@misc{KalinkatCabralDarwalletal.2017,
  author    = {Kalinkat, Gregor and Cabral, Juliano Sarmento and Darwall, William and Ficetola, G. Francesco and Fisher, Judith L. and Giling, Darren P. and Gosselin, Marie-Pierre and Grossart, Hans-Peter and Jaehnig, Sonja C. and Jeschke, Jonathan M. and Knopf, Klaus and Larsen, Stefano and Onandia, Gabriela and Paetzig, Marlene and Saul, Wolf-Christian and Singer, Gabriel and Sperfeld, Erik and Jaric, Ivan},
  title     = {Flagship umbrella species needed for the conservation of overlooked aquatic biodiversity},
  series = {Conservation biology : the journal of the Society for Conservation Biology},
  volume    = {31},
  journal   = {Conservation biology : the journal of the Society for Conservation Biology},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0888-8892},
  doi       = {10.1111/cobi.12813},
  pages     = {481 -- 485},
  year      = {2017},
  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{DarwallBremerichDeWeveretal.2018,
  author    = {Darwall, William and Bremerich, Vanessa and De Wever, Aaike and Dell, Anthony I. and Freyhof, Joerg and Gessner, Mark O. and Grossart, Hans-Peter and Harrison, Ian and Irvine, Ken and J{\"a}hnig, Sonja C. and Jeschke, Jonathan M. and Lee, Jessica J. and Lu, Cai and Lewandowska, Aleksandra M. and Monaghan, Michael T. and Nejstgaard, Jens C. and Patricio, Harmony and Schmidt-Kloiber, Astrid and Stuart, Simon N. and Thieme, Michele and Tockner, Klement and Turak, Eren and Weyl, Olaf},
  title     = {The alliance for freshwater life},
  series = {Aquatic Conservation: Marine and Freshwater Ecosystems},
  volume    = {28},
  journal   = {Aquatic Conservation: Marine and Freshwater Ecosystems},
  number    = {4},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1052-7613},
  doi       = {10.1002/aqc.2958},
  pages     = {1015 -- 1022},
  year      = {2018},
  abstract  = {1. Global pressures on freshwater ecosystems are high and rising. Viewed primarily as a resource for humans, current practices of water use have led to catastrophic declines in freshwater species and the degradation of freshwater ecosystems, including their genetic and functional diversity. Approximately three-quarters of the world's inland wetlands have been lost, one-third of the 28 000 freshwater species assessed for the International Union for Conservation of Nature (IUCN) Red List are threatened with extinction, and freshwater vertebrate populations are undergoing declines that are more rapid than those of terrestrial and marine species. This global loss continues unchecked, despite the importance of freshwater ecosystems as a source of clean water, food, livelihoods, recreation, and inspiration. 2. The causes of these declines include hydrological alterations, habitat degradation and loss, overexploitation, invasive species, pollution, and the multiple impacts of climate change. Although there are policy initiatives that aim to protect freshwater life, these are rarely implemented with sufficient conviction and enforcement. Policies that focus on the development and management of fresh waters as a resource for people almost universally neglect the biodiversity that they contain. 3. Here we introduce the Alliance for Freshwater Life, a global initiative, uniting specialists in research, data synthesis, conservation, education and outreach, and policymaking. This expert network aims to provide the critical mass required for the effective representation of freshwater biodiversity at policy meetings, to develop solutions balancing the needs of development and conservation, and to better convey the important role freshwater ecosystems play in human well-being. Through this united effort we hope to reverse this tide of loss and decline in freshwater biodiversity. We introduce several short- and medium-term actions as examples for making positive change, and invite individuals, organizations, authorities, and governments to join the Alliance for Freshwater Life.},
  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}
}
@article{HegerBernardVerdierGessleretal.2019,
  author    = {Heger, Tina and Bernard-Verdier, Maud and Gessler, Arthur and Greenwood, Alex D. and Grossart, Hans-Peter and Hilker, Monika and Keinath, Silvia and Kowarik, Ingo and K{\"u}ffer, Christoph and Marquard, Elisabeth and Mueller, Johannes and Niemeier, Stephanie and Onandia, Gabriela and Petermann, Jana S. and Rillig, Matthias C. and Rodel, Mark-Oliver and Saul, Wolf-Christian and Schittko, Conrad and Tockner, Klement and Joshi, Jasmin Radha and Jeschke, Jonathan M.},
  title     = {Towards an Integrative, Eco-Evolutionary Understanding of Ecological Novelty: Studying and Communicating Interlinked Effects of Global Change},
  series = {Bioscience},
  volume    = {69},
  journal   = {Bioscience},
  number    = {11},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0006-3568},
  doi       = {10.1093/biosci/biz095},
  pages     = {888 -- 899},
  year      = {2019},
  abstract  = {Global change has complex eco-evolutionary consequences for organisms and ecosystems, but related concepts (e.g., novel ecosystems) do not cover their full range. Here we propose an umbrella concept of "ecological novelty" comprising (1) a site-specific and (2) an organism-centered, eco-evolutionary perspective. Under this umbrella, complementary options for studying and communicating effects of global change on organisms, ecosystems, and landscapes can be included in a toolbox. This allows researchers to address ecological novelty from different perspectives, e.g., by defining it based on (a) categorical or continuous measures, (b) reference conditions related to sites or organisms, and (c) types of human activities. We suggest striving for a descriptive, non-normative usage of the term "ecological novelty" in science. Normative evaluations and decisions about conservation policies or management are important, but require additional societal processes and engagement with multiple stakeholders.},
  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}
}
@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{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}
}
@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}
}