top of page

The academic system is failing its early-career researchers  and in doing so, it is destroying itself from within.

By design, today’s universities claim to reward excellence, yet they systematically punish ambition, mobility, and high productivity.

​

Talented postdocs who follow the rules by publishing prolifically, securing competitive fellowships, building international networks, etc. are too often passed over for permanent positions in favor of candidates who promise less disruption and better "fit". I have made that point repeatedly, yet I was criticized by permanently employed colleagues. They said that "this is normal" and that "I will find a position eventually", to which I always tend to reply "when? When I burned out?". Please don't get me wrong. I know I am still "young" at 37, but I see those that are put into permanent positions because I or friends of mine applied for those positions. I often know external reviewers. I often know people at the universities. And they told me. Oh boy, they talk...

​

The core issue always pointed out is that those in charge ... perhaps should not be in charge ... said by people among their own ranks ... behind closed doors.

 

The things I was told behind closed doors are interesting. I am:

  • too competent. I publish too much. I am too active. I may make others look bad.

  • too young. I would be made permanent for a long time. What if I underperformed?

  • too invisible. Because I have done my PhD outside of Germany and then spent years in other countries than Germany, I have no "Vitamin B" in the form of established Professors backing me.

  • too outspoken. Well that is true. But if we don't criticise what is wrong, why are we in science?

 

In essence, the result is the selection of often low-performing "safe bets". Basically "the devil I know". Such dominating risk-averse logic is widespread in Germany and beyond, turning excellence into a liability. The result is a self-reinforcing cycle of frustration and talent loss: the most driven and visible researchers emigrate or exit academia entirely, while safer, less dynamic profiles accumulate. I argue that what begins as a preference for institutional comfort gradually erodes the system’s scientific vitality and innovative capacity.

​

This internal failure extends far beyond individual careers. When hiring prioritizes low-friction collegiality over genuine merit, universities weaken their core missions. Students receive suboptimal education from faculty selected more for harmony than teaching excellence or research leadership. Intellectual diversity shrinks as echo chambers form, allowing ideology to fill the vacuum left by sidelined rigorous thinkers. Long-term, this breeds stagnation: fewer groundbreaking grants, declining international competitiveness, and aging faculties disconnected from fresh perspectives. A system that consumes enormous public resources to train sharp minds, only to discard or exile them, is not sustainable. I'd argue that it is quietly cannibalizing its own future.

​

And then there is betrayal and performative empathy. An interesting marginal phenomenon is that many people that were once outspoken postdocs complaining about the system, once they secure permanent positions, quickly turn their backs on the struggles of early-career researchers (the very group they once belonged to), often pretending to care about systemic problems until the moment it requires them to acknowledge concrete cases of injustice. At that point, the only thing left is them to deflect, dismiss, or outright ask to be left alone with such inconvenient realities because "if I complain too much I get in trouble". An inconvenient truth. 

​

Meaningful reform is essential - but wont come. Universities must cut excessive bureaucracy in hiring and career progression, create more stable mid-level permanent positions outside the narrow professorial bottleneck, and shift evaluation criteria toward transparent merit that values both research output and teaching competence. Rather than fearing high-potential candidates as sources of "organizational risk", institutions should invest in them. Without these changes (i.e. less risk aversion, more investment in genuine potential) academia will continue its slow self-destruction, hemorrhaging talent while falling behind more dynamic systems abroad.

Die Rolle gebietsfremder Arten in europäischen Gewässern und ihre Folgen für Biodiversität, Umwelt und Wirtschaft

1     Invasionsbiologie

Die Invasionsbiologie befasst sich mit dem Verständnis und Management der Ursachen sowie den Folgen die durch die Einbringung gebietsfremder Arten entstehen. Ihre Ziele sind vielseitig und umfassen unter anderem: (1) die Identifizierung relevanter Vektoren und Wege durch die Arten in neue Regionen eingeführt werden (Hulme, 2016; McGeoch et al. 2016; Haubrock et al., 2025a); (2) die Vorhersage, inwiefern gebietsfremde Arten eine Belastung für Ökosysteme darstellen können (Heger und Trepl 2003; Vilizzi et al. 2021; Haubrock et al., 2025b); (3) die Prognose der Umweltbedingungen (menschliche Störungen, biotischer Widerstand usw.), die einige Lebensräume anfälliger für Invasionen machen als andere (Torres et al. 2023); (4) das Verständnis der miteinander verbundenen ökologischen und gesellschaftlichen Auswirkungen dieser Invasionen (Simberloff et al. 2013; Haubrock et al., 2025b); und (5) die Entwicklung sowohl proaktiver Strategien zur Verhinderung von Einführung und Etablierung (z. B. Biosicherheitsprotokolle) als auch reaktiver Strategien zur Minderung der Auswirkungen bereits etablierter gebietsfremder Arten (z. B. funktionale Ausrottung) (Robertson et al. 2020; Green und Grosholz 2021). Obwohl hierbei regelmäßig Konflikte zwischen Zielen abgewogen werden (Frawley und McCalman 2014a, b; Chew 2015; Kourantidou et al. 2022), hat die Invasionsbiologie trotz ihrer relativ jungen Geschichte bereits einen breiten Einfluss auf Politik und Entscheidungsfindung ausgeübt (Essl et al. 2020), inklusive nationaler Politik zur Verhinderung der Einführung und Ausbreitung gebietsfremder Arten und internationaler Abkommen (Early et al. 2016; Meyerson et al. 2022).

Obgleich die Invasionsbiologie eine noch sehr junge Disziplin ist, stellt sich die Invasionsbiologie zunehmenden Herausforderungen wie Globalisierung und fortlaufenden Veränderungen des Klimas (Brönnimann und Brönnimann 2015), der Umwelt (Foley et al. 2013; Britton, 2023) und der Technologie (Larson et al. 2020), die die Muster und Dynamiken biologischer Invasionen neugestalten (Meyerson & Mooney 2007; Soto et al. 2023). Angesichts der vielschichtigen und überwiegend negativen Auswirkungen, die die Einführung nicht-einheimischer Arten auf die Natur (Blackburn et al., 2011; Bellard et al. 2022; Rilov et al. 2024) und die Gesellschaft haben kann (Pyšek et al. 2020; Diagne et al., 2021), liegt die Forschung über biologische Invasionen an der Schnittstelle zwischen Natur- und Sozialwissenschaften (Heger et al. 2021; Bortolus & Schwindt, 2022).

