density is more effective than multi-trait limiting similarity in controlling grassland resistance against plant invasions in mesocosms}, series = {Applied vegetation science : official organ of the International Association for Vegetation Science}, volume = {21}, journal = {Applied vegetation science : official organ of the International Association for Vegetation Science}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {1402-2001}, doi = {10.1111/avsc.12373}, pages = {411 -- 418}, year = {2018}, abstract = {QuestionDisturbed areas offer great opportunities for restoring native biodiversity, but they are also prone to invasion by alien plants. Following the limiting similarity hypothesis, we address the question of whether or not similarity of plant functional traits helps developing seed mixtures of native communities with high resistance to invasive species at an early stage of restoration. LocationCentre of Greenhouses and Laboratories Durnast, Technische Universitat Munchen, Freising, Germany. MethodsUsing a system of linear equations, we designed native communities maximizing the similarity between the native and two invasive species according to ten functional traits. We used native grassland plants, two invasive alien species that are often problematic in disturbed areas (i.e., Ambrosia artemisiifolia and Solidago gigantea) and trait information obtained from databases. The two communities were then tested for resistance against establishment of the two invaders separately in a greenhouse experiment. We measured height of the invasive species and above-ground biomass, along with leaf area index, 4 and 8months after sowing respectively. ResultsBoth invasive species were successfully reduced by the native community designed to suppress S. gigantea dominated by small-seeded species. These results could be considered as partial support for the limiting similarity hypothesis. However, given the success of this mixture against both invasive species, suppression was better explained by a seed density effect resulting from the smaller seed mass of the native species included in this mixture. Further, the dominance of a fast-developing competitive species could also contribute to its success. ConclusionsThere was no unequivocal support for the limiting similarity hypothesis in terms of the traits selected. Instead we found that increasing seeding density of native species and selecting species with a fast vegetative development is an effective way to suppress invasive plants during early stages of restoration. If limiting similarity is used to design communities for restoration, early life-history traits should be taken into account.}, language = {en} } @misc{RyoJeschkeRilligetal.2020, author = {Ryo, Masahiro and Jeschke, Jonathan M. and Rillig, Matthias C. and Heger, Tina}, title = {Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1171}, issn = {1866-8372}, doi = {10.25932/publishup-51764}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-517643}, pages = {66 -- 73}, year = {2020}, abstract = {Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel patterns and the source of controversy in a general hypothesis. We apply a decision tree algorithm, assuming that evidence from various contexts can be adequately integrated in a hierarchically nested structure. As a case study, we analyzed 163 articles that studied a prominent hypothesis in invasion biology, the enemy release hypothesis. We explored if any of the nine attributes that classify each study can differentiate conclusions as classification problem. Results corroborated that machine learning can be useful for research synthesis, as the algorithm could detect patterns that had been already focused in previous narrative reviews. Compared with the previous synthesis study that assessed the same evidence collection based on experts' judgement, the algorithm has newly proposed that the studies focusing on Asian regions mostly supported the hypothesis, suggesting that more detailed investigations in these regions can enhance our understanding of the hypothesis. We suggest that machine learning algorithms can be a promising synthesis tool especially where studies (a) reformulate a general hypothesis from different perspectives, (b) use different methods or variables, or (c) report insufficient information for conducting meta-analyses.}, language = {en} } @article{RyoJeschkeRilligetal.2020, author = {Ryo, Masahiro and Jeschke, Jonathan M. and Rillig, Matthias C. and Heger, Tina}, title = {Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions}, series = {Research synthesis methods}, volume = {11}, journal = {Research synthesis methods}, number = {1}, publisher = {Wiley}, address = {Hoboken}, issn = {1759-2879}, doi = {10.1002/jrsm.1363}, pages = {66 -- 73}, year = {2020}, abstract = {Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel patterns and the source of controversy in a general hypothesis. We apply a decision tree algorithm, assuming that evidence from various contexts can be adequately integrated in a hierarchically nested structure. As a case study, we analyzed 163 articles that studied a prominent hypothesis in invasion biology, the enemy release hypothesis. We explored if any of the nine attributes that classify each study can differentiate conclusions as classification problem. Results corroborated that machine learning can be useful for research synthesis, as the algorithm could detect patterns that had been already focused in previous narrative reviews. Compared with the previous synthesis study that assessed the same evidence collection based on experts' judgement, the algorithm has newly proposed that the studies focusing on Asian regions mostly supported the hypothesis, suggesting that more detailed investigations in these regions can enhance our understanding of the hypothesis. We suggest that machine learning algorithms can be a promising synthesis tool especially where studies (a) reformulate a general hypothesis from different perspectives, (b) use different methods or variables, or (c) report insufficient information for conducting meta-analyses.}, language = {en} } @misc{JaricHegerMonzonetal.2019, author = {Jaric, Ivan and Heger, Tina and Monzon, Federico Castro and Jeschke, Jonathan M. and Kowarik, Ingo and McConkey, Kim R. and Pysek, Petr and Sagouis, Alban and Essl, Franz}, title = {Crypticity in Biological Invasions}, series = {Trends in Ecology \& Evolution}, volume = {34}, journal = {Trends in Ecology \& Evolution}, number = {4}, publisher = {Elsevier}, address = {London}, issn = {0169-5347}, doi = {10.1016/j.tree.2018.12.008}, pages = {291 -- 302}, year = {2019}, abstract = {Ecological effects of alien species can be dramatic, but management and prevention of negative impacts are often hindered by crypticity of the species or their ecological functions. Ecological functions can change dramatically over time, or manifest after long periods of an innocuous presence. Such cryptic processes may lead to an underestimation of long-term impacts and constrain management effectiveness. Here, we present a conceptual framework of crypticity in biological invasions. We identify the underlying mechanisms, provide evidence of their importance, and illustrate this phenomenon with case studies. This framework has potential to improve the recognition of the full risks and impacts of invasive species.}, language = {en} }