​

1.2    Biologische Invasionen und die Relevanz einheitlicher Terminologie

Im Allgemeinen werden biologische Invasionen als durch Menschen vermittelte Prozesse definiert, bei denen Organismen absichtlich oder unbeabsichtigt über ihre natürlichen biogeografischen Grenzen hinaus transportiert und eingebracht werden, wodurch sie sich potenziell ausbreiten, und Schäden verursachen können (Simberloff, 2013; Pyšek et al., 2020; Soto et al., 2024). Die zunehmende Multi- und Interdisziplinarität in der Invasionsbiologie hat zwar das Verständnis und Management biologischer Invasionen verbessert, jedoch auch zahlreiche nicht-synonyme Begriffe und widersprüchliche Konzeptualisierungen hervorgebracht (Lockwood et al., 2005). Eine zusätzliche Komplikation entsteht durch die ungleiche wissenschaftliche Aufmerksamkeit über Lebensräume, Taxa und geografische Regionen (MacIsaac, Tedla & Ricciardi, 2011; Watkins et al., 2021). Dies hat zur Ausbildung mehrerer wissenschaftlicher Ansichten geführt, die jeweils eigene Standards entwickeln und oft nur begrenzt interagieren (Ojaveer et al., 2015; Latombe et al., 2019). Der daraus resultierende Mix aus Begriffen und Kontexten (z.B. politisch, ästhetisch, umweltbezogen) erschwert ein universelles Verständnis und behindert wirksame Interventionen (Shackleton et al., 2019a, b; Heger et al., 2021). Folglich weist die Fachsprache der Invasionsbiologie zahlreiche uneinheitliche Definitionen auf, die Forschung, Management, Interdisziplinarität und standardisierte Kommunikation erschweren (Colautti & MacIsaac, 2004; Ricciardi & Cohen, 2007; Lockwood, Hoopes & Marchetti, 2013). Castro et al. (2023) zeigen beispielsweise, dass unklare Terminologie die effektive Berichterstattung nicht-einheimischer Taxa in regionalen Checklisten erheblich erschwert. Begriffe, die sich auf Phasen oder Auswirkungen biologischer Invasionen beziehen, sind häufig polysem, was Missverständnisse und Einschränkungen im wissenschaftlichen Austausch sowie in der Naturschutzpraxis nach sich zieht (Colautti & MacIsaac, 2004). Zudem erschwert uneinheitliche Terminologie bidirektionale Übersetzungen zwischen Sprachen (Copp et al., 2021), während Begriffe wie „Invasion“ oder „einheimisch“ zusätzlich kulturell geprägte zusätzliche Bedeutungen innehaben (Wehi et al., 2023).

Zur Standardisierung der Terminologie definieren wir den „einheimischen“ (natürlichen) Bereich einer Art als das biogeografisches Gebiet, in dem ihr Vorkommen ausschließlich durch natürliche evolutive Prozesse bestimmt wurde; ohne direkte oder indirekte menschliche Eingriffe wie Transport, Grenzverschiebungen oder das Überwinden natürlicher Barrieren. Der „nicht-einheimische“ Bereich umfasst folglich Gebiete, in denen Arten durch menschliche Eingriffe vorkommen und nicht natürlich evolviert sind (McNeill, 2003; Soto et al., 2024). Diese Definition ist unabhängig von der Dauer der Anwesenheit oder evo­lutiven Anpassung an das neue Umfeld, wobei nicht-einheimische Gebiete auch menschlich begünstigte Expansionen einschließen, etwa durch Entfernung biogeografischer Barrieren oder klimatische Veränderungen, die eine Ausbreitung erleichtert oder überhaupt erst ermöglicht haben (Essl et al., 2019).

Während der Begriff „nicht-einheimisch“ primär die evolutive Beziehung einer Art zu einem Gebiet beschreibt, bezeichnet „etabliert nicht-einheimisch“ eine Art mit sich nachweislich selbst erhaltender Population im neuen Gebiet. Der Terminus „invasiv“ bzw. „Invasivität“ ist besonders vielschichtig und variiert zwischen Definitionen, die ökologische oder wirtschaftliche Auswirkungen betonen (CBD, 1993; Executive Order 13112, 1999), und solchen, die die Ausbreitungsdynamik in den Mittelpunkt stellen (Richardson et al., 2000; Colautti & MacIsaac, 2004). Die Verwendung von Einfluss als Kriterium bringt jedoch Subjektivität mit sich: Auswirkungen sind kontextabhängig, durch Wahrnehmungen beeinflusst und nur schwer einheitlich zu quantifizieren. Lokale Bewertungen erfassen systemische oder langfristige Konsequenzen häufig nur unvollständig, und Extrapolationen übersehen räumliche und zeitliche Variabilität (Sofaer et al., 2018; Haubrock et al., 2022). Zudem verwischt ein Einfluss (d.h. „Impact“)-basiertes Verständnis reale und wahrgenommene Vorteile gebietsfremder Arten, was Priorisierung und Management insbesondere dort erschwert, wo sozioökonomische Interessen oder Klimawandel gebietsfremde Arten gegenüber einheimischen bevorteilen (Mwangi & Swallow, 2008; Rodríguez-Barreras et al., 2020).

Auch die Verwendung von Ausbreitung als zentrales Kriterium ist problematisch, da sich Ausbreitung schwer standardisiert messen lässt (Haubrock et al., 2025a). Inkonsistente Schwellenwerte, die Unterscheidung zwischen primärer und sekundärer Ausbreitung sowie die Unsicherheit von Einführungsorten (z.B. in aquatischen Ökosystemen) begrenzen die Anwendbarkeit (Shigesada & Kawasaki, 1997; Sax et al., 2005). Zudem hängt die Wahrnehmung von Ausbreitung stark vom Maßstab ab: eine Ausbreitung innerhalb eines isolierten Flusses kann anders wahrgenommen werden als dieselbe Art auf kontinentaler Ebene (Haubrock et al., 2024). Artmerkmale und Umweltkontexte beeinflussen zusätzlich die Ausbreitungsraten (Hengeveld, 1994; Richardson et al., 2020). Neuere Arbeiten (Soto et al., 2024; Oficialdegui et al., 2024; Haubrock et al., 2025a) betonen daher die Kontextabhängigkeit und multidimensionale Natur des Begriffs. Wenn Invasivität allerdings ausschließlich über Ausbreitung definiert wird, könnte „invasiv nicht-einheimisch“ durch „sich ausbreitend nicht-einheimisch“ ersetzt werden, was redundant wäre, da nahezu alle etablierten nicht-einheimischen Arten sich irgendwann innerhalb ihrer neuen ökologischen Grenzen ausbreiten, wenn auch mit unterschiedlichen Raten. Ausbreitung und Einfluss sind daher kaum voneinander zu trennen und so sollte „invasiv“ die Fähigkeit einer Population bezeichnen, zu kolonisieren, sich zu etablieren und sich auszubreiten (Blackburn et al., 2011), möglicherweise ergänzt um das Kriterium der „Superabundanz“ (d.h. eine durch günstige Bedingungen induzierte Überschreitung der Tragfähigkeit mit potenziellen ökologischen Ungleichgewichten; Ricciardi & Cohen, 2007; Aizen et al., 2014). Invasivität kann somit zeitlich und räumlich variieren: Populationen, die lange unauffällig waren, können plötzlich explosionsartig wachsen (Witte et al., 2010), weit über ihren historischen Bereich hinaus expandieren (Nadel et al., 1992) oder von harmlos zu invasiv übergehen, ausgelöst durch externe Faktoren (Spear et al., 2021).

​

1.3     Gebietsfremde Arten in europäischen und deutschen Gewässern

Die Präsenz gebietsfremder Arten in europäischen Gewässern hat in den letzten Jahrzehnten erheblich zugenommen. Das Bundesamt für Naturschutz (BfN) listet 1,015 etablierte, 1,578 unbeständige, 347 unbekannte und 107 invasive Arten auf (Haubrock et al. 2025c), wobei die Definition des Begriffs „invasiv“ variiert (Soto et al. 2024). Hinzu kommen 114 „potenziell“ invasive Arten, deren Auswirkungen ggf. noch nicht abschließend bewertet sind. Die kürzlich zusammengestellte Liste etablierter gebietsfremder Arten (s.a. Henry et al. 2023) verzeichnet für Europa insgesamt 15,187 gebietsfremde Arten von denen 1,276 in aquatischen Lebensräumen vorkommen. Die Einbringungswege sind dabei vielfältig und umfassen neben dem Handel mit Zierpflanzen auch die Frachtschifffahrt (z. B. durch Ballastwasser), den Tierhandel (z.B. exotischer Haustiere), Tourismus und Reisen, Aqua- und Hortikultur, den Import von Rohstoffen wie Holz, sowie Straßen- und Schienenverkehr (Nunes et al. 2015) und spiegeln die zunehmende Globalisierung und den intensiven Austausch zwischen Regionen wider (Meyerson & Mooney 2007).

Während Henry et al. (2023) insgesamt 2.302 gebietsfremde Arten für Deutschland auflistet, berichtet das BfN von lediglich 1.015 etablierten nicht-einheimischen Arten (Haubrock et al., 2024). Haubrock et al. (2025c) stellten kürzlich eine Liste gebietsfremder nicht-einheimischer etablierter Arten (definiert als solche, die sich über mindestens ≥ n Generationen in einem Gebiet reproduzieren, in dem sie nicht heimisch sind; sensu Soto et al. 2024) in Deutschland zusammen. Diese Liste integriert Daten aus SInAS (Standardising and Integrating Alien Species; Seebens et al. 2020), sTWIST (Seebens et al. 2017) und Casties et al. (2016). Arten ohne klare geografische Zuordnung oder jene mit unklarem Status (CASUAL oder ABSENT) wurden ausgeschlossen. Wissenschaftliche Namen wurde über die Global Biodiversity Information Facility (GBIF; Land and Edwards 2007) validiert. Die Liste umfasst auch Arten mit kontroversem Status, wie jene die innerhalb Deutschlands transloziert wurden, domestizierte Tiere und auch jene, die vor 1492 eingeführt wurden (präkolumbianische Einführungen; Archäozoen) (Kinzelbach, 2001). In Summe, zeigten Haubrock et al. (2025c) dass die Anzahlt etablierter gebietsfremder Arten in Deutschland in marinen Ökosystemen (n = 162; 8.4%) und Binnengewässern (n = 115; 5.9%) deutlich geringer sind wie jene in terrestrischen Ökosystemen.

​

1.4     Folgen für Biodiversität, Umwelt, und Wirtschaft

Gebietsfremde Arten haben weitreichende Folgen für natürliche aquatische Ökosysteme und die Gesellschaft. Diese Auswirkungen manifestieren sich in vielfältiger Weise – von der Bedrohung der Artenvielfalt über die Veränderung ökologischer Prozesse bis hin zu erheblichen wirtschaftlichen Kosten.

​

1.4.1  Auswirkungen auf die aquatische Biodiversität

Gebietsfremde Arten beeinflussen die aquatische Biodiversität, indem sie mit heimischen Arten konkurrieren, diese verdrängen oder neue ökologische Nischen besetzen. Langzeitstudien zeigen, dass solche Invasionen oft schleichend beginnen, langfristig jedoch signifikante Veränderungen hervorrufen (Haubrock & Soto, 2023; Haubrock et al., 2025b). Eine Analyse von Haubrock et al. (2024) untersuchte die Dynamik aquatischer nicht-heimischer Makroinvertebraten anhand von 151 Langzeitdatensätzen aus Deutschland. Dabei nahm zwar die absolute Anzahl gebietsfremder Arten kontinuierlich zu, ihr relativer Anteil an der Gesamtartenvielfalt jedoch ab. Dies weist auf komplexe Interaktionen hin, bei denen heimische Arten zunehmend verdrängt werden. Auffällig war zudem eine starke räumliche Verzerrung der Monitoring-Daten zugunsten des Rheins und seiner Zuflüsse, was die Notwendigkeit einer umfassenderen, einheitlicheren Erfassung unterstreicht, um Invasionsdynamiken in Deutschland realistisch abzubilden. Ein prägnantes Beispiel ist die Invasion der Schwarzmund-Grundel Neogobius melanostomus im Rhein, die laut Le Hen et al. (2023) maßgeblich zur Reduktion der heimischen Fischartenvielfalt beitrug. Während die Gesamtartenanzahl durch die Etablierung gebietsfremder Fische anstieg, sank die Zahl heimischer Arten um 26 %, ihre Abundanz sogar um 50 %. Solche Verschiebungen betreffen nicht nur die taxonomische Zusammensetzung, sondern verändern auch funktionale Eigenschaften der Gemeinschaften, was sich langfristig auf Ökosystemfunktionen auswirkt. Ein weiteres Beispiel ist der Große Höckerflohkrebs Dikerogammarus villosus, dessen zunehmende Dominanz mit einem Rückgang der Artenvielfalt und der Stabilität der Artengemeinschaft einherging (Soto et al., 2023). Diese Fälle zeigen, wie gebietsfremde Arten nicht nur die Zusammensetzung biologischer Gemeinschaften verändern (Hejda et al., 2009), sondern auch deren funktionale Dynamik beeinträchtigen (Charles & Dukes, 2007), wodurch die Widerstandsfähigkeit der Ökosysteme gegenüber zukünftigen Störungen geschwächt wird (Chaffin et al., 2016).

Abbildung 1. Wirkungsebenen biologischer Invasionen im aquatischen Kontext, von individuellen Verhaltensänderungen bis hin zu Ökosystemprozessen, einschließlich typischer Veränderungen auf jeder Ebene.

1.4.2  Auswirkungen auf die Umwelt

Gebietsfremde Arten beeinflussen nicht nur die biologische Vielfalt, sondern auch physikalische und chemische Eigenschaften ihrer neuen Lebensräume. Ein exemplarischer Fall ist die Zebramuschel Dreissena polymorpha, welche als „Habitat-Ingenieur“ wirkt (Padilla, 1997; Zaiko et al., 2009). In einigen Ökosystemen führte ihre Invasion zu deutlichen Veränderungen der Sedimentstruktur und zu einem Anstieg der benthischen Artenvielfalt in den von ihr geschaffenen Habitaten. Gleichzeitig verdrängt sie heimische Arten und verändert Nährstoffkreisläufe (Turner, 2010). Ein weiteres Beispiel ist der Rote Amerikanische Sumpfkrebs Procambarus clarkii, dessen Grabaktivitäten Ufer- und Dammstrukturen destabilisieren und Erosionsprozesse verstärken (Haubrock et al., 2019). Solche physikalischen Veränderungen haben weitreichende Konsequenzen für Biodiversität, Gewässertrübung und Lichtdurchdringung (Harvey et al., 2014) sowie für Hochwasserschutz und wasserbauliche Infrastruktur (Faller et al., 2016). Darüber hinaus werden die Auswirkungen gebietsfremder Arten durch klimatische Veränderungen verstärkt. Karatayev et al. (2014) zeigen, dass die Invasion der Zebramuschel in Kombination mit Eutrophierung zu erheblichen Verschiebungen in der Biodiversität von Seen führte. Solche Kombinationseffekte verdeutlichen die Notwendigkeit integrativer Managementansätze, die sowohl gebietsfremde Arten als auch relevante Umweltfaktoren berücksichtigen.

​

1.4.3  Wirtschaftliche Auswirkungen

Die ökonomischen Kosten gebietsfremder Arten sind beträchtlich, jedoch häufig unzureichend dokumentiert. Die 2020 veröffentlichte InvaCost-Datenbank ermöglicht erstmals eine umfassende Quantifizierung dieser wirtschaftlichen Belastungen und stellt eine strukturierte, standardisierte Sammlung globaler Kostenabschätzungen bereit (Diagne et al., 2020). Sie basiert auf einer systematischen Durchsuchung wissenschaftlicher Publikationen, Berichte und grauer Literatur und erfasst finanzielle Informationen zu Schäden, Managementmaßnahmen und Präventionsstrategien im Zusammenhang mit gebietsfremden Arten. Die Daten werden nach geografischer Region, betroffenem Sektor, Kostenkategorie (z. B. direkte Schäden vs. Managementkosten) und Zeitrahmen klassifiziert und erlauben dadurch detaillierte Analysen. Damit bildet InvaCost eine essentielle Grundlage zur Priorisierung von Maßnahmen und zur Entwicklung globaler Managementstrategien.

In Deutschland beliefen sich die geschätzten Gesamtkosten durch gebietsfremde Arten zwischen 1960 und 2020 auf rund 9,8 Milliarden USD (Haubrock et al., 2021a). Diese Kosten umfassen direkte Schäden, etwa die Zerstörung von Infrastruktur, sowie Ausgaben für Kontrollmaßnahmen. Besonders hohe finanzielle Belastungen gingen von Arten wie der Bisamratte Ondatra zibethicus und dem Amerikanischen Nerz Neovison vison aus, die sowohl landwirtschaftliche Flächen als auch wasserbauliche Anlagen schädigen. Europaweit summierten sich die Kosten im gleichen Zeitraum auf etwa 140,2 Milliarden USD, wobei aquatische Invasionen häufig unterrepräsentiert sind (Haubrock et al., 2021b). Weltweit verursachten aquatische gebietsfremde Arten Kosten von 345 Milliarden USD, wobei insbesondere Invertebraten wie die Zebramuschel oder nicht-einheimische Krustentiere zu den Hauptverursachern zählen (Cuthbert et al., 2021). Gebietsfremde Binnenmollusken wie die Zebramuschel verursachen erhebliche wirtschaftliche Schäden. Haubrock et al. (2022) schätzen die globalen Kosten gebietsfremder Süßwassermuscheln auf 63,7 Milliarden USD zwischen 1980 und 2020. Die meisten Schäden traten zwar in Nordamerika auf, wo die Muscheln Wasseraufbereitungsanlagen und andere Infrastruktursysteme beeinträchtigen, doch auch in Europa wurden neben 6,2 Millionen USD in Schäden deutliche Datenlücken festgestellt. Die Kosten durch Schäden und Ressourcenverluste übersteigen dabei die Investitionen in Prävention und Kontrolle um ein Vielfaches, was das Einsparpotenzial frühzeitiger Interventionen verdeutlicht. Ein ähnliches Muster zeigt sich bei gebietsfremden Krustentieren. Kouba et al. (2022) dokumentierten globale Kosten von 271 Millionen USD, davon 116,4 Millionen USD in Europa. Hauptverursacher sind der Signalkrebs Pacifastacus leniusculus und die Chinesische Wollhandkrabbe Eriocheir sinensis. Die Schäden umfassen insbesondere die Zerstörung von Uferstrukturen, den Verlust von Fischbeständen und die Beeinträchtigung aquatischer Ökosysteme – auch hier sind Schadenssummen deutlich höher als die Ausgaben für Prävention, was den Bedarf an systematischerem Management unterstreicht.

Wie Haubrock et al. (2022) weiter zeigten, stiegen die globalen Kosten durch gebietsfremde Fische von weniger als einer Million USD auf über eine Milliarde USD. Diese Entwicklungen verdeutlichen den drastisch wachsenden finanziellen Druck, der entsteht, wenn präventive Maßnahmen fehlen, und unterstreichen die Dringlichkeit koordinierter internationaler Strategien zur Begrenzung der ökonomischen Auswirkungen gebietsfremder Arten.

Abbildung 2. Schematische Darstellung drei zentraler Wirkungsdimensionen gebietsfremder Arten – Biodiversität, Umwelt und Wirtschaft.

1.5     Zusammenfassung

Gebietsfremde Arten haben tiefgreifende Auswirkungen auf Biodiversität, Umwelt und Wirtschaft, die sich gegenseitig verstärken. Sie bedrohen nicht nur die biologische Vielfalt, sondern verändern physikalische und chemische Eigenschaften von Ökosystemen und verursachen erhebliche wirtschaftliche Kosten. Langzeitstudien und integrative Datenbanken wie InvaCost verdeutlichen die Notwendigkeit einer besseren Überwachung und eines proaktiven Managements, um die negativen Auswirkungen dieser biologischen Invasionen zu minimieren. Ein ganzheitlicher Ansatz, der ökologische, ökonomische und soziale Aspekte berücksichtigt, ist entscheidend, um sowohl kurzfristige als auch langfristige Schäden zu begrenzen.

 

Literatur

Available upon request.

How to realistically envision an academic career as a student (written with Dr. Teun Everts)

Students often believe that with good ideas, careful work, and strong publications, they will be recognized and rewarded with long-term academic prospects. To this end, the “publish or perish” narrative is often presented as the central academic currency. Students are told to publish, then to publish more, and then to worry about journal prestige and citation counts. Although these factors remain important, they represent only the tip of the iceberg of what is needed for a successful career in present-day academia that is now more than ever characterized by intense competition, prolonged precarity and limited permanent positions (REF). Indeed, career progression and hiring likelihood is also shaped by supervision, institutional fit, teaching competence, collaboration and networking capabilities, success with grant acquisition, and tolerance for prolonged uncertainty as well as repeated times of struggle. Students considering academic careers therefore benefit from learning in an early stage not only how to do research, but also how contemporary academic systems actually function, reward, and are sustained.

​

How to think realistically about an academic career as a student

  1. Do not mistake publication success for career security.

  2. Choose supervision and lab culture more carefully than prestige.

  3. Learn early how funding shapes academic opportunity.

  4. Protect your intellectual independence and welcome pluralism.

  5. Use AI as a tool, but do not outsource judgement.

  6. Gain hands-on experience in core academic duties

  7. Build broad systemic awareness and multi-faceted skills

  8. Prioritize personal over professional well-being

  9. Ask whether you truly want the life of academia, not only its status.

 

Do not mistake publication success for career security: Students are often taught that publication and citation counts are the main currency of academic success. Surely, they are important indicators of competence and visibility, but they do not translate proportionally into stable positions or long-term recognition. Finishing a PhD with multiple (high impact) papers is considered successful, but later career stages are more often than not evaluated differently. Publications still matter, yet aside from their citations and contribution to h-factors, they are judged alongside a broader set of signals. These include independence, funding potential, leadership skills, and institutional fit. Some researchers may be still convinced that only publications in Nature and Science matter, or that a very small set of highly visible journals disproportionately determines careers. That view is likely overstated, but it reflects a real feature of academia; prestige signals continue to influence perception beyond the intrinsic quality of one’s work itself (REF). Students should therefore understand both points at once. Good publications are worth pursuing, but academic output alone does not guarantee an academic career.

​

Choose supervision and lab culture more carefully than prestige: Although the formal reputation of a department or principal investigator remain important predictors of future career success (Clauset et al., 2015), the value of a nurturing environment for a student’s personal and professional development cannot be underestimated (Mausz & Sauseng, 2026). A strong supervisor provides constructive feedback, calibrates projects, supports skill development, gives freedom for mistakes, promotes the candidate in their networks, and creates conditions in which independence can grow. A weak or absent supervisor can do the opposite, even in a prestigious setting. Students and particularly those abroad should therefore carefully assess whether a prospective lab is intellectually active, whether the supervisor is available, whether former trainees progressed well and whether expectations by both the student and prospective supervisor can be clearly communicated (Mausz & Sauseng, 2026). Students should not only expect but demand real supervision and not treat it as a fortunate coincidence of their lab choice.

​

Learn early how funding shapes academic opportunity: Many students begin their academic career with the impression that academia is organized mainly around ideas, publications, and disciplinary reputation. In practice, available funding is becoming more important, especially in an increasingly financially constrained academic system (Larson et al., 2014). Obtaining competitive funding is not just a resource but a core signal. Obtaining third party funding by early career researchers can indicate the ability to identify pressing challenges and frame them persuasively, attract trust, design creative research methodologies and solutions, possibly even manage projects and thus, reduce institutional risk. Funding also buys time, enables the employment of personnel, funds infrastructure, and secures continuity. More advanced researchers can also expand their influence beyond the individual level because funded researchers often become nodes around which teams, collaborations, and ultimately networks form. Students considering academic careers should therefore learn early how grants shape opportunity, instead of realizing this through trial and error. This does not mean reducing science to fundraising but recognizing that grant acquisition increasingly affects which ideas are pursued, which labs grow, and which researchers gain room to operate. Applying for small grants, travel support or pilot funding early can therefore be useful training rather than a research distraction.

​

Protect your intellectual independence and welcome pluralism: A successful scientific career depends not only on technical competence but also on the ability to think independently and creatively, re-think paradigms, and change one’s perception through scientific reasoning. Students benefit from exposure to competing explanations, methods, and disciplinary perspectives. Pluralism, especially in academia, improves judgment, reduces conformity, and helps distinguish strong evidence from disciplinary fashion. It also guards against premature closure, where researchers become committed to one framework before they are intellectually able to evaluate alternatives. Students should also think carefully about the relationship between science and government as well as science and activism. Research is often motivated by real socio-economic or sustainability problems, and scholars may have legitimate moral commitments. But when the desired conclusion is fixed in advance, scientific inquiry weakens. Universities should train students to become rigorous, critical thinkers capable of objectively improving society through disciplined and evidence-based inquiry, not only through advocacy.

​

Use AI as a tool, but do not outsource judgment: Students entering academia now do so in an environment where generative AI is increasingly available for writing, summarizing, searching, coding, and brainstorming. Used carefully, these tools can save time, support routine tasks, and ultimately contribute to advancing academic careers (Hao et al., 2026). But students should avoid relying on AI in place of reading, reasoning, discussion, and first-hand engagement with evidence. Scientific judgment develops through exposure to arguments, disagreement, ambiguity and conceptual difficulty. AI can support this process, but it should not replace it. One should not reject AI categorically but use it in ways that preserve independent thought independent of the data AI is trained on.

​

Gain hands-on experience in core academic duties: While educational proficiency is important, especially at universities, students should actively seek teaching assistantships, guest lectures, or tutoring roles to experience and test classroom dynamics firsthand. This will not only increase their societal contributions but also strengthens their applications for PhD programs or postdoc positions. Furthermore, teaching is a skill that must be honed. Similarly, students should be encouraged to pursue small research projects, co-supervise undergrad theses, or engage in lab assistantships early to diversify academic skillsets.

​

Build broader systemic awareness and skills: Students should deliberately build professional networks by attending conferences, joining scholarly societies and collaborating with others, while also developing skills that universities actually reward, including clear communication, time management, organization and leadership. Just as importantly, students should recognize early that academic work extends well beyond research: faculty positions often involve teaching, advising, committees, outreach and substantial administrative responsibilities. Early exposure to these tasks can help students judge more realistically whether academic life suits them and prepare them for the parts of the job that are often underestimated.

​

Prioritize personal with professional well-being: Academia's high rejection rates in grants, papers, and jobs can foster imposter syndrome, anxiety, or burnout (Bergvall et al., 2025). Therefore, it is important to build coping strategies early through mentor feedback on failures, peer support groups, or university counselling, while addressing long hours and work-life imbalance by setting boundaries and monitoring for overload. Consider financial realities, especially with modest PhD stipends and early salaries often lagging industry norms and minimize debt via scholarships, part-time work, or program cost analysis.

​

Ask whether you truly want the life of a contemporary academic: Many students are drawn to academia by its ideals, namely an inherent curiosity, urge for discovery, intellectual autonomy, knowledge transfer to future generations, and the possibility of contributing lasting knowledge. These attractions are real. But an academic career also often involves delayed stability, repeated competition, geographic mobility, administrative load, and a high degree of uncertainty. Students should therefore ask not only whether they are passionate about research, but whether they perhaps idealize it and would accept the actual structure of the career. Keeping alternative paths open is not a sign of weak commitment. It is a sign of strategic clarity.

​

Conclusion

Thinking realistically about academic careers does not require cynicism, nor does it diminish the value of scholarship. It demands distinguishing between the ideals of science and the institutional conditions under which science is pursued in contemporary climates. Students who understand this distinction early are better placed to choose supervisors, environments and opportunities that fit both their ambitions and their tolerance for uncertainty. This is likely to ultimately strengthen their academic portfolio, and thus chances of a successful and durable academic career. For some, this realism will strengthen commitment to academia. For others, it will clarify that alternative paths offers a better fit. In either case, its crucial that students are driven by informed decisions rather than inherited narratives.

​

References

Clauset, A., Arbesman, S. & Larremore, D. B. Systematic inequality and hierarchy in faculty hiring networks. Sci. Adv. 1, e1400005 (2015).

Larson, R. C., Ghaffarzadegan, N. & Xue, Y. Too many PhD graduates or too few academic job openings: The basic reproductive number R₀ in academia. Syst. Res. Behav. Sci. 31, 745–750 (2014).

Bergvall, S., Fernström, C., Ranehill, E. & Sandberg, A. The impact of PhD studies on mental health—a longitudinal population study. J. Health Econ. (2025).

Mausz, I. & Sauseng, P. How to foster a supportive research group culture. Nat. Hum. Behav. 10, 212–214 (2026).

Hao, Q., Xu, F., Li, Y. et al. Artificial intelligence tools expand scientists’ impact but contract science’s focus. Nature 649, 1237–1243 (2026).

How to Mentor Junior Researchers Under Structural Scarcity as a Postdoc (written with Dr. Teun Everts)

Academic systems in many countries feature a persistent imbalance between the number of qualified researchers and the availability of permanent positions (1). Even in countries with long-established research systems such as Germany or in systems exposed to periods of political or fiscal uncertainty, such as the United States during the Trump administration, most non-professorial academic staff are employed on fixed-term contracts, and first permanent appointments are often only acquired in the mid-forties. In Germany, for instance, professors have an average age of 53 years, and only about 4% are younger than 40. First appointments to W2 or W3 positions occur at a mean age of approximately 42–43 years, whereas postdoctoral phases are limited to six years and thus, typically end in the mid-thirties. The resulting interval of roughly 10–15 years between doctorate and permanent appointment constitutes a structurally prolonged and employment-insecure postdoctoral phase (2–4). These conditions of structural scarcity also create asymmetric hiring risk. In systems with strong tenure protections and limited post-hire correction mechanisms, committees face greater institutional cost from appointing a misaligned candidate than from rejecting a strong one. This asymmetry incentivizes conservative selection and amplifies the importance of perceived institutional fit.

 

Given typical appointment ratios, only a minority of doctoral graduates ultimately secure professorial roles. Several disciplines produce far more doctorates each year than there are lifetime professorships available (5). An ever-decreasing minority therefore ultimately transitions to professorial roles with long-term, if not permanent, outlooks. Such patterns create extended periods of uncertainty in which rejection is not exceptional but statistically expected. Performance remains essential; however, beyond a threshold of demonstrated competence, additional achievements do not proportionally increase appointment probability. Differentiation frequently hinges on network integration, institutional alignment and grant acquisition rather than output volume and quality alone (6).

Researchers in advanced postdoctoral stages are often those with established publication records, funding success, supervisory experience and international visibility and occupy a structurally distinctive position. Their short-term contracts force them to be highly productive, yet they remain institutionally vulnerable. At the same time, they increasingly serve as informal mentors to students, doctoral candidates, and early postdoctoral researchers seeking candid insight into academic career dynamics, as they tend to be more available and better approachable than many principal investigators (7). Because postdoctoral cohorts are typically highly international and often include researchers who have themselves navigated institutional, cultural, and socio-economic barriers and hardship, they may also be particularly well positioned to support students from underrepresented or disadvantaged backgrounds. This position requires bridging aspirational narratives about merit with a realistic understanding of structural constraints, thereby exercising leadership without formal authority. Moreover, serving as mentors, these researchers can play a key role in mediating negative relationships with supervisors and buffering overly harsh feedback, effectively motivating early-career-researchers to stay in academia (8,9). Academic mentors thus have an invaluable role in guiding less experienced colleagues through an academic landscape constrained by chronic resource scarcity.


How to Mentor Early Career Researchers In Times Of Structural Scarcity

  • Publishing does not prevent perishing. It is key to acknowledge that efforts and outcomes do not scale linearly; alignment, collegial reliability and administrative capacity can be equally valuable than publication record in academic hiring processes.

  • Funding acquisition is an asset that may reduce institutional risk. Guiding less experienced peers into the process of third-party funding acquisition through proposal framing strategies and introduction to their scientific networks early on can help them secure funds to not only remain in academia but also complement their CVs with acquired funding.

  • Approach rejections objectively and treat them as data, not verdicts. Controllable elements of rejections are learning opportunities; not taking them personally is a key characteristic of present-day academia.

  • Align efforts with expectations but plan probabilistically. In low-base-rate systems, multiple applications are statistically expected before success. Mentors should underline that rejections are no diagnostic of inadequacy but characteristic of competitive systems. They can demonstrate that diversification of professional activities can improve their peer’s personal growth and hiring chances.

  • Understand the likelihood of a permanent position. Individual competence is a poor predictor of acquiring permanent academic roles. Alternative career paths can be presented as reasonable and meaningful alternatives.

 

Publishing does not prevent perishing: A foundational step towards a successful academic career is recognizing the non-linear relationship between effort and outcomes. Publications establish scientific credibility and function as an entry criterion into long-term academic positions. Yet selection processes often unfold in two stages: initial validation of competence followed by differentiation based on broader evaluative criteria such as professional vision and management skills. In systems with strong tenure protections and limited post-hire correction mechanisms, hiring committees face asymmetric risks. Rejecting a strong candidate carries little institutional cost, whereas appointing a candidate perceived as misaligned may have long-term organizational implications. Such conservatism reflects institutional design and long-term risk considerations. As a result, candidates must demonstrate alignment with institutional priorities, collegial reliability and administrative capacity explicitly, rather than assuming that research productivity alone will suffice.

Funding acquisition is an asset that may reduce institutional risk: Within the current academic environment, competitive third-party funding operates as a key signal. Grant acquisition functions as external validation, financial contribution and evidence of project management competence. Although funding success is, like publication counts and citation metrics, an imperfect proxy for scientific quality, it provides external validation and financial resources, thereby reducing perceived institutional risk and increasing its weight in hiring decisions. Mentoring at advanced postdoctoral levels should therefore include explicit instruction in funding architectures, proposal framing and consortium building, in addition to scientific rigor.

​

Approach rejections objectively and treat them as data, not verdicts: Managing repeated rejections requires structured reflection rather than emotional interpretation. After each outcome, distinguishing between controllable elements—such as clarity of application materials, documentation of leadership or articulation of institutional fit—and uncontrollable factors, including budgetary constraints or internal priorities, helps prevent over-attribution to personal deficiency. Maintaining a systematic record of applications can reveal patterns and guide targeted adjustments. For instance, emphasizing collaborative and administrative contributions may counterbalance perceptions of excessive independence in contexts where predictability is valued. Emphasizing learning processes and iterative improvement over singular outcomes can transform rejection from a private stigma into a shared developmental experience.

Align efforts with expectations but plan probabilistically: Probabilistic planning further supports sustained engagement. Framing goals in terms of expected application numbers or interview rates, rather than assuming deterministic success, aligns effort with realistic base rates. In competitive systems such as academia, appointment probabilities are low by design. Recognizing this statistical context reduces the tendency to interpret each rejection as diagnostic of inadequacy. Diversifying professional activities through policy engagement, interdisciplinary collaboration or limited industry interaction can also reduce over-reliance on a single institutional outcome while strengthening transferable competencies.

​

Understand the likelihood of a permanent position: Mentorship under structural scarcity must include systemic literacy. Junior researchers benefit from understanding that productivity is necessary but insufficient, and that compatibility with institutional incentives influences outcomes. Transparent discussion of evaluation logics, funding expectations and career bottlenecks enables informed decision-making. Equally important is acknowledging numerical constraints: individual competence, brilliance, or professional track record is no guarantee of permanent academic roles. Presenting alternative trajectories in industry, public administration or independent research as legitimate and intellectually meaningful paths broadens perceived opportunity structures and mitigates binary success narratives. Destigmatizing non-academic transitions does not dilute academic standards; it contextualizes them. Encouraging early-career researchers to assess personal fit with institutional environments, ultimately distinguishing their own competence from compatibility, fosters autonomy and reduces internalization of structural limits as personal failure. This reframing protects motivation while maintaining ambition.

​

Conclusion
Structural scarcity is likely to persist and may become even more pronounced in the future. For the current generation of early-career researchers, this environment combines high intellectual demands with prolonged career uncertainty, making academic career progression more difficult and less predictable than for many previous cohorts. Researchers transitioning toward seniority occupy a consequential mentoring position that the busy schedules of principal investigators often prevent them to fill in themselves, shaping group norms through their responses to setbacks that are pervasive in contemporary academia. Understanding scarcity as a systemic feature rather than a personal verdict enables them to guide junior colleagues with probabilistic clarity, strategic awareness and expanded career imagination. Such leadership preserves intellectual ambition while reducing the psychological harm caused by unrealistic expectations, contributing to a research culture that is both rigorous and adaptive under constraint. Recognizing scarcity as structural rather than personal enables such mentors to preserve ambition while reducing unnecessary psychological harm. However, these mentoring roles are often structurally constrained and poorly institutionalized (7) and academic systems risk eroding precisely these intermediary roles through continued casualization of postdoctoral employment.

​

References

1) Larson, R. C., Ghaffarzadegan, N., & Xue, Y. (2014). Too Many PhD Graduates or Too Few Academic Job Openings: The Basic Reproductive Number R 0 in Academia. Systems Research and Behavioral Science, 31(6), 745–750. https://doi.org/10.1002/sres.2210

2) Teichler, U. The Academic Profession in Germany. Challenges and Options: The Academic Profession in Europe. https://doi.org/10.1007/978-3-319-45844-1_7 https://www.academia.edu/65061462/The_Academic_Profession_in_Germany

3) Teichler, U., & Bracht, O. (2006, September). The academic profession in Germany. In Reports of changing academic profession project workshop on quality, relevance, and governance in the changing academia: International perspectives (Vol. 20, pp. 129-150). Hiroshima: Research Institute for Higher Education, Hiroshima University.

4) Kuhnt, M., Müßig, P., & Reitz, T. (2024). There are alternatives. Models for sustainable employment structures in the German system of higher education. Frontiers in research metrics and analytics, 9, 1301354. https://pmc.ncbi.nlm.nih.gov/articles/PMC10940507

5) Bundesministerium für Bildung und Forschung (BMBF). (2021). Bundesbericht Wissenschaftlicher Nachwuchs 2021: Statistische Daten und Forschungsbefunde zu Promovierenden und Promovierten in Deutschland. W. Bertelsmann Verlag. https://www.buwin.de/

6) Clauset, A., Arbesman, S., & Larremore, D. B. (2015). Systematic inequality and hierarchy in faculty hiring networks. Science Advances, 1(1), e1400005. https://doi.org/10.1126/sciadv.1400005
7) Lambert, W. M., Nana, N., Afonja, S., Saeed, A., Amado, A. C., & Golightly, L. M. (2025). Addressing structural mentoring barriers in postdoctoral training: A qualitative study. Studies in Graduate and Postdoctoral Education, 16(1), 1–24. https://doi.org/10.1108/SGPE-04-2023-0033

8) Busch, C.A., Wiesenthal, N.J., Gin, L.E. et al. Behind the graduate mental health crisis in science. Nat Biotechnol 42, 1749–1753 (2024). https://doi.org/10.1038/s41587-024-02457-z
9) Hunter et al., 2016: Doctoral Students’ Emotional Exhaustion and Intentions to Leave Academia. m http://ijds.org/Volume11/IJDSv11p035061Hunter2198.pdf

Recalibrating academia before the peer review singularity

The German Science Foundation, Germany’s central research funding body, has just opened the door to artificial intelligence assisted peer review under defined transparency and confidentiality rules. Tools such as www.Rubezahl.ai now let scientists generate grant proposals with AI support (Deutsche Forschungsgemeinschaft, 2026). As a consequence, science may soon witness a striking scientific ecosystem change where AI writes the proposal, optimises the language, structures the hypotheses and suggests the figures, while another AI reviews it, ranks it against hundreds of other applications, and drafts the evaluation report. Meanwhile scientists watch like slightly concerned referees observing two chess engines battle at superhuman speed, foreshadowing future rejection letters reading “ReviewerGPT 9 found ApplicantGPT 8 insufficiently innovative in paragraph 4”.

 

This is certainly efficient, but also highly absurd.

​

This happening now is more than a quirky development and reveals a much deeper crisis in academia, best showcased by the widening discrepancy between applications and funding availability: while application numbers for e.g. European Research Council and Marie Skłodowska-Curie grants continue to rise, funding has not kept pace, meanwhile the system is optimized towards the use of AI and the replacement of academic-linked labour. Concomitantly, early-career researchers face chronic yet growing uncertainty, intellectual diversity narrows sharply, administrative costs soar, and public trust fades; all while science, which was meant to discover reality, risks being reduced to optimising recursively generated text, making this the moment for deliberate recalibration around five intertwined requirements.

​

First, academia must restore a genuine merit-based system that values creativity, ingenuity, and diverse contributions. Obsession with publications in top journals has distorted incentives for decades, rewarding quantity and hype over quality and robustness as landmark replication efforts in psychology recovered only 36–40 % of published findings (Aarts et al., 2015). Positions too often go to those who cause the least friction rather than those with the strongest track records and shown merit and resilience through unconventional paths. Transparent composite scores that weigh research excellence alongside teaching, mentorship, replication work, applied impact and interdisciplinary effort are feasible and should become the essential standard needed to reward what actually sustains progress.

​

Second, academia must once again function as a true public marketplace of ideas. From 1969 to 2022 the share of US faculty identifying as far left or liberal rose from roughly 45–74 %, while middle of the road faculty fell to around 15 % and conservatives declined to just 11 % (Honeycutt, 2024; see also Magness & Waugh, 2022). Similar patterns surely exist across Europe. If left unchecked, academia would become a self-enforcing echo chamber of ideological groupthink, diminishing scientific self-correction. Hiring and promotion must therefore actively counter groupthink through viewpoint diversity mechanisms, stronger academic freedom protections and explicit rejection of ideological litmus tests. Without such safeguards, the marketplace of ideas becomes captured, and science loses its power to self-correct.

​

Third, academia must become far less precarious for young minds. A recent study showed that “early-career researchers do more ‘disruptive’ science than veterans” (Lenharo et al., 2026), meanwhile we silently accept that, according to surveys, ~40 % of graduate students and postdocs experience moderate to severe anxiety or depression, rates far above population norms (Evans et al., 2018). Many talented researchers leave not for lack of ability but because the human toll is unsustainable. Essentially, academia needs more stable early career tracks, reduced hyper competition in funding, mental health support, and realistic non-academic career pathways; paired with later career accountability through regular post tenure reviews to preserve dynamism.

Fourth, institutions must cut administrative bloat and restore accountability. In the United States, between 1976 and 2018 the number of full-time administrators grew by 164 % and other professionals by 452 %, vastly outpacing student enrolment and faculty growth (Delucchi et al., 2024). This expansion drives costs and credential inflation while squeezing research, teaching, and thus the value given to the next generation of scientists. Recalibration requires leaner operations, better alignment with student outcomes such as graduation and employability, routine open science practices, and transparent performance metrics to demonstrably replace prestige with integrity as the currency of trust.

​

Fifth, academia must engage honestly with artificial intelligence. AI can ease administrative burdens and accelerate routine tasks, increasing over reliance threatens to erode the very thinking and writing skills that define scientific excellence and induces cognitive homogenization, especially among early career researchers. Meanwhile, the emerging peer review singularity risks turning evaluation into an arms race of machine generated text judged by machines that leaves the human-value in science behind. Clear guardrails are needed, maintaining AI as a tool under mandatory human oversight, with training on responsible use and explicit standards for disclosure and validation – especially for students and young minds.

​

Although likely to cite discourse, these steps are not radical but have been debated for years. What is missing is coordinated action. European research funders struggle, the DFG’s AI experiment and falling public confidence signal the same underlying drift. Europe talks boldly about global scientific leadership yet chronically underfunds the structures needed to achieve it. Increasing the funding pool while reforming its use would be far more effective than erecting new barriers. This said, recalibration will be uncomfortable, but any alternative is worse. A system that optimises for self-replication, conformity, and burnout cannot remain at the frontier. Before artificial intelligence fully colonises the evaluation loop, academia still has the agency to redefine its rules. The stakes are nothing less than the health of discovery itself and its capacity to address humanity’s greatest challenges.

​

References

Aarts, A. A., Anderson, J. E., Anderson, C. J., Attridge, P. R., Attwood, A., Axt, J., ... & Zuni, K. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), 1-8.

Delucchi, M., Dadzie, R. B., Dean, E., & Pham, X. (2024). What’s that smell? Bullshit jobs in higher education. Review of Social Economy, 82(1), 1-22.

Deutsche Forschungsgemeinschaft. (2026). Artificial Intelligence in the Review Process – DFG Position and Perspectives. Zenodo. https://doi.org/10.5281/zenodo.18886256

Evans, T. M., Bira, L., Gastelum, J. B., Weiss, L. T., & Vanderford, N. L. (2018). Evidence for a mental health crisis in graduate education. Nature biotechnology, 36(3), 282-284.

Honeycutt, N. (2024) "The Politics of University Faculty" (PsyArXiv preprint). Direct link: https://osf.io/preprints/psyarxiv/dnxqh_v1 (or DOI: 10.31234/osf.io/dnxqh).

Lenharo, M. (2026). Early-career researchers do more ‘disruptive’ science than veterans. Nature. https://www.nature.com/articles/d41586-026-01466-z   

Magness, P. W., & Waugh, D. (2022). The Hyperpoliticization of Higher Ed. The Independent Review, 27(3), 359-370.

An early 2026 thought

I am a scientist. An ecologist. I work on invasion biology, global change, biodiversity—at the points where ecological reality, society, and costs intersect. During my studies, we were told very clearly what matters: publish or perish. So I published, early, extensively, internationally, and in most cases with substance. More than two hundred peer-reviewed papers, several thousand citations, global collaborations. I received two Marie Curie Fellowships: one for my PhD abroad, one for my postdoc, which I am currently doing. In addition, I was awarded an international prize for my work in invasion science.

 

By the standards we were taught to follow, I did everything that is expected of an academic career.

​

After my PhD, I then moved back to Germany to spent six years as a postdoc at one of the arguably most renowned research institutes in that country. I was productive, visible, and I thought also successful. And then it ended. Not because I was no longer wanted. But because, according to the law, I was no longer allowed to be employed and at the same time, no one was willing to offer me a permanent perspective. This was when I first realized, that the system uses people intensively as long as they are on temporary contracts and lets them go as soon as they become institutionally inconvenient.

​

I accept that and started to write grant applications. Many, both national and international. I developed ideas further, adapted them, refined them, but failed. Sure, some applications were better than others, but what was most devestating were the reviewer comments I received. Constructive? No, not at all. It was only months later that I found out from a colleague that his lab-mate was one of the reviewers and mentioned rejecting me because "I seemed to competitive for him". This shook me, but it was around that time I won the second Marie Curie Fellowship, so I ignored it. Eventually, I continued to prepare another application within one of the most prestigious programs for scientific independence. At the same time, I contacted universities and asked whether they would be willing to host me. The answers were polite, detailed, and sobering: budget constraints, higher-education pacts, long-term commitments, lack of planning security. They wanted to focus in the coming years on maintaining existing structures. Not even if external funding were available. At some point, you begin to understand that these answers are not personal, but systemic, especially when you see who they were currently employing, not as Professors, but as mid-level researchers. 

​

Even worse is, that at the same time, I see people being appointed. Colleagues, acquaintances. And I realize that I am no longer angry, but more and more puzzled. Why? Because objectively, some of my own PhD students already perform better on paper than some of these appointees. More output, more visibility, more international experience. And yet others explain career paths, give advice, speak from a position that is not based on disciplinary superiority, but on institutional power. For instance after one rejection, I was told that I was on a good path, but still needed to close some gaps. More independently acquired third-party funding (oh well..). More PhD students (I already had three...). More leadership experience (as Post doc...?). More committee work (aehm...?). More teaching (lovely...), ideally in a way that immediately covers everything. It was kindly phrased, but between the lines, something else was written: my quality was not the problem; my insufficient fit with an ideal profile was—one that is hardly attainable without already holding a professorship.

I replied, kindly, asking if there was any possibilities to engage at that University by means of teaching, course work. Not only as a work to remain connected but to hone my skills and develop my CV even further. The response? I was ignored. Even my follow-up eMail was left unattended. What else could I do?

​

I have discussed this a lot, and I mean it: A LOT! I was told that productivity only counts up to a certain point. After that, it is about fit, diplomacy, being liked. And I understand that. No one likes to hire someone who creates conflict. Diplomacy is important. But it must come from a position of disciplinary competence. Otherwise, it means bending yourself for a lifetime and being especially nice to those who often reached their positions more by chance than by merit. But then something dangerous happens: disciplinary competence in the system slowly declines, while adaptability is rewarded. I ask myself: What remains objective once productivity is relativized? Third-party funding. Teaching. I have delivered both. After that, things become surprisingly vague. Then terms like reliability, calmness, fit start to matter. Things that are rarely said openly, but that ultimately carry decisions.

​

My dream was always to become a professor, like my parents, like my mentors at University. To teach. To pass on knowledge. To train students. Since my studies, I wanted to return to the university where it all began. Not out of nostalgia, but out of a sense of connection. By now, it is clear that all relevant new appointments there did not point toward me. Not loudly, not openly—but clearly enough. And with that, this dream has quietly come to an end.

​

This is not an individual failure. It is a structural problem. Because when a system systematically filters out people who are productive, independent, internationally visible, and strong in their field, it has consequences for the quality of teaching, for the capacity for innovation, and for the intellectual substance of universities. One then has to ask an uncomfortable question: if this is the direction in which science is developing—would inconvenient, visible, outspoken scientists of earlier generations have had any chance today to be heard at all? Or would they, too, have been sorted out as “not fitting”, “not ready yet”, or “too difficult”?

​

I am not writing this to discourage anyone. But to get it out of my head and on "paper", so that those that find their way here understand what they are getting into. The decisive question is not whether one is good enough. It is which system that person wants to be good in.

​

That decision is best made early. Not only once you realize that you have stopped expecting things to turn out differently.

bottom of page